Extraction of Urban Impervious Surface Using Two-Season WorldView-2 Images: A Comparison
暂无分享,去创建一个
Peijun Li | Huiran Jin | Cai Cai | Peijun Li | Huiran Jin | C. Cai
[1] Giorgos Mountrakis,et al. Assessing integration of intensity, polarimetric scattering, interferometric coherence and spatial texture metrics in PALSAR-derived land cover classification , 2014 .
[2] Stephen V. Stehman,et al. Estimating area and map accuracy for stratified random sampling when the strata are different from the map classes , 2014 .
[3] M. S. Moran,et al. Mapping Impervious Surfaces Using Object-oriented Classification in a Semiarid Urban Region , 2014 .
[4] C. Hladik,et al. Salt Marsh Elevation and Habitat Mapping Using Hyperspectral and LIDAR Data , 2013 .
[5] S. Stehman. Estimating area from an accuracy assessment error matrix , 2013 .
[6] Xuezhi Feng,et al. Impervious surface extraction from high-resolution satellite image using pixel- and object-based hybrid analysis , 2013 .
[7] C. Woodcock,et al. Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation , 2013 .
[8] Junhu Dai,et al. Changes of main phenophases of natural calendar and phenological seasons in Beijing for the last 30 years: Changes of main phenophases of natural calendar and phenological seasons in Beijing for the last 30 years , 2013 .
[9] Hanqiu Xu,et al. Rule-based impervious surface mapping using high spatial resolution imagery , 2013 .
[10] R. Pu,et al. A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species , 2012 .
[11] Bo Zhou,et al. apping and analyzing change of impervious surface for two decades using ulti-temporal Landsat imagery in Missouri , 2012 .
[12] Qihao Weng,et al. Remote sensing of impervious surfaces in the urban areas: Requirements, methods, and trends , 2012 .
[13] Geoffrey J. Hay,et al. How wetland type and area differ through scale: A GEOBIA case study in Alberta's Boreal Plains , 2012 .
[14] Ming-Han Li,et al. Considering plant phenology for improving the accuracy of urban impervious surface mapping in a subtropical climate regions , 2012 .
[15] 仲舒颖,et al. Changes of main phenophases of natural calendar and phenological seasons in Beijing for the last 30 years , 2012 .
[16] Uwe Stilla,et al. Machine Learning Comparison between WorldView-2 and QuickBird-2-Simulated Imagery Regarding Object-Based Urban Land Cover Classification , 2011, Remote. Sens..
[17] R. Pontius,et al. Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment , 2011 .
[18] Patricia Gober,et al. Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery , 2011, Remote Sensing of Environment.
[19] Dengsheng Lu,et al. Impervious surface mapping with Quickbird imagery , 2011, International journal of remote sensing.
[20] Jungho Im,et al. ISPRS Journal of Photogrammetry and Remote Sensing , 2022 .
[21] Peijun Li,et al. A Multilevel Hierarchical Image Segmentation Method for Urban Impervious Surface Mapping Using Very High Resolution Imagery , 2011, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[22] Xuefei Hu,et al. Impervious surface area extraction from IKONOS imagery using an object-based fuzzy method , 2011 .
[23] Xuefei Hu,et al. Estimation of impervious surfaces of Beijing, China, with spectral normalized images using linear spectral mixture analysis and artificial neural network , 2010, Geocarto International.
[24] Jaeyoung Yoon,et al. Effects of land use change and water reuse options on urban water cycle. , 2010, Journal of environmental sciences.
[25] S. Linden,et al. The influence of urban structures on impervious surface maps from airborne hyperspectral data. , 2009 .
[26] Xuefei Hu,et al. Estimating impervious surfaces from medium spatial resolution imagery using the self-organizing map and multi-layer perceptron neural networks. , 2009 .
[27] Xuefei Hu,et al. Estimating impervious surfaces using linear spectral mixture analysis with multitemporal ASTER images , 2009 .
[28] Austin Troy,et al. Object-based land cover classification of shaded areas in high spatial resolution imagery of urban areas: A comparison study , 2009 .
[29] Changshan Wu,et al. Quantifying high‐resolution impervious surfaces using spectral mixture analysis , 2009 .
[30] D. Lu,et al. Extraction of urban impervious surfaces from an IKONOS image , 2009 .
[31] Hongbing Luo,et al. Total pollution effect of urban surface runoff. , 2009, Journal of environmental sciences.
