Fei Zhang

TL;DR: Wang et al. as discussed by the authors built the Remote Sensing Ecological Index (RSEI) based on Landsat data and Tiangong-2 WIS, using multi-source remote sensing data to comprehensively evaluate the coupling and coordination relationship between urbanization and ecological environment with a coupling coordination degree model.

TL;DR: Previously published optimal remote sensing parameters can be applied to estimate the soil salt content in the Ebinur Lake Wetland National Nature Reserve (ELWNNR), and the accuracy of the first derivative of the Landsat OLI model was close to that of the hyperspectral parameter model.

TL;DR: Spatial correlation was significant, and the degree of spatial clustering was relatively high in the study area, which was mainly distributed in the water body and wetland regions, and these high-value regions exhibited a decreasing trend.

TL;DR: Wang et al. as mentioned in this paper developed comprehensive urbanization and eco-environment evaluation models to explore UAEE development of SREB in China from 2004 to 2018, and these evaluation models are subsequently combined with CCDM (Coupling coordination degree model) and GTWR (Geographically and Temporally Weighted Regression) models to measure and analyze coupling degree and spatio-temporal heterogeneity of UAEE.

TL;DR: This study combines a machine learning algorithm, WQI, and remote sensing spectral indices (difference index, DI; ratio index, RI; and normalized difference index, NDI) through fractional derivatives methods and establishes a model for estimating and assessing the water quality index.