• 제목/요약/키워드: land use and land classification

검색결과 357건 처리시간 0.024초

토지피복지도 제작을 위한 초분광 영상 EO-1 Hyperion의 최적밴드 선택기법 연구 (A Study on the EO-1 Hyperion's Optimized Band Selection Method for Land Cover/Land Use Map)

  • 장세진;이호남;김진광;채옥삼
    • 한국측량학회지
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    • 제24권3호
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    • pp.289-297
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    • 2006
  • 토지피복지도는 토지의 피복특성과 토지활용특성을 나타내는 자료로서 토지피복분류체계에 따라 계층적인 구조로 1998년부터 제작되고 있다. 대분류는 Landsat 위성영상을 활용하여 남 북한에 대한 작업이 완료되었으며, 중분류는 IRS-1C, IRS-1D, KOMPSAT, SPOT-5 영상을 저해상 컬러 영상과 영상융합을 한 후, 그 결과자료를 전문가가 도화하여 제작하고 있다. 특히 도화에 의한 중분류 토지피복지도 제작은 위성영상의 구매 및 자료처리, 토지피복 지도제작 과정에서 막대한 비용이 필요하다. 본 논문에서는 최근 많은 연구가 수행되고 있는 초분광 위성영상인 EO-1 Hyperion을 이용한 중분류 토지피복지도 제작 가능성을 연구했다. 많은 분광정보를 제공하는 Hyperion 영상과 기존에 사용하던 Landsat-7 ETM+ 영상의 토지피복분류 비교 연구를 수행하여 Hyperion의 분류정확도를 평가했다. 또한, Hyperion에 적합한 최적밴드선택 방법을 통하여 초분광 위성영상 활용의 효율성을 증대시켰다.

국토변화탐지를 위한 지형분류체계 개선안 (Proposal of Feature Classification System for Land Change Detection)

  • 박준구;노명종;조우석;방기인
    • 대한공간정보학회지
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    • 제19권2호
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    • pp.9-17
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    • 2011
  • 국내 여러 기관에서 토지피복분류체계, 토지이용현황분류체계 등 국토의 정확한 현황 파악을 위해 다양한 지형분류체계를 활용 중에 있다. 그러나 이러한 분류체계로 국토변화를 탐지하기에는 적용성이 떨어지며, 변화지역을 추출하기에도 적합하지 않다는 문제점을 가지고 있다. 본 연구에서는 국토에 대한 자연적, 인위적 변화요소들을 모두 효과적으로 나타낼 수 있는 표준 지형분류체계를 제안하고자 한다. 이를 위해 국내외 유사 지형분류체계에 대한 비교 분석을 수행하고, 이를 바탕으로 표준 지형분류 항목을 제안하였다. 자동 지형분류 적용 가능성을 평가하기 위하여 감독분류 기반의 자동 지형분류와 선행지식 기반의 자동 지형분류를 수행하여 정확도를 평가하였다.

Land Suitability Analysis using GIS and Satellite Imagery

  • Yoo, Hwan-Hee;Kim, Seong-Sam;Ochirbae, Sukhee;Cho, Eun-Rae;Park, Hong-Gi
    • 한국측량학회지
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    • 제25권6_1호
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    • pp.499-505
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    • 2007
  • A method of improving the correctness and confidence in land use classification as well as urban spatial structure analysis of local governments using GIS and satellite imagery is suggested. This study also compares and analyzes LSAS (Land Suitability Assessment System) results using two approaches-LSAS with priority classification, and LSAS using standard estimation factors without priority classification. The conclusions that can be drawn from this study are as follows. First, a method of maintaining up-to-date local government data by updating the LSAS database using high-resolution satellite imagery is suggested. Second, to formulate a scientific and reasonable land use plan from the viewpoint of territory development and urban management, a method of simultaneously processing the two described approaches is suggested. Finally, LSAS was constructed by using varieties of land information such as the cadastral map, the digital topographic map, varieties of thematic maps, and official land price data, and expects to utilize urban management plan establishment widely and effectively through regular data updating and problem resolution of data accuracy.

