• Journal of Environmental Science International
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• v.5 no.2
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• pp.103-112
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• 1996

Observational date is integral in our understanding of present climate, its natural variability and any cnange roue to anturopogenic effects. This study incorporates a brief overview of sampling requirements using data from the first ISLSCP Field Experiment (FIFE) in 1987, which was a multi-disciplinary field experiment over a 15km grid in Konza Prairie, USA. Sampling strategies were designed for precipitation and soil moisture measurements and also detecting land cover type. It was concludes that up to 8 raingages would be needed for valuable precipitation measurements covering the whole FIFE catchment, but only one soil moisture station. Results show that as new gages or station are added to the catchment then the sampling error is reduced, but the Improvement in error performance is less as the number of gages or stations increases. Sampling from remoteiy sensed instruments shows different results. It can be seen that the sampling error at 1arger resolution sizes are small due to competing error contribution from both commission and omission error.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1035-1046
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• 2022

This study evaluated the applicability of multi-resolution data fusion for land-cover classification. In the applicability evaluation, a spatial time-series geostatistical deconvolution/fusion model (STGDFM) was applied as a multi-resolution data fusion model. The study area was selected as some agricultural lands in Iowa State, United States. As input data for multi-resolution data fusion, Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite images were used considering the landscape of study area. Based on this, synthetic Landsat images were generated at the missing date of Landsat images by applying STGDFM. Then, land-cover classification was performed using both the acquired Landsat images and the STGDFM fusion results as input data. In particular, to evaluate the applicability of multi-resolution data fusion, two classification results using only Landsat images and using both Landsat images and fusion results were compared and evaluated. As a result, in the classification result using only Landsat images, the mixed patterns were prominent in the corn and soybean cultivation areas, which are the main land-cover type in study area. In addition, the mixed patterns between land-cover types of vegetation such as hay and grain areas and grass areas were presented to be large. On the other hand, in the classification result using both Landsat images and fusion results, these mixed patterns between land-cover types of vegetation as well as corn and soybean were greatly alleviated. Due to this, the classification accuracy was improved by about 20%p in the classification result using both Landsat images and fusion results. It was considered that the missing of the Landsat images could be compensated for by reflecting the time-series spectral information of the MODIS images in the fusion results through STGDFM. This study confirmed that multi-resolution data fusion can be effectively applied to land-cover classification.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.190-200
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• 2022

In this study, the island's land-use and land-cover change (LULCC) is analyzed in South Korea using remotely sensed land cover data(Globeland 30) acquired from 2000 to 2020 to meet the requirement of providing practical information for forest management. Analysis of LULCC between the 2000 and 2020 images revealed that changes to agricultural land were the most common type of change (7.6% of pixels), followed by changes to the forest (5.7%). The islands forests maintain 157,246 ha (42.2% of the total island area). Land cover types that changed to the forest from grasslands were 262 islands, while reverse cases have occurred on 421 islands. These 683 islands have a possibility of transition and disturbance. The artificial land class was newly calculated in 22 islands. The forests, which account for 42.2% of the 22 island area, turned into grassland, and 27.8% of agricultural land and grassland turned into forests. The development of artificial land often affects developed areas and surrounding areas, resulting in deforestation, management of agriculture, and landscaping. This study can provide insights concerning the fundamental data for assessing ecological functions and constructing forest management plans in islands ecosystems.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1975-1984
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• 2021

Urban expansion results in raising the temperature in the city, which can cause social, economic and physical damage. In order to prevent the urban heat island and reduce the urban land surface temperature, it is important to quantify the cooling effect of the features of the urban space. Therefore, in order to understand the relationship between each object of land cover and the land surface temperature in Seoul, the land cover map was classified into 6 classes. And the correlation and multiple regression analysis between land surface temperature and the area of objects, perimeter/area, and normalized difference vegetation index was analyzed. As a result of the analysis, the normalized difference vegetation index showed a high correlation with the land surface temperature. Also, in multiple regression analysis, the normalized difference vegetation index exerted a higher influence on the land surface temperature prediction than other coefficients. However, the explanatory power of the derived models as a result of multiple regression analysis was low. In the future, if continuous monitoring is performed using high-resolution MIR Image from KOMPSAT-3A, it will be possible to improve the explanatory power of the model. By utilizing the relationship between such various land cover types considering vegetation vitality of green areas with that of land surface temperature within urban spaces for urban planning, it is expected to contribute in reducing the land surface temperature in urban spaces.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.75-85
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• 2006

This paper has dealt with a data fusion for the problem of land-cover classification using multisensor imagery. Dempster-Shafer evidence theory has been employed to combine the information extracted from the multiple data of same site. The Dempster-Shafer's approach has two important advantages for remote sensing application: one is that it enables to consider a compound class which consists of several land-cover types and the other is that the incompleteness of each sensor data due to cloud-cover can be modeled for the fusion process. The image classification based on the Dempster-Shafer theory usually assumes that each sensor is represented by a single channel. The evidential approach to image classification, which utilizes a mass function obtained under the assumption of class-independent beta distribution, has been discussed for the multiple sets of mutichannel data acquired from different sensors. The proposed method has applied to the KOMPSAT-1 EOC panchromatic imagery and LANDSAT ETM+ data, which were acquired over Yongin/Nuengpyung area of Korean peninsula. The experiment has shown that it is greatly effective on the applications in which it is hard to find homogeneous regions represented by a single land-cover type in training process.

