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近日,中国地质大学计算机学院陈伟涛副教授团队在地质环境遥感智能解译领域的研究工作取得重要进展。相关研究成果发表在国际著名期刊《Remote Sensing》。论文第一作者为李显巨副教授,通讯作者为陈伟涛副教授。
The Indian part of Kailash Sacred Landscape (KSL) is prone to flash floods, landslides and forest fires leading to various environmental and socio-economic problems. This study aims to identify areas ...
Evapotranspiration (ET) is an essential element of the hydrological cycle and plays a significant role in regional and global climate through the hydrological circulation. Estimation and monitoring of...
Remote Sensing is a very reliable and expeditious technique for assessment and mapping of surface waterlogged areas. In this study band ratio based NDWI index (Normalized Difference Water Index) was u...
In this paper, we propose a spectral-spatial feature extraction framework based on deep learning (DL) for hyperspectral image (HSI) classification. In this framework, the variational autoencoder (VAE)...
SMAP project released a new enhanced high-resolution (3km) soil moisture active-passive product. This product is obtained by combining the SMAP radiometer data and the Sentinel-1A and -1B Synthetic Ap...
In this paper, we propose a software architecture for a feature extraction tool which is suitable for automatic extraction of sparse features from large remote sensing data capable of using higher ord...
Urban lakes are important natural, scenic and pattern attractions of the city, and they are potential development resources as well. However, lots of urban lakes in China have been shrunk significantl...
While extracting land cover from remote sensing images, each pixel in the image is allocated to one of the possible class. In reality different land covers within a pixel can be found due to continuum...
Remote-sensing and geographic-information-systems (GIS) techniques were jointly used in this study to establish a GIS database system for the Yeşilırmak watershed provinces, which include Am...

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