Zobrazeno 1 - 10
of 203
pro vyhledávání: '"Huihui Feng"'
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
ABSTRACTMultimodal change detection (MCD) combines multiple remote sensing data sources to realize surface change monitoring, which is essential for disaster evaluation and environmental monitoring. However, due to the ‘incomparable’ features in
Externí odkaz:
https://doaj.org/article/0089c1e8ebfd423b8b6466b591b8b07c
Publikováno v:
Zhongguo shuxue zazhi, Vol 37, Iss 2, Pp 223-237 (2024)
Objective To analyze the overall situation and main influencing factors of adverse reactions of blood donation of apheresis platelet donors in China by systematic review, and to provide basis for preventing and controlling adverse reactions of platel
Externí odkaz:
https://doaj.org/article/d53f8c13030046e284294614914954ac
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
A data-driven channel prediction method for distribution automation master is proposed to address the poor quality of communication network and communication system transmission problems in distribution network communication. In this paper, an adapti
Externí odkaz:
https://doaj.org/article/5bb179c99491447da5e95ab2c5b4d6e6
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 126, Iss , Pp 103630- (2024)
Multimodal Change Detection (MCD) is essential for disaster evaluation and environmental monitoring by integrating various remote sensing data to monitor surface changes. However, the significant imaging differences in multimodal images render tradit
Externí odkaz:
https://doaj.org/article/1470160ae7b84a9d96ed8d7bc14ca462
Autor:
Huihui FENG,Wei WANG,Bin ZOU
Publikováno v:
Journal of Geodesy and Geoinformation Science, Vol 5, Iss 3, Pp 67-77 (2022)
New requirements have been proposed for GIS practice teaching in colleges and universities in response to the developmental changes of national and industrial sectors during the social transition. Meanwhile, the underlying core characteristics of GIS
Externí odkaz:
https://doaj.org/article/baf55073d822452ab387509b183b86bd
Publikováno v:
Remote Sensing, Vol 16, Iss 4, p 721 (2024)
Heterogeneous change detection (CD) is widely applied in various fields such as urban planning, environmental monitoring, and disaster management. It enhances the accuracy and comprehensiveness of surface change monitoring by integrating multi-sensor
Externí odkaz:
https://doaj.org/article/695fd701b7f44b4ebe039f87a34fe38b
Publikováno v:
Frontiers in Ecology and Evolution, Vol 11 (2023)
The surface radiation is a crucial variable for understanding global climate and eco-environment change, which exhibits significant variations over time and space. In this study, we used in situ ground observations to estimate variations of the surfa
Externí odkaz:
https://doaj.org/article/7df301f07f61433c82b4aea7a1153a34
Publikováno v:
Remote Sensing, Vol 15, Iss 21, p 5227 (2023)
Sand and dust storm (SDS) weather has caused several severe hazards in many regions worldwide, e.g., environmental pollution, traffic disruptions, and human casualties. Widespread surveillance cameras show great potential for high spatiotemporal reso
Externí odkaz:
https://doaj.org/article/6819fae8a09744e2b997d9c9b09cf52f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 6687-6698 (2022)
Satellite video (SV) can acquire rich spatiotemporal information on the earth. Single object tracking (SOT) in SVs enables the continuous acquisition of the position and range of a specific object, expanding the field of remote-sensing applications.
Externí odkaz:
https://doaj.org/article/3d487cf005d54aa6a793bb3d11eeff20
Publikováno v:
Frontiers in Environmental Science, Vol 10 (2022)
Urban functional zones (UFZs) are the fundamental units for urban management and operation. The advance in earth observation and deep learning technology provides chances for automatically and intelligently classifying UFZs via remote sensing images.
Externí odkaz:
https://doaj.org/article/bd638bc99b5a4063afb2e68d564f5568