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Background: Social support is a crucial factor influencing the sustainability of physical activity (PA). This proof-of-concept study presents the development of a Social Physical Activity Index for Area (SPAIFA) an indicator reflecting opportunities for individuals to actively participate as part of a group within which opportunities for social interaction can be developed. Methods: Six government councils in the state of New South Wales, Australia, were selected encompassing 174 suburbs. Using 2 search engines' map tools, we identified PA venues for each suburb (eg, park, studios, etc). To enumerate activities per suburb, we used (1) venue websites, (2) New South Wales Office of Sport website, (3) national websites of grassroots PA for nonorganized activity (eg, parkrun, meetup, etc), and (4) social media. The database was linked to the suburb demographic profile, the area disadvantage score, walkability and open space scores, and the proportion of insufficiently active residents. Spatial analysis techniques were used to identify SPAIFA clusters. Results: SPAIFA councils' average was 9.9 activities per 10,000 people (ranging from 6.6/10,000 to 16.2/10,000). SPAIFA-Old (ie, activities specific to older adults) varied significantly (ranging from 11.7/10,000 to 0.8/10,000 seniors). Disadvantaged areas and a high proportion of insufficiently active residents were associated with being classified as low SPAIFA (P <.01). Three clusters of low SPAIFA were identified, and 17 high-risk areas where low SPAIFA was compounded by poor environmental support. Conclusions: SPAIFA can be used by councils and policymakers as an indicator for monitoring and intervening in areas where natural and/or urban design is not conducive for PA. [ABSTRACT FROM AUTHOR]

The Snake River Plain (SRP) volcanic province overlies the track of the Yellowstone hotspot, a thermal anomaly that extends deep into the mantle. Most of the area is underlain by a basaltic volcanic province that overlies a mid-crustal intrusive complex, which in turn provides the long-term heat flux needed to sustain geothermal systems. Previous studies have identified several known geothermal resource areas within the SRP. For the geothermal study presented herein, our goals were to: (1) adapt the methodology of Play Fairway Analysis (PFA) for geothermal exploration to create a formal basis for its application to geothermal systems, (2) assemble relevant data for the SRP from publicly available and private sources, and (3) build a geothermal PFA model for the SRP and identify the most promising plays, using GIS-based software tools that are standard in the petroleum industry. The study focused on identifying three critical resource parameters for exploitable hydrothermal systems in the SRP: heat source, reservoir and recharge permeability, and cap or seal. Data included in the compilation for heat source were heat flow, distribution and ages of volcanic vents, groundwater temperatures, thermal springs and wells, helium isotope anomalies, and reservoir temperatures estimated using geothermometry. Reservoir and recharge permeability was inferred from the analysis of stress orientations and magnitudes, post-Miocene faults, and subsurface structural lineaments based on magnetics and gravity data. Data for cap or seal included the distribution of impermeable lake sediments and clay-seal associated with hydrothermal alteration below the regional aquifer. These data were used to compile Common Risk Segment maps for heat, permeability, and seal, which were combined to create a Composite Common Risk Segment map for all southern Idaho that reflects the risk associated with geothermal resource exploration and identifies favorable resource tracks. Our regional assessment indicated that undiscovered geothermal resources may be located in several areas of the SRP. Two of these areas, the western SRP and Camas Prairie, were selected for more detailed assessment, during which heat, permeability, and seal were evaluated using newly collected field data and smaller grid parameters to refine the location of potential resources. These higher resolution assessments illustrate the flexibility of our approach over a range of scales.

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results. A geographic information system was used to compile a range of different data types, which we refer to as elements (e.g., faults, vents, heat flow, etc.), with distinct characteristics and measures of confidence. Discontinuous discrete data (points, lines, or polygons) for each element were transformed into continuous interpretive 2D grid surfaces called evidence layers. Because different data types have varying uncertainties, most evidence layers have an accompanying confidence layer which reflects spatial variations in these uncertainties. Risk layers, as defined here, are the product of evidence and confidence layers, and are the building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal, using a weighted sum for permeability and heat, but a different approach with seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map, using a modified weighted sum, for results that reveal favorable areas for geothermal exploration. Additional maps are also presented that do not mix contributions from evidence and confidence (to allow an isolated view of evidence and confidence), as well as maps that calculate favorability using the product of components instead of a weighted sum (to highlight where all components are present). Our approach helped to identify areas of high geothermal favorability in the western and central Snake River Plain during the first phase of study and helped identify more precise local drilling targets during the second phase of work. By identifying favorable areas, this methodology can help to reduce uncertainty in geothermal energy exploration and development.

