The integration of Geographic Information Systems (GIS) and Remote Sensing (RS) has become essential for addressing escalating global environmental challenges. This systematic literature review, strictly adhering to PRISMA guidelines, synthesizes 115 peer-reviewed articles published between 2016 and 2026 to evaluate the current state, methodological trends, and technological synergies in environmental monitoring. Our findings reveal that Forestry and Land Use/Land Cover (LULC) change, alongside water resource and disaster management, are the predominant application domains. Crucially, the review highlights a significant paradigm shift from traditional analytical methods to advanced multi-sensor data fusion and the rapid incorporation of Artificial Intelligence (AI) and Machine Learning algorithms, which drastically enhance spatial predictive accuracy. Despite these advancements, challenges such as massive geospatial data handling and sensor interoperability remain prevalent. Ultimately, this study provides a comprehensive framework for researchers and policymakers, emphasizing that leveraging cloud computing and AI-driven GIS-RS synergies is vital for formulating robust, data-driven environmental conservation and disaster mitigation strategies.
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