• Journal of Forest and Environmental Science
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• v.39 no.3
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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.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.3
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• pp.20-30
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• 2000

Average annual NDVI values from the NOAA/NASA Pathfinder AVHRR Land Data Sets from 1982 to 1994 showed comprehensive systematic displacement patterns in Asia. Inter-annual growing season data, however, did not show such systematic patterns. The most likely cause for the abrupt displacements, which appear especially in 1982, 1989 and 1990, may be changes in satellite sensors, although global warming, El Ni$\tilde{n}$o-Southern Oscillation events, changes in processing algorithms, and changes in land-use patterns in various parts of Asia may also play some role. The results suggest that researchers must be extremely careful in their inter-annual global change research, since direct use of the raw data could cause unexpected results. Growing-season NDVI shows decreases throughout most of Southeast Asia and modest gains in northern China and some parts in India, which could be related to land-use and land-cover changes.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.381-392
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• 2003

Multi-temporal approaches using sequential data acquired over multiple years are essential for satisfactory discrimination between many land-cover classes whose signatures exhibit seasonal trends. At any particular time, the response of several classes may be indistinguishable. A harmonic model that can represent seasonal variability is characterized by four components: mean level, frequency, phase and amplitude. The trigonometric components of the harmonic function inherently contain temporal information about changes in land-cover characteristics. Using the estimates which are obtained from sequential images through spectral analysis, seasonal periodicity can be incorporates into multi-temporal classification. The Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 ～ 2000 using a dynamic technique. Land-cover types were then classified both with the estimated harmonic components using an unsupervised classification approach based on a hierarchical clustering algorithm. The results of the classification using the harmonic components show that the new approach is potentially very effective for identifying land-cover types by the analysis of its multi-temporal behavior.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.511-524
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• 2014

In this study, we investigated the statistical occupations and interannual variations of land cover types over Northeast Asian region using the 12 years (2001-2012) MODerate Resolution Imaging Spectroradiometer(MODIS) land cover data sets. The spatial resolution and land cover types of MODIS land cover data sets are 500 m and 17, respectively. The 12-year average shows that more than 80% of the analysis region is covered by only 3 types of land cover, cropland (36.96%), grasslands (23.14%) and mixed forests (22.97%). Whereas, only minor portion is covered by cropland/natural vegetation mosaics (6.09%), deciduous broadleaf forests (4.26%), urban and built-up (2.46%) and savannas (1.54%). Although sampling period is small, the regression analysis showed that the occupations of evergreen needleleaf forests, deciduous broadleaf forests and mixed forests are increasing but the occupations of woody savannas and savannas are decreasing. In general, the pixels where the land cover types are classified differently with year are amount to more than 10%. And the interannual variations in the occupations of land cover types are most prominent in cropland (1.41%), mixed forests (0.82%) and grasslands (0.73%). In addition, the percentage of pixels classified as 1 type for 12 years is only 57% and the other pixels are classified as more than 2 types, even 9 types. The annual changes in the classification of land cover types are mainly occurred at the almost entire region, except for the eastern and northwestern parts of China, where the single type of land cover located. When we take into consider the time scale needed for the land cover changes, the results indicate that the MODIS land cover data sets over the Northeast Asian region should be used with caution.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.2
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• pp.123-130
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• 2020

The impact of urbanization on LST (Land Surface Temperature) and TN (Tropical Night) was observed with the analyses of land cover change and LST by associating with the frequency of TN during the period of 1996 to 2016. The analyses of land cover and LST was based on the images of Landast 5 and 8 for September in 1996, 2006, and 2016 at a 10 year interval. The hourly-collected atmospheric temperatures for the months of July and August during the period were collected from AWSs (Automatic Weather Stations) in Seoul for the frequency analysis of TN. The study area was categorized into five land cover classes: urban or built-up area, forest, mixed vegetation, bare soil and water. It was found that vegetation (-7.71%) and bare soil (-9.04%) decreased during the period while built-up (17.29%) area was expanded throughout the whole period (1996-2016), indicating gradual urbanization. The changes came along with the LST rise in the urban area of built-up and bare soil in Seoul. In addition, the frequency of TN has increased in 4.108% and 7.03% for July and August respectively between the two periods of the 10 year interval, 1996-2006 and 2006-2016. By comparing the increasing trends of land cover, LST, and TN, we found a high probability that the frequency of TN had a relationship with land cover changes by the urbanization process in the study area.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.933-940
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• 2020

