Suitability Map Research Articles

Combining Moderate and High Resolution of Satellite Images for Characterizing Suitable Habitat for Vegetation and Wildlife

Combining different resolution of remote sensing satellites becomes a unique approach for vegetation and wildlife habitat assessment study. Remote sensing technology can reach land and water on the Earth's surface, and it can interpret signals from spectral responses. When these techniques are combined with Geographical Information Systems (GIS), land can be monitored in a variety of ways. Meanwhile, changes in land use led to changes in vegetation on the ground, with natural vegetation being removed from natural forests, leaving a degraded forest. This issue was not investigated for assessing habitat suitability for important plantations such as Eucalyptus plantation. Therefore, the study employed remote sensing and Geographical Information System (GIS) to model suitability of habitat to live and to survive in the Eucalyptus plantation. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) derived from a mathematical equation can demonstrate intensity of greenness of green vegetation in particular area and time, and availability of soil moisture, respectively, is very suitable to model the greenness of the area. WorldView-2 satellite image was pre-proceed, proceed, and classified to produce land use indicator in Sabah Softwoods Berhad plantation majoring Eucalyptus spp. tree planted in Tawau, Sabah. Sentinel and Landsat 8 image were used for vegetation and water stress indicator were downloaded from Land Viewer application. Net Primary Productivity (NPP) at monthly scale was also calculated and ranked the productivity for the suitability mapping. Climatic condition based on monthly precipitation and seasonality derived from ASEAN Specialized Meteorological Centre (ASMC) was employed for ranking its suitability value. In this study, natural forest and oil palm plantation is tested to developed suitability map for vegetation and wildlife habitat to live with. All indicators were ranked 10 to 40 presenting benefit and usefulness of the indicator to vegetation and wildlife in the study area. Then, final classification was made from accumulation of those indicators into 0 to 200 (Not suitable to Highly suitable). The results showed 59.9% of the area classified as moderately suitable, 36.9% highly suitable, 3.2% least suitable and no area was classified as not suitable. This type of study assisted forest managers and policymakers for better managing of their forests for better life of trees and wildlife under their management. The methodology adapted in the study is ecologically sounded and economically viable to be modified and complied in Sustainable Forest Management (SFM) in Malaysia and other tropical forest regions.

A Maximum Entropy Model of the Distribution of Dengue Serotype in Mexico

Pathogen strain diversity is an important driver of the trajectory of epidemics. The role of bioclimatic factors on the spatial distribution of dengue virus (DENV) serotypes has, however, not been previously studied. Hence, we developed municipality-scale environmental suitability maps for the four dengue virus serotypes using maximum entropy modeling. We fit climatic variables to municipality presence records from 2012 to 2020 in Mexico. Bioclimatic variables were explored for their environmental suitability to different DENV serotypes, and the different distributions were visualized using three cutoff probabilities representing 90%, 95%, and 99% sensitivity. Municipality-level results were then mapped in ArcGIS. The overall accuracy for the predictive models was 0.69, 0.68, 0.75, and 0.72 for DENV-1, DENV-2, DENV-3, and DENV-4, respectively. Important predictors of all DENV serotypes were the growing degree days for December, January, and February, which are an indicator of higher temperatures and the precipitation of the wettest month. The minimum temperature of the coldest month between −5°C and 20°C was found to be suitable for DENV-1 and DENV-2 serotypes. Respectively, above 700–900 mm of rainfall, the suitability for DENV-1 and DENV-2 begins to decline, while higher humidity still favors DENV-3 and DENV-4. The sensitivity concerning the suitability map was developed for Mexico. DENV-1, DENV-2, DENV-3, and DENV-4 serotypes will be found more commonly in the municipalities classified as suitable based on their respective sensitivity of 91%, 90%, 89%, and 85% in Mexico. As the microclimates continue to change, specific bioclimatic indices may be used to monitor potential changes in DENV serotype distribution. The suitability for DENV-1 and DENV-2 is expected to increase in areas with lower minimum temperature ranges, while DENV-3 and DENV-4 will likely increase in areas that experience higher humidity. Ongoing surveillance of municipalities with predicted suitability of 89% and 85% should be expanded to account for the accurate DENV serotype prevalence and association between bioclimatic parameters.