In this study, we utilized the ArcGIS Geographic Information System (ArcGIS) to study the relevant datasets of park green and residential subsidiary green spaces in Wuhan City, and at the same time, scraped residential area prices data in Wuhan using big data technology. The inverse distance weight spatial interpolation method is employed to analyze the spatial patterns of residential area prices. Distances from each residential area to park green spaces at different scales are calculated to investigate their impact on residential area prices. Three strategies are proposed: the tailored allocation of different types of park based on regional characteristics, the implementation of "quantity guarantee and quality improvement" measures to enhance the quality of residential green spaces, and the promotion of interaction between park green and residential green spaces. These strategies aim to particularly uplift housing prices in economically disadvantaged areas, ultimately achieving shared prosperity. [ABSTRACT FROM AUTHOR]

ABSTRACT Access to information pertaining to land facilitates strategic planning for individuals, businesses, and governmental entities and allows them to anticipate and address contemporary challenges such as climate change, housing requirements, and economic prosperity. Improvements in information technologies contribute to data creation, analysis, and dissemination processes that enable gaining knowledge about land‐related events. Greater use of location data within property technologies gives rise to an efficient and sustainable land administration system. GeoAI can contribute greatly to the solution of spatial problems by extracting information from complex data through geospatial intelligence. Property valuation requires a spatially explicit model to evaluate locational factors with spatial analyses. In this study, a Land Administration Domain Model (LADM)‐based mass valuation model is developed for Great Britain by integrating GeoAI techniques. First, the LADM Valuation Information package is matched with the country's current organizational structure and it is extended according to the needs to create a country profile. After developing the conceptual model, a database schema is created and automatic conversion to the physical model is conducted. Loading different data sources into the database, a mass valuation application is carried out through spatial analysis and Random Forest regression analysis. As a result, a highly accurate and holistic valuation model is implemented based on the international land administration standards. [ABSTRACT FROM AUTHOR]

This study explores the complex interconnections among global population growth, energy consumption, CO2 production, and disparities in service access through the lens of a single case study. Rapid population growth in many major cities has created significant challenges related to equitable access to services and socio-economic development, thereby impacting both their energy consumption patterns and environmental impacts. The case investigated in this study, like many other cases in developing countries, exhibits differences in service provision, infrastructure development, and energy usage, particularly between the northern and southern regions, which significantly affect the quality of life, environmental sustainability, and economic development. Previous efforts to narrow these geographic disparities have yielded limited success and exhibited several shortcomings. By employing a GIS Analytical Network Process method, this study examines service accessibility patterns in a single-case city, with a particular emphasis on green spaces, food services, and educational facilities and services. This GIS-based approach seeks to achieve sustainable levels of access to multiple land uses by evaluating their accessibility and identifying areas of overlap between them. The study endeavors to increase access and density of service standards when planning the placement of new facilities based on these standards in new locations. The method developed in this study represents a critical stride toward achieving these key objectives. The findings reveal that only 47% of city population blocks enjoy high service accessibility, while 40% have moderate accessibility, and 2.6% experience poor accessibility. These insights are of significant value to urban planners, researchers, and policymakers striving to reduce energy shortages and promote sustainable energy and transportation strategies to mitigate environmental impact in urban areas. [ABSTRACT FROM AUTHOR]

This study addressed the need for a more comprehensive inventory of pit and quarry operations in Tetouan province and M’diq-Fnideq prefecture. It employed a Geographic Information System (GIS) approach, integrating various spatial remote sensing (RS) and field data to identify suitable areas for extracting alluvial, rocky, and clay materials. The used data includes quarry inventory, geological information, hydrographic networks, slope, and land use. The finding revealed 72 quarries and assessed their suitability for resource extraction. Alluvial deposits, approximately 127 million m³, were identified mainly in the primary wadis (river valley), including Oued Laou, Oued Amsa, Oued Mhajrate, and Oued Khemis. Massive rock deposits, consisting of limestone and sandstone, were estimated at 3.4 billion m³ . Clay deposits, suitable for various industrial applications, were also identified in significant quantities. In addition to confirming potential quarry deposits, our field surveys indicate that exploitation activities contribute to deforestation, and quarry waste often invades agricultural lands and forests. This information can facilitate sustainable resource management, environmental conservation, and informed policy and planning. The results highlighted the economic significance of geological resources in the study areas, contributing to various industries. Furthermore, by examining the relationship between quarries and the environment, including hydrographic networks, the study provides insights into eco-friendly quarrying practices. This methodology is expected to offer valuable insights into geological resources, guide sustainable resource management, and inform decision-making processes for regional development. [ABSTRACT FROM AUTHOR]