• Journal of Korean Society of Rural Planning
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• v.19 no.2
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• pp.121-128
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• 2013

The greenhouse gas emission according to the energy consumption is the cause of global warming. With various climates, it is occurs the direct problems to ecosystem. The various studies are being to reduce the carbon dioxide, which accounts for more than 80% of the total greenhouse gas emissions. In this study, estimate the carbon usage using potential biomass extracted from forest type map according to land-use by satellite image, and estimate the amount of carbon dioxide, according to the energy consumption of urban area. The $CO_2$ adsorption is extracted by the amount of forest based on the direct absorption of tree, the other used investigated value. The $CO_2$ emission in Jecheon was 3,985,900 $TCO_2$ by energy consumption. At the land cover classification, the forest is analyzed as 624,085ha and the farmland is 148,700ha. The carbon dioxide absorption was estimated at 1,834,850 Tons from analyzed forest. In case of farmland, it was also estimated at 706,658 Tons.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.171-183
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• 2018

Despite the rapid expansion of satellite images supply, the application of imagery is often restricted due to unautomated image processing. This paper presents the automated process for the selection of training areas which are essential to conducting supervised image classification. The training areas were selected based on the prior and cover information. After the selection, the training data were used to classify land cover in an urban area with the latest image and the classification accuracy was valuated. The automatic selection of training area was processed with following steps, 1) to redraw inner areas of prior land cover polygon with negative buffer (-15m) 2) to select the polygons with proper size of area ($2,000{\sim}200,000m^2$) 3) to calculate the mean and standard deviation of reflectance and NDVI of the polygons 4) to select the polygons having characteristic mean value of each land cover type with minimum standard deviation. The supervised image classification was conducted using the automatically selected training data with Sentinel-2 images in 2017. The accuracy of land cover classification was 86.9% ($\hat{K}=0.81$). The result shows that the process of automatic selection is effective in image processing and able to contribute to solving the bottleneck in the application of imagery.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.6
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• pp.123-130
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• 2009

Fragmentation due to land developments causes disturbances and changes of composition in forest vegetation. The purpose of the study was to develop the impact assessment model for quantitative distance or degree of disturbance by land developments. This study conducted a survey about structure and composition of forest vegetation to determine degree of impact from land developments. The results of field survey, there was a difference in structure and composition of forest vegetation such as tree canopy, herbaceous cover, and number of vine and alien species the distances from edge to interior area such as 0m, 10m, 20m, 40m, and over 60m. To assess the disturbance of forest vegetation, the factors selected were the rate of vine's cover and appearance of alien species. The impact assessment model about vine species explained by a distance, forest patch size, type of forest fragmentation, and type of vegetation ($R^2$=0.44, p<0.001). The other model about alien species explained by a distance, type of forest fragmentation, type of vegetation, and width of road (85.9%, p<0.005). The models applied to Samsong housing development in Goyang-si, Gyunggi-do. The vines and alien species in the study area have had a substantial impact on forest vegetation from edge to 20 or 40m. The impact assessment models were high reliability for estimating impacts to land developments. The impact of forest vegetation by development activities could be minimized thorough the adoption of the models introduced at the stage of EIA.

• Korean Journal of Remote Sensing
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• v.17 no.3
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• pp.275-284
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• 2001

This study was carried out to evaluate high resolution satellite imagery of IKONOS for classifying the land cover, especially forest type. The IKONOS imagery of 11km$\times$11km size was taken on April 24, 2000 in Bong-pyoung Myun Pyungchang-Gun, Kangwon Province. Land cover classes were water, coniferous evergreen, Larix leptolepis, broad-leaved tree, bare land, farm land, grassland, sandy soil and asphalted area. Supervised classification method with algorithm of maximum likelihood was applied for classification. The terrestrial survey was also carried out to collect the reference data in this area. The accuracy of the classification was analyzed with the items of overall accuracy, producer's accuracy, user's accuracy and k for test area through the error matrix. In the accuracy analysis of the test area, overall accuracy was 94.3%, producer's accuracy was 77.0-99.9%, user's accuracy was 71.9-100% and k and 0.93. Classes of bare land, sandy soil and farm land were less clear than other classes, whereas classification result of IKONOS in forest area showed higher performance than that of other resolution(5-30m) satellite data.

• Journal of Environmental Science International
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• v.18 no.4
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• pp.423-434
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• 2009

In recent years, the urban thermal environment has become worse, such as days on which the temperature goes above $30^{\circ}C$, sultry nights and heat stroke increase, due to the changes in terrestrial cover such as concrete and asphalt and increased anthropogenic heat emission accompanied by artificial structure. The land use type is an important determinant to near-surface air temperature. Due to these reasons we need to understand and improve the urban thermal environment. In this study, the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model(MMS) was applied to the metropolitan of Daegu area in order to investigate the influence of land cover changes and urban modifications increase of Albedo to the surface energy budget on the simulated near-surface air temperature and wind speed. The single urban category in existing 24-category U.S. Geological survey land cover classification used in MM5 was divided into 6 classes to account for heterogeneity of urban land cover. As a result of the numerical simulation intended for the metropolitan of Daegu assumed the increase of Albedo of roofs, buildings, or roads, the increase of Albedo (Cool scenario)can make decrease radiation effect of surface, so that it caused drops in ambient air temperature from 0.2 to 0.3 on the average during the daylight hours and smaller (or near-zero) decrease during the night. The Sensible heat flux and Wind velocity is decreased. Modeling studies suggest that increased surface albedo in urban area can reduce surface and air temperatures near the ground and affect related meteorological parameters such as winds, surface air temperature and sensible heat flux.