Assessing Sustainable Ecotourism Opportunities in Western Rajasthan, India, through Advanced Geospatial Technologies

The present study focuses on finding potential sites for ecotourism development using GIS and remote-sensing-based weightage sum overlay techniques in Western Rajasthan, India. Ecotourism is one of the fastest growing and revenue-making sectors incorporating a sustainable future. Western Rajasthan has a broad scope to develop tourism-based activity in various ways, mainly through cultural heritage, historical and archaeological wonders, and rare wildlife. Weightage sum overlay analysis is a useful and simple tool to compare each thematic layer. These values are based on various factors and understanding taken during the study. For this purpose, different data types have been taken from the USGS website. Arc GIS 10.8 and ERDAS Imagine software 2015 have been utilized to process the data. This research incorporates seven thematic layers, i.e., elevation, proximity to streams, land use/cover, population density, road connectivity, proximity to protected areas, and heritage hotspots. Based on the physical and cultural characteristics of Western Rajasthan, the weightage of each thematic layer has been decided, which is finally overlaid using Arc GIS software. After processing all the thematic layers, we finally get an outcome in the form of a suitability map. The final suitability map represents five suitability classes that divide the total area into the following categories, very high (37.31%), high (26.85%), moderate (7.89%), low (0.83%), and very low (27.12%), which represents the potential of ecotourism in Western Rajasthan.

Groundwater Management for Agricultural Purposes Using Fuzzy Logic Technique in an Arid Region

The study aimed to determine groundwater’s suitability for irrigation and cattle rearing in Kuwait. In this regard, groundwater samples were collected from Umm Al Aish (UA) and adjoining Rawdhatain (RA) water wellfields to develop groundwater suitability maps for irrigation purposes using the fuzzy logic technique in ArcGIS. RA was dominated by Na-Cl, Na-Ca, and Ca-SO4 water types, whereas UA was dominated by the Ca-Mg water type. Due to the influence of the temperature and pCO2, the carbonates were inferred to be more susceptible to precipitation in the soil than the sulfates. The ternary plots for both regions revealed that the samples’ suitability ranged from good to unsuitable. Spatial maps of nine significant parameters governing the irrigation suitability of water were mapped and integrated using the fuzzy membership values for both regions. The final suitability map derived by overlaying all the considered parameters indicated that 8% of the RA region was categorized as excellent, while UA showed only 5%. Samples situated in the study areas showed an excellent to very satisfactory range for livestock consumption. Developing a monitoring system along with innovative water resource management systems is essential in maintaining the fertility of the soil and existing groundwater reserves.

Modeling tree species richness patterns and their environmental drivers across Hyrcanian mountain forests

Perception of the way tree species richness distribution varies along the elevational gradient is necessary for applying conservation strategies in favor of biodiversity hotspots. Hyrcanian Mountain Forests of Iran are among the most biodiverse forests in the world and are inscribed in the United Nations Educational, Scientific, and Cultural Organization (UNESCO) World Heritage List. Here, the Bayesian Additive Regression Tree (BART) and Stack-Species Distribution Model (S-SDMs) were used to understand tree diversity patterns of the Hyrcanian Mountain Forests. For all the tree species, we implemented the BART model with nine environmental variables, including six bioclimatic and three topographic variables, to create a habitat suitability map. We used the area under the curve (AUC), True skill statistic (TSS), type I error, and type II error to evaluate the BART model for each tree species. All models were then stacked to estimate tree species richness. Important variables affecting the distribution of tree species in northern Iran were different for each species but, in general, topographic variables such as slope and altitude played a very important role. BART model mapped all the 29 tree species distribution effectively with AUC 0.83–0.98, TSS 0.51–0.92; and low type I and type II errors. A very important point was the high ability of this model to predict species with low presence data. The achievement of this study was identifying the biodiversity hotspots based on the tree distribution pattern along the elevational gradient. We mapped regional richness at 1 km spatial resolution and it was the first effort to predict macroecological patterns in the Hyrcanian forests of Iran. The hotspots were mainly scattered from sea level and areas with 1000 m elevation, which were close to residential areas. In conclusion, these results help forest manager to plan new conservation strategies based on tree richness hotspots.

