• Title/Summary/Keyword: Land cover

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The Study on Improving Accuracy of Land Cover Classification using Spectral Library of Hyperspectral Image (초분광영상의 분광라이브러리를 이용한 토지피복분류의 정확도 향상에 관한 연구)

  • Park, Jung-Seo;Seo, Jin-Jae;Go, Je-Woong;Cho, Gi-Sung
    • Journal of Cadastre & Land InformatiX
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    • v.46 no.2
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    • pp.239-251
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    • 2016
  • Hyperspectral image is widely used for land cover classification because it has a number of narrow bands and allow each pixel to include much more information in comparison with previous multi-spectral image. However, Higher spectral resolution of hyperspectral image results in an increase in data volumes and a decrease in noise efficiency. SAM(Spectral Angle Mapping), a method based on vector inner product to compare spectrum distribution, is a highly valuable and popular way to analyze continuous spectrum of hyperspectral image. SAM is shown to be less accurate when it is used to analyze hyperspectral image for land cover classification using spectral library. this inaccuracy is due to the effects of atmosphere. We suggest a decision tree based method to compensate the defect and show that the method improved accuracy of land cover classification.

Regional land cover patterns, changes and potential relationships with scaled quail (Callipepla squamata) abundance

  • Rho, Paikho;Wu, X. Ben;Smeins, Fred E.;Silvy, Nova J.;Peterson, Markus J.
    • Journal of Ecology and Environment
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    • v.38 no.2
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    • pp.185-193
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    • 2015
  • A dramatic decline in the abundance of the scaled quail (Callipepla squamata) has been observed across most of its geographic range. In order to evaluate the influence of land cover patterns and their changes on scaled quail abundance, we examined landscape patterns and their changes from the 1970s to the1990s in two large ecoregions with contrasting population trends: (1) the Rolling Plains ecoregion with a significantly decreased scaled quail population and (2) the South Texas Plains ecoregion with a relatively stable scaled quail population. The National Land Cover Database (NLCD) and the U.S. Geological Survey's (USGS) Land Use/Land Cover data were used to quantify landscape patterns and their changes based on 80 randomly located $20{\times}20km^2$ windows in each of the ecoregions. We found that landscapes in the Rolling Plains and the South Texas Plains were considerably different in composition and spatial characteristics related to scaled quail habitats. The landscapes in the South Texas Plains had significantly more shrubland and less grassland-herbaceous rangeland; and except for shrublands, they were more fragmented, with greater interspersion among land cover classes. Correlation analysis between the landscape metrics and the quail-abundance-survey data showed that shrublands appeared to be more important for scaled quail in the South Texas Plains, while grassland-herbaceous rangelands and pasture-croplands were essential to scaled quail habitats in the Rolling Plains. The decrease in the amount of grassland-herbaceous rangeland and spatial aggregation of pasture-croplands has likely contributed to the population decline of scaled quails in the Rolling Plains ecoregion.

The Land-cover Changes and Pattern Analysis in the Tidal Flats Using Post-classification Comparison Method: The Case of Taean Peninsula Region (선분류 후비교법을 이용한 간석지의 토지피복 변화 및 패턴 분석 - 태안반도 지역을 사례로 -)

  • Jang, Dong-Ho;Kim, Chan-Soo;Park, Ji-Hoon
    • Journal of the Korean Geographical Society
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    • v.45 no.2
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    • pp.275-292
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    • 2010
  • This study investigated the land-cover changes in the tidal flat of the Taean peninsula due to man-made environmental changes between 1972 and 2008, through time-series analysis based on a modified post-classification comparison method and multi-temporal satellite images. The analysis revealed that the land-cover of the tidal flat has changed from tidal flat to wetland and from wetland to paddy field between 1972 and 2008. Also, the pattern of detailed land-cover changes is as follows: tidal flat to wetland; lake and saltpan to bare land and paddy field. The accurate classification of each image is needed for the application of the post-classification comparison method. The overall accuracy of the classified images was found to be 95.33% on average, and the Kappa value was 0.941 on average.

