Derivation of tasseled cap transformation coefficients for SDGSAT-1 Multispectral Imager at-sensor reflectance data

The tasseled cap transformation (TCT) is a widely used technique for reducing remote sensing multispectral data into three tasseled cap (TC) components – brightness, greenness, and wetness – while retaining essential information for various applications. We derived the TCT coefficients for 7-band SDGSAT-1 Multispectral Imager data for the first time by leveraging established Sentinel-2 TCT coefficients. This was achieved through Principal Component Analysis (PCA) for dimensional reduction of SDGSAT-1 data and the Procrustes Analysis (PA) method for aligning the principal components’ eigenvectors with the directions of Sentinel-2 TC components. A comparison between the new SDGSAT-1 coefficients and those of Sentinel-2 and Landsat-8 revealed a strong correlation, demonstrating similar characteristics for brightness, greenness, and wetness components. Given the established applications of TCT, the SDGSAT-1 TCT could significantly facilitate the use of SDGSAT-1 Multispectral Imager data for vegetation monitoring, water body analysis, and change detection. This study not only presents the derivation of SDGSAT-1 TCT coefficients but also highlights the effectiveness of the PA method in deriving TC wetness component coefficients that are sensitive to water bodies and vegetation, even for multispectral data lacking the moisture-sensitive shortwave-infrared (SWIR) band.

Authors

Institutions

Publication Details

Journal
International Journal of Digital Earth
Published
2024-10-16
DOI
https://doi.org/10.1080/17538947.2024.2413885
Citations
7
Primary Topic
Remote-Sensing Image Classification
Type
article
Field-Weighted Citation Impact
2.24

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Derivation of tasseled cap transformation coefficients for SDGSAT-1 Multispectral Imager at-sensor reflectance data

Changyong Dou, Charles Galdies, Yan Lin, Haifeng Ding et al.
7 citations
International Journal of Digital Earth
Remote-Sensing Image Classification
2.24
article

Derivation of tasseled cap transformation coefficients for SDGSAT-1 Multispectral Imager at-sensor reflectance data

Changyong Dou, Charles Galdies, Yan Lin, Haifeng Ding, Nijun Jiang, Yunwei Tang
article en
7 citations

Abstract

The tasseled cap transformation (TCT) is a widely used technique for reducing remote sensing multispectral data into three tasseled cap (TC) components – brightness, greenness, and wetness – while retaining essential information for various applications. We derived the TCT coefficients for 7-band SDGSAT-1 Multispectral Imager data for the first time by leveraging established Sentinel-2 TCT coefficients. This was achieved through Principal Component Analysis (PCA) for dimensional reduction of SDGSAT-1 data and the Procrustes Analysis (PA) method for aligning the principal components’ eigenvectors with the directions of Sentinel-2 TC components. A comparison between the new SDGSAT-1 coefficients and those of Sentinel-2 and Landsat-8 revealed a strong correlation, demonstrating similar characteristics for brightness, greenness, and wetness components. Given the established applications of TCT, the SDGSAT-1 TCT could significantly facilitate the use of SDGSAT-1 Multispectral Imager data for vegetation monitoring, water body analysis, and change detection. This study not only presents the derivation of SDGSAT-1 TCT coefficients but also highlights the effectiveness of the PA method in deriving TC wetness component coefficients that are sensitive to water bodies and vegetation, even for multispectral data lacking the moisture-sensitive shortwave-infrared (SWIR) band.

International Journal of Digital EarthVol. 17(1)
University of Malta (MT), Chinese Academy of Sciences (CN), Beijing Institute of Big Data Research (CN), Aerospace Information Research Institute (CN)
National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 10%
Remote-Sensing Image Classification
2.24
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Derivation of tasseled cap transformation coefficients for SDGSAT-1 Multispectral Imager at-sensor reflectance data — Changyong Dou, Charles Galdies, et al. · International Journal of Digital Earth (2024) | TGRS Research Map | TGRS