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

Nijun Jiang,

Changyong Dou,

Yunwei Tang

et al.

International Journal of Digital Earth, Journal Year: 2024, Volume and Issue: 17(1)

Published: Oct. 16, 2024

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

Language: Английский

Assessing on-orbit radiometric performance of SDGSAT-1 MII for turbid water remote sensing DOI
Wenkai Li, Shilin Tang, Liqiao Tian

et al.

Remote Sensing of Environment, Journal Year: 2025, Volume and Issue: 321, P. 114683 - 114683

Published: Feb. 27, 2025

Language: Английский

Citations

0
Comparative assessment of machine learning algorithms for retrieving colored dissolved organic matter (CDOM) from Sentinel-2/MSI images in the coastal waters of the Persian Gulf DOI Creative Commons
Bonyad Ahmadi, Mehdi Gholamalifard, Seyed Mahmoud Ghasempouri

et al.

Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103171 - 103171

Published: April 1, 2025

Language: Английский

Citations

0
SDGSAT-1: Capabilities for Monitoring and Evaluating SDG Indicators DOI Creative Commons
Huadong Guo, Changyong Dou, Dong Liang

et al.

Chinese Journal of Space Science, Journal Year: 2024, Volume and Issue: 44(4), P. 677 - 677

Published: Jan. 1, 2024

SDGSAT-1, the world's first science satellite dedicated to assisting United Nations 2030 Sustainable Development Agenda, has been operational for over two and a half years. It provides valuable data aid in implementing Goals internationally. Through its Open Science Program, maintained consistent operations delivered free scientific technological users from 88 countries. This program produced wealth of output, with 72 papers, including 28 on processing methods 44 applications monitoring progress toward SDGs related sustainable cities, clean energy, life underwater, climate action, water sanitation. SDGSAT-1 is equipped three key instruments: multispectral imager, thermal infrared spectrometer, glimmer which have enabled ground-breaking research variety domains such as quality analysis, identification industrial heat sources, assessment environmental disaster impacts, detection forest fires. The precise measurements ongoing made possible by this invaluable significantly advance our understanding various phenomena. They are essential making well-informed decisions local global scale. Beyond application academic research, promotes cooperation strengthens developing countries' capacity accomplish their development goals. As continues gather distribute data, it plays pivotal role strategies protection, management relief, resource allocation. These initiatives highlight satellite's vital fostering international collaboration technical innovation knowledge promote future.

Language: Английский

Citations

0
Derivation of tasseled cap transformation coefficients for SDGSAT-1 Multispectral Imager at-sensor reflectance data DOI Creative Commons

Nijun Jiang,

Changyong Dou,

Yunwei Tang

et al.

International Journal of Digital Earth, Journal Year: 2024, Volume and Issue: 17(1)

Published: Oct. 16, 2024

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

Language: Английский

Citations

0