Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Lajiao Chen"'
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
It is hard to accomplish fast semantic segmentation on large remote sensing images, since current neural networks with numerous parameters often rely on significant computational resources. Our team proposes an improved fast semantic segmentation mod
Externí odkaz:
https://doaj.org/article/f4d0a0c0806c41f49f51dd3bf291d3ec
Publikováno v:
International Journal of Digital Earth, Vol 16, Iss 1, Pp 2522-2554 (2023)
Deep learning algorithms show good prospects for remote sensing flood monitoring. They mostly rely on huge amounts of labeled data. However, there is a lack of available labeled data in actual needs. In this paper, we propose a high-resolution multi-
Externí odkaz:
https://doaj.org/article/b9bbd9a97ebb422e9f6aee429e9bba14
Autor:
Xi Chen, Jinwei Dong, Lin Huang, Lajiao Chen, Zhichao Li, Nanshan You, Mrinal Singha, Fulu Tao
Publikováno v:
iScience, Vol 26, Iss 7, Pp 107096- (2023)
Summary: Floods occur more frequently in the context of climate change; however, flood monitoring capacity has not been well established. Here, we used a synergic mapping framework to characterize summer floods in the middle and lower reaches of the
Externí odkaz:
https://doaj.org/article/225a5602e2d84f1baae9fed8f67687b7
Autor:
Hong Yan, Hongchang Hu, Yaping Liu, Mahmut Tudaji, Ting Yang, Zhongwang Wei, Lajiao Chen, Mohd Yawar Ali Khan, Zhenghao Chen
Publikováno v:
Hydrology Research, Vol 53, Iss 5, Pp 782-794 (2022)
Baseflow recession is an essential part of the hydrological cycle, as it transfers unconfined aquifer storage to runoff. This study derived the parameterization of the baseflow recession from recession curves extracted from 382 catchments in China. T
Externí odkaz:
https://doaj.org/article/ed84730669e34f548fda3f1cd3ff6069
Autor:
Zhiqiang Dong, Hongchang Hu, Zhongwang Wei, Yaping Liu, Hanlin Xu, Hong Yan, Lajiao Chen, Haoqian Li, Mohd Yawar Ali Khan
Publikováno v:
Frontiers in Earth Science, Vol 10 (2022)
Background and Aims: Evapotranspiration is an important part of the water cycle and energy cycle. However, even under the same climatic condition, there are spatial differences in actual evapotranspiration (ETa) due to different land use and land cov
Externí odkaz:
https://doaj.org/article/3894b6a5523a4af09110a9cb03480e33
Publikováno v:
Frontiers in Environmental Science, Vol 10 (2022)
Optimality principles have been applied in ecohydrological modeling to derive optimal vegetation properties and describe co-evolution states of vegetation and water cycle. Unfortunately, most existing optimality-based models only consider vertical ve
Externí odkaz:
https://doaj.org/article/4811d651109a4943b75bcc0f82e900c5
Publikováno v:
International Journal of Digital Earth, Vol 12, Iss 12, Pp 1423-1440 (2019)
Partitioning of evapotranspiration (ET) into biological component transpiration (T) and non-biological component evaporation (E) is crucial in understanding the impact of environmental change on ecosystems and water resources. However, direct measure
Externí odkaz:
https://doaj.org/article/b54afb6e738947cd86672012ff2502bf
Autor:
Lajiao Chen, Lizhe Wang
Publikováno v:
Big Earth Data, Vol 2, Iss 1, Pp 86-107 (2018)
In the past three decades, breakthroughs in satellites and remote sensing have highly demonstrated their potential to characterize and model the various components of the hydrological cycle. A wealth of satellite missions are launched and some of the
Externí odkaz:
https://doaj.org/article/ed75656f3d5e443093df25517f518444
Publikováno v:
Remote Sensing, Vol 7, Iss 6, Pp 7105-7125 (2015)
In view of the fact that oil spill remote sensing could only generate the oil slick information at a specific time and that traditional oil spill simulation models were not designed to deal with dynamic conditions, a dynamic data-driven application s
Externí odkaz:
https://doaj.org/article/3726259470a7485581c3cc3ce8dbe99d
Autor:
Xiaoyan Zhu, Yanyan Pei, Zhaopei Zheng, Jinwei Dong, Yao Zhang, Junbang Wang, Lajiao Chen, Russell B. Doughty, Geli Zhang, Xiangming Xiao
Publikováno v:
Remote Sensing, Vol 10, Iss 11, p 1771 (2018)
As the biggest carbon flux of terrestrial ecosystems from photosynthesis, gross primary productivity (GPP) is an important indicator in understanding the carbon cycle and biogeochemical process of terrestrial ecosystems. Despite advances in remote se
Externí odkaz:
https://doaj.org/article/1bedca16219d42d0a1a5e118c89673e0