Target-driven extraction of built-up land changes from high-resolution imagery

Ying Zhang; Bert Guindon; Xinwu Li; Nicholas Lantz; Zhongchang Sun

doi:10.1117/1.JRS.8.084594

13 January 2014 Target-driven extraction of built-up land changes from high-resolution imagery

Ying Zhang, Bert Guindon, Xinwu Li, Nicholas Lantz, Zhongchang Sun

Author Affiliations +

Funded by: National Basic Research Program of China, 973 Project, Major State Basic Research Development Program of China, Director Foundation of CEODE, CAS, Basic Research Program of China, Earth Observation for Sensitive Factors of Global Change: Mechanisms and Methodologies, National Natural Science Foundation of China, Natural Science Foundation of China, Comparative Study on Global Environmental Change Using Remote Sensing Technology, Program of the National Natural Science Foundation of China, Major International Cooperation and Exchange Project of the Chinese National Natural Science Foundation, Major International Cooperation and Exchange Project of National Natural Science Foundation of China, Major International Cooperation, Exchange Project of National Natural Science Foundation of China

Journal of Applied Remote Sensing, Vol. 8, Issue 1, 084594 (January 2014). https://doi.org/10.1117/1.JRS.8.084594

Abstract

Information 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 target-driven 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.

Citation Download Citation

Ying Zhang, Bert Guindon, Xinwu Li, Nicholas Lantz, and Zhongchang Sun "Target-driven extraction of built-up land changes from high-resolution imagery," Journal of Applied Remote Sensing 8(1), 084594 (13 January 2014). https://doi.org/10.1117/1.JRS.8.084594

Published: 13 January 2014

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