Zobrazeno 1 - 10
of 964
pro vyhledávání: '"Sentinel-3"'
Publikováno v:
Earth and Space Science, Vol 11, Iss 8, Pp n/a-n/a (2024)
Abstract The provision of accurate wet tropospheric corrections (WTC), accounting for the delay of the radar pulses caused mostly by the atmospheric water vapor in the altimeter‐range observations, is pivotal for the full exploitation of altimeter
Externí odkaz:
https://doaj.org/article/3d6c567e2181461daf439fb2958765ce
Autor:
Ruiqi Du, Youzhen Xiang, Junying Chen, Xianghui Lu, Fucang Zhang, Zhitao Zhang, Baocheng Yang, Zijun Tang, Xin Wang, Long Qian
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 132, Iss , Pp 104081- (2024)
Understanding soil moisture dynamics is crucial for crop growth. The digital mapping of field soil moisture distribution provides valuable information for agricultural water management. The optical satellite data provides fine scale soil moisture inf
Externí odkaz:
https://doaj.org/article/179c555feebd47d6a460d04fdb8ac6c7
Publikováno v:
Frontiers in Remote Sensing, Vol 5 (2024)
Optically complex waters present significant challenges for remote sensing due to high concentrations of optically active substances (OASs) and their inherent optical properties (IOPs), as well as the adjacency effect. OASs and IOPs can be derived fr
Externí odkaz:
https://doaj.org/article/73700603ea0c499ba51ae3c1b31a9ae6
Autor:
Gaia Gleratti, Victor Martinez-Vicente, Elizabeth C. Atwood, Stefan G. H. Simis, Thomas Jackson
Publikováno v:
Frontiers in Remote Sensing, Vol 5 (2024)
Estuarine and coastal transitional waters present a challenge for the interpretation of radiometric remote sensing. Neighbouring water masses have strongly contrasting optical properties at small spatial scales. Adjacency of land adds optical contami
Externí odkaz:
https://doaj.org/article/9838702d7c6640f4b58b92e8794e47fb
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 131, Iss , Pp 103981- (2024)
Existing Land Surface Temperature (LST) fusion models encounter some challenges due to missing data, complex weather areas, and rapid land cover changes. To overcome these limitations, we proposed the Integrated SpatioTemporal Fusion Algorithm (ISFAT
Externí odkaz:
https://doaj.org/article/48640ff9f0d94b10b8974cf610dc98d7
Publikováno v:
IEEE Access, Vol 12, Pp 44586-44597 (2024)
Chromophoric dissolved organic matter (CDOM) is a crucial component of aquatic environments. Accurately quantifying the content of CDOM is essential for supporting lake water quality monitoring and management. In this study, we utilized quasi-analyti
Externí odkaz:
https://doaj.org/article/578aa6a289ab433f95425a7c1722b943
Publikováno v:
Big Earth Data, Vol 8, Iss 1, Pp 82-114 (2024)
ABSTRACTThis paper presents a novel approach for predicting the water quality indicator – Secchi disk depth (ZSD). ZSD indirectly reflects water clarity and serves as a proxy for other quality parameters. This study utilizes Deep Neural Network (DN
Externí odkaz:
https://doaj.org/article/6061434f944a424ea106c3df5c053e46
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 584-600 (2024)
Spatiotemporal fusion (STF) methods are a paramount solution for generating high spatial and temporal time series, overcoming the limitations of spatial and temporal resolution of satellite data. STF methods typically rely on band-by-band fusion, ass
Externí odkaz:
https://doaj.org/article/cd3ad994749944adbfff1da04f8c2aff
Publikováno v:
Science of Remote Sensing, Vol 10, Iss , Pp 100148- (2024)
This paper describes the selected algorithm for the ESA climate change initiative vegetation parameters project. Multi- and hyper-spectral, multi-angular, or multi-sensor top-of-canopy reflectance data call for an efficient generic retrieval system w
Externí odkaz:
https://doaj.org/article/b5cde5fbf8764051b7bfecd93f8bf8a8
Autor:
Maximiliano Arena, Paula Pratolongo, Hubert Loisel, Manh Duy Tran, Daniel Schaffer Ferreira Jorge, Ana Laura Delgado
Publikováno v:
Frontiers in Remote Sensing, Vol 5 (2024)
Externí odkaz:
https://doaj.org/article/78f491c0b7d748f687f97a35f929b908