A Novel Illumination Compensation Technique for Multi-Spectral Imaging in NDVI Detection
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Yubin Lan | Rui Jiang | Yan Xu | Pei Wang | Zhiyan Zhou | Xiwen Luo | Yan Xu | Y. Lan | Zhiyan Zhou | Xiwen Luo | Rui Jiang | Pei Wang
[1] Ali Mohamed Ali,et al. Using GreenSeeker active optical sensor for optimizing maize nitrogen fertilization in calcareous soils of Egypt , 2018 .
[2] O. Sonnentag,et al. NDVI derived from near-infrared-enabled digital cameras: Applicability across different plant functional types , 2018 .
[3] Shanyu Huang,et al. Active canopy sensor-based precision N management strategy for rice , 2012, Agronomy for Sustainable Development.
[4] Yanbo Huang,et al. Agricultural remote sensing big data: Management and applications , 2018, Journal of Integrative Agriculture.
[5] Mingquan Wu,et al. Please Scroll down for Article International Journal of Remote Sensing Nondestructive Estimation of Canopy Chlorophyll Content Using Hyperion and Landsat/tm Images Nondestructive Estimation of Canopy Chlorophyll Content Using Hyperion and Landsat/tm Images , 2022 .
[6] Bin Liu,et al. Active canopy sensing of winter wheat nitrogen status: An evaluation of two sensor systems , 2015, Comput. Electron. Agric..
[7] B. Mistele,et al. Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivars , 2011 .
[8] Dan S. Long,et al. Active Ground Optical Remote Sensing for Improved Monitoring of Seedling Stress in Nurseries , 2010, Sensors.
[9] Martha C. Anderson,et al. Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at the field scale , 2009 .
[10] Reza Ehsani,et al. Evaluation of an active optical sensor for detection of Huanglongbing (HLB) disease , 2011 .
[11] Marco Dubbini,et al. Evaluating Multispectral Images and Vegetation Indices for Precision Farming Applications from UAV Images , 2015, Remote. Sens..
[12] Fabio Henrique Rojo Baio,et al. USING PASSIVE AND ACTIVE MULTISPECTRAL SENSORS ON THE CORRELATION WITH THE PHENOLOGICAL INDICES OF COTTON , 2017 .
[13] Gero Barmeier,et al. High-Throughput Phenotyping of Wheat and Barley Plants Grown in Single or Few Rows in Small Plots Using Active and Passive Spectral Proximal Sensing , 2016, Sensors.
[14] Y. Lan,et al. Detection of rice sheath blight using an unmanned aerial system with high-resolution color and multispectral imaging , 2018, PloS one.
[15] Ning Zhang,et al. Prediction for Soybean Grain Yield Using Active Sensor GreenSeeker , 2014 .
[16] Reza Ehsani,et al. Review: A review of advanced techniques for detecting plant diseases , 2010 .
[17] Sebastian Kipp,et al. The performance of active spectral reflectance sensors as influenced by measuring distance, device temperature and light intensity , 2014 .
[18] John E. Sawyer,et al. Using Active Canopy Sensors to Quantify Corn Nitrogen Stress and Nitrogen Application Rate , 2010 .
[19] Yadvinder-Singh,et al. Site-specific fertilizer nitrogen management in irrigated transplanted rice (Oryza sativa) using an optical sensor , 2015, Precision Agriculture.
[20] Gong Wei,et al. Multi-wavelength canopy LiDAR for remote sensing of vegetation: Design and system performance , 2012 .
[21] A. Gitelson,et al. Active Sensor Reflectance Measurements of Corn Nitrogen Status and Yield Potential , 2008 .
[22] Yubin Lan,et al. Integrated sensor system for monitoring rice growth conditions based on unmanned ground vehicle system. , 2014 .
[23] S. Cao,et al. Radiometric calibration assessments for UAS-borne multispectral cameras: Laboratory and field protocols , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.
[24] Bodo Mistele,et al. Evaluation of active and passive sensor systems in the field to phenotype maize hybrids with high-throughput , 2013 .