• Korean Journal of Remote Sensing
• /
• v.23 no.3
• /
• pp.181-188
• /
• 2007

The objective of this research was to investigate the optimal land cover classification algorithm for the monitoring of North Korea with MODIS multi-temporal data based on monthly phenological characteristics. Three frequently used land cover classification algorithms, ISODATA1), SMA2), and SOM3) were employed for this study; the land cover categories were forest, grass, agricultural, wetland, barren, built-up, and water body. The outcomes of the study can be summarized as follows. First, the overall classification accuracy of ISODATA, SMA, and SOM was 69.03%, 64.28%, and 73.57%, respectively. Second, ISODATA and SMA resulted in a higher classification accuracy of forest and agricultural categories, but SOM performed better for the built-up area, bare soil, grassland, and water. A possible explanation for this difference would be related to the difference of sensitivity against the vegetation activity. This would be related to the capability of SOM to express all of their values without any loss of data by maintaining the topology between pixels of primitive data after classification, while ISODATA and SMA retain limited amount of data after normalization process. Third, we can conclude that SOM is the best algorithm for monitoring the land cover change of North Korea.

• Korean Journal of Remote Sensing
• /
• v.25 no.1
• /
• pp.71-83
• /
• 2009

This paper is written to analyze possible problems encountered with the existing data for the monitoring of land use and land cover change over the Korean peninsula and, further, to provide technical alternatives for the future land monitoring over the area. The oldest type of non-spatial data related to the land use change are cadastral statistics obtained since 1911. Annual statistics of cadastral data in early years (before 1942) can be used to assess land use change over the area. However, the cadastral statistics after the Korean War are not very appropriate for land use monitoring since the land class in cadastral data does not always correspond with actual land cover status. Majority of spatial data available for land monitoring over the area are land cover maps classified from satellite imagery since early 1970's. To analyze the suitability of land cover maps that were produced by two separate institutes with about 10 years interval, we conducted simple change detection analysis using these maps. These maps were not quite ready to be compared each other, in which they did not have the same class definition, classification method, and geometric registration. To achieve continuous and effective monitoring of land use and land cover change, particularly over North Korea, we should have a standard scheme in type and season of satellite imagery, image classification procedure, and class definition, which also should correspond to international standards.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.17 no.2
• /
• pp.121-135
• /
• 2014

Object-based classification methods provide a valid alternative to traditional pixel-based methods. This study reports the results of an object-based classification to examine land cover in the demilitarized zones(DMZs) of Inje-gun. We used land cover classes(7 classes for main category and 13 classes for sub-category) selected from the criteria by Korea Ministry of Environment. The average and standard deviation of the spectrum values, and homogeneity of GLCM were chosen to map land cover types in an hierarchical approach using the nearest neighborhood method. We then identified the distributional characteristics of land cover by considering 3 topographic characteristics (altitude, slope gradient, distance from the Southern Limited Line(SLL)) within the DMZs. The results showed that scale 72, shape 0.2, color 0.8, compactness 0.5 and smoothness 0.5 were the optimum weight values while scale, shape and color were most influenced parameters in image segmentation. The forests (92%) were main land cover type in the DMZs; the grassland(5%), the urban area (2%) and the forests (broadleaf forest: 44%, mixed forest: 42%, coniferous forest: 6%) also occupied mostly in land cover classes for sub-category. The results also showed that facilities and roads had higher density within 2 km from the SLL, while paddy, field and bare land were distributed largely outside 6 km from the SLL. In addition, there was apparent distinction in land cover by topographic characteristics. The forest had higher density at above altitude 600m and above slope gradient $30^{\circ}$ while agriculture, bare land and grass land were distributed mainly at below altitude 600m and below slope gradient $30^{\circ}$.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.107-109
• /
• 2003

Optical sensor-based land cover categories produce spectral signature confusion along with degraded classification accuracy. In the classification tasks, the goal of fusing data from different sensors is to reduce the classification error rate obtained by single source classification. This paper describes the result of land cover/land use classification derived from solely of Landsat TM (TM) and multisensor image fusion between JERS 1 SAR (JERS) and TM data. The best radar data manipulation is fused with TM through various techniques. Classification results are relatively good. The highest Kappa Coefficient is derived from classification using principal component analysis-high pass filtering (PCA+HPF) technique with the Overall Accuracy significantly high.

• Journal of Korean Society of Rural Planning
• /
• v.6 no.2 s.12
• /
• pp.50-58
• /
• 2000

The purposes of the study were to detect and evaluate the historical land use and land cover changes on the Balan watersheds from three thematic mapper (TM) data, which were taken in 1985, 1993, and 1996. The supervised and unsupervised classification methods were adopted to classify five land cover categories: Paddy, upland, forest, residential, and water. The results indicated residential areas increased significantly during the past eleven years, Forest and paddy were converted to the urban areas. Future land cover patterns were forecasted using a Markov chain method, and the simulated land coiler change ratios presented.

