Seasonal Dynamics of the Land-Surface Characteristics in Arid Regions Retrieved by Optical and Microwave Satellite Data

Establishing a quantitative relationship between Synthetic Aperture Radar (SAR) data and optical data can facilitate the fusion of these two data sources, enhancing the time-series monitoring capabilities for remote sensing of a land surface. In this study, we analyzed the Normalized Difference Vege...

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Published inRemote Sensing Vol. 16; no. 17; p. 3143
Main Authors Tian, Ying, Ackermann, Kurt, McCarthy, Christopher, Sternberg, Troy, Purevtseren, Myagmartseren, Limuge, Che, Hagiwara, Katsuro, Ogawa, Kenta, Hobara, Satoru, Hoshino, Buho
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LanguageEnglish
Published Basel MDPI AG 26.08.2024
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Abstract Establishing a quantitative relationship between Synthetic Aperture Radar (SAR) data and optical data can facilitate the fusion of these two data sources, enhancing the time-series monitoring capabilities for remote sensing of a land surface. In this study, we analyzed the Normalized Difference Vegetation Index (NDVI) and Shortwave Infrared Transformed Reflectance (STR) with the backscatter coefficients in vertical polarization VV (σ0VV) and cross polarization VH (σ0VH) across different seasons. We used optical and microwave satellite data spanning from the southern Gobi Desert region to the steppe region in northern Mongolia. The results indicate a relatively high correlation between the NDVI derived from Sentinel-2 and σ0VH (RVH = 0.29, RVH = 0.44, p < 0.001) and a low correlation between the NDVI and σ0VV (RVH = 0.06, RVH = 0.14, p < 0.01) in the Gobi Desert region during summer and fall. STR showed a positive correlation with both σ0VH and σ0VV except in spring, with the highest correlation coefficients observed in summer (RVV = 0.45, RVV = 0.44, p < 0.001). In the steppe region, significant seasonal variations in the NDVI and σ0VH were noted, with a strong positive correlation peaking in summer (RVH = 0.71, p < 0.001) and an inverse correlation with σ0VV except in summer (RVV = −0.43, RVV = −0.34, RVV = −0.13, p < 0.001). Additionally, STR showed a positive correlation with σ0VH and σ0VV in summer (RVH = 0.40, RVV = 0.39, p < 0.001) and fall (RVH = 0.38, RVV = 0.09, p < 0.01), as well as an inverse correlation in spring (RVH= −0.17, RVV= −0.38, p < 0.001) and winter (RVH = −0.21, RVV = −0.06, p < 0.001). The correlations between the NDVI, STR, σ0VH, and σ0VV were shown to vary by season and region. In the Gobi Desert region, perennial shrubs are not photosynthetic in spring and winter, and they affect backscatter due to surface roughness. In the steppe region, annual shrubs were found to be the dominant species and were found to photosynthesize in spring, but not enough to affect the backscatter due to surface roughness.
AbstractList Establishing a quantitative relationship between Synthetic Aperture Radar (SAR) data and optical data can facilitate the fusion of these two data sources, enhancing the time-series monitoring capabilities for remote sensing of a land surface. In this study, we analyzed the Normalized Difference Vegetation Index (NDVI) and Shortwave Infrared Transformed Reflectance (STR) with the backscatter coefficients in vertical polarization VV (σ⁰VV) and cross polarization VH (σ⁰VH) across different seasons. We used optical and microwave satellite data spanning from the southern Gobi Desert region to the steppe region in northern Mongolia. The results indicate a relatively high correlation between the NDVI derived from Sentinel-2 and σ⁰VH (RVH = 0.29, RVH = 0.44, p < 0.001) and a low correlation between the NDVI and σ⁰VV (RVH = 0.06, RVH = 0.14, p < 0.01) in the Gobi Desert region during summer and fall. STR showed a positive correlation with both σ⁰VH and σ⁰VV except in spring, with the highest correlation coefficients observed in summer (RVV = 0.45, RVV = 0.44, p < 0.001). In the steppe region, significant seasonal variations in the NDVI and σ⁰VH were noted, with a strong positive correlation peaking in summer (RVH = 0.71, p < 0.001) and an inverse correlation with σ⁰VV except in summer (RVV = −0.43, RVV = −0.34, RVV = −0.13, p < 0.001). Additionally, STR showed a positive correlation with σ⁰VH and σ0VV in summer (RVH = 0.40, RVV = 0.39, p < 0.001) and fall (RVH = 0.38, RVV = 0.09, p < 0.01), as well as an inverse correlation in spring (RVH= −0.17, RVV= −0.38, p < 0.001) and winter (RVH = −0.21, RVV = −0.06, p < 0.001). The correlations between the NDVI, STR, σ⁰VH, and σ⁰VV were shown to vary by season and region. In the Gobi Desert region, perennial shrubs are not photosynthetic in spring and winter, and they affect backscatter due to surface roughness. In the steppe region, annual shrubs were found to be the dominant species and were found to photosynthesize in spring, but not enough to affect the backscatter due to surface roughness.
