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The Soil and Water Assessment Tool (SWAT) enables the simulation of watershed and river basin quantity and quality of surface and ground water under the influence of land use, management, and climate change. It can be used to monitor and control soil erosion, non-point source pollution and basin management. The recent version (SWAT+) was implemented by a dedicated QGIS plugin (QSWAT) widening the userbase and the potential modelling application worldwide. QSWAT, along with additional software for preparing the input dataset and for performing the calibration/validation phase, further extends the watershed modelling capabilities. Such tools and the growing diffusion of public open geospatial datasets are expected to increase the range of applications especially with the availability climate projections datasets. The latter will enable users to simulate all the watersoil phenomena at watershed level under future conditions to better understand and plan suitable action for preserving the natural resources. [ABSTRACT FROM AUTHOR]

Current and future scenarios for global agricultural systems under a changing climate require innovative approaches, novel datasets, and methods for improving environmental resource management and better data-driven decision-making. MODIS data were complemented with Copernicus FCover, VIIRS satellite, and climatic data to consider vegetation cover, phenological phases, and seasonality of precipitation. EO data and GIScience will certainly be pivotal in ensuring the implementation of European Union (EU) and global policies such as the Sustainable Development Goals (SDGs) or the EU's Green Deal. [Extracted from the article]

Open LOD platform based on HPC capabilities for Integrated Administration and Control System of Common Agrarian Policy (Open IACS) is an EU funded project (4.5 MEur) fostering the administrative data reuse in the context of the Common Agricultural Policy (CAP) and granting open access to farmers, policy makers and third parties. Data from European paying agencies for agriculture will be harmonised, and a network of Linked Open Data will be developed. An interoperable system of EU High Performance Computing Centres will provide a platform for demonstrating different use case scenarios (e.g. applications for computing CAP performance indicators, climate change indicators and integration between environmental and agricultural data). [ABSTRACT FROM AUTHOR]

The ever-growing availability of Earth Observation (EO) data is demonstrating a wide range of potential applications in the realm of land management. On the other hand, large volumes of data need to be handled and analysed to extract meaningful information and Geomatics coupled with new approaches such as Artificial Intelligence (AI) and Machine Learning (AI) will play a pivotal role in the years to come. Training datasets need to be developed to use these new models and Volunteered Geographic Information can be one of the promising sources for EO processing. Among the various applications, agriculture may benefit from the large dataset availability and AI processing. However, several issues remain unsolved and further steps should be taken in the near future by researchers and policy makers. [ABSTRACT FROM AUTHOR]

This contribution reports the results of the application of the JRC guidelines to identify Italian agricultural areas, other than mountain areas, facing significant natural constraints (Areas with Natural Constraints -- ANCs). Spatial analysis has been carried out to integrate climatic, soil, terrain and agricultural data. The latter were integrated with administrative boundaries to classify each municipality as ANC if at least one biophysical criterion was relevant. We report maps, tables and graphs of the Italian ANCs defined by biophysical criteria depicting the new geography where agricultural activities might face significant natural constraints. [ABSTRACT FROM AUTHOR]

A big leap in the agricultural sector is expected thanks to the operational deployment of Copernicus data and services, the new Earth Observation program of the European Commission. The huge quantity of data delivered freely along with the good level of resolution (spatial, temporal and spectral) will open up new opportunities for achieving the well-known sustainability of agriculture. At the same time, the new trends of crowdsourcing and citizen science are delivering a great deal of geographical data collected by ordinary users with a bottom-up process. The two type of data and their integration will be the base for the future application in the agricultural sector, albeit management of big geospatial dataset and quality of user generated data are issues to be addressed. [ABSTRACT FROM AUTHOR]

