• Title/Summary/Keyword: Land-use and land-cover map

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Analysis of SWAT Simulated Errors with the Use of MOE Land Cover Data (환경부 토지피복도 사용여부에 따른 예측 SWAT 오류 평가)

  • Heo, Sung-Gu;Kim, Nam-Won;Yoo, Dong-Sun;Kim, Ki-Sung;Lim, Kyoung-Jae
    • Proceedings of the Korea Water Resources Association Conference
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    • 2008.05a
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    • pp.194-198
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    • 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.

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A Probability Mapping for Land Cover Change Prediction using CLUE Model (토지피복변화 예측을 위한 CLUE 모델의 확률지도 생성)

  • Oh, Yun-Gyeong;Choi, Jin-Yong;Bae, Seung-Jong;Yoo, Seung-Hwan;Lee, Sang-Hyun
    • Journal of Korean Society of Rural Planning
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    • v.16 no.2
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    • pp.47-55
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    • 2010
  • Land cover and land use change data are important in many studies including climate change and hydrological studies. Although the various theories and models have been developed, it is difficult to identify the driving factors of the land use change because land use change is related to policy options and natural and socio-economic conditions. This study is to attempt to simulate the land cover change using the CLUE model based on a statistical analysis of land-use change. CLUE model has dynamic modeling tools from the competition among land use change in between driving force and land use, so that this model depends on statistical relations between land use change and driving factors. In this study, Yongin, Icheon and Anseong were selected for the study areas, and binary logistic regression and factor analysis were performed verifying with ROC curve. Land cover probability map was also prepared to compare with the land cover data and higher probability areas are well matched with the present land cover demonstrating CLUE model applicability.

Extraction of Change of the Urban Area in Seoul from the Satellate (LANDSAT) Data (인공위성(LANDSAT) Data에 의한 서울시에 있어서의 도시역의 변화의 추출)

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

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Assessment of Land Cover Changes from Protected Forest Areas of Satchari National Park in Bangladesh and Implications for Conservation

  • Masum, Kazi Mohammad;Hasan, Md. Mehedi
    • Journal of Forest and Environmental Science
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    • v.36 no.3
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    • pp.199-206
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    • 2020
  • Satchari National Park is one of the most biodiverse forest in Bangladesh and home of many endangered flora and fauna. 206 tons of CO2 per hectare is sequestrated in this national park every year which helps to mitigate climate issues. As people living near the area are dependent on this forest, degradation has become a regular phenomenon destroying the forest biodiversity by altering its forest cover. So, it is important to map land cover quickly and accurately for the sustainable management of Satchari National Park. The main objective of this study was to obtain information on land cover change using remote sensing data. Combination of unsupervised NDVI classification and supervised classification using maximum likelihood is followed in this study to find out land cover map. The analysis showed that the land cover is gradually converting from one land use type to another. Dense forest becoming degraded forest or bare land. Although it was slowed down by the establishment of 'National Park' on the study site, forecasting shows that it is not enough to mitigate forest degradation. Legal steps and proper management strategies should be taken to mitigate causes of degradation such as illegal felling.

A Study on the Strategies for Spatial Information Service based on the Concept of Atlas - A Case Study of Land Cover Map - (아틀라스 개념을 적용한 공간정보서비스 방안 - 토지피복지도를 사례로 -)

  • Hong, Sang Ki
    • Journal of Korean Society for Geospatial Information Science
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    • v.20 no.4
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    • pp.153-159
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    • 2012
  • Recently, tthe general users' demand on utilizing spatial information and the establishment of national spatial data such as land cover map are increasingly growing. But the lack of spatial information service for the general public is making it difficult for them to use spatial information and services. In this study, spatial information service strategies based on the concept of atlas, which is familiar to us through the student atlas, were proposed to promote the public users' utilization of land cover map. For this purpose, I reviewed current domestic status and overseas cases of land cover map service and proposed the future direction of spatial information service for land cover map in terms of contents, users, and system. Finally, I defined the basic concept, characteristics and functions of the Atlas Information System and recommended strategies for environmental spatial information service. The results of this study can be applied to various national spatial information as well as land cover map and contribute to the increase of general public users' utilization of national spatial data.

Improving of land-cover map using IKONOS image data (IKONOS 영상자료를 이용한 토지피복도 개선)

  • 장동호;김만규
    • Spatial Information Research
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    • v.11 no.2
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    • pp.101-117
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    • 2003
  • High resolution satellite image analysis has been recognized as an effective technique for monitoring local land-cover and atmospheric changes. In this study, a new high resolution map for land-cover was generated using both high-resolution IKONOS image and conventional land-use mapping. Fuzzy classification method was applied to classify land-cover, with minimum operator used as a tool for joint membership functions. In separateness analysis, the values were not great for all bands due to discrepancies in spectral reflectance by seasonal variation. The land-cover map generated in this study revealed that conifer forests and farm land in the ground and tidal flat and beach in the ocean were highly changeable. The kappa coefficient was 0.94% and the overall accuracy of classification was 95.0%, thus suggesting a overall high classification accuracy. Accuracy of classification in each class was generally over 90%, whereas low classification accuracy was obtained for classes of mixed forest, river and reservoir. This may be a result of the changes in classification, e.g. reclassification of paddy field as water area after water storage or mixed use of several classification class due to similar spectral patterns. Seasonal factors should be considered to achieve higher accuracy in classification class. In conclusion, firstly, IKONOS image are used to generated a new improved high resolution land-cover map. Secondly, IKONOS image could serve as useful complementary data for decision making when combined with GIS spatial data to produce land-use map.

