Vegetation Adjusted Nighttime Light Urban Index Research Articles

Quantifying spatiotemporal patterns of urban impervious surfaces in China: An improved assessment using nighttime light data

Quantifying the spatiotemporal patterns of impervious surfaces (ISs) is crucial for assessing the environmental impacts of urbanization. Nighttime light (NTL) data provide a new way of mapping urban IS on broad scales. However, the accuracy of this approach is currently low and thus further improvements are much needed. Here we have estimated the urban IS dynamics of China from 1992 to 2009 using the Vegetation Adjusted NTL Urban Index (VANUI), which combines NTL and Normalized Difference Vegetation Index (NDVI) data. With VANUI, we were able to quantify the spatiotemporal patterns of IS in China with a much higher accuracy than previous methods. Key to this improvement was VANUI's ability to alleviate the problem of saturation inherently associated with NTL data. Our study shows that the total urban IS area of China increased substantially from 10,614.23km2 in 1992 to 31,147.63km2 in 2009, at an annual increase rate of 6.54%. China's urban IS expansion exhibited pronounced regional differences, with six large “hotspot” areas where urban IS expanded most substantially. These hotspot regions accounted for 0.87% of China's total land area, but 37.66% of the total area of urban IS expansion during 1992–2009. Measures of urban IS are not only important for characterizing urbanization patterns and processes, but also essential for assessing ecological and environmental impacts of urbanization. Our results provide a valuable dataset and new insights for better understanding the speed and scope of China's recent urbanization, as well as for designing and developing sustainable cities in China and beyond.

The Vegetation Adjusted NTL Urban Index: A new approach to reduce saturation and increase variation in nighttime luminosity

The science and policy communities increasingly require information about inter-urban variability in form, infrastructure, and energy use for cities globally and in a timely manner. Nighttime light (NTL) data from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) are able to provide information on nighttime luminosity, a correlate of the built environment and energy consumption. Although NTL data are used to map aggregate measures of urban areas such as total area extent, their ability to characterize inter-urban variation is limited due to saturation of the data values, especially in urban cores. Here we propose a new spectral index, the Vegetation Adjusted NTL Urban Index (VANUI), which combines MODIS NDVI with NTL, to achieve three key goals. First, the index reduces the effects of NTL saturation. Second, the index increases variation of the NTL signal, especially within urban areas. Third, the index corresponds to biophysical and urban characteristics. Additionally, the index is intuitive, simple to implement, and enables rapid characterization of inter-urban variability in nighttime luminosity. Assessments of VANUI show that it significantly reduces NTL saturation and increases variation of data values in core urban areas. As such, VANUI can be useful for studies of urban structure, energy use, and carbon emissions.