On the relationship between normalized difference vegetation index and land surface temperature: MODIS-based analysis in a semi-arid to arid environment

TL;DR: Wang et al. as mentioned in this paper evaluated the performance of two satellite soil moisture (SM) products, the Soil Moisture and Ocean Salinity (SMOS) and SoilMoisture Active Passive (SMAP), on drought detection and assessment in the North China Plain (NCP) over the period of 2015-2018, with a comparison between two satellite SM-based drought indices, SWDI and SMCI.

TL;DR: In this paper , a novel NDVI forecasting model was developed by combining time series decomposition (TSD), convolutional neural networks (CNN) and long short-term memory (LSTM).

TL;DR: In this paper, the authors compared the traditional regression models and support vector machine (SVM) for estimation of aboveground biomass (ABG) of an agro-pastoral ecology using vegetation indices derived from different vegetation types.

TL;DR: In this paper , the authors identify demi-decadal, seasonal, and zonal differences in LSTs in a semi-arid region in the city of Jaipur, where zones include rural and urban areas that encircle the Jhalana Reserve Forest (JRF).

TL;DR: In this article, a method has been developed for quantitative measurement of vegetation conditions over broad regions using ERTS-1 spectral bands 5 and 7, corrected for sun angle, which is shown to be correlated with aboveground green biomass on rangelands.

TL;DR: In this article, the applicability of vegetation fraction derived from a spectral mixture model as an alternative indicator of vegetation abundance was investigated based on examination of a Landsat Enhanced Thematic Mapper Plus (ETM+) image of Indianapolis City, IN, USA, acquired on June 22, 2002.

TL;DR: A simplified land surface dryness index (TVDI) based on an empirical parameterisation of the relationship between surface temperature (Ts) and vegetation index (NDVI) is suggested in this paper.

TL;DR: In this article, the authors compared the normalized difference vegetation index (NDVI) and percent impervious surface as indicators of surface urban heat island effects in Landsat imagery by investigating the relationships between the land surface temperature (LST), Percent Impervious Surface area (%ISA), and the NDVI.