Getting simultaneous red and near-infrared band data from a single digital camera for plant monitoring applications: theoretical and practical study
TLDR
In this paper, a methodology is proposed to obtain simultaneously the near-infrared and red bands from a standard single RGB camera, after having removed the nearinfrared blocking filter inside.About:
This article is published in Biosystems Engineering.The article was published on 2014-01-01 and is currently open access. It has received 37 citations till now. The article focuses on the topics: Digital camera & Multispectral image.read more
Citations
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Journal ArticleDOI
Overview and Current Status of Remote Sensing Applications Based on Unmanned Aerial Vehicles (UAVs)
TL;DR: An overview of different areas of remote sensing applications based on unmanned aerial platforms equipped with a set of specific sensors and instruments is presented, each independent from the others so that the reader does not need to read the full paper when a specific application is of interest.
Journal ArticleDOI
Autonomous systems for precise spraying – Evaluation of a robotised patch sprayer
Mariano Gonzalez-de-Soto,Mariano Gonzalez-de-Soto,Luis Emmi,Manuel Pérez-Ruiz,Juan Agüera,Pablo Gonzalez-de-Santos +5 more
TL;DR: In this article, the authors describe the development and assessment of a robotised patch spraty -20ying system that was devised for site-specific herbicide application in agricultural crops and is capable of working in groups or fleets of autonomous robots.
Journal ArticleDOI
Commercial Off-the-Shelf Digital Cameras on Unmanned Aerial Vehicles for Multitemporal Monitoring of Vegetation Reflectance and NDVI
TL;DR: The results confirm that COTS cameras, following calibration, can yield accurate reflectance estimates (under stable within-flight illumination conditions), and that consistent NDVI time series can be acquired in very variable illumination conditions.
Journal ArticleDOI
An Airborne Multispectral Imaging System Based on Two Consumer-Grade Cameras for Agricultural Remote Sensing
Chenghai Yang,John K. Westbrook,Charles P.-C. Suh,Daniel E. Martin,W. Clint Hoffmann,Yubin Lan,Bradley K. Fritz,John A. Goolsby +7 more
TL;DR: Preliminary analysis of example images has shown that this system has potential for crop condition assessment, pest detection, and other agricultural applications.
Proceedings ArticleDOI
Low-cost multispectral imaging system for crop monitoring
TL;DR: This work presents the design and development of a multispectral imaging system to precision agriculture tasks and the vegetation index will be computed from the visible and near-infrared orthomosaics for a better interpretation of the user.
References
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Journal ArticleDOI
Red and photographic infrared linear combinations for monitoring vegetation
TL;DR: In this article, the relationship between various linear combinations of red and photographic infrared radiances and vegetation parameters is investigated, showing that red-IR combinations to be more significant than green-red combinations.
Monitoring Vegetation Systems in the Great Plains with Erts
TL;DR: In this paper, a method has been developed for quantitative measurement of vegetation conditions over broad regions using ERTS-1 spectral bands 5 and 7, corrected for sun angle, which is shown to be correlated with aboveground green biomass on rangelands.
Patent
Color imaging array
TL;DR: In this article, a mosaic of selectively transmissive filters is superposed in registration with a solid state imaging array having a broad range of light sensitivity, the distribution of filter types in the mosaic being in accordance with the above-described patterns.
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A comparison of vegetation indices over a global set of TM images for EOS-MODIS
TL;DR: In this paper, a set of Landsat Thematic Mapper images representing a wide range of vegetation conditions from the NASA Landsat Pathfinder, global land cover test site (GLCTS) initiative were processed to simulate the Moderate Resolution Imaging Spectroradiometer (MODIS), global vegetation index imagery at 250 m pixel size resolution.