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The management of landscapes and agricultural activities significantly impacts phosphorus (P) and nitrogen (N) losses, directly influencing eutrophication risk. This study quantifies the eutrophication potential of different land covers through in-situ measurements and analysis of runoff and inorganic substances. The research was conducted in two sub-catchments in the Bedřichovský stream basin, Novohradské hory, Czech Republic: a forest-dominated upper sub-catchment (UFS) and an agricultural lower sub-catchment (LAS). Water flows and surface water samples were measured over a hydrological year (November 2017 to October 2018) to determine runoff and concentrations of nitrate (N-NO3−) and phosphate (P-PO43−). The ReCiPe 2016 method, as a tool for LCIA, was used to quantify the eutrophication potential, converting N and P concentrations into nitrogen equivalents (N eq ha−1 sub-catchment) for marine eutrophication and phosphorus equivalents (P eq ha−1 sub-catchment) for freshwater eutrophication. The potential loss of species (species·yr ha−1 sub-catchment) was assessed as follows. Results indicate UFS has about 60% lower freshwater and 80% lower marine eutrophication potential compared to LAS, along with about 60% lower potential for biodiversity loss. This highlights the role of forest and grassland covers in mitigating eutrophication and protecting water sources. These findings can guide landscape management practices to reduce eutrophication potential, enhancing environmental quality and biodiversity conservation. [ABSTRACT FROM AUTHOR]

In the contemporary agricultural landscape, agriculture faces four pressing demands: competitiveness, ensuring food security for a growing population, environmental sustainability, and providing farmers with acceptable living conditions. To meet this global challenge, digital technologies represent a major avenue for innovation and development towards modernized digital agriculture. In this context, irrigation advisory platforms have proven to be transformational tools for both farmers and policymakers, offering insights into the appropriate crop water requirements. This article presents a benchmarking analysis of around 20 professional irrigation advisory platforms. The methodology involves selecting 20 platforms based on accessibility ensuring geographical characteristic diversity. Our findings highlight key criteria shaping the ecosystem of such platforms, including the services offered and their objectives, the types of covered crops, the target users, the form, as well as the source, the availability of the platform, and the variety of data utilized. Lastly, we discuss the main conclusions drawn from our analysis and provide insights into the challenges and future perspectives of irrigation advisory platforms in enhancing agricultural practices and sustainability. [ABSTRACT FROM AUTHOR]

Agricultural practices have a significant impact on stream water quality in rural landscapes; however, there is still little empirical evidence of how different types of cultivation alter the hydrochemistry of running water. Thus, the current study explored the spatial dynamics of selected ion concentrations and their land cover dependence in lowland agricultural catchments. From November 2021 to October 2022, water samples were collected from 30 sites located across small tributaries of the rivers Bzura, Pilica, and Radomka for chemical analysis of their NO3, NO2, NH4, Ca, Mg, K, Na, As, Ba, Sr, and V concentrations. The results indicated a clear spatial heterogeneity of water quality, related to lithology and dominant land cover evaluated with the CORINE Land Cover 2018 dataset. Overall, sites representing agricultural land promoted increased concentrations of major and trace elements, while those with pepper cultivation were additionally contaminated with NO3 and NO2. The correlation performance for nitrogen compounds was the highest for narrower buffer zones, which was not documented for major and trace elements, which were linked more strongly with land cover at larger scales. Such new insights into the water quality dynamics of lowland agricultural catchments, being a simultaneous reflection of lithology, agricultural practices, and several municipal impacts, have significant implications for appropriate water management in rural landscapes. [ABSTRACT FROM AUTHOR]

The aim of this study was to use landscape grass from species-rich orchards for biogas production, thus preserving these very valuable areas for future generations. Since these grass clippings have high lignocellulose content, the substrate has to be pretreated before being fed into the biogas digester. In this study, three different mechanical treatment processes (cross-flow grinder, ball mill and a mounted mower) were investigated and compared with untreated grass clippings. Chemical composition, specific methane yield, degradation kinetics and microscopic images were analyzed. In order to derive recommendations, the harvesting and pretreatment processes were examined in terms of energy demand, additional methane yield, and suitability of the substrate for use in biogas plants, taking into account conservation aspects. Within the pretreatment process, ball milling leads to the highest significant increase in specific methane yield of up to 5.8% and the fastest gas formation kinetics (lag time λBM: 0.01 ± 0.0 d; duration to reach half of total gas production ½M(x)BM: 5.4 ± 0.2 d) compared to the untreated variant (λUT: 1.02 ± 0.2 d; ½M(x)UT: 6.5 ± 0.2 d). A comparison of the energy required for the mechanical disintegration of the substrates with the increased yield of methane during the digestion process shows that the mechanical processing of these substrates appears to be useful. A positive energy balance was achieved for the cross-flow grinder (12.3 kWh tVS−1) and the ball mill (21.4 kWh tVS−1), while the Amazone Grasshopper left a negative balance (−18.3 kWh tVS−1), requiring more energy for substrate pretreatment than was generated as methane surplus. In summary, the pretreatment of landscape management grass is a suitable approach for utilizing agricultural residues efficiently in a biogas plant and thus contributing to sustainable energy production. [ABSTRACT FROM AUTHOR]

Grassland is grouped into temporary, permanent, and rough grazing types in the United Kingdom (UK), making up more than 60% of the national agricultural land area. It provides avenues for grazed fodder or ensiled forage contributing a large proportion of the diets consumed by cattle and sheep. The official agricultural census data in 2011 to 2020 showed that, on average, UK cattle and sheep farming can produce meat to satisfy 83.3 and 100.8% of domestic cattle beef and sheep meat consumption levels, respectively. Out of the large agricultural census datasets, we used the populations of cattle and sheep, as well as the UK definition of a standard livestock unit (SLU), to normalise the respective herd populations into a total standard livestock unit (TSLU). We then used the annual domestic meat production in dressed carcass weight to calculate cattle and sheep meat productivity per SLU. Using the potential herbal dry matter yields per year and areas of the different grassland types across the UK, the potential total available pasture feed was calculated. This potential production of herbal biomass was translated into the potential carrying capacity expressed in a TSLU. This total potential carrying capacity was partitioned into cattle and sheep sectors so that the routes of pasture-based-only options with which to produce ruminant meat to meet the current UK domestic consumption demands were assessed. The estimated mean potential annual pasture forage feed in 2011–2020 was approximately 82.0 million (M) metric tonnes (t), which can be translated into a potential carrying capacity of 17.9 M SLUs compared with the current mean 9.36 M SLUs in the survey data of the UK. With the ratio of sheep to cattle at 8.2:25 in the national TSLU, the UK national demands at present consumption levels of cattle and sheep meat can be arithmetically met with pasture grass utilisation rates at or above 65% and 50% by cattle and sheep farming systems, respectively. [ABSTRACT FROM AUTHOR]

The evolving customer demands have significantly influenced the operational landscape of agricultural companies, including the transformation of their supply chains. As a response, many organizations are increasingly adopting green supply chain practices. This paper focuses on the initial step of selecting a green supplier, using the case study of the Semberka Company. The objective is to align the company with customer requirements and market trends. Expert decision making, grounded in linguistic values, was employed to facilitate the transformation of these values into fuzzy numbers and subsequently derive rough number boundaries. Ten economic-environmental criteria were identified, and six suppliers were evaluated against these criteria. The fuzzy rough LMAW (Logarithm Methodology of Additive Weights) method was employed to determine the criteria weights, with emphasis placed on the quality criterion. The fuzzy rough MABAC (Multi-Attributive Border Approximation Area Comparison) method was then utilized to rank the suppliers and identify the top performer. The validity of the results was established through validation techniques and sensitivity analysis. This research contributes a novel approach to green supplier selection, employing the powerful tool of fuzzy rough sets. The flexible nature of this approach suggests its potential application in future investigations. The limitation of this study is more complicated calculations for the decision maker. However, this approach is adapted to human thinking and minimizes ambiguity and uncertainty in decision making, and in future research, it is necessary to combine this approach with other methods of multi-criteria analysis. [ABSTRACT FROM AUTHOR]

