| Monitoring plant diseases and pests through remote sensing technology: A review J Zhang, Y Huang, R Pu, P Gonzalez-Moreno, L Yuan, K Wu, W Huang Computers and Electronics in Agriculture 165, 104943, 2019 | 552 | 2019 |
| New optimized spectral indices for identifying and monitoring winter wheat diseases W Huang, Q Guan, J Luo, J Zhang, J Zhao, D Liang, L Huang, D Zhang IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2014 | 261 | 2014 |
| Detecting powdery mildew of winter wheat using leaf level hyperspectral measurements JC Zhang, R Pu, J Wang, W Huang, L Yuan, J Luo Computers and Electronics in Agriculture 85, 13-23, 2012 | 211 | 2012 |
| Spectral analysis of winter wheat leaves for detection and differentiation of diseases and insects L Yuan, Y Huang, RW Loraamm, C Nie, J Wang, J Zhang Field Crops Research 156, 199-207, 2014 | 175 | 2014 |
| Using in-situ hyperspectral data for detecting and discriminating yellow rust disease from nutrient stresses J Zhang, R Pu, W Huang, L Yuan, J Luo, J Wang Field Crops Research 134, 165-174, 2012 | 158 | 2012 |
| Comparison between wavelet spectral features and conventional spectral features in detecting yellow rust for winter wheat J Zhang, R Pu, RW Loraamm, G Yang, J Wang Computers and Electronics in Agriculture 100, 79-87, 2014 | 116 | 2014 |
| Using high spatial resolution satellite imagery for mapping powdery mildew at a regional scale L Yuan, R Pu, J Zhang, J Wang, H Yang Precision Agriculture 17, 332-348, 2016 | 100 | 2016 |
| Leaf area index estimation using vegetation indices derived from airborne hyperspectral images in winter wheat Q Xie, W Huang, D Liang, P Chen, C Wu, G Yang, J Zhang, L Huang, ... IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2014 | 90 | 2014 |
| Detection of anthracnose in tea plants based on hyperspectral imaging L Yuan, P Yan, W Han, Y Huang, B Wang, J Zhang, H Zhang, Z Bao Computers and electronics in agriculture 167, 105039, 2019 | 84 | 2019 |
| Research progress of crop diseases and pests monitoring based on remote sensing J Zhang, L Yuan, J Wang, J Luo, S Du, W Huang Transactions of the Chinese society of agricultural engineering 28 (20), 1-11, 2012 | 80 | 2012 |
| Detection and discrimination of disease and insect stress of tea plants using hyperspectral imaging combined with wavelet analysis X Zhao, J Zhang, Y Huang, Y Tian, L Yuan Computers and electronics in agriculture 193, 106717, 2022 | 74 | 2022 |
| Damage mapping of powdery mildew in winter wheat with high-resolution satellite image L Yuan, J Zhang, Y Shi, C Nie, L Wei, J Wang Remote sensing 6 (5), 3611-3623, 2014 | 73 | 2014 |
| A novel combined spectral index for estimating the ratio of carotenoid to chlorophyll content to monitor crop physiological and phenological status X Zhou, W Huang, J Zhang, W Kong, R Casa, Y Huang International Journal of Applied Earth Observation and Geoinformation 76 …, 2019 | 71 | 2019 |
| Integrating remotely sensed and meteorological observations to forecast wheat powdery mildew at a regional scale J Zhang, R Pu, L Yuan, W Huang, C Nie, G Yang IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2014 | 71 | 2014 |
| Monitoring powdery mildew of winter wheat by using moderate resolution multi-temporal satellite imagery J Zhang, R Pu, L Yuan, J Wang, W Huang, G Yang PloS one 9 (4), e93107, 2014 | 70 | 2014 |
| Detecting aphid density of winter wheat leaf using hyperspectral measurements J Luo, W Huang, J Zhao, J Zhang, C Zhao, R Ma IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2013 | 63 | 2013 |
| Using satellite multispectral imagery for damage mapping of armyworm (Spodoptera frugiperda) in maize at a regional scale J Zhang, Y Huang, L Yuan, G Yang, L Chen, C Zhao Pest Management Science 72 (2), 335-348, 2016 | 61 | 2016 |
| Assessing crop damage from dicamba on non‐dicamba‐tolerant soybean by hyperspectral imaging through machine learning J Zhang, Y Huang, KN Reddy, B Wang Pest management science 75 (12), 3260-3272, 2019 | 51 | 2019 |
| Discrimination of winter wheat disease and insect stresses using continuous wavelet features extracted from foliar spectral measurements J Zhang, N Wang, L Yuan, F Chen, K Wu Biosystems Engineering 162, 20-29, 2017 | 49 | 2017 |
| Assessment of leaf chlorophyll content models for winter wheat using Landsat-8 multispectral remote sensing data X Zhou, J Zhang, D Chen, Y Huang, W Kong, L Yuan, H Ye, W Huang Remote Sensing 12 (16), 2574, 2020 | 47 | 2020 |