Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Penghai Wu"'
Autor:
Zhixiang Yin, Penghai Wu, Xinyan Li, Zhen Hao, Xiaoshuang Ma, Ruirui Fan, Chun Liu, Feng Ling
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 134, Iss , Pp 104176- (2024)
Mapping water bodies from remotely sensed imagery is crucial for understanding hydrological and biogeochemical processes. The identification of water extent is mainly dependent on optical and synthetic aperture radar (SAR) images. However, the use of
Externí odkaz:
https://doaj.org/article/1d1a00695e2e49a19d503f780a9739f3
Autor:
Wenfang Zhan, Feng Luo, Heng Luo, Junli Li, Yongchuang Wu, Zhixiang Yin, Yanlan Wu, Penghai Wu
Publikováno v:
Remote Sensing, Vol 16, Iss 2, p 235 (2024)
Crop mapping is vital in ensuring food production security and informing governmental decision-making. The satellite-normalized difference vegetation index (NDVI) obtained during periods of vigorous crop growth is important for crop species identific
Externí odkaz:
https://doaj.org/article/3b88d1e74922470b9d506a8cdf11b1c4
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 117, Iss , Pp 103195- (2023)
Reconstruction of cloud-covered thermal infrared land surface temperature (LST) is vital for the measurement of physical properties in land surface at regional and global scales. In this paper, a novel reconstruction method for Moderate Resolution Im
Externí odkaz:
https://doaj.org/article/04d4e513d787479082ab2dbfcf0f4844
Autor:
Si-Bo Duan, Zhao-Liang Li, Wei Zhao, Penghai Wu, Cheng Huang, Xiao-Jing Han, Maofang Gao, Pei Leng, Guofei Shang
Publikováno v:
International Journal of Digital Earth, Vol 14, Iss 5, Pp 640-660 (2021)
Since 1982, Landsat series of satellite sensors continuously acquired thermal infrared images of the Earth’s land surface. In this study, Landsat 5, 7, and 8 land surface temperature (LST) products in the conterminous United States from 2009 to 201
Externí odkaz:
https://doaj.org/article/fdf2618cd48440df8f8f620113232741
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 3120-3132 (2021)
Water body extraction from remote sensing images is an important task. Deep learning has become a more popular method for extracting water bodies from remote sensing images. However, these methods are usually aimed at a specific sensor and are not ap
Externí odkaz:
https://doaj.org/article/d8d86ed32fd64fdeafb217c0f0eacd85
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 3-17 (2021)
Road extraction is an important task in remote sensing image information extraction. Recently, deep learning semantic segmentation has become an important method of road extraction. Due to the impact of the loss of multiscale spatial features, the re
Externí odkaz:
https://doaj.org/article/978070cbdf8249ab83ee5945e525551f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 11926-11935 (2021)
Wetlands are highly productive ecosystems that provide functions and services important for human survival and development. Long-term wetland landscape ecological risk assessments (LERAs) are able to effectively identify key elements for landscape su
Externí odkaz:
https://doaj.org/article/64b94cf955a1481fb6c5820c59ff3cb2
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 12073-12087 (2021)
Synthetic aperture radar (SAR) water body extraction is of great significance for many applications, such as flood disaster monitoring, coastline change detection, and water resources management. However, the previous research works have mainly focus
Externí odkaz:
https://doaj.org/article/e1c700b0f0d4431c9d0a514c80c154d9
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 6410-6423 (2020)
The surface urban heat island (SUHI) is one of the most common effects of the urban ecological environment, and its long-term diurnal and seasonal fine-scale analysis remains poorly understood. This article utilized a modified reconstruction model an
Externí odkaz:
https://doaj.org/article/fa1469682f65476fb1e7082fae3f8c3d
Publikováno v:
Remote Sensing, Vol 15, Iss 3, p 674 (2023)
Obtaining accurate and timely crop area information is crucial for crop yield estimates and food security. Because most existing crop mapping models based on remote sensing data have poor generalizability, they cannot be rapidly deployed for crop ide
Externí odkaz:
https://doaj.org/article/edb51442cc454094a9cb25251330f89d