• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.47-49
• /
• 2003

Automatic land use and land cover change (LUCC) detection via remotely sensed imagery has a wide application in the area of LUCC research, nature resource and environment monitoring and protection. Under the condition that one time (T1) data is existed land use and land cover maps, and another time (T2) data is remotely sensed imagery, how to detect change automatically is still an unresolved issue. This paper developed a land use and land cover class knowledge guided method for automatic change detection under this situation. Firstly, the land use and land cover map in T1 and remote sensing images in T2 were registered and superimposed precisely. Secondly, the remotely sensed knowledge database of all land use and land cover classes was constructed based on the unchanged parcels in T1 map. Thirdly, guided by T1 land use and land cover map, feature statistics for each parcel or pixel in RS images were extracted. Finally, land use and land cover changes were found and the change class was recognized through the automatic matching between the knowledge database of remote sensing information of land use & land cover classes and the extracted statistics in that parcel or pixel. Experimental results and some actual applications show the efficiency of this method.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.1221-1223
• /
• 2003

With speediness of economy, the structure of land use has taken lots of change. How can we quickly and exactly obtain detailed land use/cover change information, and then we know land resource amount, quality, distributing and change direction. More and more high resolution satellite systems are under development. So we can make good use of RS data, existed GIS data and GPS data to extract change information and update map. In this paper a fully automated approach for detecting land use/cover change using remote sensing data with object-oriented classification based on GIS data, GPS data is presented (referring to Fig.1). At same time, I realize integrating raster with vector methods of updating the basic land use/land cover map based on 3S technology and this is becoming one of the most important developing direction in 3S application fields; land-use and cover change fields over the world. It has been successful applied in two tasks of The Ministry of Land and Resources P.R.C and taken some of benefit.

• Journal of the Korean Geographical Society
• /
• v.40 no.2 s.107
• /
• pp.221-241
• /
• 2005

Land Use and Land Cover Changes (LUCC) occur over a wide range of space and time scales, and involve complex natural, socio-economic, and institutional processes. Therefore, modelling and predicting LUCC demands an understanding of how various measured properties behave when considered at different scales. Understanding spatial and temporal variability of driving forces and constraints on LUCC is central to understanding the scaling issues. This paper aims to 1) assess the heterogeneity of land cover change processes over the landscape in northern Ghana, where intensification of agricultural activities has been the dominant land cover change process during the past 15 years, 2) characterise dominant land cover change mechanisms for various spatial scales, and 3) identify the optimal spatial scale for LUCC modelling in a savanna landscape. A multivariate statistical method was first applied to identify land cover change intensity (LCCI), using four time-sequenced NDVI images derived from LANDSAT scenes. Three proxy land use change predictors: distance from roads, distance from surface water bodies, and a terrain characterisation index, were regressed against the LCCI using a multi-scale hierarchical adaptive model to identify scale dependency and spatial heterogeneity of LUCC processes. High spatial associations between the LCCI and land use change predictors were mostly limited to moving windows smaller than 10$\times$10km. With increasing window size, LUCC processes within the window tend to be too diverse to establish clear trends, because changes in one part of the window are compensated elsewhere. This results in a reduced correlation between LCCI and land use change predictors at a coarser spatial extent. The spatial coverage of 5-l0km is incidentally equivalent to a village or community area in the study region. In order to reduce spatial variability of land use change processes for regional or national level LUCC modelling, we suggest that the village level is the optimal spatial investigation unit in this savanna landscape.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
• /
• 2019.08a
• /
• pp.120-121
• /
• 2019

• Journal of the Korean Geographical Society
• /
• v.50 no.3
• /
• pp.255-276
• /
• 2015

This paper presents a multi-agent system model of land-use and cover changes, which is developed and applied to the Gariwang-san and its vicinity, located in Pyeongchang and Jeongseon-gun, Gangwon province, Korea. The Land Use Dynamics Simulator (LUDAS) framework of this study is well suited for representing the spatial heterogeneity and dynamic interactions between human and natural environment, and capturing the impacts of forest-opening policy interventions to future socio-economic and natural environment changes. The model consists of four components: (1) a system of human population, (2) a system of landscape environment, (3) decision-making procedures integrating human(or household), environmental and policy information into forest land-use decisions, and (4) a set of policy scenarios that are related to the forest-opening. The results of model simulation by different combination of various forest management scenarios are assessed by the levels of household income, ecosystem service value and income inequality in the study region. As a result, the optimal scenario of forest-opening policies in the study region is to open the forest to local residential community for the purpose of recreation, considering the distinctive topographical feature. The model developed in this research is expected to contribute to a decision support system for sustainable forest management and various land-use policies in Korea.