A scenario-based food security analysis and halophyte crop suitability assessment in dying lake environments impacted by climate change

Climate change has significantly impacted food shortages over the past decades, and predicted projections have also indicated potentially intensive consequences for species diversity and natural environments in the coming decades. Climate change in the form of drought has resulted in environmental impacts on global dying lakes (GDLs), such as water scarcity, land degradation and food shortage. Thus, new comprehensive environmental impact assessment methods are urgently needed for GDLs to inform decision-making and minimise the negative impacts on the environment and human life and wellbeing. As state of art and progressive research, the main objective of this research is to develop an approach using a comprehensive and transferable geographic information science scenario-based suitability assessment to analyse the capability of halophyte plants as alternatives for crop modification in GDL areas. The approach was developed and examined for Salicornia suitability mapping in the Lake Urmia Basin as one of the most critical GDL cases. To obtain the ecological requirement information, we performed a scenario-based cultivation experiment on Salicornia under different salinity conditions. Accordingly, we employed relevant ecological requirements and environmental indictors for the Salicornia plant (e.g. soil characteristics and climate) to identify suitable areas for cultivating this plant under scenario-based spatial modelling and performed an uncertainty analysis. The results were achieved and validated in a field operation and laboratory analysis. According to the results, the Salicornia plant can be efficiently considered an alternative crop in farmlands around Lake Urmia that are impacted by intensive soil, aquifer salinisation and food production issues. Results pointed out that about 4.6% of the area (2372 km2) is highly suitable for the cultivation of Salicornia. As state of the art, our approach was developed in a semi-automated context but can also be customised and applied to similar case studies in GDL environments. We expect that the information and insights gained from such assessments will support stakeholders, decision makers and authorities in the development of effective policies and plans for mitigating the impacts of climate change on the fragile ecosystems of GDLs.

Agricultural land suitability assessment with GIS-based multi-criteria decision analysis and geostatistical approach in semi-arid regions

For sustainable land use planning, evaluating land characteristics and making suitable land use decisions is a priority and critical step. In order to make these evaluations safely, spatial analyzes of many criteria should be made. In this study, the suitability of the land for wheat production was evaluated by Geographical Information Systems (GIS) based Multiple Criteria Decision Analysis (MCDA) in semi-arid conditions. In obtaining the land suitability map; fuzzy set model, Analytical Hierarchy Process (AHP) and GIS are integrated. Ecological criteria weights for agricultural land suitability were determined by AHP. In the suitability analysis, a total of criteria including soil and topographic features were evaluated. Geostatistical analysis approach was applied to determine the spatial variability of soil properties (sand, clay, silt, pH, OM, CEC, ESP, CaCO3, EC). The lowest variation among soil properties was observed in pH (3.8%), while the largest variation was observed in ESP content (107.5%). The nugget/sill ratio is poor for EC and pH, while other soil properties are moderately spatially dependent. According to the results of the analysis, 25.7% (3.226 km2) of the area is highly suitable, while 27.6% (3.457 km2) is moderately suitable and 19.5% (2.440 km2) is marginally suitable for wheat cultivation. In addition, 27.2% (3.415 km2) of the area is not suitable for agricultural production. The use of geostatistical modeling, MCDA and GIS together is very beneficial in making agricultural land management decisions.

Methodological approach for the evaluation and mapping of the agronomic suitability of soils in tropical zones: Case study of the Bambouto volcanic massif (Western Cameroon) and the Bokito district (Central Cameroon)