Impact of Land Use Land Cover Change on the Forest Area of Okomu National Park, Edo State, Nigeria

  • Nosayaba Osadolor;Iveren Blessing Chenge
    • Journal of Forest and Environmental Science
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    • 제39권3호
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    • pp.167-179
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    • 2023
  • The extent of change in the Land use/Land cover (LULC) of Okomu National Park (ONP) and fringe communities was evaluated. High resolution Landsat imagery was used to identify the major vegetation cover/land use systems and changes around the national park and fringe communities while field visits/ground truthing, involving the collection of coordinates of the locations was carried out to ascertain the various land cover/land use types identified on the images, and the extent of change over three-time series (2000, 2010 and 2020). The change detection was analyzed using area calculation, change detection by nature and normalized difference vegetation index (NDVI). The result of the classification and analysis of the LULC Change of ONP and fringe communities revealed an alarming rate of encroachment into the protected area. All the classification features analyzed had notable changes from 2000-2020. The forest, which was the dominant LULC feature in 2000, covering about 66.19% of the area reduced drastically to 36.12% in 2020. Agricultural land increased from 6.14% in 2000 to 34.06% in 2020 while vegetation (degraded land) increased from 27.18% in 2000 to 38.89% in 2020. The magnitude of the change in ONP and surroundings showed the forest lost -247.136 km2 (50.01%) to other land cover classes with annual rate change of 10%, implying that 10% of forest land was lost annually in the area for 20 years. The NDVI classification values of 2020 indicate that the increase in medium (399.62 km2 ) and secondary high (210.17 km2 ) vegetation classes which drastically reduced the size of the high (38.07 km2 ) vegetation class. Consequent disappearance of the high forests of Okomu is inevitable if this trend of exploitation is not checked. It is pertinent to explore other forest management strategies involving community participation.

Standardized Agricultural Land Use Classification Scheme at Various Spatial Resolution of Satellite Images

  • Hong Seong Min;Jung In Kyun;Park Geun Ae;Kim Seong Joon
    • 한국농공학회논문집
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    • 제46권7호
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    • pp.15-21
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    • 2004
  • This study is to present a standardized agricultural land use classification scheme at various spatial resolution (from 1 m to 30 m) of satellite images including Landsat TM, KOMPSAT-1 EOC, ASTER VNIR and IKONOS panchromatic (PAN) and multi-spectral (MS) images. The satellite images were interpreted especially for identifying agricultural land use, crop types, agricultural facilities and structures of 18 items. It was found that there is a threshold spatial resolution between 4 m and 6.6 m to identify the full items. Thus it is suggested that IKONOS fusion image (MS enhanced by PAN) is required to produce land use map for agricultural purpose.

Land Use/Land Cover (LULC) Change in Suburb of Central Himalayas: A Study from Chandragiri, Kathmandu

  • Joshi, Suraj;Rai, Nitant;Sharma, Rijan;Baral, Nishan
    • Journal of Forest and Environmental Science
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    • 제37권1호
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    • pp.44-51
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    • 2021
  • Rapid urbanization and population growth have caused substantial land use land cover (LULC) change in the Kathmandu valley. The lack of temporal and geographical data regarding LULC in the middle mountain region like Kathmandu has been challenging to assess the changes that have occurred. The purpose of this study is to investigate the changes in LULC in Chandragiri Municipality between 1996 and 2017 using geographical information system (GIS) and remote sensing. Using Landsat imageries of 1996 and 2017, this study analyzed the LULC change over 21 years. The images were classified using the Maximum Likelihood classification method and post classified using the change detection technique in GIS. The result shows that severe land cover changes have occurred in the Forest (11.63%), Built-up areas (3.68%), Agriculture (-11.26%), Shrubland (-0.15%), and Bareland (-3.91%) in the region from 1996 to 2017. This paper highlights the use of GIS and remote sensing in understanding the changes in LULC in the south-west part of Kathmandu valley.

