Junjun Wu
Chinese Academy of Sciences
27 Papers
29 Citations
Junjun Wu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Computer science & Environmental science. The author has an hindex of 5, co-authored 21 publications.
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Papers
Ecological environment assessment for Greater Mekong Subregion based on Pressure-State-Response framework by remote sensing
Junjun Wu,Xin Wang,Bo Zhong,Aixia Yang,Kunsheng Jue,Jinhua Wu,Lan Zhang,Weijin Xu,Shanlong Wu,Nan Zhang,Qinhuo Liu +10 more
TL;DR: In this article, the authors explored effective indicators from remote sensing for the ecological and environmental assessment, which can provide a strong decision-making basis for promoting the sustainable development of the ecological environment in the greater Mekong subregion, as well as the technological support for the construction of the biodiversity corridor.
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Downscaling of Urban Land Surface Temperature Based on Multi-Factor Geographically Weighted Regression
TL;DR: Compared with the major statistical LST downscaling methods including thermal image sharpening algorithm (TsHarp), multiple scale factors with adaptive thresholds algorithm (MSFAT), support vector machine regression combined with gradient boosting, and GWR, MFWGR showed a stable performance and higher accuracy.
27
Analysis Ready Data of the Chinese GaoFen Satellite Data
TL;DR: The analysis ready data (ARD) has been greatly recommended by the Committee on Earth Observation Satellites (CEOS) for simplifying and fostering long time series analysis at large scale with minimum additional user effort.
26
Soil-atmosphere exchange of CH4 in response to nitrogen addition in diverse upland and wetland ecosystems: A meta-analysis
TL;DR: In this paper, the authors investigated the effects of reactive nitrogen (N) addition on soil CH4 uptake and emission rates in various upland and wetland ecosystems, and synthesized a large dataset comprising 878 paired observations from 178 studies.
26
Degraded land detection by soil particle composition derived from multispectral remote sensing data in the Otindag Sandy Lands of China
TL;DR: Wang et al. as discussed by the authors proposed a method by using the measured hyperspectral and BJ-1 multispectral image to estimate the silt content in soil quantitatively, and to develop a soil-based model which could be used in detecting desertification or land degradation.
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