An easily implemented method to estimate impervious surface area on a large scale from MODIS time-series and improved DMSP-OLS nighttime light data

Arnold, 1996, Impervious surface coverage: the emergence of a key environmental indicator, J. Am. Plan. Assoc., 62, 243, 10.1080/01944369608975688 Bauer, M.E., Loffelholz, B.C., Wilson, B., 2008. Estimating and mapping impervious surface area by regression analysis of Landsat imagery. In: Weng, Q., (Ed.), Remote Sensing of Impervious Surfaces, CRC Press, Boca Raton, FL, USA, pp. 3–19. Chen, 2004, A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter, Remote Sens. Environ., 91, 332, 10.1016/j.rse.2004.03.014 Elvidge, 2007, Global distribution and density of constructed impervious surfaces, Sensors, 7, 1962, 10.3390/s7091962 Gallo, 2016, Changes in satellite-derived impervious surface area at US historical climatology network stations, ISPRS J. Photogrammetry Remote Sens., 120, 77, 10.1016/j.isprsjprs.2016.08.006 Huang, 2016, Mapping sub-pixel urban expansion in China using MODIS and DMSP/OLS nighttime lights, Remote Sens. Environ., 175, 92, 10.1016/j.rse.2015.12.042 Knight, 2011, Mapping impervious cover using multi-temporal MODIS NDVI data, IEEE J. Selected Top. Appl. Earth Observ. Remote Sens., 4, 303, 10.1109/JSTARS.2010.2051535 Lee, 2006, Subpixel analysis of Landsat ETM+ using Self-Organizing Map (SOM) neural networks for urban land cover characterization, IEEE Trans. Geosci. Remote Sens., 44, 1642, 10.1109/TGRS.2006.869984 Li, 2015, Incorporating land use land cover probability information into endmember class selections for temporal mixture analysis, ISPRS J. Photogramm. Remote Sens., 101, 163, 10.1016/j.isprsjprs.2014.12.007 Liu, 2015, A normalized urban areas composite index (NUACI) based on combination of DMSP-OLS and MODIS for mapping impervious surface area, Remote Sens., 7, 17168, 10.3390/rs71215863 Lu, 2008, Regional mapping of human settlements in southeastern China with multisensor remotely sensed data, Remote Sens. Environ., 112, 3668, 10.1016/j.rse.2008.05.009 Lu, 2006, Use of impervious surface in urban land-use classification, Remote Sens. Environ., 102, 146, 10.1016/j.rse.2006.02.010 MRC (Mekong River Commission) Powell, 2007, Sub-pixel mapping of urban land cover using multiple endmember spectral mixture analysis: Manaus, Brazil, Remote Sens. Environ., 106, 253, 10.1016/j.rse.2006.09.005 Somers, 2011, Endmember variability in spectral mixture analysis: a review, Remote Sens. Environ., 115, 1603, 10.1016/j.rse.2011.03.003 Weng, 2012, Remote sensing of impervious surfaces in the urban areas: requirements, methods, and trends, Remote Sens. Environ., 117, 34, 10.1016/j.rse.2011.02.030 Weng, 2008, Medium spatial resolution satellite imagery for estimating and mapping urban impervious surfaces using LSMA and ANN, IEEE Trans. Geosci. Remote Sens., 46, 2397, 10.1109/TGRS.2008.917601 Wu, 2004, Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery, Remote Sens. Environ., 93, 480, 10.1016/j.rse.2004.08.003 Wu, 2003, Estimating impervious surface distribution by spectral mixture analysis, Remote Sens. Environ., 84, 493, 10.1016/S0034-4257(02)00136-0 Xian, 2010, Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat Imagery Change Detection Methods, Remote Sens. Environ., 114, 1676, 10.1016/j.rse.2010.02.018 Xie, 2017, Spatiotemporally enhancing time-series DMSP/OLS nighttime light imagery for assessing large-scale urban dynamics, ISPRS J. Photogramm. Remote Sens., 128, 1, 10.1016/j.isprsjprs.2017.03.003 Yang, 2010, A pre-screened and normalized multiple endmember spectral mixture analysis for mapping impervious surface area in Lake Kasumigaura Basin, Japan, ISPRS J. Photogramm. Remote Sens., 65, 479, 10.1016/j.isprsjprs.2010.06.004 Yang, 2012, Temporal mixture analysis for estimating impervious surface area from multi-temporal MODIS NDVI data in Japan, ISPRS J. Photogramm. Remote Sens., 72, 90, 10.1016/j.isprsjprs.2012.05.016 Yang, 2014, Mapping the human footprint from satellite measurements in Japan, ISPRS J. Photogramm. Remote Sens., 88, 80, 10.1016/j.isprsjprs.2013.11.020 Zhang, 2013, The vegetation adjusted NTL urban index: a new approach to reduce saturation and increase variation in nighttime luminosity, Remote Sens. Environ., 129, 32, 10.1016/j.rse.2012.10.022 Zhuo, 2015, An improved method of night-time light saturation reduction based on EVI, Int. J. Remote Sens., 36, 4114, 10.1080/01431161.2015.1073861