The main pillar of agriculture is the soil because it is both the support and the reservoir of essential nutrients for the plant. The food function it provides for humanity can only be fully fulfilled if it is balanced. Therefore, the development of sustainable agriculture in the world necessarily requires knowledge of the soil. The evaluation of agronomic suitability consists in determining its intrinsic capacity to sustain agricultural productivity over time. Many studies have been conducted in the domain of agricultural land assessment, but the applicability of the methods used in the tropical context requires adaptations that are not always obvious. The new methodological approach we propose for agronomic suitability assessment(AA) was designed and tested in Cameroon (Central Africa) in two pilot sites chosen in two different agro-ecological zones. The sites were the bimodal forest in Bokito which developed on yellow ferralitic soils, and the highland in the Bambouto volcanic massif which had a great pedological variability ranging from red ferralitic soils to andic ferralitic soils and andosols. The approach is inexpensive and based on the combination of four intrinsic soil parameters, namely acidity (pH), useful water reserve (RU), cation exchange capacity (CEC) and erodibility (K); according to the formula: AA = pH × RU × CEC × K. The unit of measurement is the « equivalent hour per mega joule per millimeter (eq.hr. MJ-1mm-1) ». The results showed that the agronomic suitability of the yellow ferralitic soils of Bokito varies from 0.00 to10.53 eq.hr. MJ-1mm-1. On the volcanic massif of Bambouto, the agronomic aptitude varies from 0.00 to 15.70 eq.hr. MJ-1mm-1 on the red ferralitic soils of the lower part of the massif, from 15.70 to 41.84 eq.hr. MJ-1mm-1 on andic ferralitic soils of the middle part of the massif and reaches 108.85 eq.hr. MJ-1mm-1 on the andosols of the summit part of the massif. This work could allow, on the one hand, a better allocation of agricultural land and thus participate in the development of second generation agriculture in sub-Saharan Africa; and on the other hand, contribute to determine more precisely the quality and quantity of fertilizer needed to maintain soil balance. Controlling the use of fertilizers will help to significantly reduce the quantities of chemical elements contained in agricultural products, limit water and soil pollution and thus better preserve human health.

Land suitability in sustainable cultivation practices for porang (Amorphophallus oncophyllus L.) in Pasuruan Regency, Indonesia

Porang (Amorphophallus oncophyllus L.) stands as a prominent agricultural product in Indonesia. As the demand for porang continues to grow, it becomes crucial to balance it with the expansion of suitable land for cultivation. The selection of appropriate land for crop planting requires a thorough analysis of land feasibility, commonly known as land suitability assessment. This study aims to evaluate land feasibility, identify limiting factors, and explore potential solutions for sustainable cultivation of porang in Sumberejo Village, Pasuruan, East Java. The research was employed by a matching method for land suitability assessment based on climatic, physical, and chemical data. The development of a land suitability map was achieved through the overlay of various stages using land characteristic information. The findings reveal that the residents' lands fall within the actual land classes of S3 (suitable marginal) and N (not suitable), with base saturation (nr3) and slope (eh) identified as the primary limiting factors. To improve the suitability of the selected lands, several recommendations were proposed, including the implementation of cover crops, terracing practices, and the addition of potassium-rich organic matter derived from bamboo waste. These recommendations have the potential to elevate the land class to S2 (suitable) and S3 (suitable marginal), thereby addressing the identified limitations and promoting sustainable porang cultivation.

Integrated Fuzzy AHP-TOPSIS Model for Assessing Managed Aquifer Recharge Potential in a Hot Dry Region: A Case Study of Djibouti at a Country Scale

Given the prevailing arid climate and rapid population growth, groundwater resources face unprecedented challenges globally, including depletion, seawater intrusion, and contamination. Managed aquifer recharge (MAR) technologies have emerged as valuable solutions to address these pressing issues. However, identifying suitable regions for MAR activities is a complex task, particularly at the country level. Therefore, in this study, we propose a robust approach that combines the fuzzy analytical hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) to delineate suitable sites for MAR structures. The proposed model was applied to Djibouti, a hot, dry, and water-stressed country. We identified a set of nine decision criteria and conducted a pairwise comparison survey to determine their relative importance. Additionally, the TOPSIS method was employed to integrate the decision layers and prioritize the study area. The results highlight the significance of rainfall, the slope, and the NDVI as the most influential decision parameters, while the drainage density has the least impact. A suitability analysis reveals that 16.38%, 17.96%, and 30.41% of the country have a very high, high, and moderate potential for MAR activities, respectively. Furthermore, a sensitivity analysis demonstrates the stability of the proposed model, affirming the usefulness of the generated suitability map.