A dimensionless methodology to evaluate the water saving obtainable from large-scale implementation of domestic rain water harvesting (RWH) systems in urban areas is presented. The methodology combines the use of regressive relationships for water saving evaluation based on the results of the dimensionless rainwater tank water balance and of catchment-wide information obtained from geospatial databases. The adopted RWH scheme included internal use of rainwater for toilet flushing and external use for garden irrigation. An application to a portion of the city of Rome, Italy showed the methodology to allow systematic and accurate evaluation of RWH system performance at the selected urban scale. Results pointed out high water saving potential for toilet flushing ranging between 38–65% for tank sizes within 1–50 m3. Furthermore, more than one third of the systems provided water saving benefit for irrigation larger than 20% by using a 50 m3tank. [ABSTRACT FROM PUBLISHER]

Availability of up-to-date geographic datasets, including the information voluntarily created by ordinary people, is crucial for disaster management in areas affected by catastrophic events and humanitarian crises. OpenStreetMap (OSM) is the most popular Volunteered Geographic Information (VGI) project that has been extensively used for collaborative mapping in areas affected by natural disasters. This article provides an overview on how OSM data are exploited in disaster response scenarios and illustrates their specific application during the recent Italian earthquakes [ABSTRACT FROM AUTHOR]

Eco-hydrological models, such as SWAT (Soil Water Assessment Tool), are used to simulate complex hydrological processes and LU management in relation to water quality and quantity on a wide range of ecosystems. SWAT, developed by United States Department of Agriculture, is one of the most widely used watershed-scale modelling to assess changes in landscape management practices on water, sediment, and chemical yield. However, the availability of LU maps with good spatial and thematic resolution is one of the limiting factors in watershed modelling. Updated and detailed LU maps are required to grasp the variability and complexity of modelled landscapes. In fact, detailed LU maps with crop types can improve the model's capabilities in simulating evapotranspiration, surface runoff, soil infiltration, nutrient loss, and biomass production. This work reports the achievements in developing an integrated LU map for modelling watershed processes in the Mediterranean context within the Cervaro river basin (900 sq. km ca.), South Italy (Puglia region), with a dominant agricultural LU (Figure 1). Water is a critical natural resource in a Mediterranean country like Italy, vulnerable to risks stemming from climate change such as a related risk of decrease in water availability and crop yields. We applied a methodology for geospatial data integration from the Italian Paying Agency (AGEA) responsible for managing the farmers' subsidies with the Integrated Administration and Control System (IACS) in the framework of the Common Agricultural Policy (CAP). IACS geodata, such as the Land Parcel Identification System (LPIS) and the GeoSpatial Aid Application (GSAA), are the relevant resource on LU parcels managed by Italian farms. This typology of data is one of the best maintained datasets in EU with regular updates and quality controls. Recently, IACS data reusability is becoming a reality thanks to effort of the EU Commission to opening the data within the more general action in "shaping Europe's digital future" by fostering the re-use of government-held data (Directive (EU) 2019/1024). LPIS contains homogeneous land use/cover areas digitized from ortho-imagery with high spatial resolution, resulting in a wall-to-wall map including Italian agricultural and non-agricultural areas with a full update every three years. GSAAcontains digitized on-screen parcels for which an aid is requested yearly by Italian farmers and modified/updated by the paying agency after controls to ensure accuracy. Thematic details on agriculture within GSAA is dramatically higher than the LPIS thanks to the availability of crops classes detailed with a 5-level nomenclature. Within the LPIS an additional geographical layer is also available reporting the cadastral parcels with updated LU information deriving from in-situ field checks and other administrative sources. The conflation method for integrating the three vector layers (two LPIS and GSAA) followed different steps: conversion to a common projection system, topology and geometry checks, aggregation of small polygons and nomenclatures matching (from IACS to SWAT classes) through semantic analysis. Geometric and attributes processing allowed to reduce dimensionality of the "hybrid layer": from 300k to 50k ca. polygons and from 33k LU combinations to 57 SWAT LU classes (Table 1). The "hybrid layer" (Figure 2) enables accurate modelling with SWAT to understand the relationship between LU management and water quality as an important opportunity in the context of both the reformed CAP and the Farm to Fork strategy aiming to reduce the environmental and climate footprint of the EU food system by preserving and restoring the land and freshwater resources. The spatial details coming from very high-resolution imagery and thematic details enhanced by administrative controls and farmers declarations provides much higher performances compared to classical LU maps. The EU-wide data availability, the yearly updates of information and the detailed attributes (e.g., crops typology, greening and organic practices, crop rotation, conservation tillage, etc.) can shift upward the accuracy of the eco-hydrological modelling. [ABSTRACT FROM AUTHOR]

