Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Xingguang Yan"'
Publikováno v:
International Journal of Digital Earth, Vol 16, Iss 2, Pp 4471-4491 (2023)
ABSTRACTRapid and accurate estimation of forest biomass are essential to drive sustainable management of forests. Field-based measurements of forest above-ground biomass (AGB) can be costly and difficult to conduct. Multi-source remote sensing data o
Externí odkaz:
https://doaj.org/article/aad40d444dc446659edd786b32b3394c
Publikováno v:
Shuiwen dizhi gongcheng dizhi, Vol 50, Iss 4, Pp 173-184 (2023)
In order to deeply study the main controlling factors of land subsidence in the northeast of the Xiongan New Area, the layered monitoring points of Daying Town are taken as the research object, and the causes of land subsidence are discussed based on
Externí odkaz:
https://doaj.org/article/367d1f00173c4b07bc17849380d2d4f2
Publikováno v:
Land, Vol 12, Iss 12, p 2149 (2023)
Long time series land cover classification information is the basis for scientific research on urban sprawls, vegetation change, and the carbon cycle. The rapid development of cloud computing platforms such as the Google Earth Engine (GEE) and access
Externí odkaz:
https://doaj.org/article/06ee010363ba46669b893219b9252016
Autor:
Jianhui HE, Jincai ZHANG, Yong CHEN, Xingguang YAN, Bin SHI, Guangqing WEI, Lixiang JIA, Suping LIU
Publikováno v:
Shuiwen dizhi gongcheng dizhi, Vol 48, Iss 1, Pp 146-153 (2021)
Fiber optic sensing technique has the features of distributed and high-precision measurement, especially in land subsidence monitoring. Due to the high cost and complicated environment, the monitoring data is mostly collected manually and it limits t
Externí odkaz:
https://doaj.org/article/8a7a03d8538940ddb9ea8f3537d8a24c
Publikováno v:
Remote Sensing, Vol 14, Iss 20, p 5154 (2022)
With the growth of cloud computing, the use of the Google Earth Engine (GEE) platform to conduct research on water inversion, natural disaster monitoring, and land use change using long time series of Landsat images has also gradually become mainstre
Externí odkaz:
https://doaj.org/article/986fa92301e64de2ba94e423a29c4927
In previous research on the construction of ecological security patterns (ESPs), the positioning characteristics of urban development were rarely considered, resulting in the identification of key conservation areas that are insufficiently thorough t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::26d0f47be8ab724c7d3fcb1b9e269828
https://doi.org/10.22541/au.166787465.55287870/v1
https://doi.org/10.22541/au.166787465.55287870/v1
Publikováno v:
Sustainability; Volume 14; Issue 14; Pages: 8773
Understanding the causes of poverty and identifying the transformation characteristics of poverty is the basis for achieving poverty eradication. In order to clarify the availability of construction land for poverty assessment, this paper explores th
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200731
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c82a46ae0e8e59b47808a7b703ea9ec6
https://doi.org/10.1007/978-3-031-20074-8_6
https://doi.org/10.1007/978-3-031-20074-8_6
Publikováno v:
Sustainability; Volume 14; Issue 24; Pages: 16501
In previous research on the construction of ecological security patterns (ESPs), the positioning characteristics of urban development were rarely considered, resulting in the identification of key conservation areas that are insufficient to support t
We introduce RPM-Net, a deep learning-based approach which simultaneously infers movable parts and hallucinates their motions from a single, un-segmented, and possibly partial, 3D point cloud shape. RPM-Net is a novel Recurrent Neural Network (RNN),
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6234a29809f17edc6e5b1cc95c422432