The hydrochemistry of groundwater in the Mann River basin, situated in eastern Maharashtra, was investigated through laboratory analysis with the aim of determining its suitability for consumption, agriculture, and industry. A total of 43 groundwater samples were collected from bore wells and dug wells across the basin for evaluation. Parameters including pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), and various cations and anions were examined in comparison with established standards set by the World Health Organization (WHO) and the Bureau of Indian Standards (BIS). Piper diagram analysis revealed that a significant portion of the samples fell into the CaMgHCO3 hydrochemical facies, while the Gibbs diagram suggested rock dominance in most samples. The drinking water quality index was calculated based on 11 parameters, with 52% of the samples falling into the excellent water category. The irrigation suitability assessment was based on parameters like the sodium adsorption ratio (SAR), percent sodium (%Na), and permeability index (PI), revealing that the majority of the samples were appropriate for irrigation. Moreover, assessments of industrial suitability rely on factors such as the Langelier saturation index (LSI) and Ryznar stability index (RSI) to estimate corrosion potential, with most samples showing a high propensity for corrosion and calcium carbonate deposition. Binary correlation effects were observed, suggesting that the presence of one physiochemical parameter could influence others. GIS-based maps were generated to precisely assess corrosion indices for effectively monitoring and managing water quality in the study area. This study is crucial as it evaluates the groundwater quality for its suitability for drinking, agriculture, and industry. It identifies groundwater's chemical characteristics, irrigation potential, and corrosion risks, offering key insights for water management, ensuring safe consumption, and supporting agricultural and industrial applications. [ABSTRACT FROM AUTHOR]

In the process of hydraulic engineering design, BIM is often manifested as a single model, and there is a lack of effective information sharing mechanisms among various disciplines. In order to improve the level of information sharing and design quality and efficiency and based on BIM+GIS technology, the paper analyzed the BIM design process of hydraulic engineering works and the requirements for BIM+GIS collaborative management, proposed a multi-party collaborative management mechanism of tasks, plans and personnel in the process of engineering planning, design, construction and operation and maintenance, developed a BIM+GIS collaborative management platform to achieve information sharing throughout the entire life cycle of the project. Taking the Middle Route Water Supply Project of Yinchuan metropolitan area as an example, the platform was practically applied. The application situation shows that the BIM+GIS collaborative management platform achieves unified management of engineering plan preparation and summary, task adjustment and change, visual progress control, design scheme demonstration and review. Collaborative design based on BIM+GIS achieves model assembly, collision detection and optimization design. The collaborative delivery of design based on BIM+GIS achieves the review and delivery of engineering design results. [ABSTRACT FROM AUTHOR]

AbstractDynamic community division is crucial for comprehending the interactive structure and mechanism between residents and space. Currently, there is insufficient research on dynamic community changes in travel networks regarding travel distance. This study utilizes residents’ travel trajectories to construct a multi-layer network based on travel purposes. The study establishes methods for identifying travel network communities and analyzing community evolution influence. Dynamic characteristics of travel network communities at different distances are extracted. Results show that within 3–7 km travel distance, different travel network communities exhibit continuous spatial aggregation, whereas beyond 11 km, heterogeneity is observed. Moreover, communities within 3-7 km experience drastic dynamic evolution, whereas beyond 7 km, they tend to stabilize, forming a large-scale and fixed travel mode. This study enriches the dynamic interaction research of functional space from the perspective of distance, and the experimental results provide an effective reference for urban planning and management. [ABSTRACT FROM AUTHOR]

