Zobrazeno 1 - 10
of 87
pro vyhledávání: '"LPRM"'
Publikováno v:
Algorithms, Vol 17, Iss 6, p 262 (2024)
With the rapid advancement of urban intelligence, there is an increasingly urgent demand for technological innovation in traffic management. License plate recognition technology can achieve high accuracy under ideal conditions but faces significant c
Externí odkaz:
https://doaj.org/article/38c6c61e6c5549dcbb12c29d36f53d15
Publikováno v:
Water Supply, Vol 23, Iss 2, Pp 688-705 (2023)
Soil moisture (SM) has an important role in the earth's water cycle and is a key variable in water resources management. Considering the critical state of water resources in the Urmia Lake basin, northwest Iran, this study examined the potential for
Externí odkaz:
https://doaj.org/article/20f322902c2749e0bc37f3257160c955
Autor:
Haonan Liu, Guojie Wang, Daniel Fiifi Tawia Hagan, Yifan Hu, Isaac Kwesi Nooni, Emmanuel Yeboah, Feihong Zhou
Publikováno v:
Remote Sensing, Vol 15, Iss 21, p 5108 (2023)
Satellite observations have provided global and regional soil-moisture estimates in the last four decades. However, the accuracy of these observations largely depends on reducing uncertainties in the retrieval algorithms. In this study, we address tw
Externí odkaz:
https://doaj.org/article/a1cbb0c9b0164b40ae28766ed3b175db
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 8955-8970 (2021)
Long-term surface soil moisture (SM) data are increasingly needed in water budget and energy balance analysis of watersheds. The performance of nine remotely sensed SM products from Advanced Microwave Scanning Radiometer 2 (AMSR2), Soil Moisture and
Externí odkaz:
https://doaj.org/article/3bc0d5563e7d43ee9e60d711bde60b52
Akademický článek
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Autor:
Guojie Wang, Xiaowen Ma, Daniel Fiifi Tawia Hagan, Robin van der Schalie, Giri Kattel, Waheed Ullah, Liangliang Tao, Lijuan Miao, Yi Liu
Publikováno v:
Remote Sensing, Vol 14, Iss 5, p 1225 (2022)
Soil moisture plays an essential role in the land-atmosphere interface. It has become necessary to develop quality large-scale soil moisture data from satellite observations for relevant applications in climate, hydrology, agriculture, etc. Specifica
Externí odkaz:
https://doaj.org/article/abcf3ca76cef47858fba3d29ecde867d
Akademický článek
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Publikováno v:
Sustainability; Volume 15; Issue 11; Pages: 9112
Soil moisture (SM) exists at the land-atmosphere interface and serves as a key driving variable that affects global water balance and vegetation growth. Its importance in climate and earth system studies necessitates a comprehensive evaluation and co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::ee1a0100e2414815ee71ca4399795451
Autor:
Robin van der Schalie, Mendy van der Vliet, Nemesio Rodríguez-Fernández, Wouter A. Dorigo, Tracy Scanlon, Wolfgang Preimesberger, Rémi Madelon, Richard A. M. de Jeu
Publikováno v:
Remote Sensing, Vol 13, Iss 13, p 2480 (2021)
The CCI Soil Moisture dataset (CCI SM) is the most extensive climate data record of satellite soil moisture to date. To maximize its function as a climate benchmark, both long-term consistency and (model-) independence are high priorities. Two unique
Externí odkaz:
https://doaj.org/article/bf79b46179b44a90b2260ce2ce19ea5a
Autor:
Jin Liu, Linna Chai, Zheng Lu, Shaomin Liu, Yuquan Qu, Deyuan Geng, Yongze Song, Yabing Guan, Zhixia Guo, Jian Wang, Zhongli Zhu
Publikováno v:
Remote Sensing, Vol 11, Iss 7, p 792 (2019)
High-quality and long time-series soil moisture (SM) data are increasingly required for the Qinghai-Tibet Plateau (QTP) to more accurately and effectively assess climate change. In this study, to evaluate the accuracy and effectiveness of SM data, fi
Externí odkaz:
https://doaj.org/article/348fe7c60b0347369fd7baa1a7c4d56c