Establishing a quantitative relationship between Synthetic Aperture Radar (SAR) data and optical data can facilitate the fusion of these two data sources, enhancing the time-series monitoring capabilities for remote sensing of a land surface. In this study, we analyzed the Normalized Difference Vegetation Index (NDVI) and Shortwave Infrared Transformed Reflectance (STR) with the backscatter coefficients in vertical polarization VV (σ0VV) and cross polarization VH (σ0VH) across different seasons. We used optical and microwave satellite data spanning from the southern Gobi Desert region to the steppe region in northern Mongolia. The results indicate a relatively high correlation between the NDVI derived from Sentinel-2 and σ0VH (RVH = 0.29, RVH = 0.44, p < 0.001) and a low correlation between the NDVI and σ0VV (RVH = 0.06, RVH = 0.14, p < 0.01) in the Gobi Desert region during summer and fall. STR showed a positive correlation with both σ0VH and σ0VV except in spring, with the highest correlation coefficients observed in summer (RVV = 0.45, RVV = 0.44, p < 0.001). In the steppe region, significant seasonal variations in the NDVI and σ0VH were noted, with a strong positive correlation peaking in summer (RVH = 0.71, p < 0.001) and an inverse correlation with σ0VV except in summer (RVV = −0.43, RVV = −0.34, RVV = −0.13, p < 0.001). Additionally, STR showed a positive correlation with σ0VH and σ0VV in summer (RVH = 0.40, RVV = 0.39, p < 0.001) and fall (RVH = 0.38, RVV = 0.09, p < 0.01), as well as an inverse correlation in spring (RVH= −0.17, RVV= −0.38, p < 0.001) and winter (RVH = −0.21, RVV = −0.06, p < 0.001). The correlations between the NDVI, STR, σ0VH, and σ0VV were shown to vary by season and region. In the Gobi Desert region, perennial shrubs are not photosynthetic in spring and winter, and they affect backscatter due to surface roughness. In the steppe region, annual shrubs were found to be the dominant species and were found to photosynthesize in spring, but not enough to affect the backscatter due to surface roughness.
Author Christopher McCarthy
Buho Hoshino
Ying Tian
Katsuro Hagiwara
Che Limuge
Satoru Hobara
Troy Sternberg
Myagmartseren Purevtseren
Kurt Ackermann
Kenta Ogawa
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Snippet Establishing a quantitative relationship between Synthetic Aperture Radar (SAR) data and optical data can facilitate the fusion of these two data sources,...
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SubjectTerms Arid regions
Arid zones
Asian dust source area
Backscattering
Biomass
Correlation coefficient
Correlation coefficients
Cross polarization
Deserts
Dominant species
Drought
Dust
Gobi Desert
Gobi Desert region
Infrared analysis
integration of satellite data and field data
Land area
linear spectral unmixing
Moisture content
Mongolia
normalized difference vegetation index
Normalized difference vegetative index
photosynthesis
Polarization
Precipitation
Q
reflectance
Remote monitoring
Remote sensing
Science
Seasonal variations
Sensors
Sentinel-1 and Sentinel-2
Short wave radiation
Shrubs
Spring
Spring (season)
steppe region
Steppes
Summer
Surface properties
Surface roughness
Synthetic aperture radar
time series analysis
Vegetation
Vertical polarization
Winter
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Title Seasonal Dynamics of the Land-Surface Characteristics in Arid Regions Retrieved by Optical and Microwave Satellite Data
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