As GIS progressively permeates our everyday lives, it becomes increasingly significant to incorporate emotional factors into the design and use of GIS technologies. While existing methods such as self‐report and AI‐enhanced techniques prevail in collecting emotional factors, they often miss real‐time emotional nuances and synchronization with geographically referenced and other accompanying data. To bridge this gap, we introduce "Neural Sensing," a novel approach that combines Electroencephalogram (EEG) with GIS technologies to quantitatively measure emotional responses to places. This approach offers a unique lens to understand human dynamics in a hybrid physical–virtual realm, especially by delving into our mental worlds. To demonstrate the utility of Neural Sensing, we have designed a pilot empirical study to analyze emotional reactions to geographical environments. This approach broadens the domain of GIS methodologies from remote sensing and social sensing to a neural sensing approach. Through this study, we underscore the importance of the mental dimension of the hybrid physical–virtual world and encourage GIScientists to emphasize human experiences and feelings in GIS analyses. [ABSTRACT FROM AUTHOR]

Although comprised of America's most iconic and varied ecosystems and landmarks, the boundaries of national parks have received little attention. This study uses boundary data from the National Park Service and other sources with compactness measures calculated using Geographic Information Systems. Using two common measures of compactness, the Polsby‐Popper and Reock methods, this study aims to answer several research questions: how are the type, location, and age of park units related to compactness, and how are changes in park boundaries related to changes in compactness? Compactness was found to vary between the types of national park units, as well as based on the location of parks within the country. Individual parks have become less compact over time. Due to the significance of national parks to ecosystem conservation, results of this study have crucial implications, providing some direction for future studies and federal regulation as well as overall conservation effort. [ABSTRACT FROM AUTHOR]

The mapping process generally involves intricate operations, such as symbol design, layout design, and text annotation, demanding a high level of professional expertise. The high requirement for map producers hinders the promotion and widespread adoption of mapping. Consequently, researchers are concentrating on techniques to automate and enhance the intelligence of the mapping process. For example, some studies attempt to train deep learning models for mapping, including methods like map style transfer. However, these approaches typically treat the entire map as a global input and generate a new map as output, lacking the flexibility to consider and control detailed elements within a map. Therefore, in this paper, we propose a large language model-based intelligent mapping framework, termed MapGPT, which can be used for mapping by considering the map as an integration of various map elements. Specifically, multiple professional mapping tools are designed in MapGPT, and each tool is designed to control a corresponding map element. With these tools, a large language model is used to first understand the demand of users based on mere natural language descriptions, and subsequently automatically invoke appropriate tools in sequence to generate a map. Furthermore, by utilizing a memory component to store interaction information, users can interact with MapGPT through conversation to adjust map elements such as color and position. In conclusion, MapGPT offers user-friendly mapping experience, showing potential to be a mapping assistant for professional map producers. A comprehensive demonstration of this framework is provided in a visual case study video, accessible at . [ABSTRACT FROM AUTHOR]

Recruiting undergraduate students is a significant challenge for undergraduate geography programs. Few students have robust exposure to geography in secondary school and the major has low name recognition for entering first year students. In fact, geography is often a "found" major on many campuses with students coming to the major after a general education course. But, does it need to be this way? Can geography programs take a more proactive role in building a pipeline of prospective students that is not solely tied to supporting AP Human geography teachers? In this paper, we describe an alternative path for university departments to build strong recruiting pathways, sharing the successes and challenges of building the connections and the learning advantages that students gain through early exposure to geospatial technologies. We focus on the Geospatial Semester, a dual enrollment program between James Madison University and participating school districts in Virginia (and beyond) that began in 2005. We share how departments can build a successful partnership with high schools and the process of sustaining such a program within a university setting. We will also describe the research we have done on the learning gains the Geospatial Semester provides to participating students and how extended use of geospatial technology bolters students' spatial thinking skills. [ABSTRACT FROM AUTHOR]

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Regulating services are the advantages that humans receive from regulating ecosystem processes. These services include, but are not limited to pollination, climate regulation, water purification, carbon sequestration, and erosion control. Quantifying and mapping ecosystem services in agroecosystems is one of the main effective actions to increase pay attention to these services and adopt suitable approaches to direct sustainability. The purpose of the study was quantification, and mapping of regulating ecosystem services in canola agroecosystems of Gorgan County, north of Iran. For this purpose, some regulating services such as carbon sequestration, climate regulation, soil microbial respiration, soil aggregate stability, and pollination by insects were evaluated based on the Common International Classification of Ecosystem Services framework. The information and data required for each of these services were collected through field measurements, laboratory experiments, and field surveys. After quantifying, the surveyed services in canola agroecosystems were presented on geospatial maps generated by ArcGIS software, version 10.3. Results showed that agroecosystems in the west and north of the studied region provided the more regulating services. Also, the results of the pollination showed that pollinating insects belonged to four orders and 13 families. The majority of the pollinators were Hymenoptera (44.74%), especially honey bees (Apis mellifera L.), Diptera (5.26%), Butterflies (Lepidoptera; 25%), and the beetles (Coleoptera; 25%), and Anthophora sp. and Andrena sp. were the second and the third most abundant pollinating species after honey bees. Generally, the canola agroecosystems close to the rivers and the natural ecosystems provided more services than other regions. [ABSTRACT FROM AUTHOR]