Agricultural production plays an important role in the global economy, contributing greatly to the supply of food resources and human well-being. Mapping the areas of agricultural coverage and calculating their respective average annual production values is useful for orienting food security strategies, in a context of climate change and a growing global population. Despite their importance, today no complete and updated maps exist for all types of crops. To provide this critical data lack, we have harmonized statistical datasets at a regional level of detail across Europe (EU-27) to develop a unified dataset consisting of the best available data in the context of agricultural monitoring activities carried out by the CREA. This document illustrates the methodologies adopted to create an harmonized database and an open and easy-to-use cartographic atlas of agricultural area and production, based on accessible, interoperable and reusable data available from Eurostat. The availability of detailed maps of area and crop production at a regional level can help optimize a wide range of agricultural monitoring, ranging from early warning on phytopathological conditions, to assessment of crop conditions, to production forecasts and the assessment of damage caused by extreme weather events, agricultural statistics, agricultural insurance and climate mitigation and adaptation actions. [ABSTRACT FROM AUTHOR]

Soil and weather data were used to analyse spatio-temporal yield patterns of winter cereals (wheat) and spring dicots (sunflower and coriander) in an 11-ha field in Northern Italy (44.5° N, 12.2° E), during 2010–2014. Three yield stability classes (YSCs) were established over multiple years, based on spatio-temporal characteristics across the field: high yielding and stable (HYS), low yielding and stable (LYS), and unstable. The HYS class (46% of field area) staged a 122% relative yield with low temporal variability. The unstable class (24% of field area) was slightly more productive (83% relative yield) than the LYS class (30% of field area, and 80% relative yield), but less consistent over time. Crop yields evidenced negative correlations with sand content; positive correlations with silt and clay content. Soil properties were quite consistently classified among YSCs: the LYS and unstable classes were associated with higher sand content and lower cation exchange capacity, suggesting that these characteristics lead to fluctuation and depression of final yield. Establishing YSCs based on spatio-temporal yield appears a sound approach to appraise field potential. It results in strategic and tactical decisions to be taken, depending on the profile of spatial and temporal productivity in different field areas. [ABSTRACT FROM AUTHOR]

Google Earth (GE) has recently become the focus of increasing interest and popularity among available online virtual globes used in scientific research projects, due to the free and easily accessed satellite imagery provided with global coverage. Nevertheless, the uses of this service raises several research questions on the quality and uncertainty of spatial data (e.g. positional accuracy, precision, consistency), with implications for potential uses like data collection and validation. This paper aims to analyze the horizontal accuracy of very high resolution (VHR) GE images in the city of Rome (Italy) for the years 2007, 2011, and 2013. The evaluation was conducted by using both Global Positioning System ground truth data and cadastral photogrammetric vertex as independent check points. The validation process includes the comparison of histograms, graph plots, tests of normality, azimuthal direction errors, and the calculation of standard statistical parameters. The results show that GE VHR imageries of Rome have an overall positional accuracy close to 1 m, sufficient for deriving ground truth samples, measurements, and large-scale planimetric maps. [ABSTRACT FROM AUTHOR]