[32] Q. Ge,et al. [Dynamics of autumn phenophase of woody plants in Beijing region in 1962-2007]. , 2008, Ying yong sheng tai xue bao = The journal of applied ecology.
[33] Qihao Weng,et al. Medium Spatial Resolution Satellite Imagery for Estimating and Mapping Urban Impervious Surfaces Using LSMA and ANN , 2008, IEEE Transactions on Geoscience and Remote Sensing.
[34] Changshan Wu,et al. Seasonal Sensitivity Analysis of Impervious Surface Estimation with Satellite Imagery , 2007 .
[35] Peijun Li,et al. Multispectral image segmentation by a multichannel watershed‐based approach , 2007 .
[36] C. Yang,et al. Canopy Spectra and Remote Sensing of Ashe Juniper and Associated Vegetation , 2007, Environmental monitoring and assessment.
[37] Alan T. Murray,et al. Population Estimation Using Landsat Enhanced Thematic Mapper Imagery , 2007 .
[38] Rusong Wang,et al. Monitoring and predicting land use change in Beijing using remote sensing and GIS , 2006 .
[39] D. Lu,et al. Residential population estimation using a remote sensing derived impervious surface approach , 2006 .
[40] Sangbum Lee,et al. Subpixel analysis of Landsat ETM/sup +/ using self-organizing map (SOM) neural networks for urban land cover characterization , 2006, IEEE Transactions on Geoscience and Remote Sensing.
[41] D. Lu,et al. Use of impervious surface in urban land-use classification , 2006 .
[42] M. D. White,et al. The effects of watershed urbanization on the stream hydrology and riparian vegetation of Los Peñasquitos Creek, California , 2006 .
[43] P. Dare. Shadow Analysis in High-Resolution Satellite Imagery of Urban Areas , 2005 .
[44] D. Lu,et al. Spectral Mixture Analysis of the Urban Landscape in Indianapolis with Landsat ETM+ Imagery , 2004 .
[45] Lorenzo Bruzzone,et al. Classification of hyperspectral remote sensing images with support vector machines , 2004, IEEE Transactions on Geoscience and Remote Sensing.
[46] D. Lu,et al. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies , 2004 .
[47] U. Benz,et al. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information , 2004 .
[48] C. Small. High spatial resolution spectral mixture analysis of urban reflectance , 2003 .
[49] Curt H. Davis,et al. A combined fuzzy pixel-based and object-based approach for classification of high-resolution multispectral data over urban areas , 2003, IEEE Trans. Geosci. Remote. Sens..
[50] Alan T. Murray,et al. Estimating impervious surface distribution by spectral mixture analysis , 2003 .
[51] T. Minor,et al. Detecting and discriminating impervious cover with high-resolution IKONOS data using principal component analysis and morphological operators , 2003 .
[52] Alan T. Murray,et al. Monitoring the composition of urban environments based on the vegetation-impervious surface-soil (VIS) model by subpixel analysis techniques , 2002 .
[53] E. Terrence Slonecker,et al. Remote sensing of impervious surfaces: A review , 2001 .
[54] Sachio Kubo,et al. Appraising the anatomy and spatial growth of the Bangkok Metropolitan area using a vegetation-impervious-soil model through remote sensing , 2001 .
[55] Stephen V. Stehman,et al. Practical Implications of Design-Based Sampling Inference for Thematic Map Accuracy Assessment , 2000 .
[56] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[57] Arno Schäpe,et al. Multiresolution Segmentation : an optimization approach for high quality multi-scale image segmentation , 2000 .
[58] Sharon L. Lohr,et al. Sampling: Design and Analysis , 1999 .
[59] J. R. Jensen,et al. Effectiveness of Subpixel Analysis in Detecting and Quantifying Urban Imperviousness from Landsat Thematic Mapper Imagery , 1999 .
[60] Russell G. Congalton,et al. Assessing the accuracy of remotely sensed data : principles and practices , 1998 .
[61] Laurent Najman,et al. Geodesic Saliency of Watershed Contours and Hierarchical Segmentation , 1996, IEEE Trans. Pattern Anal. Mach. Intell..
[62] C. Arnold,et al. IMPERVIOUS SURFACE COVERAGE: THE EMERGENCE OF A KEY ENVIRONMENTAL INDICATOR , 1996 .
[63] R. Blair. Land Use and Avian Species Diversity Along an Urban Gradient , 1996 .
[64] Russell G. Congalton,et al. A review of assessing the accuracy of classifications of remotely sensed data , 1991 .
[65] John R. Jensen,et al. Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .