• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.471-476
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• 2010

This study aimed at monitoring, mapping, and assessing the land degradation in the desert area. In this research, the Landsat TM and ETM+ imageries to assess the extent of land degradation for study area during the period from 1991 to 2007. Were used to study supervized, unsupervized classfication and NDVI land cover changes in the desert area in Mongolia. The classified map consists of five classes of water, vegetation, slight desertification, middle desertification and sever desertification. It shows that for determination classfication methods and NDVI, desertification map of the study area are prepared. The result showed accounting for a clear deterioration in vegetative cover, an increase of sever desertification and a decrease in middle desertification and slight desertification respectively of the total study area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.443-450
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• 2014

To fulfill the recent increasement in the public and private demands for various spatial data, the central and local governments started to produce those data. The low-level land cover map has been produced since 2000, yet the production of high-level land covered map has started later in 2010, and recently, a few regions was completed recently. Although many studies have been carried to improve the quality of land that covered in the map, most of them have been focused on the low-level and mid-level classifications. For that reason, the study for high-level classification is still insufficient. Therefore, in this study, we suggested the automatic extraction of land readjustment for paddy land that updated in the mid-level land mapping. At the study, the RapidEye satellite images, which consider efficient to apply in the agricultural field, were used, and the high pass filtering emphasized the outline of paddy field. Also, the binary images of the paddy outlines were generated from the Otsu thresholding. The boundary information of paddy field was extracted from the image-to-map registrations and masking of paddy land cover. Lastly, the snapped edges were linked, as well as the linear features of paddy outlines were extracted by the regional Hough line extraction. The start and end points that were close to each other were linked to complete the paddy field outlines. In fact, the boundary of readjusted paddy fields was able to be extracted efficiently. We could conclude in that this study contributed to the automatic production of a high-level land cover map for paddy fields.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.128-133
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• 1998

To assess the flood damages and to provide necessary information for preventing future catastrophe, it is necessary to appraise the inundated area with more accurate and rapid manner. This study attempts to evaluate the potential of satellite synthetic aperture radar (SAR) data for mapping of flood inundated area in southern part of Korea. JERS L-band SAR data obtained during the summer of 1997 were used to delineate the inundated areas. In addition, Landsat TM data were also used for analyzing the land cover condition before the flooding. Once the two data sets were co-registered, each data was separately classified. The water surface areas extracted from the SAR data and the land cover map generated using the TM data were overlaid to determine the flood inundated areas. Although manual interpretation of water surfaces from the SAR image seems rather simple, the computer classification of water body requires clear understanding of radar backscattering behavior on the earth's surfaces. It was found that some surface features, such as rice fields, runaway, and tidal flat, have very similar radar backscatter to water surface. Even though satellite SAR data have a great advantage over optical remote sensor data for obtaining imagery on time and would provide valuable information to analyze flood, it should be cautious to separate the exact areas of flood inundation from the similar features.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.381-383
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• 2003

SAR imagery offers a reliable mode of image acquisition over tropical countries for various applications. The Philippines participated in two missions to the Pacific Rim by NASA in 1996 and 2000 that saw the deployment of the AIRSAR instrument. This paper discusses the Philippine experience in the use of polarimetric and interferometric radar datasets for diverse applications, including hazards mapping, geologic and geomorphologic mapping, and land cover mapping. The results are discussed in the light of present efforts at capacity building in remote sensing, attempts at operationalizing the use of SAR for priority applications, and future ambitions in remote sensing.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.117-126
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• 2018

This study aims to evaluate the usability of polarimetric SAR measurements for discriminating water-covered area from other land cover types and to propose polarimetric parameters showing the better response to the flood. Flood-related changes in the polarimetric parameters were studied using the L-band PALSAR-2 quad-pol mode data acquired before and after the severe flood events occurred in Joso city, Japan. The experimental results showed that, among various polarimetric parameters, the HH-polarization intensity, the Shannon entropy, and the surfaces scattering component of model-based decomposition were found to be useful to discriminate water-covered areas from other land cover types. Particularly, an unsupervised change detection with the Shannon entropy provides the best result for an automated mapping of flood extents.

• Korean Journal of Remote Sensing
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• v.38 no.1
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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.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.15-22
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• 2015

To create a wind resource map, we need a contour map, a roughness map and wind data. We need a land cover map for the roughness map of these data. A land cover map represents the area showing similar characteristics after color indexing based on the scientific method. The features of land cover is classified by Remote sensing technique. In this study, we verified the application of the NDVI technique is reasonable after we created the wind resource map using roughness maps by unsupervised classification and NDVI technique. As a result, the wind resource map using the NDVI technique showed a 60% accordance rate and difference in class less than one. From the results, The NDVI technique is found alternative to create roughness maps by the unsupervised classification.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.71-79
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• 2014

Most researches have created the impervious surface map by using low-spatial-resolution satellite imagery and are inefficient to generate the object-based impervious map with a broad area. In this study, segment-based impervious surface mapping algorithm is proposed using the RapidEye satellite imagery in order to map impervious area. At first, additional bands are generated by using TOA reflectance conversion RapidEye data. And then, shadow and water class are extracted using training data of converted reflectance image. Object-based impervious surface can be generated by spectral mixture analysis based on land cover map of Ministry of Environment with medium scale, in the case of other classes except shadow and water classes. The experiment shows that result by our method represents high classification accuracy compared to reference data, quantitatively.

• Journal of Wetlands Research
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• v.13 no.3
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• pp.471-479
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• 2011

Evapotranspiration (ET) including evaporation from a land surface and transpiration from photosynthesis of vegetation is a hydrological factor that has an important role in water cycle. However, there is a limitation to understand it due to heterogeneity of land cover and vegetation. In this study, Mapping EvapoTRanspiration with Internalized Calibration (METRIC) model, one of the energy balance models, and MODerate resolution Imaging Spectroradiometer (MODIS) satellite based well-known Penman-Monteith algorithm were compared. Two ET maps were categorized and compared by land cover classification. The results represented overall applicability of the two models with the highest correlation coefficients in needleleaf and broadleaf forests. This study will be useful to estimate remote sensing based ET maps with high resolution and to figure out spatio-temporal variability and seasonal changes.

• Korean Journal of Agricultural Science
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• v.41 no.3
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• pp.205-211
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• 2014

Focused on Mt. Bogdkhan nature reserve in Mongolia, this study was conducted as a fundamental research to discover a tendency and characteristics of forest damage and to draw up measures for proper plans of forest restoration through an analysis of year-to year change using satellite images. In specific, land cover mapping was conducted by using Landsat images from 1994 to 2011, and then year-to year change was analyzed to investigate the features of forest damage in Mt. Bogdkhan. The results showed that the whole area of a reservation in Mongolia in 2011 was about $416.89km^2$; among them, forest area was $167,87km^2$, accounting for about 40.3%, followed by bare patch and grassland area (58.6%) and urban dry area (1.1%). In particular, compared in 1994, the area of forest in 2011 has increased by $6.12km^2$; while bare patch and grassland area has decreased by $10.81km^2$. Primary causes of forest degradation occurred in Mt. Bogdkhan nature reserve included illegal logging for fuel, forest and grassland degradation caused by domestic animals grazing, man-made forest fire, and disaster caused by insect pest.