Zobrazeno 1 - 10
of 160
pro vyhledávání: '"Dailiang Peng"'
Autor:
Jinkang Hu, Bing Zhang, Dailiang Peng, Jianxi Huang, Wenjuan Zhang, Bin Zhao, Yong Li, Enhui Cheng, Zihang Lou, Shengwei Liu, Songlin Yang, Yunlong Tan, Yulong Lv
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-18 (2024)
Abstract Winter wheat constitutes approximately 20% of China’s total cereal production. However, calculations of total production based on multiplying the planted area by the yield have tended to produce overestimates. In this study, we generated s
Externí odkaz:
https://doaj.org/article/86b1fd0619b648c5add0bbfe15faabd6
Autor:
Shijun Zheng, Dailiang Peng, Bing Zhang, Le Yu, Yuhao Pan, Yan Wang, Xuxiang Feng, Changyong Dou
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Northwest China has undergone notable alterations in climate and vegetation growth in recent decades. Nevertheless, uncertainties persist concerning the response of different vegetation types to climate change and the underlying mechanisms.
Externí odkaz:
https://doaj.org/article/3ac0b998af304a9db760ef156e257f65
Autor:
Xin Chen, Le Yu, Yaoyao Li, Tao Liu, Jingming Liu, Dailiang Peng, Xiaoling Zhang, Chuanglin Fang, Peng Gong
Publikováno v:
Communications Earth & Environment, Vol 5, Iss 1, Pp 1-14 (2024)
Abstract China prioritizes a coordinated and sustainable shift from rural to urban areas, termed rural-urban transformation. This involves land, population, and industry urbanization. Here we explore the spatiotemporal dynamics of rural-urban transfo
Externí odkaz:
https://doaj.org/article/2f77b91c4ddd40afa02f666dad92afb2
Autor:
Yunlong Tan, Enhui Cheng, Xuxiang Feng, Bin Zhao, Junjie Chen, Qiaoyun Xie, Hao Peng, Cunjun Li, Chuang Lu, Yong Li, Bing Zhang, Dailiang Peng
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
In the past, the use of remote sensing for winter wheat growth monitoring mainly relied on the relative growth assessment of a single vegetation index, such as normalized Vegetation index (NDVI). This study advanced the methodology by integrating fie
Externí odkaz:
https://doaj.org/article/1b689b5bb1984f6482b9acfce6ba4351
Autor:
Hongchi Zhang, Zihang Lou, Dailiang Peng, Bing Zhang, Wang Luo, Jianxi Huang, Xiaoyang Zhang, Le Yu, Fumin Wang, Linsheng Huang, Guohua Liu, Shuang Gao, Jinkang Hu, Songlin Yang, Enhui Cheng
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-18 (2024)
Abstract China, as the world’s biggest soybean importer and fourth-largest producer, needs accurate mapping of its planting areas for global food supply stability. The challenge lies in gathering and collating ground survey data for different crops
Externí odkaz:
https://doaj.org/article/efeb73df32164e10b14ed02d88500aa3
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
The accuracy of digital elevation models (DEMs) is crucial for practical applications in complex terrain. In this study, various correction models were employed to evaluate and correct the 90 m SRTM3 DEM and TanDEM-X DEM data in the Qinghai-Tibet Pla
Externí odkaz:
https://doaj.org/article/1a8a8462a160462c9bcd42e7f59173c8
Autor:
Wenquan Zhu, Zhiying Xie, Cenliang Zhao, Zhoutao Zheng, Kun Qiao, Dailiang Peng, Yongshuo H. Fu
Publikováno v:
GIScience & Remote Sensing, Vol 61, Iss 1 (2024)
ABSTRACTAccurately estimating gross primary productivity (GPP), the largest carbon flux in terrestrial ecosystems, is crucial for advancing our understanding of global carbon cycle and predicting climate feedbacks. The advancements in remote sensing
Externí odkaz:
https://doaj.org/article/ba8d284504ee40cf9fffdf9730dd44ba
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 14161-14178 (2024)
Timely and accurate crop yield estimation is crucial for managing crops, trade, and food security. The combination of remote sensing technology with machine learning methods is increasingly popular for global yield prediction. However, traditional ma
Externí odkaz:
https://doaj.org/article/74875ffdded24fa882e4d4078dbe363f
Autor:
Zhenrong Du, Le Yu, Xiyu Li, Jiyao Zhao, Xin Chen, Yidi Xu, Peng Yang, Jianyu Yang, Dailiang Peng, Yueming Xue, Peng Gong
Publikováno v:
International Journal of Digital Earth, Vol 16, Iss 2, Pp 4428-4445 (2023)
Remote sensing and land resource surveys have been used in recent decades for land use/land cover (LULC) mapping; however, keeping the developed LULC up-to-date and consistent with land survey statistics remains challenging. This study developed a pr
Externí odkaz:
https://doaj.org/article/abde08e3dbb343119a81cc7e2d363f21
Autor:
Dailiang Peng, Enhui Cheng, Xuxiang Feng, Jinkang Hu, Zihang Lou, Hongchi Zhang, Bin Zhao, Yulong Lv, Hao Peng, Bing Zhang
Publikováno v:
Remote Sensing, Vol 16, Iss 19, p 3613 (2024)
Accurately predicting winter wheat yield before harvest could greatly benefit decision-makers when making management decisions. In this study, we utilized weather forecast (WF) data combined with Sentinel-2 data to establish the deep-learning network
Externí odkaz:
https://doaj.org/article/d6413b4bc336432fa6d59fa9156250a3