Remote Sensing and Geospatial Analytics for Climate Change Assessment and Natural Resource Management

Abstract

Climate change poses unprecedented challenges to ecosystems, water resources, agriculture, and human settlements. Effective assessment and sustainable management of natural resources require continuous, large-scale, and high-resolution environmental monitoring. Remote sensing combined with geospatial analytics provides a powerful framework for observing climate-induced changes across temporal and spatial scales. This paper presents an integrated analysis of satellite-based remote sensing data and geographic information system (GIS) techniques for climate change assessment and natural resource management. The study examines the use of multispectral and hyperspectral imagery, thermal sensing, and radar data for monitoring land use change, vegetation dynamics, water availability, and climate extremes. Advanced geospatial analytics, including machine learning–based classification and trend analysis, are discussed as tools for enhancing predictive capability. The paper highlights applications in drought assessment, deforestation monitoring, coastal vulnerability analysis, and sustainable land management. Challenges related to data uncertainty, resolution limitations, and integration with socio-economic data are critically analyzed. The findings underscore the role of remote sensing and geospatial analytics as essential decision-support systems for climate adaptation and resource governance in a changing global environment.