• Atmosphere
• /
• v.28 no.4
• /
• pp.427-441
• /
• 2018

This study examines the impact of the urban parameterization scheme and the land cover change on simulated near surface temperature using Unified Model (UM) over the Seoul metropolitan area. We perform four simulations by varying the land cover and the urban parameterization scheme, and then compare the model results with 46 AWS observation data from 2 to 9 August 2016. Four simulations were performed with different combination of two urban parameterization schemes and two land cover data. Two schemes are Best scheme and MORUSES (Met Office Reading Urban Surface Exchange Scheme) and two land cover data are IGBP (International Geosphere and Biosphere Programme) and EGIS (Environmental Geographic information service) land cover data. When land use data change from IGBP to EGIS, urban ratio over the study area increased by 15.9%. The results of the study showed that the higher change in urban fraction between IGBP and EGIS, the higher the improvement in temperature performance, and the higher the urban fraction, the higher the effect of improving temperature performance of the urban parameterization scheme. 1.5-m temperature increased rapidly during the early morning due to increase of sensible heat flux in EXP2 compared to CTL. The MORUSES with EGIS (EXP3) provided best agreement with observations and represents a reasonable option for simulating the near surface temperature of urban area.

• Journal of Korean Society for Geospatial Information Science
• /
• v.22 no.4
• /
• pp.53-61
• /
• 2014

Landsat OLI satellite imagery can be applied to various remote sensing applications, such as generation of land cover map, urban area analysis, extraction of vegetation index and change detection, because it includes various multispectral bands. In addition, land cover map is an important information to monitor and analyze land cover using GIS. In this paper, land cover map is generated by using Landsat OLI and existing land cover map. First, training dataset is obtained using correlation between existing land cover map and unsupervised classification result by K-means, automatically. And then, spectral signatures corresponding to each class are determined based on training data. Finally, abundance map and land cover map are generated by using iterative spectral mixture model. The experiment is accomplished by Landsat OLI of Cheongju area. It shows that result by our method can produce land cover map without manual training dataset, compared to existing land cover map and result by supervised classification result by SVM, quantitatively and visually.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.4
• /
• pp.249-260
• /
• 2017

UHI (Urban Heat Island) is an important environmental issue occurring in highly developed (or urbanized) area such as Seoul Metropolitan City of Korea due to modification of the land surface by man-made structures. With the advance of the remote sensing technique, land cover types and LST (Land Surface Temperature) influencing UHI were frequently investigated describing that they have a positive relationship. However, the concept of land cover considers material characteristics of the urban cover in a comprehensive way and does not provide information on how human activities influence on LST in detail. Instead, land use reflects ways of land use management and human life patterns and behaviors, and explains the relationship with human activities in more details. Using this concept, LST was segmented according to land use types from the Landsat imagery to identify the human-induced heat from the surface and interannual and seasonal variation of LST with GIS. The result showed that the LST intensity of Seoul was greatest in the industrial area and followed by the commercial and residential areas. In terms of size, the residential area could be defined as the major contributor among six urban land use types (i.e., residential, industrial, commercial, transportation, etc.) affecting UHI during daytime in Seoul. For temperature, the industrial area was highest and could be defined as a major contributor. It was found that land use type was more appropriate to understand the human-induced effect on LST rather than land cover. Also, there was no significant change in the interannual pattern of LST in Seoul but the seasonal difference provided a trigger that the human life pattern could be identified from the satellite-derived LST.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.50-52
• /
• 2003

The purpose of this study is to evaluate the hydrological impact due to temporal land cover changes by gradual urbanization of a watershed. WMS HEC-1 was adopted, and DEM with 200m resolution and hydrologic soil group from 1:50,000 soil map were prepared. Land covers of 1986, 1990, 1994 and 1999 Landsat TM images were classified by maximum likelihood method. By applying the model, watershed average CN value was affected in the order of paddy, forest and urban/residential, respectively.

• Atmosphere
• /
• v.15 no.2
• /
• pp.75-90
• /
• 2005

This study examines the impacts of land cover changes on the East Asia summer monsoon with the National Center for Atmospheric Research Regional Climate Model (NCAR RegCM2), coupled with Biosphere Atmosphere Transfer Scheme (BATS). To assess the goals, two types of land cover maps were used in the simulation of summer climate. One type was NCAR land cover map (CTL) and the other was current land cover map derived from satellite data (land cover: LCV). Warm and cold surface temperature biases of $1-3^{\circ}C$ occurred over central China and Mongolia in CTL. The model produced excessive precipitation over northern land area but less over southern ocean of the model domain. Changes of biophysical parameters, such as albedo, minimum stomatal resistance and roughness length, due to the land cover changes resulted in the alteration of land-atmosphere interactions. Latent heat flux and wind speed in LCV increased noticeably over central China where deciduous broad leaf trees have been replaced by mixed farm and irrigated crop. As a result, the systematic warm biases over central China were greatly reduced in LCV. Strong cooling of central China decreased pressure gradient between East Asian continent and Pacific Ocean. The decreased pressure gradient suppressed the northward transport of moisture from south China and South China Sea. These changes reduced not only the excessive precipitation over north China and Mongolia but also less precipitation over south China. However, the land cover changes increased the precipitation over the Korean Peninsula and the Japan Islands, especially in July and August.