Spatial Metrics and Image Texture for Mapping Urban Land Use

Abstract

The arrival of new-generation, high-spatial-resolution satellite imagery (e.g., Ikonos) has opened up new opportunities for detailed mapping and analysis of urban land use. Drawing on the traditional approach used in aerial photointerpretation, this study investigates an "object-oriented" method to classify a large urban area into detailed land-use categories. Spatial metrics and texture measures are used to describe the spatial characteristics of land-cover objects within each land-use region as derived from interpreted aerial photographs. In assessing how land-use categories vary in their spatial configuration, spatial metrics were found to provide the most important information for differentiating urban land uses. A detailed land-use map with nine categories was derived for the Santa Barbara South Coast Region area. Results from our work suggest that the region-based method exploiting spatial metrics and texture measurements is a potential new avenue to extract detailed urban land-use information from highresolution satellite imagery.

A Workflow for Automated Satellite Image Processing: from Raw VHSR Data to Object-Based Spectral Information for Smallholder Agriculture

“…Textural attributes are derived from the panchromatic images using the Gray-Level Co-Occurrence Matrix (GLCM) [60], which is a statistical approach to texture characterization suitable for regions with irregular shapes [61]. This applies well to smallholder fields.…”

Spatiotemporal Analysis of Urban Land Cover Changes in Kigali, Rwanda Using Multitemporal Landsat Data and Landscape Metrics

“…The impact of urbanization on ecosystem services supply was investigated and a monetary approach was used for quantifying the value of ecosystem services in the study areas. Herold et al (2003) applied objected-oriented images analysis on very high resolution images (IKONOS and QuickBird) coupled with texture analysis for land cover assessment in Santa Barbara, California, USA. Similarly, the spatial and temporal dynamics of urban sprawl in Guangzhou, China was characterized by (Yu & Ng, 2007) by combining Landsat TM images, landscape metrics and an urban-rural gradient analysis along two selected transects.…”

“…Therefore, monitoring spatio-temporal urban growth patterns is paramount for supporting controlled urban development and satellite based data are potential for such kind of monitoring. A growing body of literature found the combination of spatio-temporal satellite data and landscape metrics (LM) worthwhile in urban land cover change analyses and environmental impact assessment (Aguilera et al, 2011;Furberg & Ban, 2010Haas & Ban, 2014;Herold et al, 2005;Herold et al, 2003;Huang et al, 2007;Kuffer & Barrosb, 2011;Liu & Yang, 2015;Seto & Fragkias, 2005). However, few case studies deriving landscape indices based on satellite data exist for Sub-Saharan African cities, giving impetus for the proposed study.…”

Supporting Global Environmental Change Research: A Review of Trends and Knowledge Gaps in Urban Remote Sensing

“…Classified data from remote sensing systems are the principal inputs to many of the urban growth models [155,156]. The availability of global coverage satellite data is changing the nature of urban land change modeling from a focus on individual cities or regions to the potential to model urban land change globally.…”