Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Xicun Zhu"'
Publikováno v:
PeerJ, Vol 12, p e17836 (2024)
Soil organic carbon (SOC) is a crucial component of the global carbon cycle, playing a significant role in ecosystem health and carbon balance. In this study, we focused on assessing the surface SOC content in Shandong Province based on land use type
Externí odkaz:
https://doaj.org/article/195da5d3bffc4b42a877903a4637e09e
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Tree species recognition accuracy greatly affects forest remote sensing mapping and forestry resource monitoring. The multispectral and texture features of the remote sensing images from the ZiYuan-3 (ZY-3) satellite at two phenological phas
Externí odkaz:
https://doaj.org/article/75d847b723764aa4a8169e11164ebaf7
Autor:
Tianyu Miao, Wenjun Ji, Baoguo Li, Xicun Zhu, Jianxin Yin, Jiajie Yang, Yuanfang Huang, Yan Cao, Dongheng Yao, Xiangbin Kong
Publikováno v:
Remote Sensing, Vol 16, Iss 7, p 1256 (2024)
Soil analysis using near-infrared spectroscopy has shown great potential to be an alternative to traditional laboratory analysis, and there is continuously increasing interest in building large-scale soil spectral libraries (SSLs). However, due to is
Externí odkaz:
https://doaj.org/article/b406ba0a6c8140f38f28abab11bdcccf
Publikováno v:
Frontiers in Forests and Global Change, Vol 6 (2023)
Vegetation greenery is essential for the sensory and psychological wellbeing of residents in residential communities. To enhance the quality of regulations and policies to improve people’s living environments, it is crucial to effectively identify
Externí odkaz:
https://doaj.org/article/655dbe6d2c4a489583d8e77917bcf988
Autor:
Canting Zhang, Xicun Zhu, Meixuan Li, Yuliang Xue, Anran Qin, Guining Gao, Mengxia Wang, Yuanmao Jiang
Publikováno v:
Horticulturae, Vol 9, Iss 10, p 1085 (2023)
Utilizing multi-source remote sensing data fusion to achieve efficient and accurate monitoring of crop nitrogen content is crucial for precise crop management. In this study, an effective integrated method for inverting nitrogen content in apple orch
Externí odkaz:
https://doaj.org/article/636a3505581e4a37abcb8429542bef59
Autor:
Wei Li, Xicun Zhu, Xinyang Yu, Meixuan Li, Xiaoying Tang, Jie Zhang, Yuliang Xue, Canting Zhang, Yuanmao Jiang
Publikováno v:
Sensors, Vol 22, Iss 9, p 3503 (2022)
As the major nutrient affecting crop growth, accurate assessing of nitrogen (N) is crucial to precise agricultural management. Although improvements based on ground and satellite data nitrogen in monitoring crops have been made, the application of th
Externí odkaz:
https://doaj.org/article/826494d04543401087ecbfe8bb8552eb
Publikováno v:
Scientific Reports, Vol 8, Iss 1, Pp 1-10 (2018)
Abstract The remote sensing technology provides a new means for the determination of chlorophyll content in apple trees that includes a rapid analysis, low cost and large monitoring area. The Back-Propagation Neural Network (BPNN) and the Supported V
Externí odkaz:
https://doaj.org/article/62648359130b42da98889557f67e25d5
Autor:
Xueyuan Bai, Zhenhai Li, Wei Li, Yu Zhao, Meixuan Li, Hongyan Chen, Shaochong Wei, Yuanmao Jiang, Guijun Yang, Xicun Zhu
Publikováno v:
Remote Sensing, Vol 13, Iss 16, p 3073 (2021)
Apple (Malus domestica Borkh. cv. “Fuji”), an important cash crop, is widely consumed around the world. Accurately predicting preharvest apple fruit yields is critical for planting policy making and agricultural management. This study attempted t
Externí odkaz:
https://doaj.org/article/2ab23b29db574748a72224b035ea3946
Publikováno v:
Remote Sensing, Vol 12, Iss 1, p 133 (2020)
The extraction of information about individual trees is essential to supporting the growing of fruit in orchard management. Data acquired from spectral sensors mounted on unmanned aerial vehicles (UAVs) have very high spatial and temporal resolution.
Externí odkaz:
https://doaj.org/article/ad3264b10f944eebafd99082435c184e
Publikováno v:
PLoS ONE, Vol 12, Iss 10, p e0186751 (2017)
The new-shoot-growing stage is an important period of apple tree nutrition distribution. The objective of this study is to provide technical support for apple tree nutrition diagnosis by constructing quantitative evaluation models between the apple l
Externí odkaz:
https://doaj.org/article/b506dd0ac02340299e098c8e2fd7c572