{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T13:01:47Z","timestamp":1773147707535,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2011,3,15]],"date-time":"2011-03-15T00:00:00Z","timestamp":1300147200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Hyperspectral image analysis is gaining momentum in a wealth of natural resources and agricultural applications facilitated by the increased availability of low-cost imaging systems. In this study, we demonstrate the development of the Vegetation Mobile Mapping System (VMMS), a low-cost hyperspectral sensing system that is supported by consumer-grade digital camera(s). The system was developed using off-the-shelf imaging and navigation components mainly for ground-based applications. The system integrates a variety of components including timing and positioning GPS receivers and an Inertial Measurement Unit (IMU). The system was designed to be modular and interoperable allowing the imaging components to be used with different navigation systems. The technique used for synchronizing captured images with GPS time was presented. A relative radiometric calibration technique utilizing images of homogeneous targets to normalize pixel gain and offset parameters was used. An empirical spectral calibration method was used to assign wavelengths to image bands. Data acquisition parameters to achieve appropriate spatial coverage were presented. The system was tested in ground-based data collection and analysis experiments that included water quality and vegetation studies.<\/jats:p>","DOI":"10.3390\/rs3030570","type":"journal-article","created":{"date-parts":[[2011,3,16]],"date-time":"2011-03-16T04:06:03Z","timestamp":1300248363000},"page":"570-586","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Design and Development of a Multi-Purpose Low-Cost Hyperspectral Imaging System"],"prefix":"10.3390","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6182-4017","authenticated-orcid":false,"given":"Amr","family":"Abd-Elrahman","sequence":"first","affiliation":[{"name":"School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA"},{"name":"Gulf Coast Research and Education Center, University of Florida, Wimauma, FL 33598, USA"}]},{"given":"Roshan","family":"Pande-Chhetri","sequence":"additional","affiliation":[{"name":"School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA"},{"name":"Gulf Coast Research and Education Center, University of Florida, Wimauma, FL 33598, USA"}]},{"given":"Gary","family":"Vallad","sequence":"additional","affiliation":[{"name":"Gulf Coast Research and Education Center, University of Florida, Wimauma, FL 33598, USA"}]}],"member":"1968","published-online":{"date-parts":[[2011,3,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1080\/01431160600746456","article-title":"A survey of image classification methods and techniques for improving classification performance","volume":"28","author":"Lu","year":"2007","journal-title":"Int. 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