Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Duole Feng"'
Autor:
Yuanyuan Zhao, Duole Feng, Le Yu, Yuqi Cheng, Meinan Zhang, Xiaoxuan Liu, Yidi Xu, Lei Fang, Zhiliang Zhu, Peng Gong
Publikováno v:
Remote Sensing, Vol 11, Iss 5, p 599 (2019)
Northeast China is a major grain production area, an ecological important forest area, and the largest old industrial base which is now suffering from economic growth slowdown and brain drain. Accurate and long-term dynamic land cover maps are highly
Externí odkaz:
https://doaj.org/article/ad680910611440869f80563ede7fcd8b
Publikováno v:
Remote Sensing, Vol 9, Iss 10, p 1034 (2017)
Volunteered geographic data are being used increasingly to support land cover mapping and validation, yet the reliability of the volunteered data still requires further research. This study proposes data-based guidelines to help design the data colle
Externí odkaz:
https://doaj.org/article/cf7c371bb74347c7ad74847e40f4ea99
Publikováno v:
Science China Life Sciences. 62:661-667
The lack of refined spatial detail on bird distribution in China has hindered further research due to the large geographic unit (provincial level) in existing national bird distribution data. Based on multi-source bird distribution data, we built a m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cba512a22486da4c66ae99adc44f3f2d
https://doi.org/10.1007/s11427-018-9419-2
https://doi.org/10.1007/s11427-018-9419-2
Publikováno v:
International Journal of Remote Sensing. 40:6185-6202
Accurate and up-to-date land use land cover (LULC) mapping has long been a challenge in Africa. Recently, three LULC maps with moderate spatial resolution (20 m to 100 m) have been developed using ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1a8a2aeaceadcce338047d3cf3607e0c
https://doi.org/10.1080/01431161.2019.1587207
https://doi.org/10.1080/01431161.2019.1587207
Autor:
Le Yu, Kwame Oppong Hackman, Xiaomeng Huang, Peng Gong, Yuqi Cheng, Jiyao Zhao, Duole Feng, Xueliang Cai, Yuanyuan Zhao, Dailiang Peng, Yidi Xu, Hui Lu, Chaoqing Yu
Publikováno v:
International Journal of Remote Sensing. 39:7328-7349
Accurate land-use/land-cover mapping based on remote-sensing images depends on clear and frequent observations. This study aimed to explore how many Landsat images were needed within a year and when they should be acquired, for cropland mapping in Af
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b88edc1aa1c111a18a04dcd6b2ea09ba
https://doi.org/10.1080/01431161.2018.1468115
https://doi.org/10.1080/01431161.2018.1468115
Publikováno v:
International Journal of Remote Sensing. 39:3926-3938
Recent developments in global land-cover mapping have focused on spatial resolution improvement with more heterogeneous features to integrate spatial, spectral and temporal information. In this stu...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::356257800218579a8afae4009b80d317
https://doi.org/10.1080/01431161.2018.1452073
https://doi.org/10.1080/01431161.2018.1452073
Autor:
Yidi Xu, Le Yu, Meinan Zhang, Lei Fang, Yuqi Cheng, Duole Feng, Zhiliang Zhu, Yuanyuan Zhao, Peng Gong, Xiaoxuan Liu
Publikováno v:
Remote Sensing; Volume 11; Issue 5; Pages: 599
Remote Sensing, Vol 11, Iss 5, p 599 (2019)
Remote Sensing, Vol 11, Iss 5, p 599 (2019)
Northeast China is a major grain production area, an ecological important forest area, and the largest old industrial base which is now suffering from economic growth slowdown and brain drain. Accurate and long-term dynamic land cover maps are highly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a95d06567a8065f5bd3c6bc079ed56e6
Publikováno v:
International Journal of Remote Sensing. 37:5632-5646
Land-cover mapping is an important research topic with broad applicability in the remote-sensing domain. Machine learning algorithms such as Maximum Likelihood Classifier (MLC), Support Vector Machine (SVM), Artificial Neural Network (ANN), and Rando
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b0d5fe20df3811a146e49b3f9ca1b17
https://doi.org/10.1080/01431161.2016.1246775
https://doi.org/10.1080/01431161.2016.1246775
Autor:
Duole Feng, Xiaoyi Wang, Yanlei Chen, Peng Gong, Yuqi Bai, Yuanyuan Zhao, John Radke, Cristián F. Estades, Gregory S. Biging, Mauricio Galleguillos, Le Yu, H. Jaime Hernández
Publikováno v:
Remote Sensing of Environment. 183:170-185
Stretching over 4300 km north to south, Chile is a special country with complicated landscapes and rich biodiversity. Accurate and timely updated land cover map of Chile in detailed classification categories is highly demanded for many applications.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd2b8dd1f071bb2517ede166b5e42a86
https://doi.org/10.1016/j.rse.2016.05.016
https://doi.org/10.1016/j.rse.2016.05.016
Autor:
Peng Gong, Yuanyuan Zhao, Duole Feng, Le Yu, Congcong Li, Jie Wang, Yuqi Bai, Alan Belward, Nicholas Clinton, Zhiliang Zhu
Publikováno v:
International Journal of Remote Sensing. 37:4648-4664
A new African land-cover data set has been developed using multi-seasonal Landsat Operational Land Imager (OLI) imagery mainly acquired around 2014, supplemented by Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+). Each path/row
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53bb46d1ce6a7e9d9b04f998c27a5976
https://doi.org/10.1080/01431161.2016.1218090
https://doi.org/10.1080/01431161.2016.1218090