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The Expectation of the Land Use and Land Cover Using CLUE-S Model and Landsat Images (CLUE-S 모델과 시계열 Landsat 자료를 이용한 토지피복 변화 예측)

  • Kim, Woo-Sun;Yun, Kong-Hyun;Heo, Joon;Jayakumar, S.
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.1
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    • pp.33-41
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    • 2008
  • Land use/land cover is very important to understand the change in the land cover between specific periods. But as there are number of factors which are responsible for the change in the land cover, it is very difficult to identify the specific factors. Therefore in the study we made an attempt to use the land use strategies quantitatively and conducted simulation study. The input data using the CLUE-S model are the satellite data of 1987 and 2001 from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) and we conducted simulations for 23 years from 1987 to 2010. As a result, the accuracy between the land use map derived from original satellite data and simulation for 2001 was 93.69% and in this reason we could expect land use and land cover in the future.

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Evaluation of a Land Use Change Matrix in the IPCC's Land Use, Land Use Change, and Forestry Area Sector Using National Spatial Information

  • Park, Jeongmook;Yim, Jongsu;Lee, Jungsoo
    • Journal of Forest and Environmental Science
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    • v.33 no.4
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    • pp.295-304
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    • 2017
  • This study compared and analyzed the construction of a land use change matrix for the Intergovernmental Panel on Climate Change's (IPCC) land use, land use change, and forestry area (LULUCF). We used National Forest Inventory (NFI) permanent sample plots (with a sample intensity of 4 km) and permanent sample plots with 500 m sampling intensity. The land use change matrix was formed using the point sampling method, Level-2 Land Cover Maps, and forest aerial photographs (3rd and 4th series). The land use change matrix using the land cover map indicated that the annual change in area was the highest for forests and cropland; the cropland area decreased over time. We evaluated the uncertainty of the land use change matrix. Our results indicated that the forest land use, which had the most sampling, had the lowest uncertainty, while the grassland and wetlands had the highest uncertainty and the least sampling. The uncertainty was higher for the 4 km sampling intensity than for the 500 m sampling intensity, which indicates the importance of selecting the appropriate sample size when constructing a national land use change matrix.

A Study to Evaluate Impervious Area Ratio by Geographic Information Data (지리정보자료에 따른 불투수면적률 산정 결과에 대한 연구)

  • Min Suh Chae;Kyoung Jae Lim;Joong-Hyuk Min;Minji Park;Jichul Ryu;Mijin Lee;Sohyeon Park;Youn Shik Park
    • Journal of Korean Society on Water Environment
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    • v.39 no.2
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    • pp.142-152
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    • 2023
  • Infiltration is a process by which precipitation infuses into subsurface soils. The process determines the surface flow and baseflow volume, and it is one of most important hydrological processes regarding nonpoint source pollution management. Therefore, the Ministry of Environment has developed a guideline to determine the impervious area ratio to understand the hydrological process in administrative districts and watersheds. The impervious area ratio can be determined using land use or land cover maps. Three approaches were explored to determine the impervious area ratio in 25 districts in Seoul. The impervious area ratio was determined by employing the Land registration map and Land property data in the first approach, Land property map in the second approach, and Land cover map in the third approach. The ratio ranged from 38.96% to 83.01% in the first approach, 38.98% to 83.02% in the second approach, and 37.62% to 76.63% in the third approach. Although the ranges did not provide any significant differences in the approaches, some districts displayed differences up to 9.48% by the approach. These differences resulted from the fact that the data were land use or land cover, especially in the area of airport, residential complex area, and school sites. In other words, division of the pervious and impervious areas in an individual plot was not allowed in the Land registration map, while it was allowed in the Land cover map. Therefore, it was concluded that there is a need to revise the guideline so that a reasonable impervious area ratio can be determined in the districts.

A STUDY ON IDENTIFICATION OF URBAN CHARACTERISTIC USING SPATIAL ARRANGEMENT METHOD

  • Chou, Tien-Yin;Kuo, Ching-Yi
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.984-987
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    • 2003
  • In order to rapidly catch up urban region’s detailed land-use or land-cover information; this research used the post-classification algorithm (Spatial Reclassification Kernel: SPARK) to create a land-use map of Taichung City. We discussed the urban land-use classification model with the IKONOS images. The conclusions may be distinguished as follows:(a) Using the Maximum-Likelihood algorithm to classify seven broad land-cover categories. The overall accuracy in this stage achieves 92.72% and Kappa coefficient will be obtained 0.91; and (b) Using the SPARK method to classify images for detect the land-use, the overall accuracy achieves higher 89.64% and Kappa coefficient will be 0.86. To conclude, the research process in this study can fully and carefully describe local land-use pattern and assist the demand of land management and resources planning reference.

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