Abstract
Nighttime light data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) provides a unique data source for mapping and monitoring urban areas at regional and global scales. This study proposes an object similarity-based thresholding method using VIIRS DNB data to map urban areas. The threshold for a target potential urban object was determined by comparing its similarity with all reference urban objects with known optimal thresholds derived from Landsat data. The proposed method includes four major steps: potential urban object generation, threshold optimization for reference urban objects, object similarity comparison, and urban area mapping. The proposed method was evaluated using VIIRS DNB data of China and compared with existing mapping methods in terms of threshold estimation and urban area mapping. The results indicated that the proposed method estimated thresholds and mapped urban areas accurately and generally performed better than the cluster-based logistic regression method. The correlation coefficients between the estimated thresholds and the reference thresholds were 0.9201–0.9409 (using Euclidean distance as similarity measure) and 0.9461–0.9523 (using Mahalanobis distance as similarity measure) for the proposed method and 0.9435–0.9503 for the logistic regression method. The average Kappa Coefficients of the urban area maps were 0.58 (Euclidean distance) and 0.57 (Mahalanobis distance) for the proposed method and 0.51 for the logistic regression method. The proposed method shows potential to map urban areas at a regional scale effectively in an economic and convenient way.
Highlights
Only occupying less than 3% of Earth’s terrestrial surface, urban areas have accommodated more than half of the global population by 2015 [1] and have exerted enormous influence on their surroundings [2,3]
The Day/Night Band (DNB) from Visible Infrared Imaging Radiometer Suite (VIIRS) sensor, onboard the Suomi National Polar-Orbiting Partnership (NPP), which was launched in October 2011, presents an unprecedented night observation capability [19]
We propose a new local thresholding method based on object similarity to map urban areas at a regional scale from VIIRS DNB data
Summary
Only occupying less than 3% of Earth’s terrestrial surface, urban areas have accommodated more than half of the global population by 2015 [1] and have exerted enormous influence on their surroundings [2,3]. Remote sensing provides a powerful data source for mapping urban areas and monitoring urbanization dynamics at different scales. Moderate- and coarse-resolution images are more effective for the extraction of urban areas at regional and global scales [9,10,11,12] because of wide coverage and high temporal resolution. Nighttime light data of coarse resolution, capturing information on human activities, have been widely available and providing unique and valuable data sources for mapping urban areas and monitoring urbanization dynamics. The Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) has been collecting nighttime light emission from the earth surface since 1992, and its recorded nighttime light (NTL) data have been widely used in urban area mapping and monitoring [13,14,15,16,17,18]. VIIRS DNB has a broader radiometric measurement range and outperforms at low-light detection, which significantly reduces the saturation and over-glow problem inherent to DMSP/OLS data [20,21]
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