In agricultural landscape management, the conventional top-down approaches that primarily focus on market-led responses struggle to preserve the landscape elements essential for environmental sustainability. To address this deficiency, land use and land cover change (LUCC) scenarios promote an integrated understanding of landscape dynamics and highlight the inconsistency between the compartmentalisation of the public sector ("siloisation") and the necessity for management that reflects the interdependencies of socio-ecological systems. This study investigates the extent to which the creation and dissemination of LUCC scenarios lead to modifications in the values, attitudes, and behaviours of local actors engaged in land management, giving particular emphasis to the role of these scenarios in encouraging integrated management. To accomplish this objective, we interviewed local actors who actively participated in the co-construction of the scenario narratives or learned about the scenarios during dissemination workshops. We then analysed the data via a thematic and lexicometric analysis. The findings highlighted the dual function of these scenarios as a catalyst for pre-existing political will to promote integrated management and as a tool for raising awareness about major environmental challenges. At the group level, the outcomes encompassed aspects such as basing political decisions on the results of scenarios and fostering collaboration between institutions. These outcomes were observed among the actors involved in co-constructing scenarios or those with pre-existing motivations to pursue integrated management initiatives. Additional personal outcomes included an increased awareness of environmental challenges and the consolidation of non-formalised knowledge. We argue that combining co-construction and dissemination enhances the outcomes of scenarios considerably. [ABSTRACT FROM AUTHOR]

Information on the spatiotemporal variability of soil properties and states within the agricultural landscape is vital to identify management zones supporting precision agriculture (PA). Ground-penetrating radar (GPR) and electromagnetic induction (EMI) techniques have been applied to assess soil properties, states, processes, and their spatiotemporal variability. This paper reviews the fundamental operating principles of GPR and EMI, their applications in soil studies, advantages and disadvantages, and knowledge gaps leading to the identification of the difficulties in integrating these two techniques to complement each other in soil data studies. Compared to the traditional methods, GPR and EMI have advantages, such as the ability to take non-destructive repeated measurements, high resolution, being labor-saving, and having more extensive spatial coverage with geo-referenced data within agricultural landscapes. GPR has been widely used to estimate soil water content (SWC) and water dynamics, while EMI has broader applications such as estimating SWC, soil salinity, bulk density, etc. Additionally, GPR can map soil horizons, the groundwater table, and other anomalies. The prospects of GPR and EMI applications in soil studies need to focus on the potential integration of GPR and EMI to overcome the intrinsic limitations of each technique and enhance their applications to support PA. Future advancements in PA can be strengthened by estimating many soil properties, states, and hydrological processes simultaneously to delineate management zones and calculate optimal inputs in the agricultural landscape. [ABSTRACT FROM AUTHOR]

Non-point sources of water pollution caused by agricultural crop production are a serious problem in Czechia, at present. This paper describes a new approach for the mutual delineation and assessment of different pollution sources where the critical points method is used to identify the origin of contamination and the source areas. The critical points, i.e., sites presenting the entry of quick surface and drainage runoff into waters, are classified into three (for surface pollution sources using a WaTEM/SEDEM model) or four (subsurface = drainage sources via the catchment-measures need index) categories, respectively. This enabled us to prioritize the most endangered areas at different scales, ranging from the third-order catchments to very small subcatchments, and to design the appropriate combination of control measures to mitigate surface and drainage water runoff, with these being the main drivers of associated pollution. This methodology was applied to a study conducted in the Czech Republic within the entire Vltava River basin, with a total area of 27,578 km2, and utilized in depth to assess a 543 km2 catchment of the Vlašimská Blanice River. When the effect of the designed surface runoff control measures system had been assessed for sediment transport through outlet profiles of the fourth-order catchments, the average reduction reached 43%. The total reduction in the subsurface transport of nitrogen within the fourth-order catchments was 24%. The approach and results are planned to be projected into river basin management plans for the Vltava River basin. Nevertheless, a thorough reassessment of current legislations and strategies is needed to enable the broader adoption of mitigation measures and sustainable management patterns within agricultural landscapes. [ABSTRACT FROM AUTHOR]

Sustainable agricultural landscape management needs reliable and accurate soil maps and updated geospatial soil information. Recently, machine learning (ML) models have commonly been used in digital soil mapping, together with limited data, for various types of landscapes. In this study, we tested linear and nonlinear ML models in predicting and mapping soil properties in an agricultural lowland landscape of Lombardy region, Italy. We further evaluated the ability of an ensemble learning model, based on a stacking approach, to predict the spatial variation of soil properties, such as sand, silt, and clay contents, soil organic carbon content, pH, and topsoil depth. Therefore, we combined the predictions of the base learners (ML models) with two meta-learners. Prediction accuracies were assessed using a nested cross-validation procedure. Nonetheless, the nonlinear single models generally performed well, with RF having the best results; the stacking models did not outperform all the individual base learners. The most important topographic predictors of the soil properties were vertical distance to channel network and channel network base level. The results yield valuable information for sustainable land use in an area with a particular soil water cycle, as well as for future climate and socioeconomic changes influencing water content, soil pollution dynamics, and food security. [ABSTRACT FROM AUTHOR]

Continuous observation and management of agriculture are essential to estimate crop yield and crop failure. Remote sensing is cost-effective, as well as being an efficient solution to monitor agriculture on a larger scale. With high-resolution satellite datasets, the monitoring and mapping of agricultural land are easier and more effective. Nowadays, the applicability of deep learning is continuously increasing in numerous scientific domains due to the availability of high-end computing facilities. In this study, deep learning (U-Net) has been implemented in the mapping of different agricultural land use types over a part of Punjab, India, using the Sentinel-2 data. As a comparative analysis, a well-known machine learning random forest (RF) has been tested. To assess the agricultural land, the major winter season crop types, i.e., wheat, berseem, mustard, and other vegetation have been considered. In the experimental outcomes, the U-Net deep learning and RF classifiers achieved 97.8% (kappa value: 0.9691) and 96.2% (Kappa value: 0.9469), respectively. Since little information exists on the vegetation cultivated by smallholders in the region, this study is particularly helpful in the assessment of the mustard (Brassica nigra), and berseem (Trifolium alexandrinum) acreage in the region. Deep learning on remote sensing data allows the object-level detection of the earth's surface imagery. [ABSTRACT FROM AUTHOR]

The problems of atmospheric pollutants are causing significant concern across the globe and in India. The aggravated level of atmospheric pollutants in the surrounding environment poses serious threats to normal living conditions by deteriorating air quality and causing adverse health impacts. Pollutant concentration increases during harvesting seasons of Kharif/Rabi due to stubble burning and is aggravated by other points or mobile sources. The present study is intended to monitor the spatio-temporal variation of the major atmospheric pollutants using Sentinel-5P TROPOMI data through cloud computing. Land Use/Land Cover (LULC-categorization or classification of human activities and natural coverage on the landscape) was utilised to extract the agricultural area in the study site. It involves the cloud computing of MOD64A1 (MODIS Burned monthly gridded data) and Sentinel-5P TROPOMI (S5P Tropomi) data for major atmospheric pollutants, such as CH4, NO2, SOX, CO, aerosol, and HCHO. The burned area output provided information regarding the stubble burning period, which has seen post-harvesting agricultural residue burning after Kharif crop harvesting (i.e., rice from April to June) and Rabi crop harvesting (i.e., wheat from September to November). The long duration of stubble burning is due to variation in farmers' harvesting and burning stubble/biomass remains in the field for successive crops. This period was used as criteria for considering the cloud computing of the Sentinel-5P TROPOMI data for atmospheric pollutants concentration in the study site. The results showed a significant increase in CH4, SO2, SOX, CO, and aerosol concentration during the AMJ months (stubble burning of Rabi crops) and OND months (stubble burning of Kharif crops) of each year. The results are validated with the ground control station data for PM2.5/PM10. and patterns of precipitation and temperature-gridded datasets. The trajectory frequency for air mass movement using the HYSPLIT model showed that the highest frequency and concentration were observed during OND months, followed by the AMJ months of each year (2018, 2019, 2020, and 2021). This study supports the role and robustness of Earth observation Sentinel-5P TROPOMI to monitor and evaluate air quality and pollutants distribution. [ABSTRACT FROM AUTHOR]