Land-use change matrix data is important for calculating the LULUCF (land use, land use change and forestry) sector of the national greenhouse gas inventory. In this study, land cover changes in 2004 and 2019 were compared using the Wall-to-Wall technique with a land cover map of Sejong City from the Ministry of Environment. Sejong City was classified into six land use classes according to the Intergovernmental Panel on Climate Change (IPCC) guidelines: Forest land, crop land, grassland, wetland, settlement and other land. The coordinate system of the land cover maps of 2004 and 2019 were harmonized and the land use was reclassified. The results indicate that during the 15 years from 2004 to 2019 forestlands and croplands decreased from 50.4% (234.2 ㎢) and 34.6% (161.0 ㎢) to 43.4% (201.7 ㎢) and 20.7% (96.2 ㎢), respectively, while Settlement and Other land area increased significantly from 8.9% (41.1 ㎢) and 1.4% (6.9 ㎢) to 35.6% (119.0 ㎢) and 6.5% (30.3 ㎢). 79.㎢ of cropland area (96.2 ㎢) in 2019 was maintained as cropland, and 8.8 ㎢, 1.7 ㎢, 0.5 ㎢, 5.4 ㎢, and 0.4 ㎢ were converted from forestland, grassland, wetland, and settlement, respectively. This research, however, is subject to several limitations. The uncertainty of the land use change matrix when using the wall-to-wall technique depends on the accuracy of the utilized land cover map. Also, the land cover maps have different resolutions and different classification criteria for each production period. Despite these limitations, creating a land use change matrix using the Wall-to-Wall technique with a Land cover map has great advantages of saving time and money.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.411-419
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• 2022

DPR Korea has been creating cropland across the country due to its chronic food shortage. Cropland was about 17.4% at the end of the 1980s, but it increased steadily to 19.6% at the end of the 1990s, 24.8% at the end of the first decade of 2000s, and 25.4% at the end of the 2010s. On the other hand, the forest land declined from about 74.8% in the late 1980s to 69.5% in the late 2010s. Urbanization is also progressing, increasing from about 1.15% at the end of the 1980s to 1.68% at the end of the 2010s. Most of the deforestation that occurred in DPR Korea was caused by conversion to cropland. These characteristics of land cover changes in DPR Korea provide useful information and implications for international and inter-Korean cooperation for DPR Korea.

• Journal of Forest and Environmental Science
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• v.36 no.3
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• pp.199-206
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• 2020

Satchari National Park is one of the most biodiverse forest in Bangladesh and home of many endangered flora and fauna. 206 tons of CO₂ per hectare is sequestrated in this national park every year which helps to mitigate climate issues. As people living near the area are dependent on this forest, degradation has become a regular phenomenon destroying the forest biodiversity by altering its forest cover. So, it is important to map land cover quickly and accurately for the sustainable management of Satchari National Park. The main objective of this study was to obtain information on land cover change using remote sensing data. Combination of unsupervised NDVI classification and supervised classification using maximum likelihood is followed in this study to find out land cover map. The analysis showed that the land cover is gradually converting from one land use type to another. Dense forest becoming degraded forest or bare land. Although it was slowed down by the establishment of 'National Park' on the study site, forecasting shows that it is not enough to mitigate forest degradation. Legal steps and proper management strategies should be taken to mitigate causes of degradation such as illegal felling.

• 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.

• 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.