Zobrazeno 1 - 10
of 392
pro vyhledávání: '"Remote sensing inversion"'
Remote sensing estimation on regional continuous daily evapotranspiration based on Richards equation
Publikováno v:
Shuiwen dizhi gongcheng dizhi, Vol 51, Iss 5, Pp 35-44 (2024)
Evapotranspiration (ET) is an important part of water cycle in nature, and the estimation of evapotranspiration on spatio-temporal scale has always been a hot issue. Remote sensing can estimate evapotranspiration on regional scale, but it is difficul
Externí odkaz:
https://doaj.org/article/d94a4595dd604dc39ef5442a049e00a5
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
With increased precipitation and meltwater, most lakes on the Tibetan Plateau have expanded rapidly. However, the impact of erosion and sedimentation following lake expansion remains unclear. Using Lexiewudan and Yanhu Lakes as examples, we created a
Externí odkaz:
https://doaj.org/article/a2aacc172894413b8e9634dc7e7042e0
Autor:
Bolin Fu, Linhang Jiang, Hang Yao, Yingying Wei, Mingming Jia, Weiwei Sun, Yanli Yang, Tengfang Deng
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
Mangroves are vital coastal ecosystems that provide crucial links between land and sea. Tree height is a key indicator for assessing mangroves’ health status. Currently, there are still numerous challenges in estimating mangrove tree height. In thi
Externí odkaz:
https://doaj.org/article/5eaf83dc5a3d4c96b81a3bc96f39254f
Autor:
Jinzhao Zou, Yanan Wei, Yong Zhang, Zheng Liu, Yuefeng Gai, Hongyan Chen, Peng Liu, Qian Song
Publikováno v:
Frontiers in Environmental Science, Vol 12 (2024)
Remote sensing has become an effective way for regional soil organic matter (SOM) quantitative analysis. Topographic factors affect SOM content and distribution, also influence the accuracy of SOM remote sensing inversion. In large region with comple
Externí odkaz:
https://doaj.org/article/bee98173240743e893fa6b26db72c0e7
Publikováno v:
IEEE Access, Vol 12, Pp 24791-24802 (2024)
Chlorophyll-a is an important parameter that is used to measure the water quality, and its concentrations indicate the degree of eutrophication. Taking the waters of Chaohu Lake as the research area, four remote sensing inversion models of the chloro
Externí odkaz:
https://doaj.org/article/eceb4142843f4b8292ba921a299ad8ee
Autor:
Zhixin Wang, Zhenqi Zhang, Hailong Li, Hong Jiang, Lifei Zhuo, Huiwen Cai, Chao Chen, Sheng Zhao
Publikováno v:
Journal of Marine Science and Engineering, Vol 12, Iss 10, p 1742 (2024)
Due to the increasing impact of climate change and human activities on marine ecosystems, there is an urgent need to study marine water quality. The use of remote sensing for water quality inversion offers a precise, timely, and comprehensive way to
Externí odkaz:
https://doaj.org/article/8681b1467b1d4d218c5ec26023d80a68
Autor:
Haili Dong, Fei Tian
Publikováno v:
Agriculture, Vol 14, Iss 10, p 1777 (2024)
Soil salinization is an essential risk factor for agricultural development and food security, and obtaining regional soil salinity information more reliably remains a priority problem to be solved. To improve the accuracy of soil salinity inversion,
Externí odkaz:
https://doaj.org/article/49d38efaf3ab4a7c9cab3078a66f75c4
Autor:
Yunyang Jiang, Zixuan Zhang, Huaijiang He, Xinna Zhang, Fei Feng, Chengyang Xu, Mingjie Zhang, Raffaele Lafortezza
Publikováno v:
Remote Sensing, Vol 16, Iss 19, p 3627 (2024)
The Leaf Area Index (LAI) is a critical parameter that sheds light on the composition and function of forest ecosystems. Its efficient and rapid measurement is essential for simulating and estimating ecological activities such as vegetation productiv
Externí odkaz:
https://doaj.org/article/7aa95db653544e19aa841367e00b3a08
Autor:
Hongxia Zheng, Yulin Wu, Haifeng Han, Juan Wang, Shanwei Liu, Mingming Xu, Jianyong Cui, Muhammad Yasir
Publikováno v:
Frontiers in Marine Science, Vol 11 (2024)
Nitrogen is one of the critical factors in water pollution and eutrophication, so applying the deep learning method in remote sensing inversion of nitrogen can provide basic information for environmental management. This paper proposes a two-step fea
Externí odkaz:
https://doaj.org/article/2770ce2baf2f4445b3d2bac774584b59
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 127, Iss , Pp 103644- (2024)
Currently, hyperspectral remote sensing technology used for vegetation monitoring mainly uses empirical and semi-empirical statistical methods to calculate heavy metal content. Combining physical models and machine learning algorithms is an effective
Externí odkaz:
https://doaj.org/article/c4286d16a00e4de8a9e8de65e76188a7