Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Yingpin Yang"'
Autor:
Xinjie He, Qiting Huang, Dewei Yang, Yingpin Yang, Guoxue Xie, Shaoe Yang, Cunsui Liang, Zelin Qin
Publikováno v:
Fire, Vol 7, Iss 10, p 370 (2024)
Open biomass burning has significant adverse effects on regional air quality, climate change, and human health. Extensive open biomass burning is detected in most regions of China, and capturing the characteristics of open biomass burning and underst
Externí odkaz:
https://doaj.org/article/098474208e8543b6aca2fff8e3f0953b
Autor:
Yingpin Yang, Zhifeng Wu, Wenju Xiao, Ya’nan Zhou, Qiting Huang, Tianjun Wu, Jiancheng Luo, Haiyun Wang
Publikováno v:
Remote Sensing, Vol 15, Iss 16, p 3942 (2023)
Monitoring agricultural abandonment is essential in understanding the effects on the environment and food security. Polarimetric synthetic aperture radar (PolSAR) is an efficient approach for the monitoring of large-scale agricultural land cover in c
Externí odkaz:
https://doaj.org/article/6b0ec6ff954a473596363f5519e2b25b
Autor:
Tianjun Wu, Jiancheng Luo, Lijing Gao, Yingwei Sun, Yingpin Yang, Ya'nan Zhou, Wen Dong, Xin Zhang
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 9241-9253 (2021)
Grassland resources guarantee the balance of ecosystems and the sustainable development of animal husbandry. Spatial information is essential for grass resource management in pastoral areas, which can be extracted quickly on a large-scale by using re
Externí odkaz:
https://doaj.org/article/94207e68b9f84ca087850c68aa756c95
Publikováno v:
GIScience & Remote Sensing, Vol 56, Iss 8, Pp 1170-1191 (2019)
Farmland parcel-based crop classification using satellite data plays an important role in precision agriculture. In this study, a deep-learning-based time-series analysis method employing optical images and synthetic aperture radar (SAR) data is pres
Externí odkaz:
https://doaj.org/article/cf974d23285e4530817aebbf735b8ee6
Autor:
Wei Liu, Jian Wang, Jiancheng Luo, Zhifeng Wu, Jingdong Chen, Yanan Zhou, Yingwei Sun, Zhanfeng Shen, Nan Xu, Yingpin Yang
Publikováno v:
Remote Sensing, Vol 12, Iss 22, p 3733 (2020)
Accurate, timely, and reliable farmland mapping is a prerequisite for agricultural management and environmental assessment in mountainous areas. However, in these areas, high spatial heterogeneity and diversified planting structures together generate
Externí odkaz:
https://doaj.org/article/85acd3d5efa648999291feece6677e4e
Autor:
Boxiong Qin, Biao Cao, Hua Li, Zunjian Bian, Tian Hu, Yongming Du, Yingpin Yang, Qing Xiao, Qinhuo Liu
Publikováno v:
Remote Sensing, Vol 12, Iss 11, p 1834 (2020)
Surface upward longwave radiation (SULR) is a critical component in the calculation of the Earth’s surface radiation budget. Multiple clear-sky SULR estimation methods have been developed for high-spatial resolution satellite observations. Here, we
Externí odkaz:
https://doaj.org/article/d4a7c6e970c648edbf9f70d2d1cc9f16
Publikováno v:
Remote Sensing, Vol 11, Iss 20, p 2342 (2019)
The time series (TS) of the normalized difference vegetation index (NDVI) has been widely used to trace the temporal and spatial variability of terrestrial vegetation. However, many factors such as atmospheric noise and radiometric correction residua
Externí odkaz:
https://doaj.org/article/184e36338b784cff97317c669efef73d
Publikováno v:
Remote Sensing, Vol 11, Iss 20, p 2380 (2019)
Deep convolutional neural networks have promoted significant progress in building extraction from high-resolution remote sensing imagery. Although most of such work focuses on modifying existing image segmentation networks in computer vision, we prop
Externí odkaz:
https://doaj.org/article/108442cb4d204d32b64465119b73e7f1
Autor:
Yingwei Sun, Jiancheng Luo, Tianjun Wu, Ya’nan Zhou, Hao Liu, Lijing Gao, Wen Dong, Wei Liu, Yingpin Yang, Xiaodong Hu, Lingyu Wang, Zhongfa Zhou
Publikováno v:
Sensors, Vol 19, Iss 19, p 4227 (2019)
Accurate crop classification is the basis of agricultural research, and remote sensing is the only effective measuring technique to classify crops over large areas. Optical remote sensing is effective in regions with good illumination; however, it us
Externí odkaz:
https://doaj.org/article/f1e9265af781498f962f5220bff6cdd7
Publikováno v:
Sensors, Vol 18, Iss 12, p 4505 (2018)
Radiometric normalization attempts to normalize the radiomimetic distortion caused by non-land surface-related factors, for example, different atmospheric conditions at image acquisition time and sensor factors, and to improve the radiometric consist
Externí odkaz:
https://doaj.org/article/ba0f8473cdc54a6fa86e6752fda1d119