Progress in Satellite Remote Sensing of Land Surface: New Algorithms, Sensors and Datasets

Dear Colleagues,

In scientific research on Earth systems, satellite remote sensing plays the most important role in quantifying land surface states, which are represented by soil moisture, land surface temperature, vegetation, snow cover, water bodies, and glaciers. In addition to providing direct support for various industrial applications, it can also provide vital input data for researchers in the fields of climate change, river basin hydrology, agricultural application, energy budget, and the water and carbon cycle. This Topic on “Progress in Satellite Remote Sensing of Land Surface: New Algorithms, Sensors and Datasets” will cover recent advances in remote sensing sensors, algorithms, and datasets for quantifying land surface parameters. Original research reports, review articles, and commentaries are welcome. The issue will host papers covering remote sensing algorithms for retrieving land surface parameters including, but not limited to, soil, snow and ice, forest, grass land, farmland, and water and urban areas. Papers focusing on new orbital sensors and land surface datasets are also welcome. Data from new satellites, such as the recently launched FengYun satellite series, are warmly encouraged to be used in this Topic.

Dr. Shengli Wu
Dr. Lingmei Jiang
Dr. Jinyang Du
Prof. Dr. Kebiao Mao
Dr. Tianjie Zhao
Topic Editors