Tropical dry forests (TDFs) represent 42% of all tropical forests; they are extensive, but little is known of their structure and function. The fine litterfall represents the main route of circulation of organic materials and nutrients in these ecosystems. The objective of this study was to compare several remnants of TDFs located in contrasting landscape units—Mountain and Lomerio—and with different precipitation, in terms of the fluxes of organic materials to the soil, derived from the production of fine litterfall from the canopy. The fine litterfall (including woody material up to 2 cm in diameter) was collected monthly from April 2020 to March 2021, in 29 circular plots of 500 m2 randomly established. High rates of litterfall were recorded in the Lomerio landscape (4.9 Mg ha−1) than in the Mountain landscape (4.5 Mg ha−1). The monthly leaf litter production showed clear seasonal patterns, which were largely driven by the importance of the species in the landscape and the effect of precipitation during the study. Annual fine litter production observed in this study in comparison with other TDFs indicates relevant productivity levels, which contribute to the activation of biogeochemical cycles and improved ecosystem functionality. [ABSTRACT FROM AUTHOR]

Water scarcity is a growing challenge in semi-arid and sub-humid areas. There are over 2000 small reservoirs (SRs) with storage capacities of up to 1 × 106 m3 across West Africa's dry areas. Based on a comprehensive literature review, we found strong evidence that SRs enable improved food security, livelihoods, and income diversification through fishing and livestock production. However, their productivity is far below their potential. Evidence on water quantity and quality is scattered, making deriving conclusions difficult. Review findings suggest that, unlike large dams, SRs have minimal impact on water balance and rainfall-runoff. There is, therefore, considerable potential to develop more SRs. However, high rates of sedimentation substantially reduce reservoir storage capacity. Poor irrigation management and agronomic practices also contribute to low productivity. Water quality is not systematically monitored, so SRs can increase health risks such as malaria and schistosomiasis. With the intensification of settlements, livestock, and agriculture around the reservoirs, it is critical to improve water quality and quantity monitoring. We conclude that SRs are important nature-based solutions, but need more investment to support the climate-proofing of agriculture and livelihoods. We recommend governments develop long-term small reservoir support programs to strengthen local capacities to manage the reservoirs and their watersheds sustainably. [ABSTRACT FROM AUTHOR]

The P-factor for support practice of the Universal Soil Loss Equation (USLE) accounts for soil conservation measures and leads to a significant reduction in the modelled soil loss. However, in the practical application, the P-factor is the most neglected factor overall due to high effort for determining or lack of input data. This study provides a new method for automatic derivation of the main cultivation direction from seed rows and tramlines on agricultural land parcels using the Fast Line Detector (FLD) of the Open Computer Vision (OpenCV) package and open remote sensing data from Google Earth™. Comparison of the cultivation direction with the mean aspect for each land parcel allows the determination of a site-specific P-factor for the soil conservation measure contouring. After calibration of the FLD parameters, the success rate in a first application in the low mountain range Fischbach catchment, Germany, was 77.7% for 278 agricultural land parcels. The main reasons for unsuccessful detection were problems with headland detection, existing soil erosion, and widely varying albedo within the plots as well as individual outliers. The use of a corrected mask and enhanced parameterization offers promising improvements for a higher success rate of the FLD. [ABSTRACT FROM AUTHOR]

Farmland scale management represents an inevitable trend toward global modern agriculture. In the new development context, the key to solving the tough problem of the insufficient supply of rural public goods is to effectively improve the enthusiasm of farming households to participate in rural collective action in countries with a small arable area per capita, such as India, China and countries in Eastern Europe. This paper adopts the Institutional Analysis and Development (IAD) framework in the context of a land system with Chinese characteristics, and uses sample data of 3663 rural households in 17 provinces to study the impact of farmland scale and various relevant systems on farming households' participation in rural collective action. We found that the advantages of collective action, such as reduced production costs, enhanced risk resistance and improved production efficiency, can offset the disadvantages incurred by free-riding behavior, and the expansion of farmland scale can significantly facilitate rural collective action. Additionally, as the farmland scale expands, stable farmland tenure and reasonable farmland tenure transfer can help to optimize the allocation of arable land resources, increase investment, and reduce free-riding behavior, thus effectively stimulating farming households to actively participate in collective action. However, since socialized agricultural services lead to the separation of the suppliers and the users of rural public goods, the expansion of farmland scale shows a negative effect. Therefore, in the context of the continuous migration of the rural population to cities, a stable farmland tenure adjustment mechanism should be established, while the balance between farmland tenure transfer and socialized agricultural services, in pushing forward rural collective action, should be emphasized, so as to ensure the effective supply of rural public goods in propelling farmland scale management. Especially in promoting the development of socialized agricultural services, more attention should be paid to specifying the responsibilities and obligations of the main provider of commercialized services in the supply of rural public goods. [ABSTRACT FROM AUTHOR]

As the world becomes increasingly urbanized, it is vital for planners and policy-makers to understand the patterns of urban expansion and the underlying driving forces. This study examines the spatiotemporal patterns of urban expansion in the Texas Triangle megaregion and explores the drivers behind the expansion. The study used data from multiple sources, including land cover and imperviousness data from the National Land Cover Database (NLCD) 2001-2016, transportation data from the Texas Department of Transportation (TxDOT), and ancillary socio-demographic data from the U.S. Census Bureau. We conducted spatial cluster analysis and mixed-effect regression analysis. The results show that: (1) urban expansion in the Texas Triangle between 2001 and 2016 showed a decreasing trend, and 95% of the newly urbanized land was in metropolitan areas, especially at the periphery of the central cities; (2) urban expansion in non-metropolitan areas displayed a scattered pattern, comparing to the clustered form in metro areas; (3) the expansion process in the Texas Triangle exhibited a pattern of increased development compactness and intensity; and (4) population and economic growth played a definitive role in driving the urban expansion in the Texas Triangle while highway density also mattered. These results suggest a megaregion-wide emerging trend deviating from the sprawling development course known in Texas' urban growth history. The changing trend can be attributed to the pro-sustainability initiatives taken by several anchor cities and metropolitan planning agencies in the Texas Triangle. [ABSTRACT FROM AUTHOR]

Promoting the preservation and appreciation of ecosystem services is an important value guide for land use optimization. In this research, Fengdu County in the Three Gorges Reservoir Area was selected as the focus of a case study. From the perspective of the source and sink landscape of ecosystem services, a MOP model and FLUS model were used to optimize the areas of various land use types and the spatial configurations of those land use types in the study area in 2035 under a strict ecological constraint (SEC) scenario, a moderate ecological constraint (MEC) scenario, and a relaxed ecological constraint (REC) scenario. We also superimposed and adjusted the results of land use optimization under the three ecological constraint scenarios, and obtained land use regionalization results that integrated multiple scenarios. The results indicated that (1) there were large differences in the areas and spatial distributions of the source and sink landscapes under the three scenarios. Under the SEC scenario, the important source landscapes (ISLs), common source landscapes (CSLs), and sink landscapes (SLs) areas covered 1676.62 km², 1190.43 km², and 33.81 km², respectively. A large area of the CSLs and a small area of the SLs were transformed into ISLs area, and the degree of fragmentation of the landscape was low. Under the MEC scenario, the ISLs, CSLs, and SLs areas covered 1609.22 km², 1241.60 km², and 49.74 km², respectively. The development of the source landscapes and sink landscapes was similar, and the degree of fragmentation was moderate. Under the REC scenario, the ISLs, CSLs, and SLs areas covered 1603.96 km², 1243.32 km², and 53.58 km², respectively. A large area of CSLs was transformed into SLs area, and the degree of fragmentation was high. (2) Fengdu County was divided into seven types of areas: ecological conservation area; agricultural production area; construction optimization area; construction-ecological area; ecological-agricultural area; agricultural-construction area; and integrated development area. The results of this study can provide references for the territorial spatial planning and management of ecological barrier zones. [ABSTRACT FROM AUTHOR]

