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Comparative analysis of remote sensing platforms for assessing maize crop biophysical characteristics and evapotranspiration estimation

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dc.contributor.authorAl-Majali, Zaid, author
dc.contributor.authorChávez, José L., advisor
dc.contributor.authorDavenport, Frances, committee member
dc.contributor.authorO'Connel, Jessica, committee member
dc.date.accessioned2024-09-09T20:51:19Z
dc.date.available2024-09-09T20:51:19Z
dc.date.issued2024
dc.description.abstractThe rapid growth in population, climate variability, and decreasing water resources necessitate innovative agricultural practices to ensure food security and resource conservation. This study investigates the effectiveness of various multispectral imagery from remote sensing (RS) platforms (such as Unmanned Aircraft Systems (UAS), PlanetDove microsatellites, Sentinel-2, Landsat 8/9, and proximal MSR-5) in the appropriate estimation of crop biophysical characteristics (CBPCs) and actual crop evapotranspiration (ETa) for maize fields in northeastern Colorado. The research aimed at evaluating the accuracy of vegetation indices (VIs) derived from different sources of RS data in estimating key CBPCs, including leaf area index (LAI), crop height (Hc), and fractional cover (Fc), as well as the ETa. Field experiments were conducted at the USDA-ARS Limited Irrigation Research Farm in Greeley, Colorado, in 2022. Different irrigation strategies were used to assess the maize's water use response. Surface reflectance data was collected using the MSR sensor, and observed LAI, Hc, and Fc values served as ground truth for validating remote sensing estimates. The study applied various statistical analyses to compare the performance of different remote sensing platforms and models. Results indicate that higher-resolution platforms, particularly UAS, provided higher accuracy in estimating VIs and CBPCs than other satellite platforms. The study also highlights the influence of environmental conditions on the accuracy of remote sensing models, with locally calibrated models outperforming those developed in dissimilar conditions. The findings underscore the potential of advanced remote sensing technologies in enhancing precision agriculture practices and optimizing water resource management.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.identifierAlMajali_colostate_0053N_18585.pdf
dc.identifier.urihttps://hdl.handle.net/10217/239191
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2020-
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.titleComparative analysis of remote sensing platforms for assessing maize crop biophysical characteristics and evapotranspiration estimation
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineCivil and Environmental Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)

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