This article examines the potential of fuzzy set theory for analysing gradual changes in land use patterns within peri-urban areas. The primary objective of the study was to propose a methodology based on fuzzy set theory for the precise delineation of city boundaries and the identification and spatial localisation of the urban–rural transition zone. The analysis focused on elucidating the defining parameters of this area and the scope of land use changes within the urban–rural transition zone. The analysis employed data from four discrete time points. The data were collected in 2005, 2010, 2017, and 2022. The characteristics of the urban–rural transition zone were evaluated through an examination of historical data and the current land use patterns in regions experiencing direct urbanization pressure. The study demonstrated that, although spatial barriers remain, the city's development has continued at a consistent pace. Between 2005 and 2010, the area of land classified as urban exhibited a 10% increase, with a further 7% increase observed in the subsequent period, spanning 2010 to 2017. In the most recent period under examination, the urban land area increased by 9%, a figure that is consistent with the rates observed in previous years. These results indicate the stability of urbanization processes in the analysed city, while also revealing significant changes in the limits of urban development and in the intensity of land use. The research project concentrated on the city of Olsztyn and the neighbouring suburban areas, which are subject to direct influence from the city's expansion. The area under study encompasses 202.4 km2 within an eight-km radius of the city centre. The authors of the study emphasized the necessity for systematic monitoring of changes in the transition zone between urban and rural areas. This is to ensure effective control of spatial development and ongoing adjustment of planning tools to effectively prevent uncontrolled expansion. The methodology used enabled the precise delimitation of urban development and the transition zone. This allowed for an in-depth analysis of changes in land use intensity. [ABSTRACT FROM AUTHOR]

Limited research from the Global South has examined pedestrian accessibility to key destinations, particularly while considering efficient and practical sidewalk-specific conditions. This study employs a case-based approach, scrutinising walking access to three central squares, Mexico City's Zocalo, Lima's Plaza San Martin, and Buenos Aires' Plaza de la República, within a 10-min walking radius. Geographic Information Systems (GIS) and Google Street View (GSV) were leveraged to conduct a virtual street audit, assessing six microscale features influencing the walking experience (kerb ramps, pavement continuity, sidewalk width, well-maintained sidewalks, active uses, and green spaces). These data facilitated the construction of a genuine pedestrian network and allowed the assessment of three-tiered pedestrian accessibility models that comprised easy access, comfortable routes, and vibrant walks. The findings reveal significant spatial inequities in pedestrian access. About 10% of buildings near Mexico City's and Lima's central squares lack pedestrian accessibility due to inadequate and interrupted sidewalk and crosswalk infrastructure, disproportionately impacting those with mobility limitations. Conversely, Buenos Aires exhibits better pedestrian facilities, with accessible, comfortable, and lively routes reaching approximately 20% of buildings surrounding the Plaza de la República. These results underscore the significant disparities in street infrastructure and networks within these historic neighbourhoods, emphasising the imperative for more inclusive, pedestrian-friendly urban planning in Latin American cities. [ABSTRACT FROM AUTHOR]