The trade agreement between the European Union and the Mercosur countries will increase deforestation in the Mercosur countries and Brazil, in particular, if ratified by member countries. We use a computable general equilibrium model to analyze how trade, land use, and agricultural production will change as a result of the agreement. We then use a statistical model to spatially allocate the predicted deforestation within the Brazilian Amazon. The models estimate that the agreement will cause additional deforestation in Brazil ranging from 56 to 173 thousand ha to accommodate increases in cropland area, depending on the level of governance, use of double-cropping techniques, and trade elasticity parameters. Most additional deforestation in Amazonia would be clustered near current deforestation hotspot areas. Some hotspots threaten the integrity of Indigenous lands and conservation units. Although a low deforestation scenario with gains in welfare is theoretically possible when high governance and multiple-cropping systems are in place, political challenges remain and cast doubt on Brazil's ability to rein on illegal deforestation. [ABSTRACT FROM AUTHOR]

Dynamics of arable and pastoral farming systems in Scotland over the period 1867-2020 are documented using time series analysis methods, including for nonlinear dynamical systems. Results show arable and pastoral farming, at a national scale, are dynamic over a range of timescales, with medium- and short-term dynamics associated with endogenous system forces and exogenous factors, respectively. Medium-term dynamics provide evidence of endogenous systems-level feedbacks between farming sectors responding to change in world and national cereal prices as an economic driver, and act to dampen impacts of exogenous shocks and events (weather, disease). Regime shifts are identified in national cereal prices. Results show change and dynamics as emergent properties of system interactions. Changes in dynamics and strength of endogenous dampening over the duration of the study are associated with dynamical changes from major governmental policy decisions that altered the boundary conditions for interdependencies of arable and pastoral farming. [ABSTRACT FROM AUTHOR]

Natural resource management has entered a new stage in 2018 in the People's Republic of China (China) marked by the establishment of the Ministry of Natural Resources of China (MNRPRC). More functions and responsibilities are integrated in the MNRPRC to build a uniform management system for full natural resource features in China with the aim of implementing uniform spatial planning and regulation, management, use and control, surveying, and registration for full natural resources. This paper first provides a detailed analysis regarding full natural resources with the perspectives of spatial forms and rights, restrictions, and responsibilities (RRRs); then, the modelling foundation of the "uniform" concept in natural resource registration is reconsidered. Lastly, we put forward a basic conceptual model for the uniform registration of full natural resources based on LADM (Land Administration Domain Model). [ABSTRACT FROM AUTHOR]

Global land ownership patterns have been shifting in recent decades, as institutional and non-traditional investors redirect capital into rural areas. Such investment is a stimulating alternative for innovative profit-driven land uses that move beyond agriculture. This paper explores how 'new money' economies have created place effects in three rural case studies across the United Kingdom, through concepts of built, natural, social, and economic capital. The case studies are informed by secondary research, site visits, and interviews, providing snapshots of investment impact. They represent diverse transformations in rural land use via new forms of direct investment, active investment, and processes of financing rather than financialisation, with distinct spatial and temporal characteristics. The case studies include new wine production in Kent, England; transforming the Menie Estate into Trump International Golf Links Scotland (TIGLS); and farm diversification in Northern Ireland. The conclusions tell three investment stories, where place effects reflect the dichotomies, contestation, and symbiosis between investors and local contexts. New land uses create place effects where economic potential often conflicts with natural capital impacts, although they foster knowledge creation and exchange. The underlying values of the investors and their navigation of local politics also have key roles to play in shaping the built, natural, social, and economic place effects. [ABSTRACT FROM AUTHOR]

Terraced tourism sustainability depends on maintenance for terraced landscape. The effective measures for protecting terraces rest on the cooperation among multi-stakeholders. Therefore, a multi-stakeholder involvement mechanism (MSIM) is very important for terraced landscape conservation. Dazhai village in Longji Terraces, Guangxi Province, Southwest China, explored a MSIM to maintain terraced tourism sustainability in the past 20 years. Based on the statistical data and the data from household interviews, this study analyses the development history of Dazhai tourism. Comparing the changes in different stages in components of MSIM of Dazhai, we revealed the successful key factors of MSIM for maintaining terraces tourism sustainability includes identifying accurately core attractions and stakeholders, an effective communication strategy, a democratic decision-making mechanism, dynamic benefit distribution schemes (BDS) facing terraced conservation, coordination teams with foresight and selflessness, and the effective supervision and management. In the end, we conclude that economic income is the most important driver stimulating villagers in Dazhai to insist on growing rice. It is crucial factor to drive farmers to protect their terraces. but economic income improvement of the households depends on a systemic and dynamic MSIM. The most important causes for Dazhai MSIM success results from the wise coordination teams and the effective communication strategy. [ABSTRACT FROM AUTHOR]

Abandonment of agricultural land is a process described from different regions of many industrialized countries. Given the current focus on land use, land use change and food security, it appears highly relevant to develop improved tools to identify and monitor the dynamics of agricultural land abandonment. In particular, the temporal aspect of abandonment needs to be assessed and discussed. In this study, we used the detailed information available through the Norwegian subsidy claim database and analyzed the history of use of unique land parcels through a fourteen-year period. We developed and tested five different statistics identifying these land parcels, their temporal dynamics and the extent of occurrence. What became apparent was that a large number of land parcels existing in the database as agricultural land were taken out of production, but then entered into production again at a later stage. We believe that this approach to describe the temporal dynamics of land abandonment, including how it can be measured and mapped, may contribute to the understanding of the dynamics in land abandonment, and thus also contribute to an improved understanding of the food production system. [ABSTRACT FROM AUTHOR]

Despite the need for preserving the carbon pools in fire-prone southern European landscapes, emission reductions from wildfire risk mitigation are still poorly understood. In this study, we estimated expected carbon emissions and carbon credits from fuel management projects ongoing in Catalonia (Spain). The planning areas encompass about 1000 km2 and represent diverse fire regimes and Mediterranean forest ecosystems. We first modeled the burn probability assuming extreme weather conditions and historical fire ignition patterns. Stand-level wildfire exposure was then coupled with fuel consumption estimates to assess expected carbon emissions. Finally, we estimated treatment cost-efficiency and carbon credits for each fuel management plan. Landscape-scale average emissions ranged between 0.003 and 0.070 T CO2 year−1 ha−1. Fuel treatments in high emission hotspots attained reductions beyond 0.06 T CO2 year−1 per treated ha. Thus, implementing carbon credits could potentially finance up to 14% of the treatment implementation costs in high emission areas. We discuss how stand conditions, fire regimes, and treatment costs determine the treatment cost-efficiency and long-term carbon-sink capacity. Our work may serve as a preliminary step for developing a carbon-credit market and subsidizing wildfire risk management programs in low-revenue Mediterranean forest systems prone to extreme wildfires. [ABSTRACT FROM AUTHOR]

The dry stone wall landscape surrounding the town of Cres is a unique cultural landscape; it is one of the largest well-preserved historical olive groves in the Croatian Adriatic, while simultaneously serving as pasture for sheep. Still, there are currently no studies that capture this landscape as a multifunctional whole or which acknowledge its relevance within the current multidisciplinary discussions. The aim of this paper is to clarify past and current circumstances surrounding and affecting it. The study focuses on two main pillars of landscape preservation: (1) dry stone wall structures and (2) agro-pastoral practices; giving an overview of its historical formation and current management and trends. The goal is to establish knowledge that can be used as a foundation for the management of this area and present a good practice example for the preservation of historical landscapes in the Mediterranean region. The research involved combined desk and fieldwork: cartographic data analysis, literature analysis, GIS elaboration, terrestrial and aerial photographs and observations, followed by interviews with local informants. Continuous investing in the production of quality olive oil and the evolution of the landscape into a multifunctional agro-pastoral-touristic space is what enabled its preservation. This multifunctionality can only be matched by a diversity of scientific studies and this study aimed at providing the first step--a foundation for the identification of the values of the Cres landscape, with the scope of better precising further planning and management. [ABSTRACT FROM AUTHOR]

