Browse > Article
http://dx.doi.org/10.7780/kjrs.2017.33.6.2.5

Updating Land Cover Maps using Object Segmentation and Past Land Cover Information  

Kwak, Geun-Ho (Department of Geoinformatic Engineering, Inha University)
Park, Soyeon (Department of Geoinformatic Engineering, Inha University)
Yoo, Hee Young (Geoinformatic Engineering Research Institute, Inha University)
Park, No-Wook (Department of Geoinformatic Engineering, Inha University)
Publication Information
Korean Journal of Remote Sensing / v.33, no.6_2, 2017 , pp. 1089-1100 More about this Journal
Abstract
This paper presented a method using past land cover maps in image segmentation and training set collection for updating land cover maps. In this method, the object boundaries in past land cover maps were used for segmenting image clearly. Also, the classes of past land cover maps were used to extract additional informative training set from the initial classification result using a small number of initial training set. To evaluate the applicability of proposed method, a case study for updating land cover maps was carried out using middle-level land cover maps and WorldView-2 image in the Taean-gun, South Korea. As a result of the case study, the confusions between urban and barren, paddy/dry field and grassland in the initial classification result were reduced by adding training set. In addition, the object segmentation using boundaries of past land cover map cleared land cover boundaries and improved classification accuracy. Based on the result of case study, the proposed method using past land cover maps is expected to be useful for updating land cover maps.
Keywords
Land cover classification; Object-based; Past land cover information; Training set;
Citations & Related Records
Times Cited By KSCI : 8  (Citation Analysis)
연도 인용수 순위
1 Defries, R.S. and A.S. Belward, 2000. Global and regional land cover characterization from satellite data: An introduction to the Special Issue, International Journal of Remote Sensing, 21(6-7): 1083-1092.   DOI
2 Hong, S.-M., I.-K. Jung, and S.-J. Kim, 2004. Standardizing agriculture-related land cover classification scheme using IKONOS satellite imagery, Korean Journal of Remote Sensing, 20(4): 253-259 (in Korean with English Abstract).   DOI
3 Johnson, B.A. 2013. High-resolution urban land-cover classification using a competitive multi-scale object-based approach, Remote Sensing Letters, 4(2): 131-140.   DOI
4 Kim, Y.-J., S.-Y. Cha, and Y.-H. Cho, 2014. A study of landcover classification methods using airborne digital ortho imagery in stream corridor, Korean Journal of Remote Sensing, 30(2): 207-218 (in Korean with English Abstract).   DOI
5 Lee, M.-J., K.-H. Kim, and J.-H. Park, 2014. National environment atlas development and application base on spatial information environmental, Journal of Environmental Policy, 13(4): 51-78 (in Korean with English Abstract).   DOI
6 Lee, S., S.K. Choi, S. Noh, N. Lim, and J. Choi, 2015. Automatic extraction of initial training data using national land cover map and unsupervised classification and updating land cover map, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 33(4): 267-275 (in Korean with English Abstract).   DOI
7 Liu, B., X. Yu, P. Zhang, X. Tan, A. Yu, and Z. Xue, 2017. A semi-supervised convolutional neural network for hyperspectral image classification, Remote Sensing Letters, 8(9): 839-848.   DOI
8 Ministry of environment, 2017. Environmental Geographic Information Service (EGIS), http://egis.me.go.kr, Accessed on Sep. 1, 2017.
9 Breiman, L., 2001. Random forests, Machine Learning, 45(1): 5-32.   DOI
10 Benz, U.C., P. Hofmann, G. Willhauck, I. Lingenfelder, and M. Heynen, 2004. Multi-resolution, objectoriented fuzzy analysis of remote sensing data for GIS-ready information, ISPRS Journal of Photogrammetry and Remote Sensing, 58(3): 239-258.   DOI
11 Byun, Y.G. and Kim, Y.I. 2010. Development and Evaluation of Image Segmentation Technique for Object-based Analysis of High Resolution Satellite Image, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 28(6): 627-636 (in Korean with English Abstract).
12 Camps-Valls, G., T.V.B. Marsheva, and D. Zhou, 2007. Semi-supervised graph-based hyperspectral image classification, IEEE Transactions on Geoscience and Remote Sensing, 45(10): 3044-3054.   DOI
13 Chen, Z. and J. Wang, 2010. Land use and land cover change detection using satellite remote sensing techniques in the mountainous Three Gorges Area, China, International Journal of Remote Sensing, 31(6): 1519-1542.   DOI
14 Definiens, A. G., 2009. Definiens eCognition developer 8 user guide, Definens AG, Munchen, Germany.
15 Yoo, H.Y., N.-W. Park, S. Hong, K. Lee, and Y. Kim, 2015. Classification of multi-temporal SAR data by using data transform based features and multiple classifiers, Korean Journal of Remote Sensing, 31(3): 205-214 (in Korean with English Abstract).   DOI
16 Na, H.-S. and J.-S. Lee, 2014. Analysis of land cover characteristics with object-based classification method - focusing on the DMZ in Inje-gun, Gangwon-do, Journal of the Korean Association of Geographic Information Studies, 17(2): 121-135 (in Korean with English Abstract).   DOI
17 Oh, K.-Y., M.-J. Lee, and W.-Y. No, 2016. A study on the improvement of sub-divided land cover map classification system - based on the land cover map by ministry of environment, Korean Journal of Remote Sensing, 32(2): 105-118 (in Korean with English Abstract).   DOI
18 Sunwoo, W., D. Kim, S. Kang, and M. Choi, 2016. Application of KOMSAT-2 imageries for change detection of land use and land cover in the west coasts of the Korean peninsula, Korean Journal of Remote Sensing, 32(2): 141-153 (in Korean with English Abstract).   DOI