Geocarto International

Geospatial Intelligence for Climate Resilience, Water Security and Sustainable Agriculture

Geocarto International is pleased to welcome you to submit your research to the Article Collection "Geospatial Intelligence for Climate Resilience, Water Security and Sustainable Agriculture".

Climate change, environmental degradation, and increasing pressure on natural resources are deeply intertwined. This is triggering complex problems for water resources, agriculture, livelihoods, and environmental well-being. With the advancement of modern technologies such as Earth Observation (EO), Geographic Information System (GIS), Geospatial Modeling, and Artificial Intelligence (AI), environmental problems can be better analysed and addressed in different spatiotemporal contexts. Geospatial Intelligence refers to the process of combining data from different sources such as satellite imagery and observations, climate data, field data, spatial databases, and analytical and modeling methods to produce actionable and decision-making information about the environment. This Article Collection will bring together research on new and innovative uses of geospatial technology in assessing climate change risks, water resource status, agricultural sustainability, and environmental change. Particular emphasis will be placed on integrated and data-driven approaches that combine Earth Observation, geospatial analysis, machine learning, spatial modeling, and decision-support techniques to better understand complex ecological systems, assess future risks, and support effective environmental management and decision-making.

Climate extremes such as floods, droughts, changes in rainfall patterns, and rising temperatures are currently affecting water availability, agricultural production, ecosystems, and the sustainability of human habitation and livelihoods in different regions around the Globe. Conventional environmental monitoring methods have several limitations in many cases, such as wide-area monitoring, long-term data collection, and the ability to analyse different types of environmental data simultaneously. Geospatial Intelligence can overcome these limitations to a large extent. Through this, it is possible to regularly and spatially monitor environmental changes in an area by combining satellite data, climate data, field observations, and data from various models. In addition, in many cases, it is also possible to analyse risks and changes in near-real-time. In particular, using Remote Sensing, GIS, AI, and Environmental Modeling together can identify climate and environmental risks in advance, determine which areas are most vulnerable, and develop effective strategies for natural resource management and climate adaptation based on information and evidence.

This Article Collection welcomes research on climate risk, water security, and agricultural sustainability using Geospatial Technology within the scope of the journal. This includes EO, Google Earth Engine (GEE), climate variability and climate extremes, flood and drought risk assessment, water resources and groundwater monitoring, agricultural drought and crop condition assessment, soil moisture and crop-water stress, Land Use/Land Cover (LULC) change, UAV/Drone-based environmental monitoring, Machine Learning (ML) and Artificial Intelligence (AI) for geospatial prediction, GIS-based Multi-Criteria Decision Analysis (MCDA), hydrological and environmental modelling, vulnerability and resilience assessment, and spatial decision-support systems for climate adaptation and sustainable resource management. Research that integrates multiple data sources, such as satellite, climate, field observation, and model-derived data, and combines different analytical and modelling approaches will be particularly encouraged. This Collection will primarily accept original research articles and review articles, with special emphasis on methodological innovation, spatial analysis, modeling, and the use of geospatial technologies in practical research applications.

Meet the Guest Advisors

Jayanta Das is an Assistant Professor in the Department of Geography at Rampurhat College, India. His research focuses on geospatial technologies, remote sensing and GIS, environmental modelling, climate-related hazards, water resources, and agricultural and livelihood vulnerability. His work integrates earth observation, spatial modelling, machine learning, and multi-criteria decision-making for environmental assessment and sustainable resource management.

Brototi Biswas is a Professor in the Department of Geography & Remote Sensing at Mizoram University, India, with around 20 years of research and teaching experience in Geography and Geospatial Science. Her research interests include climate change, water resources, environmental hazards, land-use/land-cover dynamics, and geospatial applications for environmental assessment.