Generating daily land surface temperature at Landsat resolution by fusing Landsat and MODIS data Q Weng, P Fu, F Gao Remote Sensing of Environment 145, 55-67, 2014 | 537 | 2014 |
A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery P Fu, Q Weng Remote Sensing of Environment 175, 205-214, 2016 | 491 | 2016 |
Deep learning-based fusion of Landsat-8 and Sentinel-2 images for a harmonized surface reflectance product Z Shao, J Cai, P Fu, L Hu, T Liu Remote Sensing of Environment 235, 111425, 2019 | 207 | 2019 |
Modeling annual parameters of clear-sky land surface temperature variations and evaluating the impact of cloud cover using time series of Landsat TIR data Q Weng, P Fu Remote Sensing of Environment 140, 267-278, 2014 | 159 | 2014 |
High-throughput field phenotyping using hyperspectral reflectance and partial least squares regression (PLSR) reveals genetic modifications to photosynthetic capacity K Meacham-Hensold, CM Montes, J Wu, K Guan, P Fu, EA Ainsworth, ... Remote sensing of environment 231, 111176, 2019 | 149 | 2019 |
A survey and analysis on automatic image annotation Q Cheng, Q Zhang, P Fu, C Tu, S Li Pattern Recognition 79, 242-259, 2018 | 143 | 2018 |
Assessing the Impacts of Urbanization-Associated Land Use/Cover Change on Land Surface Temperature and Surface Moisture: A Case Study in the Midwestern United States Y Jiang, P Fu, Q Weng Remote Sensing 7 (4), 4880-4898, 2015 | 129 | 2015 |
Hyperspectral leaf reflectance as proxy for photosynthetic capacities: an ensemble approach based on multiple machine learning algorithms P Fu, K Meacham-Hensold, K Guan, CJ Bernacchi Frontiers in Plant Science 10, 730, 2019 | 111 | 2019 |
Mapping Urban Impervious Surface by Fusing Optical and SAR Data at the Decision Level Z Shao, H Fu, P Fu, L Yin Remote Sensing 8 (11), 945, 2016 | 103 | 2016 |
Modeling diurnal land temperature cycles over Los Angeles using downscaled GOES imagery Q Weng, P Fu ISPRS Journal of Photogrammetry and Remote Sensing 97, 78-88, 2014 | 96 | 2014 |
Variability in annual temperature cycle in the urban areas of the United States as revealed by MODIS imagery P Fu, Q Weng ISPRS Journal of Photogrammetry and Remote Sensing 146, 65-73, 2018 | 90 | 2018 |
Mapping soil organic carbon stock by hyperspectral and time-series multispectral remote sensing images in low-relief agricultural areas L Guo, X Sun, P Fu, T Shi, L Dang, Y Chen, M Linderman, G Zhang, ... Geoderma 398, 115118, 2021 | 85 | 2021 |
Temporal variations of artificial nighttime lights and their implications for urbanization in the conterminous United States, 2013–2017 Y Xie, Q Weng, P Fu Remote Sensing of Environment 225, 160-174, 2019 | 84 | 2019 |
A Deep Semantic Alignment Network for the Cross-Modal Image-Text Retrieval in Remote Sensing Q Cheng, Y Zhou, P Fu, Y Xu, L Zhang IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2021 | 83 | 2021 |
Consistent land surface temperature data generation from irregularly spaced Landsat imagery P Fu, Q Weng Remote Sensing of Environment 184, 175-187, 2016 | 82 | 2016 |
Responses of urban heat island in Atlanta to different land-use scenarios P Fu, Q Weng Theoretical and Applied Climatology, 1-13, 2017 | 81 | 2017 |
Mapping field-scale soil organic carbon with unmanned aircraft system-acquired time series multispectral images L Guo, P Fu, T Shi, Y Chen, H Zhang, R Meng, S Wang Soil and Tillage Research 196, 104477, 2020 | 68 | 2020 |
The Dynamic Analysis between Urban Nighttime Economy and Urbanization Using the DMSP/OLS Nighttime Light Data in China from 1992 to 2012 H Fu, Z Shao, P Fu, Q Cheng Remote Sensing 9 (5), 416, 2017 | 68 | 2017 |
A physical model-based method for retrieving urban land surface temperatures under cloudy conditions P Fu, Y Xie, Q Weng, S Myint, K Meacham-Hensold, C Bernacchi Remote Sensing of Environment 230, 111191, 2019 | 66 | 2019 |
Estimating photosynthetic traits from reflectance spectra: A synthesis of spectral indices, numerical inversion, and partial least square regression P Fu, K Meacham‐Hensold, K Guan, J Wu, C Bernacchi Plant, Cell & Environment 43 (5), 1241-1258, 2020 | 64 | 2020 |