Saudi Arabian cities have rapidly expanded their urban areas, especially their city centers, over the last four decades. This growth has led to increased vehicular usage. As a result, the daily walking experience for residents has been adversely affected. Walkability has several positive effects on people's health and the urban environment. It serves as a means of transportation and helps create a sense of place. This enhances the legibility of urban structures and deepens emotional bonds with the city. This study uses the medium-sized Saudi Arabian city of Onaizah as a case study. It explores the feasibility of creating urban walking corridors to encourage more walking. According to Saudi Arabia's Vision 2030, sustainable urban development and improved quality of life are key priorities. The study addresses walkability as a way to enhance the urban landscape of the city center. Geographic Information Systems (GISs) were used to analyze data and generate urban corridors in the city center. The results indicate that walking in Onaizah can be improved through three urban corridors. These corridors measure 1335 m, 1624 m, and 1937 m, respectively. They represent urban, commercial, and heritage corridors. This provides planners and decision makers an opportunity to prioritize pedestrian connectivity and improve the physical environment. Such efforts contribute to sustainable urban development. Various criteria-analysis methods were employed to assess the factors that led to the conclusion of these urban corridors. This includes evaluations of land use, transportation, and environmental considerations. The study aligns with Saudi Arabia's Vision 2030 by promoting walking and enhancing overall walkability. It also aims to create a sustainable and livable urban environment for the community in Onaizah. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is an important soil element for sustaining plant growth and the integrity of terrestrial ecosystems, and the soil P cycle is strongly influenced by climate change and agricultural activities. However, little is known about how soil P has evolved with climate change and intensive agriculture at mid‐high latitudes, where the soil P cycle is sensitive to climate change. To answer this question, an ecohydrological model (EcoHAT‐P) driven by remote sensing data was used in this study to calculate soil P concentration and loss and was calibrated and validated using 272 soil samples collected in the Sanjiang Plain, a typical mid‐high latitude region with a long history of strong agricultural activity. Soil P concentration and loss, and plant uptake of soil P, were analyzed for the years 2000–2019 and 2020–2040. The results showed that soil total P, soil P loss, and plant P uptake all increased under intensive agriculture. The soil P cycle at mid‐high latitudes was more sensitive to temperature than to precipitation. Increased temperature would increase soil P loss and plant P uptake by 93.94% and 8.16%, respectively, and soil legacy P from intensive agriculture would become the main source even if external P inputs were eliminated. The results highlight the evolution of soil P transport at mid‐high latitudes and clarify the response of soil P cycle to climate change under intensive agriculture. [ABSTRACT FROM AUTHOR]

In order to minimize human impact on the environment, it is crucial to determine the best way to utilize land through assessments of its suitability. This research focuses on the Anantnag district in the Kashmir valley, exploring its potential as a suitable area for mulberry agroforestry. Consequently, the selection of suitable sites for mulberry-based agroforestry has become an essential element of sustainable land use planning and agriculture, with the aim of maintaining ecological equilibrium. In the context of a Geographic Information System (GIS), we employ a method called multi-criteria assessment to evaluate the suitability of a specific site for mulberry agroforestry in the study area. This assessment involves considering various factors such as slope, temperature, rainfall, land use and land cover (LULC), as well as the physical and chemical properties of the soil. To assign scores to these criteria, we utilized the analytic hierarchy process (AHP) technique, conducted interviews with local experts, and referred to existing literature. By applying a weighted overlay analysis, which takes into account the importance of each parameter, we generated a map depicting the suitability of the research area for mulberry agroforestry. The map for mulberry agroforestry suitability in the study area indicates that 16.59% of the land is highly suitable, 28.16% is moderately suitable, 40.29% is marginally suitable, and 14.96% is unsuitable. To ensure the accuracy of the findings, satellite images, Sentinel-2b LULC mapping, and GPS-enabled field surveys were extensively employed to verify the results. These findings can be utilized by farmers, regional developers, and the government to inform their decisions regarding potential mulberry agroforestry areas and develop sustainable agroforestry management strategies for the region. [ABSTRACT FROM AUTHOR]

Waste mismanagement occurs in the canal catchment area due to uneven waste transportation services, allowing waste to leak into the canal. This research aims to identify catchment areas of the canal with the potential for waste mismanagement, estimate the amount of waste that could enter the channels and compare the results with the density of floating waste above the channel. The research method involves spatial analysis using GIS, incorporating various variables such as land use, building data for population and waste generation calculations, road network data for channel access, and service area data for garbage truck transportation. Next, we conduct an overlay analysis to create a zone map of potential littering areas in the channel, accompanied by an estimate of the waste amount. Furthermore, we used aerial mapping with a UAV as comparative data to monitor the density of floating waste. The results indicate that approximately 296 hectares of land, a potential zone for waste disposal into canals, generate 161,750 litres daily, accounting for 33% of the total waste generation in the water catchment area. This research successfully detected the density of floating waste at the top of the canal, particularly in four areas of the potential zone: Sambung Jawa Ward, Bontorannu Ward, Balang Baru Ward, and Pa'baengbaeng Ward, proves that there is mismanagement of waste on land. This situation demonstrates the need to address waste mismanagement by examining regional zones with access to a waste bank as an alternative solution. [ABSTRACT FROM AUTHOR]

