Land Use Change Matrix Research Articles

Optimal Sampling Intensity in South Korea for a Land-Use Change Matrix Using Point Sampling

To report changes in land use, the forestry sector, and land-use change matrix (LUCM), monitoring is necessary in South Korea to adequately respond to the Post-2020 climate regime. To calculate the greenhouse gas statistics observing the principle of transparency required by the Climate Change Convention, a consistent nationwide land-use classification and LUCM are required. However, in South Korea, land-use information is available from the 5th National Forest Inventory conducted in 2006 onwards; therefore, developing methods to determine historical LUCM information, including the base year required by the Intergovernmnetal Panel on Climate Change (IPCC), is essential. To determine the optimal sampling intensity for measuring systematic land-use changes and to estimate the corresponding area of land-use categories for previously unmeasured years, seven intensities—2 × 2 km to 8 × 8 km—were tested using the areas of the 3rd and 4th aerial photographs in time series for forestland, cropland, grassland, wetland, and settlements, according to their standard deviations and estimates of uncertainty. Analyses of statistical accuracy, statistical efficiency, economic efficiency, and convenience showed that a sampling intensity of 4 × 4 km was ideal. Additionally, the categorized areas of unmeasured land-use years were calculated through linear interpolation and extrapolation. Our LUCM can be utilized for developing a national greenhouse gas inventory.

표본강도에 따른 토지이용변화 매트릭스의 불확도 비교

표본강도에 따른 토지이용변화 매트릭스의 불확도 비교

점 표본점(Point sampling) 방법을 이용한 국가수준 토지이용변화 매트릭스 개발

Land‐Use Change Matrix (LUCM) is critical activity data in the Land‐Use, Land‐Use Change and Forestry (LULUCF) sector for reporting National Greenhouse Gas Inventory. To produce a LUCM, it is necessary to clearly define six land‐use categories and apply a consistent methodology according to the IPCC guideline. This study was conducted to develop a LUCM at national level in South Korea using the point sampling approach. In this study, 5,600 mapped sample points systematically distributed across the country were used to detect land‐use categories with interpretation of ortho‐photos and national spatial information including satellite images. With a produced LUCM based on classified sampling points in 1992 and 2005, simple and modified ratio estimators were used to estimate the areas and uncertainties for each land‐use category and converted land‐use category in 2005. The uncertainties from both estimators were acceptable according to the National GHG report. However, the total areas for each land‐use category estimated by the simple estimator were different from the official national statistics. As a result, the modified estimator, which employed the official national statistics of total area by land‐use category in 2005, can be used for the consistency and uncertainty assessment. To apply point sampling, an optimal sampling intensity should be determined considering economic efficiency and statistical accuracy.

Projection of the probability of local extinction of canopy tree species in forest landscapes

Tree species are endangered mainly by the exploitation of old-growth forests, and in Japan by a change from traditional coppicing (Satoyama) to monoculture plantations. The protection of old-growth forest or the revival of traditional Satoyama management might avoid local extinctions. To evaluate these possibilities, we developed a model to project the dominance and probabilities of local extinction of tree species in deciduous forests by combining land-use change and canopy tree replacement matrices. The land-use change matrix represents the probability of land-use transition during a unit interval (25 years). We calculated the probabilities of transition among old-growth forest, immature secondary forest, mature secondary forest, conifer plantation, and pasture from historical records. The probabilities of canopy replacement in old-growth and secondary forests were estimated from canopy–understory associations. Changes in canopy composition after logging of old-growth and secondary forests and forest recovery following abandonment of clear-cut plantations and pasture were estimated from field data. Using the combined matrix model, we projected the abundance and probabilities of local extinction of 19 tree species under four scenarios: business as usual, forest protection, Satoyama (traditional coppice management), and Satoyama forest protection. Satoyama management increased the abundance of disturbance-dependent species but contributed little to the reduction of local extinction. Forest protection decreased extinction probabilities and the dominance of tree species did not change greatly. In particular, forest protection greatly decreased the local extinction probabilities of species with continuous recruitment in old-growth forest, such as Fagus crenata, F. japonica, and Acer mono, but Satoyama did not.

Implication of Land-Use and Land-Cover Change into Carbon Dioxide Emissions in Karang Gading and Langkat Timur Wildlife Reserve, North Sumatra, Indonesia

Mangrove forest in the context of climate change is important sector to be included in the inventory of greenhouse gas (GHG) emissions. The present study describes land-use and land-cover change during 2006–2012 of a mangrove forest conservation area, Karang Gading and Langkat Timur Laut Wildlife Reserve (KGLTLWR) in North Sumatra, Indonesia and their implications to carbon dioxide emissions. A land-use change matrix showed that the decrease of mangrove forest due to increases of other land-use such as aquaculture (50.00%) and oil palm plantation (28.83%). Furthermore, the net cumulative of carbon emissions in KGLTLWR for 2006 was 3804.70 t CO2-eq year-1, whereas predicting future emissions in 2030 was 11,318.74 t CO2-eq year-1 or an increase of 33.61% for 12 years. Source of historical emissions mainly from changes of secondary mangrove forests into aquaculture and oil palm plantation were 3223.9 t CO2-eq year-1 (84.73%) and 959.00 t CO2-eq year-1 (25.21%), respectively, indicating that the KGLTLWR is still a GHG emitter. Mitigation scenario with no conversion in secondary mangrove forest reduced 16.21% and 25.8% carbon emissions in 2024 and 2030, respectively. This study suggested that aquaculture and oil palm plantation are drivers of deforestation as well as the largest of GHG emission source in this area.

Exploring Land use and Land cover change in themining areas of Wa East District, Ghana usingSatellite Imagery

Abstract Satellite imagery has been widely used to monitorthe extent of environmental change in both mine andpost mine areas. This study uses Remote sensing and GeographicalInformation System techniques for the assessmentof land use/land cover dynamics of mine relatedareas in Wa East District of Ghana. Landsat satellite imageriesof three different time periods, i.e., 1991, 2000 and2014 were used to quantify the land use/cover changes inthe area. Supervised Classification using Maximum LikelihoodTechnique in ERDAS was utilized. The images werecategorized into five different classes: Open Savannah,Closed Savannah, Bare Areas, Settlement and Water. Imagedifferencing method of change detection was used toinvestigate the changes. Normalized Differential VegetativeIndex valueswere used to correlate the state of healthyvegetation. The image differencing showed a positive correlationto the changes in the Land use and Land coverclasses. NDVI values reduced from 0.48 to 0.11. The landuse change matrix also showed conversion of savannahareas into bare ground and settlement. Open and closesavannah reduced from 50.80% to 36.5% and 27.80% to22.67% respectively whiles bare land and settlement increased.Overall accuracy of classified 2014 image andkappa statistics was 83.20% and 0.761 respectively. Thestudy revealed the declining nature of the vegetation andthe significance of using satellite imagery. A higher resolutionsatellite Imagery is however needed to satisfactorilydelineate mine areas from other bare areas in such Savannahzones.