Bing Zhang

TL;DR: Li et al. as mentioned in this paper used the high temporal resolution of MODIS to improve the accuracy of land cover classification of the North China Plain using MODIS_EVI time series from 2003.

TL;DR: In this article, the authors proposed an end-member-guided unmixing network (EGU-Net), which is a two-stream Siamese deep network that learns an additional network from the pure or nearly pure endmembers to correct the weights of another unmixer by sharing network parameters and adding spectrally meaningful constraints.

TL;DR: A comparative study for linear regression-based algorithms for noise estimation for hyperspectral images using simulated images with different signal-to-noise ratio (SNR) and real image types, concluding instructive guidance is concluded for their practical applications.

TL;DR: In this article, the authors investigated temporal and spatial variations in water chemistry affected by humans and to characterize the rela- tionships between surface water (e.g. reservoirs, lakes and rivers) and groundwater near the Jialu River in the shallow Qua- ternary aquifer.

TL;DR: A support vector machine (SVM) classifier integrated with a subspace projection method to address the problems of mixed pixels and noise is first used to model the posterior distributions of the classes based on the spectral information, then the spatial information of the image pixels is modeled using an adaptive Markov random field (MRF) method.