{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T09:38:11Z","timestamp":1776505091016,"version":"3.51.2"},"reference-count":299,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,6]],"date-time":"2023-01-06T00:00:00Z","timestamp":1672963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003664","name":"Korea Forest Service","doi-asserted-by":"publisher","award":["2020184D10-2222-AA02"],"award-info":[{"award-number":["2020184D10-2222-AA02"]}],"id":[{"id":"10.13039\/501100003664","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The key elements that underpin food security require the adaptation of agricultural systems to support productivity increases while minimizing inputs and the adverse effects of climate change. The advances in precision agriculture over the past few years have substantially enhanced the efficiency of applying spatially variable agronomic inputs for irrigation, such as fertilizers, pesticides, seeds, and water, and we can attribute them to the increasing number of innovations that utilize new technologies that are capable of monitoring field crops for varying spatial and temporal changes. Remote sensing technology is the primary driver of success in precision agriculture, along with other technologies, such as the Internet of Things (IoT), robotic systems, weather forecasting technology, and global positioning systems (GPSs). More specifically, multispectral imaging (MSI) and hyperspectral imaging (HSI) have made the monitoring of the field crop health to aid decision making and the application of spatially and temporally variable agronomic inputs possible. Furthermore, the fusion of remotely sensed multisource data\u2014for instance, HSI and LiDAR (light detection and ranging) data fusion\u2014has even made it possible to monitor the changes in different parts of an individual plant. To the best of our knowledge, in most reviews on this topic, the authors focus on specific methods and\/or technologies, with few or no comprehensive reviews that expose researchers, and especially students, to the vast possible range of remote sensing technologies used in agriculture. In this article, we describe\/evaluate the remote sensing (RS) technologies for field crop monitoring using spectral imaging, and we provide a thorough and discipline-specific starting point for researchers of different levels by supplying sufficient details and references. We also high light strengths and drawbacks of each technology, which will help readers select the most appropriate method for their intended uses.<\/jats:p>","DOI":"10.3390\/rs15020354","type":"journal-article","created":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T04:47:08Z","timestamp":1673239628000},"page":"354","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":228,"title":["Remote Sensing in Field Crop Monitoring: A Comprehensive Review of Sensor Systems, Data Analyses and Recent Advances"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8105-3304","authenticated-orcid":false,"given":"Emmanuel","family":"Omia","sequence":"first","affiliation":[{"name":"Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea"}]},{"given":"Hyungjin","family":"Bae","sequence":"additional","affiliation":[{"name":"Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea"}]},{"given":"Eunsung","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Smart Agricultural Systems, Chungnam National University, Daejeon 34134, Republic of Korea"}]},{"given":"Moon Sung","family":"Kim","sequence":"additional","affiliation":[{"name":"Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, Powder Mill Road, BARC-East, Bldg 303, Beltsville, MD 20705, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1044-349X","authenticated-orcid":false,"given":"Insuck","family":"Baek","sequence":"additional","affiliation":[{"name":"Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, Powder Mill Road, BARC-East, Bldg 303, Beltsville, MD 20705, USA"}]},{"given":"Isa","family":"Kabenge","sequence":"additional","affiliation":[{"name":"Department of Agricultural and Biosystems Engineering, Makerere University, Kampala P.O. Box 7062, Uganda"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8397-9853","authenticated-orcid":false,"given":"Byoung-Kwan","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea"},{"name":"Department of Smart Agricultural Systems, Chungnam National University, Daejeon 34134, Republic of Korea"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,6]]},"reference":[{"key":"ref_1","unstructured":"FAO (2017). 2017 The State of Food and Agrivulture Leveraging Food Systems for Inclusive Rural Transformation, Food & Agriculture Organization."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Sishodia, R.P., Ray, R.L., and Singh, S.K. (2020). Applications of Remote Sensing in Precision Agriculture: A Review. Remote Sens., 12.","DOI":"10.3390\/rs12193136"},{"key":"ref_3","unstructured":"Morison, J.I.L., and Matthews, R.B. (2016). 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