Advances in Remote Sensing

Advances in Remote Sensing

ISSN Print: 2169-267X
ISSN Online: 2169-2688
www.scirp.org/journal/ars
E-mail: ars@scirp.org
"Assessment of UAV Based Vegetation Indices for Nitrogen Concentration Estimation in Spring Wheat"
written by Olga S. Walsh, Sanaz Shafian, Juliet M. Marshall, Chad Jackson, Jordan R. McClintick-Chess, Steven M. Blanscet, Kristin Swoboda, Craig Thompson, Kelli M. Belmont, Willow L. Walsh,
published by Advances in Remote Sensing, Vol.7 No.2, 2018
has been cited by the following article(s):
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[14] Drought Damage Assessment for Crop Insurance Based on Vegetation Index by Unmanned Aerial Vehicle (UAV) Multispectral Images of Paddy Fields in Indonesia
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[15] Diagnosis of Nitrogen Content in the Leaves of Apple Tree Using Spectral Imagery
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[17] A kite balloon system for the monitoring of gatherings in open areas
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[18] Drone-Based Vegetation Index Analysis to Estimated Nitrogen Content on The Rice Plantations
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[23] The feasibility of using a low-cost near-infrared, sensitive, consumer-grade digital camera mounted on a commercial UAV to assess Bambara groundnut yield
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[24] Comparative Sensitivity of Vegetation Indices Measured via Proximal and Aerial Sensors for Assessing N Status and Predicting Grain Yield in Rice Cropping Systems
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[25] Wheat yield and protein estimation with handheld‐and UAV‐based reflectance measurements
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[26] 분광 영상을 이용한 사과나무 잎의 질소 영양 상태 진단
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[27] Analisis Indeks Vegetasi Berbasis Drone untuk Menduga Kandungan Nitrogen pada Pertanaman Padi (Drone-Based Vegetation Index Analysis to Estimated …
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[28] Drought damage assessment for crop insurance based on vegetation index by unmanned aerial vehicle (UAV) multispectral images of paddy fields in …
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[29] Review on unmanned aerial vehicles, remote sensors, imagery processing, and their applications in agriculture
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[30] Aerial Robotics in Agriculture: Parafoils, Blimps, Aerostats, and Kites
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[31] Optimizing Top Dressing Nitrogen Fertilization Using VENμS and Sentinel-2 L1 Data
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[35] Non-destructive method of Biomass and Nitrogen (N) level estimation in Stevia rebaudiana using various multispectral indices
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[36] Potato Crop Stress Identification in Aerial Images using Deep Learning-based Object Detection
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[37] Random forest regression results in accurate assessment of potato nitrogen status based on multispectral data from different platforms and the critical concentration …
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[38] The Application of an Unmanned Aerial System and Machine Learning Techniques for Red Clover-Grass Mixture Yield Esti-mation Under Variety Performance Trials
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[39] Development and Evaluation of Unmanned Aerial Vehicles for High Throughput Phenotyping of Field-based Wheat Trials
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[40] Determination of nitrogen and chlorophyll content in two varieties of winter wheat plants means of ground and airborne spectrometry
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[41] Estimation of Leaf Nitrogen Content of Wheat Based on UAV Image at Filling Stage
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[42] Analysis of remote sensing based vegetation indices (VIs) for unmanned aerial system (UAS)
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[43] Estimation of Winter Wheat Nitrogen Content, Biomass and Yield using UAV Images in South Korea
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[44] Intra-Field Canopy Nitrogen Retrieval from Unmanned Aerial Vehicle Imagery for Wheat and Corn Fields
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[45] An Approach for Route Optimization in Applications of Precision Agriculture Using UAVs
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[46] 基于无人机图像的小麦灌浆期叶片氮含量估算
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[47] Development and Evaluation of Unmanned Aerial Vehicles for High Throughput Phenotyping of Field-based Wheat Trials.
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[48] Analysis of Remote Sensing based Vegetation Indices (VIs) for Unmanned Aerial System (UAS): A Review
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[49] Management and characterization of abiotic stress via PhénoField®, a high-throughput field phenotyping platform
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[50] Management and characterization of abiotic stress via PhénoField®, a high-throughput field phenotyping platform.
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[51] UAVs technology for the development of GUI based application for precision agriculture and environmental research
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[52] Evaluación del aprovechamiento de la fertilización nitrogenada en la caña de azúcar mediante la fotogrametría multiespectral
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[53] Análisis de imágenes multiespectrales de sembrados de caña de azúcar adquiridas con vehículos aéreos no tripulados
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[54] Crop and Environment
[55] Automating the Quantification of Coastal Change Using Historical Aerial Images: A Case Study Along Cork Coastline, Ireland
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