• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.580-583
• /
• 2007

Various matching methods have been introduced by investigators to improve digital elevation model (DEM) accuracy of satellite imagery. This study proposed an area-based matching method according to land cover property using correlation coefficient of pixel brightness value between the two images for DEM generation from IKONOS stereo imagery. For this, matching line (where "matching line" implies straight line that is approximated to complex nonlinear epipolar geometry) is established by exterior orientation parameters to minimize search area. The matching is carried out based on this line. Land cover classes are divided off into water, urban land, forest and agricultural land. Matching size is selected using a correlation-coefficient image in the four areas. The selected sizes are $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively. And hence, DEM is generated from IKONOS stereo imagery using the selected matching sizes and land cover map on the four types.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.1
• /
• pp.12-25
• /
• 2021

Land cover maps are used in various fields in urban expansion and development. This study analyzed the amount of land cover change over time using multi-sensor information, focusing on the waterfront area of the Taehwa River. In order to apply high-accuracy aerial hyperspectral images, patterns with Field-spectral were reviewed and compared with time series Digital map. The hyperspectral image was set as 13 land cover grades, and the time series digital map was classified into 7 and the waterfront area was classified into 5-6 grades and analyzed. As a result of analysis of the change in land cover of the digital map from the 1990s to 2010, it was found that forest areas were rapidly decreasing and Farmland and grassland were becoming urban. As for the land cover change(2010~2019) in the waterfront area(set 500m) analyzed through hyperspectral images, it was found that Farmland(1.4㎢), Forest(1.0㎢), and grassland (0.8㎢) were converted into urbanized and dried areas, and urbanization was accelerating around the Taehwa River waterfront. Recently, a lot of research has been conducted on the production of land cover maps using high-precision satellite images and aerial hyperspectral images, so it is expected that more detailed and precise land cover maps can be produced and utilized.

• Atmosphere
• /
• v.20 no.4
• /
• pp.415-426
• /
• 2010

A Land cover map over East Asian region (Kongju national university Land Cover map: KLC) is classified by using support vector machine (SVM) and evaluated with ground truth data. The basic input data are the recent three years (2006-2008) of MODIS (MODerate Imaging Spectriradiometer) NDVI (normalized difference vegetation index) data. The spatial resolution and temporal frequency of MODIS NDVI are 1km and 16 days, respectively. To minimize the number of cloud contaminated pixels in the MODIS NDVI data, the maximum value composite is applied to the 16 days data. And correction of cloud contaminated pixels based on the spatiotemporal continuity assumption are applied to the monthly NDVI data. To reduce the dataset and improve the classification quality, 9 phenological data, such as, NDVI maximum, amplitude, average, and others, derived from the corrected monthly NDVI data. The 3 types of land cover maps (International Geosphere Biosphere Programme: IGBP, University of Maryland: UMd, and MODIS) were used to build up a "quasi" ground truth data set, which were composed of pixels where the three land cover maps classified as the same land cover type. The classification results show that the fractions of broadleaf trees and grasslands are greater, but those of the croplands and needleleaf trees are smaller compared to those of the IGBP or UMd. The validation results using in-situ observation database show that the percentages of pixels in agreement with the observations are 80%, 77%, 63%, 57% in MODIS, KLC, IGBP, UMd land cover data, respectively. The significant differences in land cover types among the MODIS, IGBP, UMd and KLC are mainly occurred at the southern China and Manchuria, where most of pixels are contaminated by cloud and snow during summer and winter, respectively. It shows that the quality of raw data is one of the most important factors in land cover classification.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.2 no.1
• /
• pp.5-16
• /
• 1984

This study is about land cover mapping (land use mapping) and change for a period of years in urban area by use of satellite (LANDSAT) data. Definitely, land cover map in 1979 and 1983 of Seoul which has eminant increase of population were produced and change of land cover map for 4 years was considered. The redeveloped software and procedure in this study make it possible to produce land cover maps of urban area in same condition regardless of difference in data acquisition day.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.1
• /
• pp.15-22
• /
• 2015

To create a wind resource map, we need a contour map, a roughness map and wind data. We need a land cover map for the roughness map of these data. A land cover map represents the area showing similar characteristics after color indexing based on the scientific method. The features of land cover is classified by Remote sensing technique. In this study, we verified the application of the NDVI technique is reasonable after we created the wind resource map using roughness maps by unsupervised classification and NDVI technique. As a result, the wind resource map using the NDVI technique showed a 60% accordance rate and difference in class less than one. From the results, The NDVI technique is found alternative to create roughness maps by the unsupervised classification.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.763-765
• /
• 2003

We made a hazard map using GIS and remote sensing for he greatest inundation damage that happened for the 20th century. We calculated the land cover classification using Landsat from 1983 to 2000. We calculated it from a damage report and an aerial photo for a flood. We considered relation of both land cover classification and the damage. We expected the inundation damage in the future and made a hazard map.

