Sensor-based measurements of NDVI in small grain and corn fields by tractor, drone, and satellite platforms

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Author(s)Miller, Jarrod O.
Author(s)Mondal, Pinki
Author(s)Sarupria, Manan
Date Accessioned2024-04-25T16:54:23Z
Date Available2024-04-25T16:54:23Z
Publication Date2024-02-01
DescriptionThis article was originally published in Crop and Environment. The version of record is available at: https://doi.org/10.1016/j.crope.2023.11.001. © 2023 The Author(s). Published by Elsevier Ltd on behalf of Huazhong Agricultural University.
AbstractThe use of sensors for variable rate nitrogen (VRN) applications is transitioning from equipment-based to drone and satellite technologies. However, regional algorithms, initially designed for proximal active sensors, require evaluation for compatibility with remotely sensed reflectance and N-rate predictions. This study observed normalized difference vegetation index (NDVI) data from six small grain and two corn fields over three years. We employed three platforms: tractor-mounted active sensors (T-NDVI), passive multispectral drone (D-NDVI), and satellite (S-NDVI) sensors. Averaged NDVI values were extracted from the as-applied equipment polygons. Correlations between NDVI values from the three platforms were positive and strong, with D-NDVI consistently recording the highest values, particularly in areas with lower plant biomass. This was attributed to D-NDVI's lower soil reflectance and its ability to measure the entire biomass within equipment polygons. For small grains, sensors spaced on equipment booms might not capture accurate biomass in poor-growing and low NDVI regions. Regarding VRN, S-NDVI and D-NDVI occasionally aligned with T-NDVI recommendations but often suggested half the active sensor rate. Final yields showed some correlation with landscape variables, irrespective of N application. This finding suggests the potential use of drone or satellite imagery to provide multiple NDVI maps before application, incorporating expected landscape responses and thereby enhancing VRN effectiveness.
SponsorWe would like to acknowledge our Maryland farmer cooperators and Shawn Tingle for his assistance in the field. We acknowledge the support provided by the Harry R. Hughes Center for Agro-Ecology. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
CitationMiller, Jarrod O., Pinki Mondal, and Manan Sarupria. “Sensor-Based Measurements of NDVI in Small Grain and Corn Fields by Tractor, Drone, and Satellite Platforms.” Crop and Environment 3, no. 1 (March 2024): 33–42. https://doi.org/10.1016/j.crope.2023.11.001.
ISSN2773-126X
URLhttps://udspace.udel.edu/handle/19716/34308
Languageen_US
PublisherCrop and Environment
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
Keywordscorn
Keywordsdrone
KeywordsNDVI
Keywordsnitrogen
Keywordssatellite
Keywordssmall grains
TitleSensor-based measurements of NDVI in small grain and corn fields by tractor, drone, and satellite platforms
TypeArticle
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