A geospatial approach in monitoring the variations on surface soil moisture and vegetation water content: a case study of Palakkad District, Kerala, India

• Published in: Environmental earth sciences 2022-10, Vol.81 (20), Article 494
• Main Authors: Viswambharan, Sajeesh, Kumaramkandath, Indu Tarur, Tali, Javaid Ahmad
• Format: Article
• Language: English
• Subjects: Anomalies; Biogeosciences; Climate and vegetation; Climate change; Correlation; Drought; Earth and Environmental Science; Earth Sciences; Environmental Science and Engineering; Geochemistry; Geology; High temperature; Hydrology/Water Resources; Image processing; Land surface temperature; Landsat; Mathematical analysis; Moisture content; Moisture effects; Moisture index; Normalized difference vegetative index; Original Article; Parameterization; Regression coefficients; Remote sensing; Satellite imagery; Soil; Soil moisture; Soil moisture variations; Soil surfaces; Soil water; Statistical analysis; Statistical methods; Surface temperature; Terrestrial Pollution; Vegetation; Vegetation index; Water; Water content
• ISSN: 1866-6280; 1866-6299
• DOI: 10.1007/s12665-022-10611-6

Soil moisture and vegetation water content play an important role in studies involving vegetation, drought, and climate change. The present paper gives details of how to calculate the Soil Moisture Index (SMI), Normalized Difference Moisture Index (NDMI), and Normalized Difference Water Index (NDWI) using Landsat 7 ETM + and Landsat 8 OLI (Operational Land Imager) and Thermal Infrared Sensor (TIRS) data and how spatially and temporally it has been changed over Palakkad District, Kerala. The present study develops an image processing method using band 3 (Green), band 4(Red), band 5 (NIR), band 6 (SWIR 1), and band 10 (TIR) of Landsat 8 and band 2 (Green), band 3 (Red), band 4 (NIR), band 5 (SWIR) and band 6 (TIR) of Landsat 7 data for determining the different spectral indices. The relationship between Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) are based on experimental parameterization for soil moisture index. Both LST and NDVI are considered indispensable data to obtain SMI calculation. The statistical analysis of NDVI and LST was exposed in the standardized regression coefficient. The study found a weak negative correlation between NDVI and LST in both 2001 ( R 2  = 0.37) and 2021 ( R 2  = 0.16). As the LST increases, the vegetative cover reduces due to the record of high temperatures in the study area. The SMI result for 2021 shows that the majority of the study area experienced extreme anomalies when compared to the 2001 result. Second, a significant negative correlation existed between SMI and LST ( R 2  = 0.664 in 2001 and R 2  = 1 in 2021), which indicates that the surface soil moisture reduces with LST. The normalized difference moisture index (NDMI) value ranges from – 0.71 to 0.75 in 2001 and – 0.33 to 0.40 in 2021. In 2001 and 2021, the normalized difference water index (NDWI) ranges from – 0.47 to 0.64 and – 0.531 to 0.154, respectively. Therefore, the current study gives a clear understanding of considerable variations in soil moisture and vegetation water content in the Palakkad District during the study period.