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

Revealing the driving factors of urban wetland park cooling effects using Random Forest regression and SHAP algorithm DOI
Yue Deng, Weiguo Jiang, Ziyan Ling

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106151 - 106151

Published: Jan. 1, 2025

Language: Английский

Citations

1
Identification of spodumene using a remote-sensing index cube from SDGSAT-1 and other satellites DOI Creative Commons
Siyuan Li, Nannan Zhang, Yongping Li

et al.

International Journal of Digital Earth, Journal Year: 2025, Volume and Issue: 18(1)

Published: Jan. 2, 2025

Language: Английский

Citations

0
Urban wetland landscape patterns and cooling effects in Guilin utilizing GF-1/6 and SDGSAT-1 data DOI Creative Commons
Ziqi Meng, Huadong Guo, Jingjuan Liao

et al.

International Journal of Digital Earth, Journal Year: 2025, Volume and Issue: 18(1)

Published: Feb. 24, 2025

Language: Английский

Citations

0
Water Body Detection Using Sentinel-2 Imagery Through Particle Swarm Intelligence: A Novel Framework for Optimizing Spectral Multi-Band Index DOI Creative Commons

Baydaa Ismail Abrahim,

Ammar A Jasim,

Mohammed Riyadh Mahmood

et al.

Eng—Advances in Engineering, Journal Year: 2025, Volume and Issue: 6(3), P. 59 - 59

Published: March 20, 2025

Water body detection from satellite imagery is still challenging due to spectral confusion and the limitation of traditional water indices. This paper proposes a new approach by incorporating Particle Swarm Optimization with Spectral Multi-Band Index for enhanced bodies using Sentinel-2 imagery. The proposed optimizes coefficients seven bands (Blue, Green, NIR, NIR-Narrow, Vapor, SWIR1, SWIR2) an intelligent PSO adaptive inertia weight early stopping mechanisms. work strategy fitness function that applies dynamic thresholding target-based optimization, allowing it calibrate precisely local characteristics body. performance PSO-SMBWI was evaluated against indices, including NDWI, MNDWI, AWEI. results indicate has highest accuracy, which exactly coincides ground truth coverage (12.12%), while AWEI have deviations +1.24%, +0.53%, +12.15%, respectively. method automatically handles multi-resolution band integration in 10 m, 20 60 m eliminates manual threshold tuning. Furthermore, our consensus-based validation ensures robust verification. Its effectiveness its optimization framework comprehensive analysis. Hence, most suitable any geographical context on highly accurate mapping. research contributes lot area remote sensing introducing automated, accurate, very computationally efficient detection.

Language: Английский

Citations

0
Exploring the influence of urban morphology on summer daytime and nighttime LST based on SDGSAT-1 DOI Creative Commons

Changyin Han,

Qixia Man,

Pinliang Dong

et al.

International Journal of Digital Earth, Journal Year: 2025, Volume and Issue: 18(1)

Published: April 6, 2025

Language: Английский

Citations

0
Evaluating the Sustainable Development Science Satellite 1 (SDGSAT-1) Multi-Spectral Data for River Water Mapping: A Comparative Study with Sentinel-2 DOI Creative Commons

Duomandi Jiang,

Yunmei Li, Qihang Liu

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(15), P. 2716 - 2716

Published: July 24, 2024

SDGSAT-1, the first scientific satellite dedicated to advancing United Nations 2030 Agenda for Sustainable Development, brings renewed vigor and opportunities water resource monitoring research. This study evaluates effectiveness of SDGSAT-1 in extracting bodies comparison Sentinel-2 multi-spectral imager (MSI) data. We applied a confidence thresholding method delineate river from land, utilizing Normalized Differential Water Body Index (NDWI), Difference (MNDWI), Shaded (SWI). It was found that SWI works best while NDWI Sentinel-2. Specifically, demonstrates proficiency delineating broader spectrum MNDWI effectively mitigates impact shadows, SDGSAT-1’s extraction rivers offers high precision, clear outlines, shadow exclusion. overall outperforms Sentinel-2’s accuracy (overall accuracy: 90% vs. 91%, Kappa coefficient: 0.771 0.416, F1 value: 0.844 0.651), likely due its deep blue bands. highlights comprehensive advantages data bodies, providing theoretical basis future

Language: Английский

Citations

2
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