A Study on Improvement of Air Quality Dispersion Model Application Method in Environmental Impact Assessment (I) - Focusing on AERMOD Meteorological Preprocessor - (환경영향평가에서의 대기질 확산모델 적용방법 개선 연구(I) - AERMOD 기상 전처리를 중심으로 -)

  • Kim, Suhyang;Park, Sunhwan;Tak, Jongseok;Ha, Jongsik;Joo, Hyunsoo;Lee, Naehyun
    • Journal of Environmental Impact Assessment
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    • v.31 no.5
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    • pp.271-285
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    • 2022
  • The AERMET, the AERMOD meteorological preprocessing program, mainly used for environmental impact assessment and Integrated Environmental Permit System (IEPS) in Korea, has not considered the land covers characterasitics, and used only the past meteorological data format CD-144. In this study, two results of AERMET application considering CD-144 format and ISHD format, being used internationally, were compared. Also, the atmospheric dispersion characteristics were analyzed with consideration of land cover. In the case of considered the CD-144 format, the actual wind speed was not taken into account in the weak wind (0.6~0.9m/s) and other wind speed due to the unit conversion problem. The predicted concentration considering land cover data was up to 387% larger depending on the topographic and emission conditions than without consideration of land cover. In conclusion, when using meteorological preprocessing program in AERMOD modelling, AERMET, with ISHD format, land cover characterasitics in the area should be considered.

Matching Techniques with Land Cover Image for Improving Accuracy of DEM Generation from IKONOS Imagery (IKONOS 영상을 이용한 DEM 추출의 정확도 향상을 위한 토지피복도 활용 정합기법)

  • Lee, Hyo Seong;Park, Byung Uk;Han, Dong Yeob;Ahn, Ki Weon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.1D
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    • pp.153-160
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    • 2009
  • In relation to digital elevation model(DEM) production using high resolution satellite imagery, existing studies present that DEM accuracy differently show according to land cover property. This study therefore proposes auto-selection method of window size for correlation matching according to land cover property of IKONOS Geo-level stereo image. For this, land cover classified image is obtained by IKONOS color image with four bands. In addition, correlation-coefficients are computed at regular intervals in pixels of the window-search area to shorten of matching time. As the results, DEM by the proposed method showed more accurate than DEM using the fixed window-size matching. We estimate that accuracy of the proposed DEM improved more than DEM by digital map and ERDAS in agricultural land.

Evaluating the Land Surface Characterization of High-Resolution Middle-Infrared Data for Day and Night Time (고해상도 중적외선 영상자료의 주야간 지표면 식별 특성 평가)

  • Baek, Seung-Gyun;Jang, Dong-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.2
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    • pp.113-125
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    • 2012
  • This research is aimed at evaluating the land surface characterization of KOMPSAT-3A middle infrared (MIR) data. Airborne Hyperspectral Scanner (AHS) data, which has MIR bands with high spatial resolution, were used to assess land surface temperature (LST) retrieval and classification accuracy of MIR bands. Firstly, LST values for daytime and nighttime, which were calculated with AHS thermal infrared (TIR) bands, were compared to digital number of AHS MIR bands. The determination coefficient of AHS band 68 (center wavelength $4.64{\mu}m$) was over 0.74, and was higher than other MIR bands. Secondly, The land cover maps were generated by unsupervised classification methods using the AHS MIR bands. Each class of land cover maps for daytime, such as water, trees, green grass, roads, roofs, was distinguished well. But some classes of land cover maps for nighttime, such as trees versus green grass, roads versus roofs, were not separated. The image classification using the difference images between daytime AHS MIR bands and nighttime AHS MIR bands were conducted to enhance the discrimination ability of land surface for AHS MIR imagery. The classification accuracy of the land cover map for zone 1 and zone 2 was 67.5%, 64.3%, respectively. It was improved by 10% compared to land cover map of daytime AHS MIR bands and night AHS MIR bands. Consequently, new algorithm based on land surface characteristics is required for temperature retrieval of high resolution MIR imagery, and the difference images between daytime and nighttime was considered to enhance the ability of land surface characterization using high resolution MIR data.

