Relative Radiometric Normalization of Landsat Multispectral Scanner (MSS) Data Using an Automatic Scattergram—Controlled Regression

Space Informatics for Sustainable Development 2026 Book chapter

View at publisher
Authors: Christopher D. Elvidge, Ding Yuan, R. D. Weerackoon, Ross S. Lunetta
DOI: 10.1201/9781003761556-2
Cited by: 169

Abstract

The scientific requirement for increased understanding of human impacts on terrestrial carbon stocks and biodiversity has created renewed interest in the use of Landsat Multispectral Scanner (MSS) data for the analysis of land-cover change. A series of five Landsat MSS sensors were used to acquire earth observations over a 21 year period (1972–1992), forming the longest available set of repetitive satellite observations of the earth’s surface.

Fields of Study & Subjects

Remote-Sensing Image Classification Remote Sensing in Agriculture Soil Geostatistics and Mapping

Publication details

Journal / source
Space Informatics for Sustainable Development
Publisher
CRC Press
Volume
61
Issue
10
Pages
11–21
Publication date
23 January 2026
Language
EN
Document type
Book chapter