• Journal of Korean Society on Water Environment
• /
• v.24 no.6
• /
• pp.690-700
• /
• 2008

The Soil and Water Assessment Tool (SWAT) model users tend to use the readily available input dataset, such as the Ministry of Environment (MOE) land cover data ignoring temporal and spatial changes in land cover. The SWAT model was calibrated and validated with this land cover data. The EI values were 0.79 and 0.85 for streamflow calibration and validation, respectively. The EI were 0.79 and 0.86 for sediment calibration and validation, respectively. With newly prepared landcover dataset for the Doam-dam watershed, the SWAT model better predicts hydrologic and sediment behaviors. The number of HRUs with new land cover data increased by 70.2% compared with that with the MOE land cover, indicating better representation of small-sized agricultural field boundaries. The SWAT estimated annual average sediment yield with the MOE land cover data was 61.8 ton/ha/year for the Doam-dam watershed, while 36.2 ton/ha/year (70.7% difference) of annual sediment yield with new land cover data. Especially the most significant difference in estimated sediment yield was 548.0% for the subwatershed #2. Therefore it is recommended that one needs to carefully validate land cover for the study watershed for accurate hydrologic and sediment simulation with the SWAT model.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2008.05a
• /
• pp.194-198
• /
• 2008

Significant soil erosion and water quality degradation issues are occurring at highland agricultural areas of Kangwon province because of agronomic and topographical specialities of the region. Thus spatial and temporal modeling techniques are often utilized to analyze soil erosion and sediment behaviors at watershed scale. The Soil and Water Assessment Tool (SWAT) model is one of the watershed scale models that have been widely used for these ends in Korea. In most cases, the SWAT users tend to use the readily available input dataset, such as the Ministry of Environment (MOE) land cover data ignoring temporal and spatial changes in land cover. Spatial and temporal resolutions of the MOE land cover data are not good enough to reflect field condition for accurate assesment of soil erosion and sediment behaviors. Especially accelerated soil erosion is occurring from agricultural fields, which is sometimes not possible to identify with low-resolution MOD land cover data. Thus new land cover data is prepared with cadastral map and high spatial resolution images of the Doam-dam watershed. The SWAT model was calibrated and validated with this land cover data. The EI values were 0.79 and 0.85 for streamflow calibration and validation, respectively. The EI were 0.79 and 0.86 for sediment calibration and validation, respectively. These EI values were greater than those with MOE land cover data. With newly prepared land cover dataset for the Doam-dam watershed, the SWAT model better predicts hydrologic and sediment behaviors. The number of HRUs with new land cover data increased by 70.2% compared with that with the MOE land cover, indicating better representation of small-sized agricultural field boundaries. The SWAT estimated annual average sediment yield with the MOE land cover data was 61.8 ton/ha/year for the Doam-dam watershed, while 36.2 ton/ha/year (70.7% difference) of annual sediment yield with new land cover data. Especially the most significant difference in estimated sediment yield was 548.0% for the subwatershed #2 (165.9 ton/ha/year with the MOE land cover data and 25.6 ton/ha/year with new land cover data developed in this study). The results obtained in this study implies that the use of MOE land cover data in SWAT sediment simulation for the Doam-dam watershed could results in 70.7% differences in overall sediment estimation and incorrect identification of sediment hot spot areas (such as subwatershed #2) for effective sediment management. Therefore it is recommended that one needs to carefully validate land cover for the study watershed for accurate hydrologic and sediment simulation with the SWAT model.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.25 no.5
• /
• pp.15-27
• /
• 2022

Climate change is considered a severe global problem closely related to carbon storage. However, recent urbanization and land-use changes reduce carbon stocks in terrestrial ecosystems. Recently, the role of protected areas has been emphasized as a countermeasure to the climate change, and protected areas allow the area to continue to serve as a carbon sink due to legal restrictions. This study attempted to expand the scope of these protected areas to an evaluation-based environmental spatial information theme map. In this study, the area of each grade was compared, and the distribution of land cover for each grade was analyzed using the Ecological and Nature Map, Environmental Conservation Value Assessment Map and Urban Ecological Map of Sejong Special Self-Governing City. Based on this, the average carbon storage for each grade was derived using the InVEST Carbon model. As a result of the analysis, the high-grade area of the environmental spatial information generally showed a wide area of the natural area represented by the forest area, and accordingly, the carbon storage amount was evaluated to be high. However, there are differences in the purpose of production, evaluation items, and evaluation methods between each environmental spatial information, there are differences in area, land cover, and carbon storage. Through this study, environmental spatial information based on the evaluation map can be used for land use management in the carbon aspect, and it is expected that a management plan for each grade suitable for the characteristics of each environmental spatial information is required.

• Spatial Information Research
• /
• v.20 no.5
• /
• pp.25-35
• /
• 2012

This study compared the influence of water quality according to the data sources of spatial information. Firstly, land cover map was constructed through image classification of Daecheong-dam basin and the accuracy of image classification from satellite image showed high as 88.76% in comparison with the large-scaled land cover map in Ministry of Environment, to calculate Event Mean Concentration (EMC) by land cover that impact on the evaluation of nonpoint source pollutant loads. Also curve number and direct runoff were calculated by spatial overlay with soil map and land cover map from image classification. And Seokcheon and Daecheong-Dam basin showed high in the analysis of curve number and direct runoff. Samgacheon-Joint and Sokcheon-Downstream basin showed high in the nonpoint source pollutant loads of BOD from direct runoff and EMC. And Samgacheon-Joint and Bonghwangcheon- Downstream basin showed high in the nonpoint source pollutant loads of TN and TP. Nonpoint source pollutant loads from image classification were compared with those by the land cover map from Ministry of Environment to present the effectivity of nonpoint source pollutant loads from satellite image. And Daecheong-Dam Upstream basin showed high as 10.64%, 11.70% and 20.00% respectively in the errors of nonpoint source pollutant loads of BOD, TN, and TP. Therefore, it is desirable that spatial information including with paddy and dry field is applied to the evaluation of nonpoint source pollutant loads in order to simulate water quality of basin effectively.