Detection of Urban Expansion and Surface Temperature Change using Landsat Satellite Imagery (Landsat 위성영상을 이용한 도시확장 및 지표온도 변화 탐지)

  • Song, Yeong-Sun
    • Journal of Korean Society for Geospatial Information Science
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    • v.13 no.4 s.34
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    • pp.59-65
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    • 2005
  • It is very important to detect land cover/land use change from the past and to use it for future urban plan. This paper investigated the application of Landsat satellite imagery for detecting urban growth and assessing its impact on surface temperature in the region. Land cover/land use change detection was carried out by using 30m resolution Landsat satellite images and hierarchial approach was introduced to detect more detail change on the changing area through high resolution aerial photos. Also, surface temperature according to land cover/land use was calculated from Landsat TM thermal infrared data and compared with real temperature to analyze the relationship between urban expansion and surface temperature. As a result, the urban expansion has raised surface radiant temperature in the urbanized area. The method using remote sensing data based on GIS was found to be effective in monitoring and analysing urban growth and in evaluating urbanization impact on surface temperature.

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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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Land Cover Change Detection in the Nakdong River Basin Using LiDAR Data and Multi-Temporal Landsat Imagery (LiDAR DEM과 다중시기에 촬영된 Landsat 영상을 이용한 낙동강 유역 내 토지피복 변화 탐지)

  • CHOUNG, Yun-Jae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.18 no.2
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    • pp.135-148
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    • 2015
  • This research is carried out for the land cover change detection in the Nakdong River basin before and after the 4 major rivers restoration project using the LiDAR DEM(Digital Elevation Model) and the multi-temporal Landsat imagery. Firstly the river basin polygon is generated by using the levee boundaries extracted from the LiDAR DEM, and the four river basin imagery are generated from the multi-temporal Landsat-5 TM(Thematic Mapper) and Landsat-8 OLI(Operational Land Imager) imagery by using the generated river basin polygon. Then the main land covers such as river, grass and bare soil are separately generated from the generated river basin imagery by using the image classification method, and the ratio of each land cover in the entire area is calculated. The calculated land cover changes show that the areas of grass and bare soil in the entire area have been significantly changed because of the seasonal change, while the area of the river has been significantly increased because of the increase of the water storage. This paper contributes to proposing an efficient methodology for the land cover change detection in the Nakdong River basin using the LiDAR DEM and the multi-temporal satellite imagery taken before and after the 4 major rivers restoration project.

A Study on Categorizing Ecosystem Groups for Climate Change Risk Assessment - Focused on Applicability of Land Cover Classification - (기후변화 리스크 평가를 위한 생태계 유형분류 방안 검토 - 국내 토지피복분류 적용성을 중심으로 -)

  • Yeo, Inae;Bae, Haejin;Hong, Seungbum
    • Journal of Environmental Impact Assessment
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    • v.26 no.6
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    • pp.385-403
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    • 2017
  • This study showed the national ecosystem classification for the spatial standards of ecosystems-based approaches to the risk assessments and adaptation plan. The characteristics of climate change risk assessment, implement national adaptation plans, and ecosystem/habitat classification status was evaluated. Focusing on the land cover classification widely utilized as spatial data for the assessments of biodiversity and ecosystem services in the UK and other countries in Europe, the applicability of the national land cover classification for climate change risk assessments was reviewed. Considering the ecosystem classification for climate change risk assessment and establishing adaptation measures, it is difficult to apply rough classification method to the land cover system because of lack of information on habitat trend by categorization. The results indicated that forest ecosystems and agro-ecosystem occupied 62.3% and 25.0% of land cover, respectively, of the entire country. Although the area is small compared with the land area, wetland ecosystem (2.9%), marine ecosystem (0.4%), coastal ecosystem (0.6%), and urban ecosystem (6.1%) can be included in the risk assessments. Therefore, it is necessary to subdivide below the medium classification for the forest and agricultural land, as well as Inland wetland, which has a higher proportion of habitat preference of taxa than land area, marine/coastal habitat, and transition areas such as urban and natural ecosystem.