Assessing crop yield trends over years is a key step in site specific management, in view of improving the economic and environmental profile of agriculture. This study was conducted in a 11.07 ha area under Mediterranean climate in Northern Italy to evaluate the spatial variability and the relationships between six remotely sensed vegetation indices (VIs) and grain yield (GY) in five consecutive years. A total of 25 satellite (Landsat 5, 7, and 8) images were downloaded during crop growth to obtain the following VIs: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI), Green Normalized Difference Vegetation Index (GNDVI), Green Chlorophyll Index (GCI), and Simple Ratio (SR). The surveyed crops were durum wheat in 2010, sunflower in 2011, bread wheat in 2012 and 2014, and coriander in 2013. Geo-referenced GY and VI data were used to generate spatial trend maps across the experimental field through geostatistical analysis. Crop stages featuring the best correlations between VIs and GY at the same spatial resolution (30 m) were acknowledged as the best periods for GY prediction. Based on this, 2–4 VIs were selected each year, totalling 15 VIs in the five years with r values with GY between 0.729** and 0.935**. SR and NDVI were most frequently chosen (six and four times, respectively) across stages from mid vegetative to mid reproductive growth. Conversely, SAVI never had correlations high enough to be selected. Correspondence analysis between remote VIs and GY based on quantile ranking in the 126 (30 m size) pixels exhibited a final agreement between 64% and 86%. Therefore, Landsat imagery with its spatial and temporal resolution proved a good potential for estimating final GY over different crops in a rotation, at a relatively small field scale. [ABSTRACT FROM AUTHOR]

Abstract The cultivation of marginal lands for bioenergy production has recently become a topic of research interest for the agronomic and agricultural economy scientific communities. The growing availability of arable land in the Mediterranean regions, as a consequence of the decline of cereal cropping systems and grain legume, provides ample opportunities for performing successful feedstock production on unmanaged areas. This paper seeks to capture and analyze ongoing and emerging questions concerning bioenergy production on marginal lands in the Mediterranean area in a framework of sustainability indicators. A qualitative methodology was adopted to evaluate the effectiveness of eight critical issues that bio-energy developers, scholars and policymakers should consider in terms of agronomic, techno-economic and methodological practices for growing bioenergy feedstock. The issues investigated on selected case studies are: Greenhouse gas emissions; soil quality; land restoration and phytoremediation capacity; water use and efficiency; biodiversity; land use/cover changes; farmers' willingness and acceptance of new agro-system, and profitability of value chain. Starting from an in-depth analysis of the definition of marginal land from the perspective of ecosystem service cascade, we synthesize how these challenges are nowadays addressed and which are the key bottlenecks, trends and potential directions for guiding future research into bioenergy production in the Mediterranean regions. The findings of this study suggest that dedicated energy crops can be grown on marginal lands with substantial positive effects in terms of sustainability aspects, although more efforts should be carried out through agronomic research especially on water use efficiency and biodiversity conservation, as well as by national and EU institutions and policies for promoting economic opportunities and integration with surrounding agro-ecosystems and farmers' involvement. Developing a site-specific landscape design with the use of Life Cycle Assessment and certification schemes with sustainability indicators is of primary importance for the effective bioenergy production on marginal lands. Graphical abstract fx1 Highlights • Key issues concerning bioenergy production in the Mediterranean area were analyzed. • The concept of marginal land was analyzed. • The use of tailored GBEP sustainability indicators was fostered. • Eight critical issues were reviewed discussing key results and future challenges. • Possible technical and policies improvement solutions are proposed. [ABSTRACT FROM AUTHOR]

The paper proposes a methodology to assess water consumption in urban agriculture. Green and blue water footprints were calculated for five selected community gardens (CGs) in Rome (Italy) based on weather, crops, and yields. Then, the water requirement for all the CGs of the city, identified by means of a geodatabase, was estimated. For a cultivated area of 4.06 ha, an overall water requirement of 22,036 m3 (13,596 m3 green and 8,440 m3 blue) resulted from the assessment. Considering also the efficiency of the irrigation system, blue water consumption would reach 20,000 m3 in the worst scenario (furrow irrigation). [ABSTRACT FROM AUTHOR]

