Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Erjiang Fu"'
Autor:
Dajun Lian, Qimin He, Li Li, Kefei Zhang, Erjiang Fu, Guangyan Li, Rui Wang, Biqing Gao, Kangming Song
Publikováno v:
Remote Sensing, Vol 15, Iss 13, p 3247 (2023)
Precipitable water vapor (PWV) is an important meteorological factor for predicting extreme weather events such as tropical cyclones, which can be obtained from zenith tropospheric delay (ZTD) by using a conversion. A time difference of ZTD arrival (
Externí odkaz:
https://doaj.org/article/03b948a8cd60435dade2318c6115c37c
Autor:
Xuewei Zhang, Kefei Zhang, Suqin Wu, Hongtao Shi, Yaqin Sun, Yindi Zhao, Erjiang Fu, Shuo Chen, Chaofa Bian, Wei Ban
Publikováno v:
Remote Sensing, Vol 14, Iss 20, p 5087 (2022)
The leaf area index (LAI) is critical for the respiration, transpiration, and photosynthesis of crops. Color indices (CIs) and vegetation indices (VIs) extracted from unmanned aerial vehicle (UAV) imagery have been widely applied to the monitoring of
Externí odkaz:
https://doaj.org/article/d7973141a35549a182d4804028d242a9
Autor:
Longjiang Li, Kefei Zhang, Suqin Wu, Haobo Li, Xiaoming Wang, Andong Hu, Wang Li, Erjiang Fu, Minghao Zhang, Zhen Shen
Publikováno v:
Remote Sensing, Vol 14, Iss 17, p 4280 (2022)
Global navigation satellite systems (GNSS) has been applied to the sounding of precipitable water vapor (PWV) due to its high accuracy and high spatiotemporal resolutions. PWV obtained from GNSS (GNSS-PWV) can be used to investigate extreme weather p
Externí odkaz:
https://doaj.org/article/3f35ed3b15a04fe4b5772d03a25f92cc
Autor:
Jinxiang Liu, Kefei Zhang, Suqin Wu, Hongtao Shi, Yindi Zhao, Yaqin Sun, Huifu Zhuang, Erjiang Fu
Publikováno v:
Remote Sensing, Vol 14, Iss 3, p 785 (2022)
The convolutional neural network (CNN) method has been widely used in the classification of hyperspectral images (HSIs). However, the efficiency and accuracy of the HSI classification are inevitably degraded when small samples are available. This stu
Externí odkaz:
https://doaj.org/article/25cd76b099644b5fa0c1cb88a73c0e13
Autor:
Xuewei Zhang, Kefei Zhang, Yaqin Sun, Yindi Zhao, Huifu Zhuang, Wei Ban, Yu Chen, Erjiang Fu, Shuo Chen, Jinxiang Liu, Yumeng Hao
Publikováno v:
Remote Sensing, Vol 14, Iss 2, p 331 (2022)
The leaf area index (LAI) is of great significance for crop growth monitoring. Recently, unmanned aerial systems (UASs) have experienced rapid development and can provide critical data support for crop LAI monitoring. This study investigates the effe
Externí odkaz:
https://doaj.org/article/948a263f5f1646819334db949c5b8a7e
Autor:
Haobo Li, Xiaoming Wang, Suqin Wu, Kefei Zhang, Erjiang Fu, Ying Xu, Cong Qiu, Jinglei Zhang, Li Li
Publikováno v:
Remote Sensing, Vol 13, Iss 7, p 1390 (2021)
Nowadays, precipitable water vapor (PWV) retrieved from ground-based Global Navigation Satellite Systems (GNSS) tracking stations has heralded a new era of GNSS meteorological applications, especially for severe weather prediction. Among the existing
Externí odkaz:
https://doaj.org/article/5116d17966a743c6a39055000b8f507f
Autor:
Song, Dajun Lian, Qimin He, Li Li, Kefei Zhang, Erjiang Fu, Guangyan Li, Rui Wang, Biqing Gao, Kangming
Publikováno v:
Remote Sensing; Volume 15; Issue 13; Pages: 3247
Precipitable water vapor (PWV) is an important meteorological factor for predicting extreme weather events such as tropical cyclones, which can be obtained from zenith tropospheric delay (ZTD) by using a conversion. A time difference of ZTD arrival (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::5649b7df5d20629b1837cf7f7cfacf59
Autor:
Qimin He, Kefei Zhang, Suqin Wu, Dajun Lian, Li Li, Zhen Shen, Moufeng Wan, Longjiang Li, Rui Wang, Erjiang Fu, Biqing Gao
Publikováno v:
Spatial Statistics. 51:100664
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2004988cfa9dc02ce2025adc78b8b35
https://doi.org/10.1016/j.spasta.2022.100664
https://doi.org/10.1016/j.spasta.2022.100664
Autor:
Suqin Wu, Cong Qiu, Kefei Zhang, Haobo Li, Erjiang Fu, Li Li, Ying Xu, Jinglei Zhang, Xiaoming Wang
Publikováno v:
Remote Sensing, Vol 13, Iss 1390, p 1390 (2021)
Remote Sensing; Volume 13; Issue 7; Pages: 1390
Remote Sensing; Volume 13; Issue 7; Pages: 1390
Nowadays, precipitable water vapor (PWV) retrieved from ground-based Global Navigation Satellite Systems (GNSS) tracking stations has heralded a new era of GNSS meteorological applications, especially for severe weather prediction. Among the existing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::28479f7a1e45bdb0077ddc9d1aa0477d
https://www.mdpi.com/2072-4292/13/7/1390
https://www.mdpi.com/2072-4292/13/7/1390
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9789811631375
The Global Navigation Satellite Systems (GNSS) radio occultation (RO) is a relatively new effective technique for atmospheric sounding and has been routinely used in operational numerical weather prediction models run by major world forecasting cente
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7a058d30ce92cdec9cfee07fef9cfa7
https://doi.org/10.1007/978-981-16-3138-2_17
https://doi.org/10.1007/978-981-16-3138-2_17
