• 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.

• 한국지리정보학회지
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• 제26권1호
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• pp.69-88
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• 2023

효율적인 공간계획은 기후변화에 성공적으로 대응하기 위해 필요한 요소 중 하나이다. 연구자들은 흔히 토지이용 및 공간계획 연구를 수행하기 위해 LULC(Land-Use/Land-Cover) 데이터를 활용하고 있다. 그러나 LULC 데이터는 어떠한 도시 표면의 특징을 분류할 수 있는 조건이 몇 가지로 한정되어 있어 여러 도시에서 나타나는 각기 다른 도시구조를 기존 토지피복 분류법으로는 쉽게 분석할 수 없다. 이러한 토지피복 자료의 한계는 도시 열섬 분야에서 사용되는 LCZ(Local Climate Zone) 자료를 통해 극복될 것으로 보인다. 따라서 본 연구는 먼저 LCZ 데이터가 도시 열섬 분야뿐만 아니라 다른 분야에도 적용될 수 있는지를 논의하고, 두 번째로 LCZ 데이터가 기존 LULC 데이터의 문제점을 동일하게 가지는지 논의하는 것을 목적으로 한다. 연구 방법론은 크게 두 가지로 진행된다. 첫째, 문헌고찰을 통해 LCZ와 관련된 기후, 토지이용, 도시공간구조 분야의 연구를 종합하여 현재 어떤 연구에 LCZ 데이터가 활용되고 있는지, 토지이용과 도시공간구조 분야에서 어떻게 적용·활용될 수 있는지 분석한다. 다음으로 GIS 공간분석을 활용하여 LCZ 데이터도 역시 LULC 데이터에 내재한 몇 가지 오류를 공유하고 있는지에 대해 비교·분석한다.

• 대한원격탐사학회지
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• 제32권4호
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• pp.353-364
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• 2016

Yangon city is experienced a rapid urban expansion over the last two decades due to accelerate with the socioeconomic development. This research work studied an investigation into the application of the integration of the Remote Sensing (RS) and Geographic Information System (GIS) for observing Land Use and Land Cover (LULC) patterns and evaluate its impact on Land Surface Temperature (LST) of the downtown, suburban 1 and suburban 2 of Yangon city. The main purpose of this paper was to examine and analyze the variation of the spatial distribution property of the LULC of urban spatial information related with the LST and Normalized Difference Vegetation Index (NDVI) using RS and GIS. This paper was observed on image processing of LULC classification, LST and NDVI were extracted from Landsat 8 Operational Land Imager (OLI) image data. Then, LULC pattern was linked with the variation of LST data of the Yangon area for the further connection of the correlation between surface temperature and urban structure. As a result, NDVI values were used to examine the relation between thermal behavior and condition of land cover categories. The spatial distribution of LST has been found mixed pattern and higher LST was located with the scatter pattern, which was related to certain LULC types within downtown, suburban 1 and 2. The result of this paper, LST and NDVI analysis exhibited a strong negative correlation without water bodies for all three portions of Yangon area. The strongest coefficient correlation was found downtown area (-0.8707) and followed suburban 1 (-0.7526) and suburban 2(-0.6923).

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.516-518
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• 2003

This study discusses an effort to build a model to link normalized difference vegetation indices (NDVI) and socio-economic indicators derived from village survey (1990, 1993, 1996, and 2000) statistical data in Bekasi, West Java, Indonesia. Socio-economics indicators of sub-district level, in this study the number of agricultural households (AH), are aggregated from village level data. NDVI from Landsat-TM resolution data (1989 and 1997) are computed to detect land use/land cover (LULC) dynamics in the sub-district areas. Attention is mainly paid on the examination of agricultural land cover changing in the sub-district level. NDVI measurements might be used to predict AH dynamics as showed by computed linear regression models.