Climate and soil suitability zonation for Litchi (Litchi chinensis) in India using geo-science tool-based analytical hierarchy process

Litchi (Litchi chinensis) plantations in new areas without any land suitability assessment putting small farmers at risk of economic loss. The unique capability of the Geographical information system (GIS) for integration, analysis, and interpretation of spatial data has been leveraged for the identification, and mapping of potential litchi cultivation zones in India to help farmers and policymakers make informed decisions. Five climate-derived parameters including the number of days per year having a minimum temperature <12 °C (CumD-Tmin < 12), number of days per year having a minimum temperature <0 °C (CumD-Tmin < 0), number of days per year having a mean temperature <20 °C (CumD-Tmean < 20), highest daily maximum temperature (°C) (Thmax) and average annual rainfall (mm), and eight soil parameters viz. soil depth, clay content, slope, stoniness, drainage conditions, pH, electrical conductivity (EC), organic carbon were identified as suitability parameters. Geospatial data at a grid 0.1° × 0.1° of all the identified climate parameters and spatial layers of eight soil data were analysed using Arc-GIS 10.2. The analytical hierarchy process (AHP) was used for assigning relative weightage to the suitability parameters. Using the weighted sum of feature layers, a climate suitability map, a soil suitability map and finally a litchi cultivation potential zones (LCPZs) map were developed. The northward shift of the suitability zone is indicated under climate change projections. The new approach of identifying suitability parameters in relation to the plant’s requirement and its integration in GIS using AHP can be extended to other crops and regions.

Innovative Methods for Mapping the Suitability of Nature-Based Solutions for Landslide Risk Reduction

The impacts of climate change are becoming more widespread across the world, with hydro-meteorological extreme events on the rise, causing severe threats to nature and communities. Increasing trends in the frequency and intensity of floods and landslides have been projected by climate models. This necessitates the development of more effective measures such as nature-based solutions (NBS) which can complement grey infrastructures. Recent studies have identified knowledge gaps and limitations in existing research and tools that aid in spatial planning for the implementation of large-scale NBS and proposed new methodologies for the spatial allocation of large-scale NBS for flood risk reduction. This work presents a novel method for mapping the suitability of NBS addressing geo-hydrological hazards such as shallow landslides, debris flow, and rockfall, which are typically caused due to slope instability. This methodology incorporates landslide susceptibility mapping, and was used to create a toolbox ESRI ArcGIS environment to aid decision-makers in the planning and implementation of large-scale NBS. The spatial allocation toolbox was applied to the case study Portofino promontory, Liguria region, Italy, and 70% of the area was found to be highly susceptible to landslides. The produced suitability maps show that 41%, 33%, and 65% of the study area is suitable for the restoration of terraces, bio-engineering, and vegetative measures such as NBS for landslide risk reduction.

Recycled water could recharge aquifers in the Central Valley

Drawing out too much groundwater, or overdrafting, is a serious problem in California. As a result, groundwater sustainability agencies are considering using recycled municipal wastewater to recharge aquifers. In our study, we employ suitability mapping and the models C2VSimFG and Ichnos to identify appropriate areas for managing aquifer recharge with recycled water in California's Central Valley. The factors that influence suitability include soil properties, proximity to recycled water sources, and the residence time, or amount of time that recharged water spends underground. There are many suitable areas in the Central Valley that are immediately adjacent to water recycling facilities. However, adequate supply is an issue in most locations. Roughly half of the groundwater sustainability agencies in critically overdrafted basins of the Central Valley have enough potentially suitable locations to meet their recharge goals, but not all of them have access to enough recycled water. The methods demonstrated here can serve as tools for agencies considering using recycled water for aquifer recharge.

Suitability evaluation of rural sewage treatment facilities in China considering lifcycle environmental impacts and regional differences

Centralized vs. decentralized sewage treatment is one of the key issues in the planning of rural sewage treatment (RST) in China due to the country's diverse regional characteristics. There are very limited comprehensive evaluation models for selecting regionally suitable schemes and facilities, particularly for national or provisional scale planning. As a scenario-based multi-attribute decision-making (MADM) issue, this paper develops a novel RST suitability evaluation model by integrating the multi-attribute analytic hierarchy process (AHP) with the technique for order preference by similarity to an ideal solution (TOPSIS). The suitability evaluation model sets up 3 small-centralized and 4 decentralized RST facilities as candidates and includes 12 evaluation indicators that cover economic cost, life cycle environmental impacts, technical features and operations management. Eight generic scenarios are classified for Chinese rural areas based on differences in three major characteristic factors, i.e., population density (PD), the economic development level (EDL), and topographic slope (TS). The universal evaluation results show that a centralized sewage treatment scheme is more suitable for areas with a high PD/high EDL/low TS, while a decentralized scheme is more suitable for areas with a low PD/low EDL/high TS. Sensitivity analysis shows that in regions with a high PD/low EDL, the indicator weight of the construction investment cost in the model has a great influence on the facility suitability ranking. However, in regions with a high PD/high EDL, the ranking is the most sensitive to the indicator weights of the global warming potential and sewage treatment effect. Furthermore, as a spatial decision issue, an RST suitability map of Hunan Province in China is produced at the county level of resolution, and the map is generally consistent with our field knowledge of several counties in Hunan Province. The presented evaluation framework can be integrated into environmental decision support systems in the future to help local and central governments, water utilities, design institutes and other stakeholders scientifically plan RST projects.