Agricultural land demand tends to be in weak condition vis-à-vis settlement development, transport infrastructure and industry expansion. At the same time, the awareness and demand of consumers for regional food is constantly rising, in particular in urban regions. The resulting challenge is that high demand for regional food is concentrated at places where land for food production tends to be particularly under pressure. Against this background, our article reflects on the extent to which regional food supply chains support the status of agricultural demand in the competition for land. The main aim of our paper is to understand the role of proximity between the different stages of value creation, including cultivation, production (manual or industrial) and trade (retail, direct marketing). Our empirical study on the example of three products in Bavaria (Germany) shows that short distances within food value chains support the agricultural condition in land use dynamics (beer, sweet cherry, asparagus). The analyses are based on official and internal statistics as well as expert interviewing. This mixed-methods approach results in value-creation mappings and provides spatial differentiation of the economic process. Proximity between at least two stages of value creation plays an important role to explain the economic trends and land use dynamic. These findings are rooted in arguments of efficiency, tacit knowledge, networks, as well as product reputation. However, the role of proximity does not automatically play a role but has to be stabilized by strategic measures such as product innovation and marketing measures. [ABSTRACT FROM AUTHOR]

Since Important Agricultural Heritage Systems (IAHS) were launched by the FAO to protect the sustainable traditional agricultural systems around the world, their conservation has become a new difficult issue under the context of urbanization. Farmers in IAHS sites giving up small-scale traditional farming due to their low economic benefit and high labor intensity are considered as the main cause hindering effective conservation of these heritages. This study takes the Kuancheng traditional chestnut cultivation system (KTCCS) in northern China as a case to assess its economic and socio-cultural sustainability. Based on questionnaires and interviews, this study found that: the traditional ecological farming methods were still used by local farming households to plant chestnut trees; and most farmers support IAHS conservation. KTCCS performs economic and socio-cultural sustainability. For a household, the labor productivity of chestnut cultivation was 1.33 times that of their non-farm jobs because of the low labor input of chestnut cultivation. Farmers widely consider they live in a harmonious social environment but are lower than other households in economic status. Most farmers still lack an understanding of indigenous traditional knowledge and cultures. In the future, secondary and tertiary industries should be developed to provide farmers with employment opportunities in their hometowns for protecting KTCCS. [ABSTRACT FROM AUTHOR]

Land integration is an important means of increasing the multifunctional value of arable land. The scientific measurement of the integrative value of arable land before and after land consolidation can improve farmers' overall understanding of the value of arable land, increase their awareness of arable land protection, and encourage them to implement arable land protection policies. Additionally, it can provide a theoretical basis for the formulation of reasonable compensation standards for arable land in various areas of the Manas River Basin and effectively promote the use of the "Shawan model". In this paper, the sample used for the survey was made up of 380 farmers from 10 villages in three different regions of Shawan City (county-level city). The participatory farmer assessment (PRA) method was used to conduct a detailed investigation of the integration of farmers' cultivated land, while the landscape pattern index method was used to analyze the intensity of the cultivated land integration pattern. By constructing a measurement system for the integrative value of cultivated land and adding up the economic, pro-ecological, and social values before and after the integration of the cultivated land, estimated using the income reduction method, the equivalent factor method, and the shadow engineering method, we found that the cultivated land in each region of Shawan City (county-level city) was more effectively integrated, the scale of the field expanded, the shape of the patches tended to be more regular, and the field surface more flat. However, the degree of integration varied from region to region, with the degree of integration from the largest to the smallest as follows: oasis agricultural zone > oasis/desert ecological zone > hilly zone. We found that the integration of cultivated land has a significant effect on the integrated value of cultivated land, and the value of cultivated land in different regions showed different degrees of improvement after integration. The cultivated land of villages located in the oasis/desert ecotone showed a significant overall improvement after integration, followed by cultivated land in the oasis agricultural area. The value of cultivated land increased significantly, while the value of cultivated land in the hilly area showed less improvement after integration. The value of cultivated land integration in different regions is related to the intensity of the cultivated land integration, the per capita cultivated land area, the ecosystem biomass, and the crop planting area. The purpose of this paper is to effectively diagnose and promote the "Shawan Model" (land integration), formulate reasonable compensation standards for cultivated land in different regions of the Manas River Basin, and implement cultivated land protection policies. [ABSTRACT FROM AUTHOR]

The Anxi Tieguanyin Tea Culture System, as the proposed location of a globally important agricultural heritage system (GIAHS), has demonstrated the great significance of a network of heritage settlements and landscapes and supported rural revitalization and the participation and empowerment of women, based on agricultural heritage. Through fieldwork, participant observation, and in-depth interviews, this study attempts to analyze the experience of rural revitalization in Xiping. Firstly, the unique cultural heritage found within the agricultural landscape, formed by the multiparty linkage and dynamic adaptation of the surrounding natural environment by local residents, has shaped the Anxi Tieguanyin tea culture system of Xiping. Secondly, local residents actively participate in tea competitions and tea associations, so that the implementation process of agricultural cultural heritage preservation and development can be from the perspective of a shared experience. Thirdly, intangible cultural heritage features, such as the Female Tea Master Training Institute, have played a vital role in the development of tea towns and have proved conducive to women's participation and empowerment. The results show that the agricultural heritage of the area, based on the Tea Manor and its multi-functional resources, has helped Xiping to move toward a more sustainable future, while eventually supporting a local society with a more distinctive rural landscape of which people can be proud. This system meets the need for local socio-economic and cultural development, and the promotion of the sustainable development of the entire region. [ABSTRACT FROM AUTHOR]

The intensification of agriculture over the last few decades has caused habitat loss, which poses a significant threat to the survival of populations and species. Where habitats are connected, populations may escape the destruction of their habitat by migrating to another one. Consequently, the functional connectivity of landscapes has become an important focus for species conservation. Kettle holes are hotspots of biodiversity that provide suitable conditions for wildlife species (i.e., amphibians, insects, aquatic plants) and contribute to landscape heterogeneity. They are also considered to function as stepping stone habitats that contribute to habitat connectivity. This study assesses the contribution of kettle holes for (i) habitat provision and (ii) the functional connectivity of three amphibian species with different movement ranges, and (iii) the study identifies areas where the creation of stepping stone biotopes could improve functional connectivity. The contribution of kettle holes was assessed using GIS-based clustering within three research areas in Germany. It was found that the importance of kettle holes for providing amphibian habitats in the three studied areas was equal to or higher than that of other wetland habitats. The state of functional connectivity and the contribution of kettle holes differed strongly depending on the species’ range. For the short-range species, landscapes were highly fragmented, and the contribution of kettle holes was much smaller than that of corridor habitats. For the long-range species, all habitats suited for amphibian reproduction were connected, and the contribution of kettle holes was similar to that of corridor habitats. However, the contribution of both was mostly redundant. Overall, the results showed that kettle holes play a crucial role in habitat provision and function as important stepping stone biotopes in agricultural landscapes. The clustering method applied in this study provides a simple tool for landscape planning and environmental protection agencies, which can be easily adapted to analyze functional connectivity and habitat interactions for different species or landscapes. [ABSTRACT FROM AUTHOR]

Featured Application: An integrated method was applied in this study to analyze the processes of agricultural evolution. Our methods can be an exemplary for other agro-pastoral ecotone or ecologically fragile area in other world's regions, highlighting the application of an integrated method for land-use change analysis. Assessing historical landscape change and its related land–use changes is necessary for understanding agricultural evolution processes and their ecological effects. In our study, the landscape patterns of paddy fields and dry farmland were studied using information obtained from remote-sensing data. Land-use changes related to cultivated land were analyzed based on transition probability index and trajectory computing method. Furthermore, the possible driving force and water resource effect of cultivated land changes were discussed. The results indicated that paddy field and dry farmland expanded by 56.99% and 10.92% in the West Songnen Plain, respectively, compared with their own area in 1990. Trajectory analyses showed that dry farmland was usually more stable than paddy field. Climate warming, wind speed reduction, population growth, technological development, as well as land use policies all drove cultivated land changes. The net water consumption of cultivated land showed an increased trend. To achieve the sustainable development of land-system, optimizing land-use structure as well as configuration between water and soil resources should be given more attention in the future. [ABSTRACT FROM AUTHOR]

