| Feature selection of time series MODIS data for early crop classification using random forest: A case study in Kansas, USA P Hao, Y Zhan, L Wang, Z Niu, M Shakir Remote Sensing 7 (5), 5347-5369, 2015 | 257 | 2015 |
| Transfer Learning for Crop classification with Cropland Data Layer data (CDL) as training samples P Hao, L Di, C Zhang, L Guo Science of The Total Environment 733, 138869, 2020 | 90 | 2020 |
| An improved high spatial and temporal data fusion approach for combining Landsat and MODIS data to generate daily synthetic Landsat imagery M Wu, C Wu, W Huang, Z Niu, C Wang, W Li, P Hao Information fusion 31, 14-25, 2016 | 86 | 2016 |
| An overview of the applications of earth observation satellite data: impacts and future trends Q Zhao, L Yu, Z Du, D Peng, P Hao, Y Zhang, P Gong Remote Sensing 14 (8), 1863, 2022 | 85 | 2022 |
| The potential of time series merged from Landsat-5 TM and HJ-1 CCD for crop classification: a case study for Bole and Manas Counties in Xinjiang, China P Hao, L Wang, Z Niu, A Aablikim, N Huang, S Xu, F Chen Remote Sensing 6 (8), 7610-7631, 2014 | 56* | 2014 |
| Rapid in-season mapping of corn and soybeans using machine-learned trusted pixels from Cropland Data Layer C Zhang, L Di, P Hao, Z Yang, L Lin, H Zhao, L Guo International Journal of Applied Earth Observation and Geoinformation 102 …, 2021 | 53 | 2021 |
| High resolution crop intensity mapping using harmonized Landsat-8 and Sentinel-2 data P HAO, H Tang, Z CHEN, YU Le, M Wu Journal of Integrative Agriculture 18 (12), 2883-2897, 2019 | 46 | 2019 |
| Reconstruction of daily 30 m data from HJ CCD, GF-1 WFV, Landsat, and MODIS data for crop monitoring M Wu, X Zhang, W Huang, Z Niu, C Wang, W Li, P Hao Remote Sensing 7 (12), 16293-16314, 2015 | 45 | 2015 |
| Fine crop mapping by combining high spectral and high spatial resolution remote sensing data in complex heterogeneous areas M Wu, W Huang, Z Niu, Y Wang, C Wang, W Li, P Hao, B Yu Computers and Electronics in Agriculture 139, 1-9, 2017 | 43 | 2017 |
| Comparison of hybrid classifiers for crop classification using normalized difference vegetation index time series: A case study for major crops in North Xinjiang, China P Hao, L Wang, Z Niu PloS one 10 (9), e0137748, 2015 | 43 | 2015 |
| AgKit4EE: A toolkit for agricultural land use modeling of the conterminous United States based on Google Earth Engine C Zhang, L Di, Z Yang, L Lin, P Hao Environmental Modelling & Software 129, 104694, 2020 | 42 | 2020 |
| Early-season crop type mapping using 30-m reference time series P HAO, H TANG, Z CHEN, Q MENG, Y KANG Journal of Integrative Agriculture 19 (7), 1897-1911, 2020 | 40 | 2020 |
| Using moderate-resolution temporal NDVI profiles for high-resolution crop mapping in years of absent ground reference data: a case study of bole and manas counties in Xinjiang … P Hao, L Wang, Y Zhan, Z Niu ISPRS International Journal of Geo-Information 5 (5), 67, 2016 | 40 | 2016 |
| Crop classification using crop knowledge of the previous-year: Case study in Southwest Kansas, USA P Hao, L Wang, Y Zhan, C Wang, Z Niu, M Wu European Journal of Remote Sensing 49 (1), 1061-1077, 2016 | 40 | 2016 |
| Spatiotemporal changes of urban impervious surface area and land surface temperature in Beijing from 1990 to 2014 P Hao, Z Niu, Y Zhan, Y Wu, L Wang, Y Liu GIScience & Remote Sensing 53 (1), 63-84, 2016 | 38 | 2016 |
| FROM-GLC Plus: Toward near real-time and multi-resolution land cover mapping L Yu, Z Du, R Dong, J Zheng, Y Tu, X Chen, P Hao, B Zhong, D Peng, ... GIScience & Remote Sensing 59 (1), 1026-1047, 2022 | 36 | 2022 |
| Annual cropland mapping using reference Landsat time series—a case study in Central Asia P Hao, F Löw, C Biradar Remote Sensing 10 (12), 2057, 2018 | 31 | 2018 |
| Annual dynamic dataset of global cropping intensity from 2001 to 2019 X Liu, J Zheng, L Yu, P Hao, B Chen, Q Xin, H Fu, P Gong Scientific Data 8 (1), 283, 2021 | 30 | 2021 |
| Potential of multitemporal Gaofen-1 panchromatic/multispectral images for crop classification: case study in Xinjiang Uygur Autonomous Region, China P Hao, L Wang, Z Niu Journal of Applied Remote Sensing 9 (1), 096035-096035, 2015 | 29 | 2015 |
| Early-season crop mapping using improved artificial immune network (IAIN) and Sentinel data P Hao, H Tang, Z Chen, Z Liu PeerJ 6, e5431, 2018 | 28 | 2018 |
王力Li Wangthe Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS)Verified email at radi.ac.cn