Dairy farm wastewater contains high BOD, COD, and TSS, thus harming the environment if discharged without proper treatment. However, it is rich in nutrients, primarily nitrogen and phosphorus, which are needed by microalgae to grow and synthesis useful and high-value organic compounds. Microalgae biomass can be generated from a cultivation system that is integrated with wastewater sources efficiently. Selecting a suitable location is thereby crucial for the sustainable development of microalgae cultivation. This study aimed to select suitable locations in Cangkringan District, Indonesia for microalgae cultivation sites using the analytical hierarchy process (AHP) method integrated with geographic information system (GIS) and weighted overlay analysis (WOA). AHP helped determine the relative weights of the relevant factors, including dairy farm wastewater, temperature, land use, land elevation, and land slope in the study area. These weights were subsequently applied in WOA to determine locations that were most suitable for microalgae cultivation sites. The results of WOA, presented in the form of a land suitability map, showed that 0.1% (0.04 km²) of the studied areas is highly suitable for the development of microalgae cultivation and that a significant portion, approximately 67.2% (29.75 km²), is not suitable. [ABSTRACT FROM AUTHOR]

The El Haouz and El Kelaa Des Sraghna region is renowned for its agriculture, but is facing problems of salinisation due to its arid climate and unfavourable weather conditions. To remedy this, localised irrigation systems have been introduced to provide water for crops and improve yields. This study examines the impact of these irrigation systems on soil salinity in the region by comparing upstream and downstream areas. Using remote sensing techniques, we identify areas at risk of high salinity and collect soil samples for physical and chemical analysis in the field. These analyses enable us to monitor changes in salinisation and assess the effectiveness of localised irrigation in the areas concerned. Our results reveal two distinct zones in the region: an upstream zone with low salinity, with electrical conductivity ranging from 66 µS/cm to 345 µS/cm, and a downstream zone with higher salinity, with electrical conductivity ranging from 228 µS/cm to 1.075 µS/cm, attributed to the use of localised irrigation for crops. The remote sensing maps anticipated this difference, which was confirmed by the field analyses. [ABSTRACT FROM AUTHOR]

Soil erosion is both the cause and effect of land degradation. Land use/land cover conversion that changes the inherent landscape structure of watersheds leads to soil loss increase. Pantabangan-Carranglan Watershed (PCW) as a major source of irrigation, electricity, biodiversity, livelihood, and other ecosystem services, thus, it is imperative to spatially and temporally estimate the soil erosion within its boundary to assist and guide decision-makers in planning conservation and management of the watershed. Using the Revised Universal Soil Loss Equation (RUSLE) model, remotely sensed data, soil analysis, and geographical information system, the soil erosion rate in PCW was estimated. Results showed that there is increasing soil erosion in PCW over time. In 2010 soil erosion rate was estimated to be 134 tons·ha-1·yr-1 which increased to 141 tons·ha-1·yr-1 and 154 tons·ha-1·yr-1 in 2015 and 2020, respectively. Considering the average soil erosion rate and land cover types in PCW, annual crop and open/barren land cover types have the highest average soil erosion rate through time with moderate and catastrophic erosion levels, respectively. [ABSTRACT FROM AUTHOR]

The present comprehensive review delves into the pivotal role of morphometric analysis in watershed management, particularly in prioritizing sub-watersheds (SW) and reservoir catchments. Herein, the authors highlight the critical areas of water spread, soil erosion patterns and aquifer recharge. The study emphasizes the significance of morphometric parameters for effective conservation measures. The review takes a multifaceted approach, analyzing various parameters, exploring mathematical expressions and discussing the tools for sub-watershed (SW) prioritization. The areal, relief and linear parameters play a crucial role in comprehending watershed drainage networks, which in turn impact soil erosion, runoff, flood etc. In view of utility of fundamental Horton's laws, the present study provides a detailed description of each parameter's classification where the range of values and the impact of digital elevation model (DEM) accuracy on morphometric analyses have been discussed. While acknowledging the laborious nature of traditional morphometric analysis, the review also advocates for modern data reduction methods such as principal component analysis (PCA). In the present work, we have described the gaps observed in the sequenced literature reports cited through the content. In addition, the assessing parameter correlations are also acknowledged for emphasizing the ongoing challenges. [ABSTRACT FROM AUTHOR]