Mountain pine beetle (Dendroctonus ponderosae Hopkins; MPB) is an aggressive bark beetle that attacks numerous Pinus spp. and causes extensive mortality in lodgepole pine (Pinus contorta Douglas ex Loudon; LPP) forests in the western United States and Canada. We used pre-outbreak LPP attributes, cumulative MPB attack severity, and areal extent of mortality data to identify subwatershed-scale forest attributes associated with severe MPB-caused tree mortality that occurred across the Northern Rockies, USA from 1999-2014. We upscaled stand-level data to the subwatershed scale to allow identification of large LPP areas vulnerable to MPB. The highest mortality occurred in subwatersheds where LPP mean basal area was greater than 11.5 m² ha-1 and LPP quadratic mean diameter was greater than or equal to 18 cm. A coarse assessment of federally-owned LPP-dominated forestland in the analysis area indicated about 42% could potentially be silviculturally treated. Silvicultural management may be a suitable option for many LPP forests, and our hazard model can be used to identify subwatersheds with LPP attributes associated with high susceptibility to MPB across landscape spatial scales. Identifying highly susceptible subwatersheds can help prioritize general areas for potential treatments, especially where spatially extensive areas of contiguous, highly susceptible LPP occur. [ABSTRACT FROM AUTHOR]

Land use science usually adopts a case study approach to investigate landscape change processes, so we considered a meta-analysis an appropriate tool for summarizing general patterns and heterogeneous findings across multiple case studies over a large geographic area. Mountain landscapes in the Apennines (Italy) have undergone significant variations in the last century due to regional and national socio-economic changes. In this work, we reviewed 51 manuscripts from different databases and examined 57 case studies. We explored heterogeneous data sets, adopting a stepwise approach to select the case studies: Step 1, a general overview of the main studies; Step 2, an analysis of the features of the study sites and of land-use/cover transitions; Step 3, a landscape pattern analysis. We standardized the processing methods to obtain a new set of homogeneous data suitable for comparative analysis. After some pre-processing of the selected paper due to the broad heterogeneity of the data, we calculated common landscape metrics ex novo. We obtained digital images used to perform automatic segmentation with eCognition Developer 64 software. Our review indicated that most case studies were in Central and Southern Italy, 83% were examined at local scale, 77% carried out change detection, but only 38% included both change detection and landscape spatial pattern analysis. The results revealed a clear trend of forest expansion (+78%) and the reduction of croplands (-49%) and grasslands (-19%). We did not find significant changes in the landscape spatial patterns. [ABSTRACT FROM AUTHOR]

Whether or not reservoirs contain water throughout the dry season is critical to avoiding late season crop failure in seasonally-arid agricultural landscapes. Locations, volumes, and temporal dynamics, particularly of small (<1 MmX) reservoirs are poorly documented globally, thus making it difficult to identify geographic and intra-annual gaps in reservoir water availability. Yet, small reservoirs are the most vulnerable to drying out and often service the poorest of farmers. Using the transboundary Volta River Basin (∼ 413,000 sq km) in West Africa as a case study, we present a novel method to map reservoirs and quantify the uncertainty of Landsat derived reservoir area estimates, which can be readily applied anywhere in the globe. We applied our method to compare the accuracy of reservoir areas that are derived from the Global SurfaceWater MonthlyWater History (GSW) dataset to those that are derived when surface water is classified on Landsat 8 OLI imagery using the Normalised Difference Water Index (NDWI), Modified NDWI with band 6 (MNDWI1), and Modified NDWI with band 7 (MNDWI2). We quantified how the areal accuracies of reservoir size estimates vary with the water classification method, reservoir properties, and environmental context, and assessed the options and limitations of using uncertain reservoir area estimates to monitor reservoir dynamics in an agricultural context. Results show that reservoir area estimates that are derived from the GSW data are 19% less accurate for our study site than MNDWI1 derived estimates, for a sample of 272 reservoir extents of 0.09 to 72 ha. The accuracy of Landsat-derived estimates improves with reservoir size and perimeter-area ratio, while accuracy may decline as surface vegetation increases. We show that GSW derived reservoir area estimates can provide an upper limit for current reservoir capacity and seasonal dynamics of larger reservoirs. Data gaps and uncertainties make GSW derived reservoir extents unsuitable for monitoring reservoirs that are smaller than 5.1 ha (holding ∼ 49,759 m3), which constitute 674 (56%) reservoirs in the Volta basin, or monitoring seasonal fluctuations of most small reservoirs, limiting its utility for agricultural planning. This study is one of the first to test the utility and limitations of the newly available GSW dataset and provides guidance on the conditions under which this, and other Landsat-based surface water maps, can be reliably used to monitor reservoir resources. [ABSTRACT FROM AUTHOR]

Freshwater ecosystems are among the most threatened on Earth, facing environmental and anthropogenic pressures often surpassing their terrestrial counterparts. Land use and land cover change (LUCC) such as degradation and fragmentation of the terrestrial landscape negatively impacts aquatic ecosystems. Satellite imagery allows for an impartial assessment of the past to determine habitat alterations. It can also be used as a forecasting tool in the development of species conservation strategies through models based on ecological factors extracted from imagery. In this study, we analyze Landsat time sequences (1984-2015) to quantify LUCC around three freshwater ecosystems with endemic cichlids in Tanzania. In addition, we examine population growth, agricultural expansion, and climate change as stressors that impact the habitats. We found that the natural vegetation cover surrounding Lake Chala decreased from 15.5% (1984) to 3.5% (2015). At Chemka Springs, we observed a decrease from 7.4% to 3.5% over the same period. While Lake Natron had minimal LUCC, severe climate change impacts have been forecasted for the region. Subsurface water data from the Gravity Recovery and Climate Experiment (GRACE) satellite observations further show a decrease in water resources for the study areas, which could be exacerbated by increased need from a growing population and an increase in agricultural land use. [ABSTRACT FROM AUTHOR]

In response to the need for generic remote sensing tools to support large-scale agricultural monitoring, we present a new approach for regional-scale mapping of agricultural land-use systems (ALUS) based on object-based Normalized Difference Vegetation Index (NDVI) time series analysis. The approach consists of two main steps. First, to obtain relatively homogeneous land units in terms of phenological patterns, a principal component analysis (PCA) is applied to an annual MODIS NDVI time series, and an automatic segmentation is performed on the resulting high-order principal component images. Second, the resulting land units are classified into the crop agriculture domain or the livestock domain based on their land-cover characteristics. The crop agriculture domain land units are further classified into different cropping systems based on the correspondence of their NDVI temporal profiles with the phenological patterns associated with the cropping systems of the study area. A map of the main ALUS of the Brazilian state of Tocantins was produced for the 2013-2014 growing season with the new approach, and a significant coherence was observed between the spatial distribution of the cropping systems in the final ALUS map and in a reference map extracted from the official agricultural statistics of the Brazilian Institute of Geography and Statistics (IBGE). This study shows the potential of remote sensing techniques to provide valuable baseline spatial information for supporting agricultural monitoring and for large-scale land-use systems analysis. [ABSTRACT FROM AUTHOR]

This paper discusses the evolution of socio-cultural and political relations that defined access to, use, and management of land resources in northeast Ghana during the pre-colonial and colonial periods. The aim is to historicise current meta-narratives about degradation of the natural landscape in the rural savannahs of northeast Ghana. Many of those degradation narratives take their root in the past during the colonial era, but the conceptual underpinnings of those narratives have remained essentially a-historical, a-political, and a-cultural. This paper shows that the organisation of space and land uses in pre-colonial communities in northeast Ghana was governed by certain traditional knowledge systems which were ignored by the colonial authorities. While narratives about landscape degradation by natives were propagated by the colonial government to justify a need to preserve the environment, their attempts to control land management matters were essentially for political and economic reasons. The study concludes that current policy frameworks on desertification and land management need to move beyond inherent historical biases. Rather, attention ought to be given to critical historical reflections on the dynamic processes by which variations in socio-economic relations of resource access/use, farming practices, land tenure arrangements, and political agendas interact with changes in the biophysical environment to produce different land cover trajectories over time. [ABSTRACT FROM AUTHOR]