Analysis of Water Harvesting Structures Sites Appropriateness Using GIS-Based Methodology: Diyala, Iraq, as a Case Study

Water harvesting is an effective technology that may be used to collect unused runoff, therefore meeting various water needs and mitigating droughts. The study area is experiencing severe water lacks, so the goal of this research is to find ideal locations for structures of water harvesting through the use of a geographical information system-based multi-criteria analysis model that employs fuzzy logic with the analytical hierarchy process model. According to the hydrology and geomorphic criteria of the research area, a suitability map for water harvesting was constructed, and 17 and 12 sites suitable for check dams and farm ponds, respectively, were suggested in the regions with high and very high classes. Thus, this study’s findings underline the significance of geospatial modeling in planning water facilities and addressing the water shortage issue in the study region.

Towards sustainable marine spatial planning of aquaculture

An efficient and adaptive strategy within the EU Marine Spatial Planning Directive has to manage the existing and increasing conflicts between human uses and habitat conservation in coastal-marine areas. Among the different human activities developed along the coasts, aquaculture occupies a primary role. In this context, the aims of this research have been: (1) to propose a conceptual model suitable for aquaculture marine spatial planning; (2) to collect and integrate indicators useful for the characterization of the study area in terms of socio-ecological-economic sensitivities and pressures; and (3) to identify and map the most suitable areas for the development of new fish and shellfish farms. The study area is the Apulia Region (Southern Italy) with a coastline of about 1,000 km, in the Adriatic and Ionian Seas, and characterized by several economic activities within a high value natural context. The evaluation of area’s suitability for fish and shellfish farms have been carried out through the ecological characterization of the coastal areas, the identification of the socio-economic, ecological, cultural, and legal-military constraints and the estimate of the “Suitability Index” that, through a Weighted Linear Combination, integrates environmental variables and allows to classify areas as “Highly Suitable”, “Suitable” or “Unsuitable”. The “highly suitable areas” for new fish and shellfish farms are mainly located in northernmost of the Southern Adriatic Sea along the Gargano coast and in the Gulf of Manfredonia, whilst concerning the Northern Ionian Sea they are at a mean distance of 5 Km from the shoreline. The suitability maps have shown that existing fish farms are in line with their suitable areas but, surprisingly, this has seemed not to be true for shellfish farms. This can be explained by the fact that these aquaculture activities have traditionally been present in some areas (e.g., Taranto Seas), currently strongly impacted by human activities. This research has highlighted that despite aquaculture is generally conceived as an environmental impacting activity, it could be also impacted by other environmental and/or anthropic stressors (i.e., industrial ports, sewage discharges). Considering all these elements, the present research addresses decision-makers, providing information and tools necessary to plan in a more aware way, and also stakeholders interested in investing in the aquaculture sector, who could benefit from the proposed suitability maps for fish and shellfish farms for a sustainable development of this sector.

Predicting Suitable Areas for African Swine Fever Outbreaks in Wild Boars in South Korea and Their Implications for Managing High-Risk Pig Farms.

