Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Comparative Evaluation of Operational Land Imager sensor on board Landsat 8 and Landsat 9 for Land use Land Cover Mapping over a Heterogeneous Landscape

Shahfahad, S, Naikoo, MW, Rahman, A, Gagnon, A, Islam, ARMT, Mosavi, A and Talukdar, S (2023) Comparative Evaluation of Operational Land Imager sensor on board Landsat 8 and Landsat 9 for Land use Land Cover Mapping over a Heterogeneous Landscape. Geocarto International (TGEI), 38 (1). ISSN 1010-6049

[img]
Preview
Text
Comparative evaluation of operational land imager sensor on board landsat 8 and landsat 9 for land use land cover mapping over a heterogeneous (1).pdf - Published Version
Available under License Creative Commons Attribution.

Download (9MB) | Preview
Open Access URL: https://doi.org/10.1080/10106049.2022.2152496 (published)

Abstract

Since its advent in 1972, the Landsat satellites have witnessed consistent improvements in sensor characteristics, which have significantly improved accuracy. In this study, a comparison of the accuracy of Landsat OLI and OLI-2 satellites in land use land cover (LULC) mapping has been made. For this, image fusion techniques have been applied to enhance the spatial resolution of both OLI and OLI-2 multispectral images, and then a support vector machine (SVM) classifier has been used for LULC mapping. The results show that LULC classification from OLI-2 has better accuracy (83.4%) than OLI (92.4%). The validation of classified LULC maps shows that the OLI-2 data is more accurate in distinguishing dense and sparse vegetation as well as darker and lighter objects. The relationship between LULC maps and surface biophysical parameters using Local Moran’s I also shows better performance of the OLI-2 sensor in LULC mapping than the OLI sensor.

Item Type: Article
Uncontrolled Keywords: Landsat datasets; Land use land cover; Surface biophysical parameters; Moran's I; Support vector machine; 0909 Geomatic Engineering; Geological & Geomatics Engineering
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Divisions: Biological & Environmental Sciences (from Sep 19)
Publisher: Taylor & Francis
SWORD Depositor: A Symplectic
Date Deposited: 30 Nov 2022 11:23
Last Modified: 23 May 2023 09:45
DOI or ID number: 10.1080/10106049.2022.2152496
URI: https://researchonline.ljmu.ac.uk/id/eprint/18227
View Item View Item