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TitleTarget-driven extraction of built-up land changes from high resolution imagery
AuthorZhang, Y; Guindon, B; Li, X; Lantz, N; Sun, Z
SourceJournal of Applied Remote Sensing vol. 8, no. 1, 2014 p. 1-12,
Alt SeriesEarth Sciences Sector, Contribution Series 20130273
PublisherSPIE-Intl Soc Optical Eng
Mediapaper; on-line; digital
File formatpdf
AreaBeijing; China
Lat/Long WENS116.0000 117.0000 40.0000 39.0000
Subjectsgeophysics; remote sensing; landform classification; land use; urban planning; urban geology; modelling; models; satellite imagery; RapidEye; SPOT5
Illustrationsflow charts; satellite images
ProgramRemote Sensing Science
Released2014 01 13
AbstractInformation on land conversion to modern urban use is needed for many studies such as the impact of urbanization on environmental quality. Although extensive remote sensing research has been undertaken to detect conversion of nonurban to urban lands, little effort has been directed at assessing modernization of existing built-up land. Detection and quantification of this class of urban growth present significant challenges since the difference between radiometric signatures before and after "land modernization" is much more subtle and complicated than the case of conversion from typical rural to impervious urban land surfaces. A targetdriven approach is presented for an efficient extraction of built-up land change distribution that provides superior results to those based on the traditional data-driven land cover approaches. The extraction strategy, integrating pixel- and object-based methodologies, is comprised of three components: delineation of the baseline built-up areas, detection of the areas that have undergone change and integration of targeted change features to generate a final built-up land change map. A case study was carried out using RapidEye and SPOT5 images over suburban Beijing, China. The overall accuracy of built-up change mapping is about 91% and exceeds accuracies achievable by pixel or segment processing used in isolation.
Summary(Plain Language Summary, not published)
New urban development often involves the "modernization" of existing built-up areas, which can include, for example, the replacement of old structures in small agricultural villages with modern housing or industrial facilities. Detection of these changes in existing built-up areas using satellite remote sensing is challenging since the old and modernized structures can appear very similar in the satellite images. This paper presents a new approach for extracting this type of urban land change information using high resolution (i.e., high detail) satellite images. A test study of the method has been carried out for suburban Beijing, China, where rapid changes in built-up areas are occurring. The overall accuracy of the new approach for change mapping is approximately 91%, which is superior to results from more traditional remote sensing methods.

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