Remote Sensing from Different Sources for Crop Growth Monitoring in the Area of the Lower Northern Mississippi

Yanbo Huang (), Gary Feng, Haile Tewolde and Mark W. Shankle
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Yanbo Huang: USDA-ARS Genetics and Sustainable Agriculture Research Unit, Mississippi State, MS 39762, USA
Gary Feng: USDA-ARS Genetics and Sustainable Agriculture Research Unit, Mississippi State, MS 39762, USA
Haile Tewolde: USDA-ARS Genetics and Sustainable Agriculture Research Unit, Mississippi State, MS 39762, USA
Mark W. Shankle: Pontotoc Ridge-Flatwoods Branch Experiment Station, Mississippi State University, Pontotoc, MS 38863, USA

Challenges, 2023, vol. 14, issue 1, 1-17

Abstract: Remote sensing monitoring of crop growth began from airborne photography to assist in crop pest management and has evolved into monitoring from satellites, manned aircraft, unmanned aerial vehicles (UAVs), and ground-based systems for crop production process modeling, optimization, and control. In recent years, for crop growth remote sensing monitoring, apart from satellites, manned aircrafts, and ground-based systems, UAVs have been developed and widely used for low-altitude remote sensing of crop fields to uniquely provide a cost-effective, flexible tool for field crop growth remote sensing. Additionally, their data create a critical layer between all other remote sensing platforms. This paper overviews the use of remote sensing from difference sources, especially airborne remote sensing from manned aircraft and UAVs, to monitor crop growth in the area of the lower northern Mississippi from the Mississippi Delta to the Black Prairie, one of the most important agricultural areas in the U.S. In this paper, three sites typical in the area are demonstrated for remote sensing monitoring of crop growth, and the issues and challenges are identified and discussed for future opportunities to integrate remote sensing data from different sources to improve crop monitoring in this area and surrounding areas.

Keywords: remote sensing; crop growth monitoring; crop production management; unmanned aerial vehicle (search for similar items in EconPapers)
JEL-codes: A00 C00 Z00 (search for similar items in EconPapers)
Date: 2023
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