위성영상을 이용한 토지이용 변화 검색기법 비교연구 (Comparison of Land Use Change Detection Methods with Satellite Image)

  • 박순호;김우관
    • 한국지역지리학회지
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    • 제5권1호
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    • pp.137-150
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    • 1999
  • 우리나라에서 위성자료를 이용한 토지이용에 관한 연구는 현황분석이 중심이고, 토지이용 변화에 관한 연구는 분석기법에 대한 적실성 평가 없이 특정기법이 적용되어 왔다. 본 연구는 도시지역의 토지이용 변화 검색에 많이 활용되고 있는 다섯 가지 토지이용 변화 검색기법을 선정하여 대구광역시 북구를 사례로 각 검색기법의 정확도를 비교 분석하였다. 핵심데이터는 1994년과 1997년에 촬영한 Landsat TM영상과 항공사진이다. 위성자료를 이용한 토지이용 변화검색에는 pre-classification comparison method가 post-classification comparison method보다 효과적이었다. Pre-classification comparison methods 중에서는 image differencing method가, 특히 임계치 1.0에서의 image differencing method의 DIF2 변화이미지의 경우가 가장 정확도가 높게 나타났다.

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일본의 토지적성구분론과 우리나라의 적용성 고찰 (Review of Land Suitability Classification in Japan and Its Application to Korea)

  • 황한철;최수명
    • 농촌계획
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    • 제2권2호
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    • pp.45-56
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    • 1996
  • Land suitability classification(LSC) is an appraisal and grouping(or the process of appraisal anti grouping) of specific tracts(of land) in terms of their relative land suitability for a definEd use, and is one of the land use planning techniques. This paper reviews the selected studies on LSC whose purposes are to especially contribute land use planning in case of Japan, So, this study examines the LSC's application to Korea based on Japanes LSC studies with a view to development of the methods on LSC for rational land use planning in our rural area. The result resolves itself into Table 2. However, it is undesirable to borrow from Japanes LSC studies like that, because of the difference of administrative,geographical,traditional,social and economical conditions. Therefore, it is necessary that the many case studies and examinations should be carried out in order to develop the methods on LSC suitable to Korean actual circumstances.

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도시생태계 구조를 고려한 비오톱 유형 구분 (Biotope-Type Classification Considering Urban Ecosystem Structure)

  • 김정호;한봉호
    • 한국조경학회지
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    • 제34권2호
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    • pp.1-17
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    • 2006
  • The purpose of this study was to analyze biotope types of urban land-use patterns. Forest areas were considered according to vegetation type and potential for succession. Urban ecosystem structure was analyzed according to land use, land coverage, vegetation structure (actual vegetation, diameter at breast height, layer structure, and revetment). As a results of the classification, the biotopes were divided into 71 types according to the urban ecosystem structure. In the case of the Hanam province, the biotopes were divided into 51 types: 26 forest types; 5 swampy and grass land types; 3 farm land types; 3 types of planted land, and 8 types of urbanization.

Land use classification using CBERS-1 data

  • Wang, Huarui;Liu, Aixia;Lu, Zhenhjun
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.709-714
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    • 2002
  • This paper discussed and analyzed results of different classification algorithms for land use classification in arid and semiarid areas using CBERS-1 image, which in case of our study is Shihezi Municipality, Xinjiang Province. Three types of classifiers are included in our experiment, including the Maximum Likelihood classifier, BP neural network classifier and Fuzzy-ARTMAP neural network classifier. The classification results showed that the classification accuracy of Fuzzy-ARTMAP was the best among three classifiers, increased by 10.69% and 6.84% than Maximum likelihood and BP neural network, respectively. Meanwhile, the result also confirmed the practicability of CBERS-1 image in land use survey.

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