• 대한원격탐사학회지
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• 제38권1호
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• pp.111-126
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• 2022

Land use and land cover (LULC) mapping is an important factor in geospatial analysis. Although highly precise ground-based LULC monitoring is possible, it is time consuming and costly. Conversely, because the synthetic aperture radar (SAR) sensor is an all-weather sensor with high resolution, it could replace field-based LULC monitoring systems with low cost and less time requirement. Thus, LULC is one of the major areas in SAR applications. We developed a LULC model using only KOMPSAT-5 single co-polarized data and digital elevation model (DEM) data. Twelve HH-polarized images and 18 VV-polarized images were collected, and two HH-polarized images and four VV-polarized images were selected for the model testing. To train the LULC model, we applied the conditional generative adversarial network (cGAN) method. We used U-Net combined with the residual unit (ResUNet) model to generate the cGAN method. When analyzing the training history at 1732 epochs, the ResUNet model showed a maximum overall accuracy (OA) of 93.89 and a Kappa coefficient of 0.91. The model exhibited high performance in the test datasets with an OA greater than 90. The model accurately distinguished water body areas and showed lower accuracy in wetlands than in the other LULC types. The effect of the DEM on the accuracy of LULC was analyzed. When assessing the accuracy with respect to the incidence angle, owing to the radar shadow caused by the side-looking system of the SAR sensor, the OA tended to decrease as the incidence angle increased. This study is the first to use only KOMPSAT-5 single co-polarized data and deep learning methods to demonstrate the possibility of high-performance LULC monitoring. This study contributes to Earth surface monitoring and the development of deep learning approaches using the KOMPSAT-5 data.

• 한국대기환경학회지
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• 제25권3호
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• pp.196-210
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• 2009

The land surface precesses is very important to predict urban meteorological conditions. Thus, the latest land use data set to reflect the rapid progress in urbanization was applied to simulate urban thermal environment in Daegu. Because use of the U.S geological Survey (USGS) 25-category data, currently in the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5), does not accurately described the heterogeneity of urban surface, we replaced the land use data in USGS with the latest land-use data of the Korea Ministry of Environment over Daegu. The single urban category in existing 24-category U.S. Geological survey land cover classification used in MM5 was divided into 5 classes to account for heterogeneity of urban land cover. The new land cover classification (MC-LULC) improved the capability of MM5 to simulate the daytime part of the diurnal temperature cycle in the urban area. The 'MC-LULC' simulation produced the observed temperature field reasonably well, including spatial characteristics. The warm cores in western Daegu is characterized by an industrial area.

• Advances in environmental research
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• 제9권1호
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• pp.19-39
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• 2020

Urban heat island (UHI) is one of the most important climatic implications of urbanization and thus a matter of key concern for environmentalists of the world in the twenty-first century. The relationship between climate and urbanization has been better understood with the introduction of thermal remote sensing. So, this study is an attempt to understand the influence of urbanization on local temperature for a small developing city. The study focuses on the investigation of intensity of atmospheric and surface urban heat island for a small urbanizing district of Punjab, India. Landsat 8 OLI/TIRS satellite data and field observations were used to examine the spatial pattern of surface and atmospheric UHI effect respectively, for the month of April, 2018. The satellite data has been used to cover the larger geographical area while field observations were taken for simultaneous and daily temperature measurements for different land use types. The significant influence of land use/land cover (LULC) patterns on UHI effect was analyzed using normalized built-up and vegetation indices (NDBI, NDVI) that were derived from remote sensing satellite data. The statistical analysis carried out for land surface temperature (LST) and LULC indicators displayed negative correlation for LST and NDVI while NDBI and LST exhibited positive correlation depicting attenuation in UHI effect by abundant vegetation. The comparison of remote sensing and in-situ observations were also carried out in the study. The research concluded in finding both nocturnal and daytime UHI effect based on diurnal air temperature observations. The study recommends the urgent need to explore and impose effective UHI mitigation measures for the sustainable urban growth.