Over the past century, rapid population growth and continuous exploitation of natural resources have caused numerous changes. A notable transformation involves the modification of land surface temperature (LST), which is impacted by changes in Land Use-Land Cover (LULC). The most important approach in discovering changes is to increase the accuracy of classification methods. Deep learning techniques have been successfully used, and this improved performance has been carried over to image classification. This study aims to monitor and mapping the spatial and temporal changes of LULC and LST in Izeh city using remote sensing, GIS, and deep learning. LULC and LST maps for the years 2001 and 2021 were created by processing thermal and multispectral bands. Two methods were used to generate the land use-land cover map: pixel-based (Max Likelihood (ML)) and object-based (Fully Convolutional Network (FCN)). During this period, the percentages of changes in water, urban, and wasteland classes increased, whereas those for grassland, forest, and wetland classes decreased. The average LST changes followed this order: wasteland > urban > grassland > forest > wetland > water. The normalized differential vegetation index (NDVI), normalized differential water index (NDWI), and normalized differential build-up index (NDBI) were utilized to analyze the relationship between LST and LULC. A linear, positive relationship between LST and NDBI was observed, indicating the direct effect of urban development on the increase in LST in the study area. The overall accuracy for LULC maps using the ML method was over 80.74% in 2001 and over 90.76% in 2021. With the FCN method, the accuracy was over 93% in 2001 and over 98% in 2021. Finally, evaluation the spatiotemporal environmental effects of unchecked human activity on LULC and its relationship with LST can be achieved using remote sensing, GIS, and deep learning approaches. [ABSTRACT FROM AUTHOR]

The unpredictable nature of renewable energy sources, such as solar and wind, raises concerns about consistent power supply based on a single type. Green hydrogen presents a promising solution to mitigate the environmental effects of fossil fuels and control the unpredictability of renewable energy sources. Yet, developing green hydrogen systems mandates immense financial commitments, vitally stressing the importance of determining the most appropriate locations before constructing them. As such, the primary purpose of this paper was to propose an initial spatial analysis and prioritize the most suitable locations for installing solar-based green hydrogen systems in Tunisia. For this reason, an exhaustive literature survey was conducted to develop a GIS-based MCDM approach, taking into account technical, topography, environmental, and accessibility criteria. Then, EDAS, ARAS, MOORA, and COPRAS techniques were used to rank the most promising sites resulting from the previous stage. The study revealed that sites of high suitability, primarily in the southeastern and southwestern parts of Tunisia, spanned a total area of 1591 km2 (0.78%). Among such regions, Sfax, Monastir, and Sousse appeared to hold the top ranking as the most suitable locations for solar-based hydrogen. The "most suitable" sites had a hydrogen potential capacity of 9910 Mt per year, with Sfax, Monastir, and Sousse accounting for 14.5% of that capacity. By tapping into this immense potential and embracing the green hydrogen industry, Tunisia has the opportunity to lead in renewable energy adoption. This move could help ensure energy security, reduce dependence on imports, stimulate economic growth, and steer the nation toward a more sustainable and prosperous future. [ABSTRACT FROM AUTHOR]

Natural river landscapes can be biodiversity hotspots but are one of the most human altered ecosystems with habitats significantly damaged around the world, and a third of fish populations threatened with extinction. While riparian ecosystems have been negatively altered by anthropogenic activities, effective planning and restoration strategies can reverse negative impacts by improving habitat quality. However, restoring rivers requires appropriate data on current riparian health while also considering priorities for different stakeholders. To address this, a Geographic Information System (GIS) was used to create a new and transferable restoration priority model based on a section of the river Linth in Switzerland as a case study. The restoration priority model is founded on connectivity, river condition, national priority species and species hotspots. Landscape change of the riparian zone was analyzed using aerial imagery and landscape metrics. Almost a quarter of rivers within the study area were considered high or very high restoration priority, with many aquatic species set to benefit from restoration. From 1946 to 2019, the riparian landscape became highly fragmented due to significant growth in impervious surfaces and a concomitant loss of agricultural land. The GIS model provides a tool by which environmental agencies can manage natural features over large scales, while also planning priorities and targeting conservation strategies to the areas of greatest need. [ABSTRACT FROM AUTHOR]