Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Meihong Fang"'
Autor:
Meihong Fang, Xiangyan Hu, Jing M. Chen, Xueshiyi Zhao, Xuguang Tang, Haijian Liu, Mingzhu Xu, Weimin Ju
Publikováno v:
Forests, Vol 15, Iss 8, p 1463 (2024)
Vegetation canopy water content (CWC) crucially affects stomatal conductance and photosynthesis and, consequently, is a key state variable in advanced ecosystem models. Remote sensing has been shown to be an effective tool for retrieving CWCs. Howeve
Externí odkaz:
https://doaj.org/article/7934728cb79549dda0a95946a9fed97a
Autor:
Zhifeng Yu, Qiyu Huang, Xiaoxue Peng, Haijian Liu, Qin Ai, Bin Zhou, Xiaohong Yuan, Meihong Fang, Ben Wang
Publikováno v:
Sensors, Vol 22, Iss 12, p 4593 (2022)
To improve the ability of remote sensing technology in recognizing black-odorous water bodies in Hangzhou, this study analyzed the typical spectral characteristics of black-odorous water in Hangzhou based on measured spectral data and water quality p
Externí odkaz:
https://doaj.org/article/5cfb29d942a54d948f517dda967ae31e
Autor:
Chunhua Zhang, Weimin Ju, Jingming Chen, Meihong Fang, Mengquan Wu, Xueli Chang, Tao Wang, Xiqun Wang
Publikováno v:
Forests, Vol 9, Iss 11, p 689 (2018)
China’s forests have functioned as important carbon sinks. They are expected to have substantial future potential for biomass carbon sequestration (BCS) resulting from afforestation and reforestation. However, previous estimates of forest BCS have
Externí odkaz:
https://doaj.org/article/4e5ef77246a94f1c817c1bf708533f62
Publikováno v:
Remote Sensing, Vol 9, Iss 3, p 291 (2017)
Nitrogen is an essential nutrient in many terrestrial ecosystems because it affects vegetation’s primary production. Due to the variety of nitrogen-containing substances and the differences in their composition across species, statistical approache
Externí odkaz:
https://doaj.org/article/5e17316641d54cf88b9b4f9ef327ad3a
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 26, Iss 3, p 319 (2015)
This study examines the spatio-temporal variations in the sea-surface chlorophyll-a (Chl-a) concentration and their associated underlying driving forces in the northern South China Sea (SCS) from 2004 - 2010. A stratified analysis method and the Mode
Externí odkaz:
https://doaj.org/article/788c3b6d67dd45ed8ea052e47b0be22b
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 61:1-19
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 56:3119-3136
The PROSPECT model has been widely used to estimate leaf biochemical constituents, but retrieval of leaf mass per area (LMA) in fresh leaves has proved to be difficult due to the predominant water absorption in the infrared spectral region. At wavele
Publikováno v:
Remote Sensing of Environment. 258:112382
Individual tree identification is a key step for forest surveying and monitoring. To identify individual trees with airborne LiDAR data, a local maximum (LM) filter technique is typically performed. With LM, the highest point in a filtering window is
Publikováno v:
IGARSS
Recently, drought is recognized as a crucial factor on controlling inter-annual variations of the terrestrial carbon cycle. Remote sensing of hydrological and ecological land surface variables offers a very important aid for identifying the impact of
Publikováno v:
Biosystems Engineering. 106:223-233
Heavy metal stress in soils results in subtle changes in leaf chlorophyll concentration, which are related to crop growth and crop yield. Accurate estimation of the chlorophyll concentration of a crop under heavy metal stress is essential for precisi