Assessment of the Spatiotemporal Variations of Soil Moisture Content in Louisiana from 2020 to 2025 Hydrological Year Using Remote Sensing (NDMI Method)

Abstract

Moisture variability plays a critical role in land–atmosphere interactions, ecosystem health, and environmental sustainability, particularly in regions experiencing increasing climatic variability. This study assesses the spatiotemporal variation of surface soil moisture conditions using remote sensing techniques and the Normalized Difference Moisture Index (NDMI). Multispectral satellite imagery was acquired and processed to generate NDMI maps that capture changes in vegetation and surface moisture in Louisiana. Image processing and spatial analysis were carried out using geographic information system (GIS) tools to examine temporal trends and spatial patterns of moisture distribution. The results reveal distinct spatial heterogeneity and temporal fluctuations in moisture conditions across the study area. Areas with higher NDMI values indicate relatively high moisture content and healthier vegetation, while lower NDMI values correspond to moisture-stressed zones, bare surfaces, or areas undergoing land-use change. Seasonal variations reflect the influence of rainfall patterns, vegetation phenology, and anthropogenic activities on surface moisture dynamics. The analysis demonstrates that NDMI effectively captures moisture variations in soil and provides a reliable means of monitoring environmental conditions over time. This study highlights the usefulness of satellite-based NDMI for assessing moisture variability at regional scales and underscores its potential application in environmental monitoring, land-use planning, agricultural management, and climate-related studies. The findings contribute to improved understanding of surface moisture dynamics and support evidence-based decision-making for sustainable environmental management.