The unavoidable diet change in emerging countries, projected for the coming years, will significantly increase the global consumption of animal protein. It is expected that Brazilian livestock production, responsible for close to 15% of global production, be prepared to answer to the increasing demand of beef. Consequently, the evaluation of pasture quality at regional scale is important to inform public policies towards a rational land use strategy directed to improve livestock productivity in the country. Our hypothesis is that MODIS images can be used to evaluate the processes of degradation, restoration and renovation of tropical pastures. To test this hypothesis, two field campaigns were performed covering a route of approximately 40,000 km through nine Brazilian states. To characterize the sampled pastures, biophysical parameters were measured and observations about the pastures, the adopted management and the landscape were collected. Each sampled pasture was evaluated using a time series of MODIS EVI2 images from2000-2012, according to a new protocol based on seven phenological metrics, 14 Boolean criteria and two numerical criteria. The theoretical basis of this protocol was derived from interviews with producers and livestock experts during a third field campaign. The analysis of the MODIS EVI2 time series provided valuable historical information on the type of intervention and on the biological degradation process of the sampled pastures. Of the 782 pastures sampled, 26.6% experienced some type of intervention, 19.1% were under biological degradation, and 54.3% presented neither intervention nor trend of biomass decrease during the period analyzed. [ABSTRACT FROM AUTHOR]

Groundwater overdraft has consequences in the long-run for the economic and ecological sustainability of an agricultural landscape. In response to aquifer depletion, we examine the tradeoff of non-market ecosystem service benefits (e.g., groundwater supply, greenhouse gases, and surface water quality) and market returns from crops in the Lower Mississippi River Delta. Farmers may turn to conjunctive water management using on-farm reservoirs and tail water recovery when groundwater pumping becomes expensive. We use separate objectives for market returns from crops and the non-market benefits of ecosystem services to study whether on-farm reservoirs are built with optimal cropping and irrigation choices. The use of reservoirs enables the landscape to attain up to 10% higher market returns for a given level of all non-market ecosystem service benefits by lowering the costs of irrigation, increasing groundwater levels, and reducing fuel combustion and associated greenhouse gas (GHG) emissions from groundwater pumping. A landscape that internalizes both non-market ecosystem service benefits and market value from crops has 30% greater social value than a landscape where only market returns or only non-market value is optimized. [ABSTRACT FROM AUTHOR]

Remote sensing (RS) has played an important role in extensive agricultural monitoring and management for several decades. However, the current spatial resolution of satellite imagery does not have enough definition to generalize its use in highly-fragmented agricultural landscapes, which represents a significant percentage of the world’s total cultivated surface. To characterize and analyze this type of landscape, multispectral (MS) images with high and very high spatial resolutions are required. Multi-source image fusion algorithms are normally used to improve the spatial resolution of images with a medium spatial resolution. In particular, pansharpening (PS) methods allow one to produce high-resolution MS images through a coherent integration of spatial details from a panchromatic (PAN) image with spectral information from an MS. The spectral and spatial quality of source images must be preserved to be useful in RS tasks. Different PS strategies provide different trade-offs between the spectral and the spatial quality of the fused images. Considering that agricultural landscape images contain many levels of significant structures and edges, the PS algorithms based on filtering processes must be scale-aware and able to remove different levels of detail in any input images. In this work, a new PS methodology based on a rolling guidance filter (RGF) is proposed. The main contribution of this new methodology is to produce artifact-free pansharpened images, improving the MS edges with a scale-aware approach. Three images have been used, and more than 150 experiments were carried out. An objective comparison with widely-used methodologies shows the capability of the proposed method as a powerful tool to obtain pansharpened images preserving the spatial and spectral information. [ABSTRACT FROM AUTHOR]

Riparian Zones are considered biodiversity and ecosystem services hotspots. In arid environments, these ecosystems represent key habitats, since water availability makes them unique in terms of fauna, flora and ecological processes. Simple yet powerful remote sensing techniques were used to assess how spatial and temporal land cover dynamics, and water depth reflect distribution of key land cover types in riparian areas. Our study area includes the San Miguel and Zanjon rivers in Northwest Mexico. We used a supervised classification and regression tree (CART) algorithm to produce thematic classifications (with accuracies higher than 78%) for 1993, 2002 and 2011 using Landsat TM scenes. Our results suggest a decline in agriculture (32.5% area decrease) and cultivated grasslands (21.1% area decrease) from 1993 to 2011 in the study area. We found constant fluctuation between adjacent land cover classes and riparian habitat. We also found that water depth restricts Riparian Vegetation distribution but not agricultural lands or induced grasslands. Using remote sensing combined with spatial analysis, we were able to reach a better understanding of how riparian habitats are being modified in arid environments and how they have changed through time. [ABSTRACT FROM AUTHOR]

Land cover mapping (LCM) in complex surface-mined and agricultural landscapes could contribute greatly to regulating mine exploitation and protecting mine geo-environments. However, there are some special and spectrally similar land covers in these landscapes which increase the difficulty in LCM when employing high spatial resolution images. There is currently no research on these mixed complex landscapes. The present study focused on LCM in such a mixed complex landscape located in Wuhan City, China. A procedure combining ZiYuan-3 (ZY-3) stereo satellite imagery, the feature selection (FS) method, and machine learning algorithms (MLAs) (random forest, RF; support vector machine, SVM; artificial neural network, ANN) was proposed and first examined for both LCM of surface-mined and agricultural landscapes (MSMAL) and classification of surface-mined land (CSML), respectively. The mean and standard deviation filters of spectral bands and topographic features derived from ZY-3 stereo images were newly introduced. Comparisons of three MLAs, including their sensitivities to FS and whether FS resulted in significant influences, were conducted for the first time in the present study. The following conclusions are drawn. Textures were of little use, and the novel features contributed to improve classification accuracy. Regarding the influence of FS: FS substantially reduced feature set (by 68% for MSMAL and 87% for CSML), and often improved classification accuracies (with an average value of 4.48% for MSMAL using three MLAs, and 11.39% for CSML using RF and SVM); FS showed statistically significant improvements except for ANN-based MSMAL; SVM was most sensitive to FS, followed by ANN and RF. Regarding comparisons of MLAs: for MSMAL based on feature subset, RF achieved the greatest overall accuracy of 77.57%, followed by SVM and ANN; for CSML, SVM had the highest accuracies (87.34%), followed by RF and ANN; based on the feature subsets, significant differences were observed for MSMAL and CSML using any pair of MLAs. In general, the proposed approach can contribute to LCM in complex surface-mined and agricultural landscapes. [ABSTRACT FROM AUTHOR]

Land suitability analysis is employed to evaluate the appropriateness of land for a particular purpose whilst integrating both qualitative and quantitative inputs, which can be continuous in nature. However, in agricultural modelling there is often a disregard of this contiguous aspect. Therefore, some parametric procedures for suitability analysis compartmentalise units into defined membership classes. This imposition of crisp boundaries neglects the continuous formations found throughout nature and overlooks differences and inherent uncertainties found in the modelling. This research will compare two approaches to suitability analysis over three differing methods. The primary approach will use an Analytical Hierarchy Process (AHP), while the other approach will use a Fuzzy AHP over two methods; Fitted Fuzzy AHP and Nested Fuzzy AHP. Secondary to this, each method will be assessed into how it behaves in a climate change scenario to understand and highlight the role of uncertainties in model conceptualisation and structure. Outputs and comparisons between each method, in relation to area, proportion of membership classes and spatial representation, showed that fuzzy modelling techniques detailed a more robust and continuous output. In particular the Nested Fuzzy AHP was concluded to be more pertinent, as it incorporated complex modelling techniques, as well as the initial AHP framework. Through this comparison and assessment of model behaviour, an evaluation of each methods predictive capacity and relevance for decision-making purposes in agricultural applications is gained. [ABSTRACT FROM AUTHOR]

