Application of Drone and WorldView-4 Satellite Data in Mapping and Monitoring Grazing Land Cover and Pasture Quality: Pre- and Post-Flooding

Clement E. Akumu, Eze O. Amadi and Samuel Dennis
Additional contact information
Clement E. Akumu: Department of Agricultural and Environmental Sciences, College of Agriculture, Tennessee State University, Nashville, TN 37209, USA
Eze O. Amadi: Department of Agricultural and Environmental Sciences, College of Agriculture, Tennessee State University, Nashville, TN 37209, USA
Samuel Dennis: Department of Agricultural and Environmental Sciences, College of Agriculture, Tennessee State University, Nashville, TN 37209, USA

Land, 2021, vol. 10, issue 3, 1-13

Abstract: Frequent flooding worldwide, especially in grazing environments, requires mapping and monitoring grazing land cover and pasture quality to support land management. Although drones, satellite, and machine learning technologies can be used to map land cover and pasture quality, there have been limited applications in grazing land environments, especially monitoring land cover change and pasture quality pre- and post-flood events. The use of high spatial resolution drone and satellite data such as WorldView-4 can provide effective mapping and monitoring in grazing land environments. The aim of this study was to utilize high spatial resolution drone and WorldView-4 satellite data to map and monitor grazing land cover change and pasture quality pre-and post-flooding. The grazing land cover was mapped pre-flooding using WorldView-4 satellite data and post-flooding using real-time drone data. The machine learning Random Forest classification algorithm was used to delineate land cover types and the normalized difference vegetation index (NDVI) was used to monitor pasture quality. This study found a seven percent (7%) increase in pasture cover and a one hundred percent (100%) increase in pasture quality post-flooding. The drone and WorldView-4 satellite data were useful to detect grazing land cover change at a finer scale.

Keywords: drone and satellite data; mapping grazing land cover change; flood event (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2073-445X/10/3/321/pdf (application/pdf)
https://www.mdpi.com/2073-445X/10/3/321/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:10:y:2021:i:3:p:321-:d:520971

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().