scholarly journals A pre-screened and normalized multiple endmember spectral mixture analysis for mapping impervious surface area in Lake Kasumigaura Basin, Japan

2010 ◽  
Vol 65 (5) ◽  
pp. 479-490 ◽  
Author(s):  
Fan Yang ◽  
Bunkei Matsushita ◽  
Takehiko Fukushima
Keyword(s):  
Surface Area ◽  
Impervious Surface ◽  
Spectral Mixture Analysis ◽  
Lake Kasumigaura ◽  
Mixture Analysis ◽  
Impervious Surface Area ◽  
Spectral Mixture

scholarly journals EXAMINATION OF SPECTRAL TRANSFORMATIONS ON SPECTRAL MIXTURE ANALYSIS

2018 ◽  
Vol XLII-3 ◽  
pp. 267-270
Author(s):  
Y. Deng ◽  
C. Wu
Keyword(s):  
Surface Area ◽  
Absolute Error ◽  
Impervious Surface ◽  
Spectral Mixture Analysis ◽  
Mixture Analysis ◽  
Impervious Surface Area ◽  
Paired Samples ◽  
The Difference ◽  
Statistical Analysis Technique ◽  
Spectral Mixture

While many spectral transformation techniques have been applied on spectral mixture analysis (SMA), few study examined their necessity and applicability. This paper focused on exploring the difference between spectrally transformed schemes and untransformed scheme to find out which transformed scheme performed better in SMA. In particular, nine spectrally transformed schemes as well as untransformed scheme were examined in two study areas. Each transformed scheme was tested 100 times using different endmember classes’ spectra under the endmember model of vegetation- high albedo impervious surface area-low albedo impervious surface area-soil (V-ISAh-ISAl-S). Performance of each scheme was assessed based on mean absolute error (MAE). Statistical analysis technique, Paired-Samples T test, was applied to test the significance of mean MAEs’ difference between transformed and untransformed schemes. Results demonstrated that only NSMA could exceed the untransformed scheme in all study areas. Some transformed schemes showed unstable performance since they outperformed the untransformed scheme in one area but weakened the SMA result in another region.

scholarly journals Extraction of High-Precision Urban Impervious Surfaces from Sentinel-2 Multispectral Imagery via Modified Linear Spectral Mixture Analysis

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2873 ◽  
Author(s):  
Rudong Xu ◽  
Jin Liu ◽  
Jianhui Xu
Keyword(s):  
High Precision ◽  
Impervious Surface ◽  
Spectral Mixture Analysis ◽  
Landsat 8 ◽  
Impervious Surfaces ◽  
Mixture Analysis ◽  
Spectral Bands ◽  
Linear Spectral Mixture Analysis ◽  
Sentinel 2A ◽  
Spectral Mixture

This study explores the performance of Sentinel-2A Multispectral Instrument (MSI) imagery for extracting urban impervious surface using a modified linear spectral mixture analysis (MLSMA) method. Sentinel-2A MSI provided 10 m red, green, blue, and near-infrared spectral bands, and 20 m shortwave infrared spectral bands, which were used to extract impervious surfaces. We aimed to extract urban impervious surfaces at a spatial resolution of 10 m in the main urban area of Guangzhou, China. In MLSMA, a built-up image was first extracted from the normalized difference built-up index (NDBI) using the Otsu’s method; the high-albedo, low-albedo, vegetation, and soil fractions were then estimated using conventional linear spectral mixture analysis (LSMA). The LSMA results were post-processed to extract high-precision impervious surface, vegetation, and soil fractions by integrating the built-up image and the normalized difference vegetation index (NDVI). The performance of MLSMA was evaluated using Landsat 8 Operational Land Imager (OLI) imagery. Experimental results revealed that MLSMA can extract the high-precision impervious surface fraction at 10 m with Sentinel-2A imagery. The 10 m impervious surface map of Sentinel-2A is capable of recovering more detail than the 30 m map of Landsat 8. In the Sentinel-2A impervious surface map, continuous roads and the boundaries of buildings in urban environments were clearly identified.

Analysis on Spatial Pattern of Urban Heat Island and Impervious Surface Using Linear Spectral Mixture Analysis

2011 ◽  
Vol 216 ◽  
pp. 600-604
Author(s):  
Jing Hu Pan ◽  
Pei Ji Shi ◽  
Feng Juan Zheng
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Impervious Surface ◽  
Spectral Mixture Analysis ◽  
Heat Island ◽  
Mixture Analysis ◽  
Linear Spectral Mixture Analysis ◽  
Urban Heat ◽  
Space Dependence ◽  
Spectral Mixture

Based on Landsat ETM+ data within the metropolitan area of Lanzhou, China, green vegetation(GV) and impervious surface was extracted by a constrained linear spectral mixture analysis (LSMA),together with single window algorithm to invert land surface temperature ,and the correlation analysis was then conducted to examine the relationship between urban heat island (UHI) effect and impervious surface. Four types of end members with high albedo, GV, soil and low albedo are selected to model complicated urban land cover, estimation accuracy is assessed using Root-Mean-Square (RMS)error and color aerial images, with the help of Mantel and Partial Mantel. Spatial relationship of land surface temperatures (LST), impervious surface and GV were analyzed. Results indicate that impervious surface distribution and GV can be derived from Landsat TM/ETM+ images with satisfactory precision. Impervious surface and GV were positively correlated with UHI, while LST has space dependence, it has high space dependence, and was higher correlated with impervious surface than GV.

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