This study analyzed the spatiotemporal pattern of settlement expansion in Abuja, Nigeria, one ofWest Africa's fastest developing cities, using geoinformation and ancillary datasets. Three epochs of Land-use Land-cover (LULC) maps for 1986, 2001 and 2014 were derived from Landsat images using support vector machines (SVM). Accuracy assessment (AA) of the LULC maps based on the pixel count resulted in overall accuracy of 82%, 92% and 92%, while the AA derived from the error adjusted area (EAA) method stood at 69%, 91% and 91% for 1986, 2001 and 2014, respectively. Two major techniques for detecting changes in the LULC epochs involved the use of binary maps as well as a post-classification comparison approach. Quantitative spatiotemporal analysis was conducted to detect LULC changes with specific focus on the settlement development pattern of Abuja, the federal capital city (FCC) of Nigeria. Logical transitions to the urban category were modelled for predicting future scenarios for the year 2050 using the embedded land change modeler (LCM) in the IDRISI package. Based on the EAA, the result showed that urban areas increased by more than 11% between 1986 and 2001. In contrast, this value rose to 17% between 2001 and 2014. The LCM model projected LULC changes that showed a growing trend in settlement expansion, which might take over allotted spaces for green areas and agricultural land if stringent development policies and enforcement measures are not implemented. In conclusion, integrating geospatial technologies with ancillary datasets offered improved understanding of how urbanization processes such as increased imperviousness of such a magnitude could influence the urban microclimate through the alteration of natural land surface temperature. Urban expansion could also lead to increased surface runoff as well as changes in drainage geography leading to urban floods. [ABSTRACT FROM AUTHOR]

Mapping species through classification of imaging spectroscopy data is facilitating research to understand tree species distributions at increasingly greater spatial scales. Classification requires a dataset of field observations matched to the image, which will often reflect natural species distributions, resulting in an imbalanced dataset with many samples for common species and few samples for less common species. Despite the high prevalence of imbalanced datasets in multiclass species predictions, the effect on species prediction accuracy and landscape species abundance has not yet been quantified. First, we trained and assessed the accuracy of a support vector machine (SVM) model with a highly imbalanced dataset of 20 tropical species and one mixed-species class of 24 species identified in a hyperspectral image mosaic (350-2500 nm) of Panamanian farmland and secondary forest fragments. The model, with an overall accuracy of 62% ± 2.3% and F-score of 59% ± 2.7%, was applied to the full image mosaic (23,000 ha at a 2-m resolution) to produce a species prediction map, which suggested that this tropical agricultural landscape is more diverse than what has been presented in field-based studies. Second, we quantified the effect of class imbalance on model accuracy. Model assessment showed a trend where species with more samples were consistently over predicted while species with fewer samples were under predicted. Standardizing sample size reduced model accuracy, but also reduced the level of species over- and under-prediction. This study advances operational species mapping of diverse tropical landscapes by detailing the effect of imbalanced data on classification accuracy and providing estimates of tree species abundance in an agricultural landscape. Species maps using data and methods presented here can be used in landscape analyses of species distributions to understand human or environmental effects, in addition to focusing conservation efforts in areas with high tree cover and diversity. [ABSTRACT FROM AUTHOR]

Since agriculture directly contributes to global anthropogenic greenhouse gas (GHG) emissions, integrating trees into agricultural landscapes through agroforestry systems is a viable adaptive strategy for climate change mitigation. The objective of this study was to evaluate the carbon (C) sequestration and financial benefits of C sequestration according to Quebec's Cap-and-Trade System for Greenhouse Gas Emissions Allowances (C & T System) or the Système de plafonnement et d'échange de droits d'émission de gaz à effet de serre du Québec (SPEDE) program for two experimental 10-year-old tree-based intercropping (TBI) systems in southern Quebec, Canada. We estimated total C stored in the two TBI systems with hybrid poplar and hardwoods and adjacent non-TBI systems under agricultural production, considering soil, crop and crop roots, litterfall, tree and tree roots as C stocks. The C sequestration of the TBI and adjacent non-TBI systems were compared and the market value of the C payment was evaluated using the net present value (NPV) approach. The TBI systems had 33% to 36% more C storage than adjacent non-TBI systems. The financial benefits of C sequestration after 10 years of TBI practices amounted to of $2,259-$2,758 CAD ha 1 and $1,568-$1,913 CAD ha 1 for St. Edouard and St. Paulin sites, respectively. We conclude that valorizing the C sequestration of TBI systems could be an incentive to promote the establishment of TBI for the purpose of GHG mitigation in Quebec, Canada. [ABSTRACT FROM AUTHOR]

Many small-scale private forest owners increasingly focus their management on amenity functions rather than on wood production functions. This paradigm shift is an opportunity to implement novel forestry management approaches, such as forested land zoning. Forest zoning consists in separating the land base in three zones that have different management objectives: (1) conservation zones; (2) ecosystem management zones; and (3) intensive production zones, which locally increase productivity, as a trade off to increase the land area dedicated to conservation and ecosystem management. We evaluate the ecological feasibility of implementing forest zoning on a private property (216 ha) at St-Benoît-du-Lac, Québec (Canada) characterised by agricultural and forest land uses. As a basis for delineating conservation and ecosystem management zones, historical and contemporary data and facts on forest composition and dynamics were reviewed, followed by a detailed forest vegetation analysis of forest communities. Delineating intensive production zones was straightforward, as fertile agricultural field margins located downslope were used to establish multifunctional hybrid poplar buffers. At St-Benoît-du-Lac, a realistic zoning scenario would consist of (1) conservation zones covering 25% of the forestland (37 ha); (2) ecosystem management zones covering 75% of the forestland (113 ha, including restoration zones on 24 ha); and (3) intensive production zones on 2.8 ha. Based on a yield projection of 13 t/ha/year for hybrid poplars, only 5.6% of agricultural field areas would need to be converted into agroforestry systems to allow for the loss of wood production in a conservation zone of 37 ha of forest. Ecosystem services provision following the implementation of zoning would include increased habitat quality, biodiversity protection and enhancement (by restoration of some tree species), carbon storage, non-point source aquatic pollution control, local biomass production for heating, and increased forest economic value. [ABSTRACT FROM AUTHOR]

Rice is one of the major crops cultivated predominantly in flooded paddies, thus a large amount of water is consumed during its growing season. Accurate paddy rice maps are therefore important inputs for improved estimates of actual evapotranspiration in the agricultural landscape. The main objective of this study was to obtain flooded paddy rice maps using multi-temporal images of Moderate Resolution Imaging Spectroradiometer (MODIS) in the Krishna River Basin, India. First, ground-based spectral samples collected by a field spectroradiometer, CROPSCAN, were used to demonstrate unique contrasts between the Normalized Difference Vegetation Index (NDVI) and the Land Surface Water Index (LSWI) observed during the transplanting season of rice. The contrast between Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) from MODIS time series data was then used to generate classification decision rules to map flooded rice paddies, for the transplanting seasons of Kharif and Rabi rice crops in the Krishna River Basin. Consistent with ground spectral observations, the relationship of the MODIS EVI vs. LSWI of paddy rice fields showed distinct features from other crops during the transplanting seasons. The MODIS-derived maps were validated against extensive reference data collected from multiple land use field surveys. The accuracy of the paddy rice maps, when determined using field plot data, was approximately 78%. The MODIS-derived rice crop areas were also compared with the areas reported by Department of Agriculture (DOA), Government of India (Government Statistics). The estimated root mean square difference (RMSD) of rice area estimated using MODIS and those reported by the Department of Agriculture over 10 districts varied between 3.4% and 6.6% during 10 years of our study period. Some of the major factors responsible for this difference include high noise of the MODIS images during the prolonged monsoon seasons (typically June-October) and the coarse spatial resolution (500 m) of the MODIS images compared to the small crop fields in the basin. However, this study demonstrates, based on multi-year analysis, that MODIS images can still provide robust and consistent flooded paddy rice extent and areas over a highly heterogeneous large river basin. [ABSTRACT FROM AUTHOR]