Agricultural drought is a complex phenomenon with major impacts on ecosystems, biodiversity, and ecosystem services. This study examines drought severity in Lorestan, Iran, using spatial analysis of vegetation indices, including the Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI). Landsat images from 2004, 2014, and 2024 were processed using TerrSet software to assess drought trends. The results show a clear increase in drought severity in Lorestan over the past 20 years, with fewer areas free from drought and more regions facing mild to moderate drought conditions. The analysis of results reveals that drought-free areas changed by approximately 14.7%, while areas under mild drought increased by 6.5% and moderate drought by 8.2%. These shifts show a strong correlation with observed land degradation (bare land + 8.1%, dense vegetation − 8.5%), confirming heightened ecosystem stress through integrated drought indices. This trend indicates a growing threat to crops, water resources, and ecosystem stability. The study demonstrates the effectiveness of using vegetation indices like NDVI, VCI, TCI, and VHI for monitoring drought patterns. These tools can help detect early warning signs, allowing farmers and policymakers to take timely action. To reduce the damaging effects of drought, improved water management, sustainable farming practices, and long-term adaptation strategies are urgently needed. By incorporating these monitoring techniques into regular assessments, authorities can better prepare for and respond to future droughts, protecting both agriculture and the environment.

Forest degradation is a serious environmental issue that has significant implications for ecological stability, biodiversity, and human well-being. Identifying the extent and severity of forest degradation is crucial for effective management and conservation of forest ecosystems. The objective of this study was to assess the ecological vulnerability of the forest in the Dadabad region using spatial analysis and landscape metrics. The land cover map of the area was divided into 13 sub-basins to quantify landscape metrics, and the severity of human activities, degradation level, and ecological vulnerability were calculated for each sub-basin. Each sub-basin was evaluated as a single landscape to determine the extent of degradation, and landscape zoning was performed based on the degradation coefficients. The study found that sub-basins 2 and 4 had the highest levels of degradation, while sub-basins 3, 7, 8, 11, and 12 were the least degraded. Over half of the Dadabad region, 37.8% for protection and 32.25% for rehabilitation, was recommended for conservation planning. The research highlights the importance of using spatial analysis of landscape metrics to assist managers and planners in protecting and conserving natural areas.

Selection of suitable sites for wind power plants is one of the most important decision on wind resources development. Site selection for the establishment of large wind power plants requires spatial evaluation taking technical, economic, and environmental considerations into account. This study has applied a combination of PROMETHEE and Fuzzy AHP methods in a geographical information system environment to carry out spatial site selection for wind power plants in Lorestan Province of Iran. The fuzzy analytic hierarchy process method is used to determine the weights of the criteria whereas the PROMETHEE method is used to prioritise the alternatives based on the weights obtained from the fuzzy AHP. The integration of GIS and MCDM makes a powerful tool for the selection of the best suitable sites because GIS provides efficient manipulation, analysis and presentation of spatial data while MCDM supplies consistent weight of alternatives and criteria.The results showed that about 7.38 % of the area of Lorestan province is most suitable for wind power plants development. Sensitivity analysis shows that suitable zones coincide with suitable divisions of the input layers. The sensitivity analysis showed satisfactory results for the combination of PROMETHEE and Fuzzy AHP methods in wind power plant site selection.

Landfill site selection is a complex decision-making process which requires the evaluation of various environmental, social, and economic criteria. The present research aims to propose a GIS-based Stepwise Weight Assessment Ratio Analysis (SWARA) method for landfill site selection in the east of Lorestan province, Iran. The study used 11 criteria including land use, distance from protected areas, slope, elevation, distance from the water resource, distance from the road, geology, distance from the fault, soil texture, distance from the city, and distance from the village. The results show that the proposed method can be used as a reliable tool for landfill site selection. The method provides decision-makers with a systematic approach to evaluate and rank potential sites based on their suitability. The study found that distance from water resources and soil texture were the most important criteria for landfill site selection in the study area. The proposed method can help decision-makers to identify suitable sites for landfill development considering potential environmental impacts. The study highlights the importance of using the GIS-based SWARA technique for landfill site selection, as it provides a comprehensive and efficient approach to decision-making. The proposed GIS-based SWARA method can be used as a valuable tool for landfill site selection in other regions and can help in achieving sustainable development goals.