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http://dx.doi.org/10.7848/ksgpc.2022.40.5.367

Construction Method of ECVAM using Land Cover Map and KOMPSAT-3A Image  

Kwon, Hee Sung (Dept. of Spatial Information, Kyungpook National University)
Song, Ah Ram (Dept. of Convergence & Fusion System Engineering, Kyungpook National University)
Jung, Se Jung (Dept. of Convergence & Fusion System Engineering, Kyungpook National University)
Lee, Won Hee (Dept. of Convergence & Fusion System Engineering, Kyungpook National University)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.40, no.5, 2022 , pp. 367-380 More about this Journal
Abstract
In this study, the periodic and simplified update and production way of the ECVAM (Environmental Conservation Value Assessment Map) was presented through the classification of environmental values using KOMPSAT-3A satellite imagery and land cover map. ECVAM is a map that evaluates the environmental value of the country in five stages based on 62 legal evaluation items and 8 environmental and ecological evaluation items, and is provided on two scales: 1:25000 and 1:5000. However, the 1:5000 scale environmental assessment map is being produced and serviced with a slow renewal cycle of one year due to various constraints such as the absence of reference materials and different production years. Therefore, in this study, one of the deep learning techniques, KOMPSAT-3A satellite image, SI (Spectral Indices), and land cover map were used to conduct this study to confirm the possibility of establishing an environmental assessment map. As a result, the accuracy was calculated to be 87.25% and 85.88%, respectively. Through the results of the study, it was possible to confirm the possibility of constructing an environmental assessment map using satellite imagery, optical index, and land cover classification.
Keywords
Environmental Geographic Information; Land cover map; Environmental Conservation Value Assessment Map; Deep Learning;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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1 Jeon, S. W., Song, W. K., Lee, M. J., and Kang, B. J. (2010), Improvement of the environmental conservation value assessment map (ECVAM) by complement of the vegetation community stability item, Journal of the Korean Society of Environmental Restoration Technology, 13(2), 114-123.
2 Kim, E., Jeon, S. W., Song, W., Kwak, J., and Lee, J. (2012), Application of ECVAM as a indicator for monitoring national environment in Korea, Journal of Environmental Policy, 11(2), 3-16. (in Korean with English abstract) https://doi.org/10.17330/joep.11.2.201206.3   DOI
3 Lee, S. H. and Lee, M. J. (2020), A Study on Deep Learning Optimization by Land Cover Classification Item Using Satellite Imagery, Korean Journal of Remote Sensing, 36(6_2), 1591-1604. (in Korean with English abstract) https://doi.org/10.7780/kjrs.2020.36.6.2.9   DOI
4 Song, W., Kim, E., Jeon, S. W., Park, S., and Lee, J. (2012), Improvement of the Criteria on Naturalness of the Environmental Conservation Value Assessment Map (ECVAM), Journal of the Korea Society of Environmental Restoration Technology, 15(2), 31-40. (in Korean with English abstract) https://doi.org/10.13087/kosert.2012.15.2.031   DOI
5 Kim G., Roh Y. H., Jung H., Choi J. Y., and Yoon J. (2017), Extraction of Managerial Vulnerable Areas with Outstanding Natural Environment Using Gap Analysis Based the Environmental Conservation Value Assessment Map (ECVAM), Journal of the Korean Cartographic Association, 17(2): 111-123. (in Korean with English abstract) http://doi.org/10.16879/jkca.2017.17.2.111   DOI
6 Yang, C., Hou, J., and Wang, Y. (2021), Extraction of land covers from remote sensing images based on a deep learning model of NDVI-RSU-Net, Arabian Journal of Geosciences, 14(20), 1-12. https://doi.org/10.1007/s12517-021-08420-5   DOI
7 Kim, G., Lee, E., Kim, O. S., Yoon, J., Lee, J. H., and Kim, J. (2018), Monitoring of Deregulation Areas on Land Use Regulation using the Environmental Conservation Value Assessment Map, Journal of the Korean Cartographic Association, 18(3), 67-76. (in Korean with English abstract) http://doi.org/10.16879/jkca.2018.18.3.067   DOI
8 Zhao, Y., Li, Y., Dong, X., and Yang, B. (2018), Lowfrequency noise suppression method based on improved DnCNN in desert seismic data, IEEE Geoscience and Remote Sensing Letters, 16(5), 811-815. https://doi.org/10.1109/LGRS.2018.2882058   DOI
9 Jo, W., Lim, Y., and Park, K. H. (2019), Deep learning based Land Cover Classification Using Convolutional Neural Network-a case study of Korea, Journal of the Korean Geographical Society, 54(1), 1-16. (in Korean with English abstract)
10 Kim, G., Lee, E. J., Yoon, J., Lee, J. H., and Hwang, S. Y. (2018), Evaluation of Land Use Management Grade Using Environmental Conservation Value Assessment Map (ECVAM) and Restriction on Acts of Use District, Journal of the Association of Korean Geographers, 7(3), 479-488. (in Korean with English abstract) https://doi.org/10.25202/JAKG.7.3.15   DOI
11 Kuwata, K. and Shibasaki, R. (2015), Estimating crop yields with deep learning and remotely sensed data, In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 858-861). IEEE. https://doi.org/10.1109/IGARSS.2015.7325900   DOI
12 Yang, H. J., Kim, G. H., Yoon, J. H., Jun, C. M., Lee, E. J., and Hwang, S. Y. (2018), Improvement in Legislative Assessment of the Environmental Conservation Value Assessment Map Considering the Restriction on Acts of Special-Purpose Areas, Journal of the Korean Society of Environmental Restoration Technology, 21(1), 13-30. (in Korean with English abstract) https://doi.org/10.13087/kosert.2018.21.1.13   DOI
13 Kim, Y., Choi, J., Yoon, J. H., Kim, O. S., and Kim, G. (2018), Applicability study on developing 1:5000 environmental conservation value assessment map (ECVAM) using precise forest type map, Journal of the Association of Korean Geographers, 7(1): 115-128. (in Korean with English abstract) https://doi.org/10.25202/JAKG.7.1.9   DOI
14 Lee, M. J., Jeon, S. W., Lee, C. S., Kang, B. J., and Song, W. K. (2007), A study on basic plan for upscaling environmental conservation value assessment map (ECVAM) of national land in South Korea, Journal of Environmental Policy, 6(3), 115-145. (in Korean with English abstract) https://doi.org/10.17330/joep.6.3.200709.115   DOI
15 Lee, Y. S. and Phil, J. M. (2017), A Comparison and Analysis of Deep Learning Framework, The Journal of The Korea Institute of Electronic Communication Sciences, 12(1): 115-122. (in Korean with English abstract) https://doi.org/10.13067/JKIECS.2017.12.1.115   DOI
16 Song, A. and Kim, Y. (2017), Deep learning-based hyperspectral image classification with application to environmental geographic information systems, Korean Journal of Remote Sensing, 33(6_2), 1061-1073. (in Korean with English abstract) https://doi.org/10.7780/kjrs.2017.33.6.2.3   DOI