Journal of Remote Sensing, Environmental Science & Geotechnical Engineering ISSN: 3107-7366 (Online)

Auther: Dr. Anjali Sharma, Mr. Rohit Verma

Abstract: Soil instability beneath the surface can lead to catastrophic infrastructure failures and environmental hazards. Early detection of such subsurface instabilities is crucial for effective risk mitigation. Vegetation stress, observable via remote sensing, has emerged as a promising proxy for detecting areas affected by subsurface soil anomalies such as sinkholes, subsidence, or soil liquefaction. This paper reviews the principles and applications of remote sensing technologies, especially multispectral and hyperspectral imaging, in monitoring vegetation stress related to underlying soil instability. Vegetation indices like NDVI (Normalized Difference Vegetation Index) and stress-related spectral signatures are discussed. A table summarizing common vegetation indices used in soil instability detection is included. Case studies highlight successful monitoring in mining and karst regions. Limitations such as atmospheric interference and seasonal variations are addressed. The study concludes that remote sensing of vegetation stress offers a non-invasive, cost-effective approach for preliminary screening of subsurface soil instability zones, aiding geotechnical investigations and infrastructure planning.

Keywords: Vegetation Stress, Remote Sensing, Soil Instability, NDVI, Hyperspectral Imaging, Subsurface Monitoring