Research Papers

Mapping urban and peri-urban agriculture using high spatial resolution satellite data

[+] Author Affiliations
Dionys Forster

Department of Water and Sanitation in Developing Countries, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Ueberlandstrass 133, Duebendorf, CH-8600 Switzerland

Yves Buehler, Tobias W. Kellenberger

Remote Sensing Laboratories, Department of Geography, University of Zurich, Winterthurerstr. 190, Zurich, ZH CH-8057 Switzerland

J. Appl. Remote Sens. 3(1), 033523 (March 31, 2009). doi:10.1117/1.3122364
History: Received August 6, 2008; Revised March 13, 2009; Accepted March 26, 2009; March 31, 2009; Online March 31, 2009
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Abstract

In rapidly changing peri-urban environments where biophysical and socio-economic processes lead to spatial fragmentation of agricultural land, remote sensing offers an efficient tool to collect land cover/land use (LCLU) data for decision-making. Compared to traditional pixel-based approaches, remote sensing with object-based classification methods is reported to achieve improved classification results in complex heterogeneous landscapes. This study assessed the usefulness of object-oriented analysis of Quickbird high spatial resolution satellite data to classify urban and peri-urban agriculture in a limited peri-urban area of Hanoi, Vietnam. The results revealed that segmentation was essential in developing the object-oriented classification approach. Accurate segmentation of shape and size of an object enhanced classification with spectral, textural, morphological, and topological features. A qualitative, visual comparison of the classification results showed successful localisation and identification of most LCLU classes. Quantitative evaluation was conducted with a classification error matrix reaching an overall accuracy of 67% and a kappa coefficient of 0.61. In general, object-oriented classification of high spatial resolution satellite data proved the promising approach for LCLU analysis at village level. Capturing small-scale urban and peri-urban agricultural diversity offers a considerable potential for environmental monitoring. Challenges remain with the delineation of field boundaries and LCLU diversity on more spatially extensive datasets.

© 2009 Society of Photo-Optical Instrumentation Engineers

Citation

Dionys Forster ; Yves Buehler and Tobias W. Kellenberger
"Mapping urban and peri-urban agriculture using high spatial resolution satellite data", J. Appl. Remote Sens. 3(1), 033523 (March 31, 2009). ; http://dx.doi.org/10.1117/1.3122364


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