• 대한공간정보학회지
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• 제21권2호
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• pp.107-116
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• 2013

본 연구는 새로운 기후변화 시나리오인 RCP 시나리오의 스토리라인을 기반으로 미래 토지피복변화를 예측하고, RCP 시나리오하의 미래 기후 및 토지피복 변화가 유역 내 유출량에 미치는 영향을 분석하는데 그 목적을 둔다. RCP 4.5 및 8.5하의 기후 자료가 기후변화 시나리오로 사용되었고, 토지피복변화 시나리오는 RCP 4.5 및 8.5 시나리오의 스토리라인과 로지스틱 회귀모형(LR)을 이용하여 개발된 모델에 의해 생성되었다. 기후변화만 고려한 경우, 토지피복변화만 고려한 경우로 두 가지 시나리오를 설정하고, 각각의 시나리오에 따른 대상 유역 내 유출량을 모의한 결과는 유출량의 계절적 변화를 뚜렷이 나타내었다. 기후변화는 봄과 겨울에 유출량을 증가, 여름과 가을에 유출량을 감소시키는 것으로 예측되었다. 반면 토지피복변화는 기후변화에 비해 상대적으로 유역 내 유출량 변화에 미소한 영향을 주지만, 강수 유무에 따라 유출량의 증가 및 감소 패턴이 뚜렷이 나타났다. 따라서 수자원 정책결정에 있어서 미래 토지피복변화에 따른 홍수 및 가뭄의 패턴에 적합한 수자원 정책이 필요할 것으로 판단된다.

• 한국물환경학회지
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• 제27권2호
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• pp.159-166
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• 2011

The use of land cover was sharply changed during 1975~2007 in the Kyungan watershed $(561.12 km^2)$. The changes occurred over an area of more than $227.65 km^2$ during the overall period at changing rates of 1.04% per year for water area, 1.79% per year for residential area, 2.99% per year for bare area, 3.03% per year for wetland area, 3.04% per year for grass area, 0.87% per year for forest and 2.32% per year for agriculture area. Water, residential, bare and wetland areas increased, while grass, forest and agriculture areas decreased during the last 32 years. BOD concentrations of representative sites for each sub-watershed continuously increased until the early 2000s as residential area increased with the highest discharged load, but decreased after the mid 2000s except upper Kyungan watershed. Such decline appears to be associated with the planning of Total Maximum Daily Load management for Gwangju city and expansion of waste water treatment plant. It is necessary to control land use/cover changes of the upper watershed and to prepare appropriate watershed management system for improvement in river environment including water quality, stream flow and bio-diversity.

• 한국지리정보학회지
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• 제16권2호
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• pp.47-64
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• 2013

본 연구에서는 위성 자료를 기반으로 생성된 토지피복 정보를 시계열적인 분석을 통해 지난 30년간 부산 경남 지역의 경관 구조 변화를 추적하고 해당 지역 기온 변화와의 상관성을 파악하였다. 토지 피복 자료의 기하학적 구조를 정량화하기 위해 경관구조 분석 프로그램인 FRAGSTATS를 사용하여 토지피복별 경관지수를 산출하였다. 이를 통해 주요 토지이용의 변화상과 개발에 따른 경관의 분절화 과정을 확인하였다. 부산과 경남 지역의 10개 측후소 자료에 따르면, 부산의 평균 기온은 1980년대 $14.1^{\circ}C$에서 2000년대 $14.8^{\circ}C$로 증가하였고, 경남 지역의 평균 기온은 1980년대 $13.2^{\circ}C$에서 2000년대 $13.9^{\circ}C$로 증가하였다. 이러한 장기 기온 변화패턴은 도시화와 같은 우리나라 동남부의 전형적인 경관구조 변화와 상관성을 갖는 것으로 판단된다. 부산시 분석 자료에 의하면, 지난 30년간 도시역은 전체 면적의 9.7%에서 26.8%로 증가하였고, 산림과 농경지는 각각 58%에서 48.4%로, 28.3%에서 13.4%로 감소하였다. 해당 기간별 기온자료와 비교해보면, 도시역이 증가하고 산림과 농경지 면적이 꾸준히 감소함에 따라 부산의 평균기온이 1990년대 이후 큰 폭으로 증가하였다. 경남지역의 도시역 면적은 12배 이상 증가해 매우 빠른 도시화를 겪었다. 도시화에 따른 기온 변화는 지역적으로 구분되었는데, 경남 해안지역은 기온상승의 폭이 가장 낮았고 중부경남에 이어 내륙 산악지역에서 가장 높은 기온증가율이 나타났다.