Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Menglin Si"'
Publikováno v:
Remote Sensing, Vol 16, Iss 7, p 1232 (2024)
The urban–rural temperature difference is widely used in measuring surface urban heat island intensity (SUHII), where the accurate determination of rural background is crucial. However, traditionally, the entire permeable rural surface has been sel
Externí odkaz:
https://doaj.org/article/91b19096a1b740a3b2e5732f4e634f6c
Autor:
Lei He, Yaowen Xie, Jian Wang, Juanjuan Zhang, Menglin Si, Zecheng Guo, Changhui Ma, Qiang Bie, Zhao-Liang Li, Jian-Sheng Ye
Publikováno v:
Ecological Indicators, Vol 154, Iss , Pp 110694- (2023)
Warming and precipitation variations have significant impacts on carbon uptake in the Tibetan Plateau. However, which climatic variable or process primarily drives the inter-annual variations of carbon uptake is not clear. Using multiple gross primar
Externí odkaz:
https://doaj.org/article/23a85e5a79bf42869b4b18fea41420ae
Publikováno v:
International Journal of Remote Sensing. :1-21
Autor:
Guofei Shang, Menglin Si, Hua Wu, Françoise Nerry, Xia Zhang, Zhao-Liang Li, Bo-Hui Tang, Pei Leng
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing
ISPRS Journal of Photogrammetry and Remote Sensing, 2022, 183, pp.321-335. ⟨10.1016/j.isprsjprs.2021.11.017⟩
ISPRS Journal of Photogrammetry and Remote Sensing, 2022, 183, pp.321-335. ⟨10.1016/j.isprsjprs.2021.11.017⟩
International audience; In this study, the global surface urban heat island (SUHI) for 1711 cities during 2003–2019 was quantified by the dynamic urban-extent (DUE) scheme with the land surface temperature datasets from Moderate Resolution Imaging
Autor:
Zhao‐Liang Li, Hua Wu, Si‐Bo Duan, Wei Zhao, Huazhong Ren, Xiangyang Liu, Pei Leng, Ronglin Tang, Xin Ye, Jinshun Zhu, Yingwei Sun, Menglin Si, Meng Liu, Jiahao Li, Xia Zhang, Guofei Shang, Bo‐Hui Tang, Guangjian Yan, Chenghu Zhou
Publikováno v:
Reviews of Geophysics. 61
Publikováno v:
Progress In Electromagnetics Research C. 102:31-46
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing
IEEE Transactions on Geoscience and Remote Sensing, 2021, 59 (5), pp.4262-4272. ⟨10.1109/TGRS.2020.3009647⟩
IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2021, 59 (5), pp.4262-4272. ⟨10.1109/TGRS.2020.3009647⟩
IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, In press, pp.1-11. ⟨10.1109/TGRS.2020.3009647⟩
IEEE Transactions on Geoscience and Remote Sensing, 2021, 59 (5), pp.4262-4272. ⟨10.1109/TGRS.2020.3009647⟩
IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2021, 59 (5), pp.4262-4272. ⟨10.1109/TGRS.2020.3009647⟩
IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, In press, pp.1-11. ⟨10.1109/TGRS.2020.3009647⟩
International audience; Net surface shortwave radiation (NSSR) is a key parameter that drives the surface material exchange and energy balance. Herein, we propose an improved artificial neuron network (ANN) with parameterized (ANN-P) method to first
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::926db27f35bcb8e4af7a50af010abce2
https://hal.science/hal-03005960/file/Siml-TGRS-2020-August-preprint.pdf
https://hal.science/hal-03005960/file/Siml-TGRS-2020-August-preprint.pdf
Publikováno v:
Science of The Total Environment. 618:819-828
Satellite-derived aerosol optical depth (AOD) has been proven effective for estimating ground-level particles with an aerodynamic diameter
Publikováno v:
IGARSS
Net surface shortwave radiation (NSSR) is a key parameter for the estimation of surface energy budget. This paper proposes a method to directly estimate the NSSR from simulated Chinese Gaofen-5 (GF-5) data without using any ancillary information. Fir
Publikováno v:
Remote Sensing of Environment. 184:316-328
Satellite-based remote sensing data have been widely used in estimating ground-level PM2.5 concentrations as it can provide spatially detailed information. Most modern satellite-based PM2.5 estimates use statistical models that demand dense PM2.5 mon