African swine fever (ASF) is a highly contagious disease affecting domestic pigs and wild boars, with no effective vaccine or treatment available. In South Korea, extensive measures have been implemented to prevent ASF transmission between wild boars and ASF spillover from wild boars to pig farm sectors, including the search for ASF-infected carcasses in mountainous forests and the installation of fences across wide areas of these forests. To determine the priority search range for infected carcasses and establish pig farm-centered quarantine measures, it is necessary to predict the specific path of ASF outbreaks in wild boars and identify pig farms at high risk of ASF spillover from wild boars. Here, we aimed to predict suitable areas and geographical paths for ASF outbreaks in wild boars using the MaxEnt model and shortest-path betweenness centrality analysis. The analysis identified a high frequency of ASF outbreaks in areas with a suitability value ≥0.4 on the suitability map and in areas within a 1.8 km range from the path on the shortest-path map, indicating these areas were high-risk zones for ASF outbreaks. Among the 5063 pig farms analyzed, 37 were in the high-risk zone on the suitability map, 499 were in the high-risk zone on the shortest-path map, and 9 were in both risk zones. Of the 51 pig farm sectors with a dense distribution of pig farms (kernel density ≥ 8), 25 sectors were in contact with or partially overlapped the high risk zone on the suitability map, 18 sectors were located within the high risk zone on the shortest-path map, and 14 sectors were located within both risk zones. These findings aided in determining the priority range for searches for wild boar carcasses and enabled the establishment of preemptive ASF prevention measures around the pig farming sectors that are at risk of ASF spillover from wild boars.

Land suitability evaluation for cattle grazing through multi-criteria approach using remote sensing and GIS

The current study aimed to map the potential grazing areas available in the Thondamuthur block of Coimbatore district in Tamil Nadu, India. Factors like distance from cattle location, distance from water sources (natural and manmade), slope, enhanced vegetation index (EVI) and land surface water index (LSWI) were considered. Various suitability classes (very high, high, moderate, low and very low) were derived for each factor and the final suitability map was prepared by using the analytic hierarchy process (AHP) and weighted overlay techniques using Sentinel-2A data. The results revealed that the high suitability category occupied the largest area (14.81%) followed by the very high suitability category (3.57%). The moderate, low and very low suitability categories occupied a small per cent of the total area viz., 1.66%, 0.20% and 0.03%, respectively. The identified areas could be brought under scientific management for pasture development.

Habitat suitability mapping using logistic regression analysis of long-term bioacoustic bat survey dataset in the Cassadaga Creek watershed (USA)

Bat species show global ecological importance, yet their numbers are declining worldwide. Understanding bat-habitat interactions is crucial in terms of developing effective conservation plans. In an effort to model bat habitat suitability in the Cassadaga Creek watershed, long-term bioacoustic bat data (spanning 2009–2020) was compiled, georeferenced and statistically analyzed using logistic regression techniques. In total, 1600 bat occurrence records from five species of bat (559 Eptesicus fuscus, 560 Lasionycteris noctivagans, 143 Lasiurus borealis, 260 Lasiurus cinereus, and 78 Myotis lucifugus) were paired with pseudo-absence points to study the relationship between bat calling behavior and land cover. All bats but Myotis lucifugus had a statistically significant relationship with forested land cover, and all bats had negative interactions with agricultural habitats. Geospatial data was coupled with the statistical output to create maps of habitat suitability and echolocation calling density. This work provides a model that can be employed worldwide to evaluate bat habitat needs or patterns in echolocation behavior. Future research will incorporate a more recently collected dataset that is of greater geographic diversity with a larger number of environmental variables in the species distribution model.

Soil Survey Relevant Information for Land Suitability Zoning and Territorial Planning. Case study Usumacinta Watershed Mexico

In Mexico during the last decades, the anthropic pressure exerted on natural ecosystems and land dedicated to productive activities has been increasing, causing intense negative environmental effects on soil, water, flora and fauna resources.&nbsp; These effects can be addressed through adequate land-use planning; an essential step for the definition and application of management programs is the zoning land by suitability. Soils, conceptualized as a natural body constitute a useful approach for the study and analysis of the natural system. Therefore, the objective of this article is to show the importance and the fundamental role of soil information, acquired through soil survey, in land suitability zoning and territorial planning. From database of soils, qualifiers of soil properties were used to define limitation related with effective soil depth, fertility, soil drainage and salinity - sodicity. Then for each one of these limitation factors, individual maps&nbsp; were constructed, which by a decision model were integrated in a final land suitability map. The results, according to this map show, in the lowlands where slope is less than 12%, three general groups of land suitability: Lands of classes I to III, with slight limitations to crop production(23.2%, of the total area), lands with moderate limitations class IV (8.2 %) y and lands of classes IV, V and VI with moderate to severe limitations,very poor drainage and flooding (24.4%). In the highlands, were the slope is higher than 12% have moderate (class IV, 10%)&nbsp; to severe limitations (VI-VII, 31%)&nbsp; and&nbsp; class VIII (3%).