Crop Response to Disease and Water Scarcity Quantified by Normalized Difference Latent Heat Index

Early detection and quantification of plants’ response to disease and water shortage conditions are very important for the agricultural management. This study represents the first utilization of Normalized Difference Latent Heat Index (NDLI) as a dimensionless indicator to assess plant health. By integrating NDLI with thermal infrared and surface energy balance (SEB) components, we aim to enhance the analysis of crop conditions and water scarcity in rice-growing areas. The integration between NDLI and land surface temperature exhibits a strong correlation (r = −0.82) with crop evapotranspiration (ET) derived from the widely used residual Surface Energy Balance Algorithm for Land model. Besides, the performance of NDLI- and SEB-based ET method proved its ability to provide the precise information of paddy field conditions by showing the significant correlations with the crop canopy biophysical properties that are traditionally represented and inferred by the multispectral remote sensing indices. The correlation coefficients of NDLI- and SEB-derived ET with Normalized Difference Vegetation Index (NDVI), Normalize Difference Water Index (NDWI), and Optimization of the Soil Adjusted Vegetation Index (OSAVI) were 0.84, 0.55, and 0.84, respectively. Also, NDLI- and SEB-derived ET exhibits a high degree of consistency with the ET determined through the SEBAL method, with difference less than 10% of the observations over 98.1% of the paddy fields of concern. Interestingly, the abnormally low ET signatures over the confirmed disease-infected regions of paddy fields are obviously observed in the NDLI- and SEB-derived ET maps, but not in the SEBAL-derived ET map. The findings of this work suggest that NDLI can be considered as a valuable indicator to provide information of the water stress status and health of the crop plants for advanced food-supply management.