In the context of environmental sustainability there has been an increasing interest in bioenergy production from renewable resources, and is expected that European biofuel production from energy crops will increase as a consequence of the achievement of policy targets. The aim of this paper is to assess the agronomic feasibility of biomass crop cultivation to provide profitable renewable feedstocks in a marginal and heavy-metal polluted area located in the Sulcis district, Sardinia (Italy). Results from literature review and unpublished data from field trials carried out in Sardinia were analysed to establish the main agronomic traits of crops (e.g., yield potential and input requirements). A Geographical Information System (GIS)-based procedure with remotely sensed data is also used to evaluate the land suitability and the actual land use/cover, considering a future scenario of expansion of energy crops on these marginal areas avoiding potential conflicts with food production. The results of the review suggests that giant reed, native perennial grasses and milk thistle are the most suitable energy crops for this area. The land suitability analysis shows that about 5700 ha and 1000 ha could be available for feedstock cultivation in the study area and in the most polluted area, respectively. The results obtained from land suitability process and agronomic evaluation will serve as a base to support technical and economical feasibility studies, as well as for the evaluation of environmental sustainability of the cultivation in the study area. [ABSTRACT FROM AUTHOR]

Geo-tagged photographs are used increasingly as a source of Volunteered Geographic Information (VGI), which could potentially be used for land use and land cover applications. The purpose of this paper is to analyze the feasibility of using this source of spatial information for three use cases related to land cover: Calibration, validation and verification. We first provide an inventory of the metadata that are collected with geo-tagged photographs and then consider what elements would be essential, desirable, or unnecessary for the aforementioned use cases. Geo-tagged photographs were then extracted from Flickr, Panoramio and Geograph for an area of London, UK, and classified based on their usefulness for land cover mapping including an analysis of the accompanying metadata. Finally, we discuss protocols for geo-tagged photographs for use of VGI in relation to land cover applications. [ABSTRACT FROM AUTHOR]

Volunteered Geographic Information (VGI) represents a growing source of potentially valuable data for many applications, including land cover map validation. It is still an emerging field and many different approaches can be used to take value from VGI, but also many pros and cons are related to its use. Therefore, since it is timely to get an overview of the subject, the aim of this article is to review the use of VGI as reference data for land cover map validation. The main platforms and types of VGI that are used and that are potentially useful are analysed. Since quality is a fundamental issue in map validation, the quality procedures used by the platforms that collect VGI to increase and control data quality are reviewed and a framework for addressing VGI quality assessment is proposed. A review of cases where VGI was used as an additional data source to assist in map validation is made, as well as cases where only VGI was used, indicating the procedures used to assess VGI quality and fitness for use. A discussion and some conclusions are drawn on best practices, future potential and the challenges of the use of VGI for land cover map validation. [ABSTRACT FROM AUTHOR]

Predicting the availability and quality of freshwater resources is a pressing concern in the Mediterranean area, where a number of agricultural systems depend solely on precipitation. This study aims at predicting streamflow and nonpoint pollutant loads in a temporary river system in the Mediterranean basin (Sulcis area, Sardinia, Italy). Monthly discharge, suspended sediment, nitrate nitrogen, total nitrogen, mineral phosphorus, and dissolved oxygen in-stream monitoring data from gauge stations were used to calibrate and validate the Soil and Water Assessment Tool model for the period 1979–2009. A Sequential Uncertainty Fitting procedure was used to auto-calibrate parameter uncertainties and model evaluation. Monthly simulation during the validation period showed a positive model performance for streamflow with Nash–Sutcliffe efficiency and percent bias values of 0.7% and 18.7%, respectively. The simulation results at a watershed level indicate that the sediment load was 1.13 t ha−1 year−1, while for total nitrogen and total phosphorus, the simulated values were 4.8 and 1.18 kg ha−1 year−1, respectively. These results were consistent with the values of soil and nutrient losses observed in the Mediterranean area, although hot-spot areas with high nutrient loadings were identified. The calibrated model could be used to assess long-term impacts on water quality associated with the simulated land use scenarios. [ABSTRACT FROM AUTHOR]