scholarly journals Modeling Land Use and Land Cover Dynamic Using Geographic Information System and Markov-CA

2020 ◽  
Vol 5 (2) ◽  
pp. 210
Author(s):  
Millary Agung Widiawaty ◽  
Arif Ismail ◽  
Moh. Dede ◽  
N. Nurhanifah

The need for built-up area increases along with a rise in population growth in many regions. This phenomenon leads to a tremendous change in agricultural land and decrease in the environmental carrying capacity. Therefore, this study aims to determine Land Use and Land Cover (LULC) dynamics and the drivers used for its modeling in 2030. This is a quantitative study, which uses the dynamic models of Geographic Information System (GIS) and Markov-CA. Data were obtained from the CNES-Airbus satellite imageries in 2009, 2014, and 2019 by using Google Earth at East Cirebon. The drivers include road density, distance to CBD, total population, distance to settlements, land slope and distance to rivers. The interaction between drivers and LULC change was analyzed using binary logistic regression. The results showed that the rise of built-up area reached 36.4 percent and causes the loss of 0.78 km2 of agricultural land from 2009 to 2019. The LULC simulation in 2030 shows an increase in the built-up area by 82.85 percent with probabilities above 0.6. Meanwhile the significant drivers for changes include road density and distance to settlements. In conclusion, efforts to reduce LULC change in agricultural land into built-up area is by re-strengthening spatial planning-based environmental awareness for the community. Keywords: Built-up area; GIS; LULC; Markov-CA; Spatial modeling   Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

Author(s):  
Mitiku Badasa Moisa ◽  
Daniel Assefa Negash ◽  
Biratu Bobo Merga ◽  
Dessalegn Obsi Gemeda

Abstract The impact of land-use land-cover (LULC) change on soil resources is getting global attention. Soil erosion is one of the critical environmental problems worldwide with high severity in developing countries. This study integrates the Revised Universal Soil Loss Equation model with a geographic information system to estimate the impacts of LULC conversion on the mean annual soil loss in the Temeji watershed. In this study, LULC change of Temeji watershed was assessed from 2000 to 2020 by using 2000 Landsat ETM+ and 2020 Landsat OLI/TIRS images and classified using supervised maximum likelihood classification algorithms. Results indicate that the majority of the LULC in the study area is vulnerable to soil erosion. High soil loss is observed when grassland and forest land were converted into cultivated land with a mean soil loss of 88.8 and 86.9 t/ha/year in 2020. Results revealed that about 6,608.5 ha (42.8%) and 8,391.8 ha (54.4%) were categorized under severe classes in 2000 and 2020, respectively. Accordingly, the soil loss severity class is directly correlated with the over-exploitation of forest resources and grasslands for agricultural purposes. These results can be useful for advocacy to enhance local people and stakeholder's participation toward soil and water conservation practices.


2018 ◽  
Vol 225 (2) ◽  
pp. 245-273
Author(s):  
Assist. Prof. Dr. Saleem Y. Jamal

     Land use refers to the human activity associated with a particular area of land. The land cover refers to the pattern of appearances located on the surface of the earth. Survey, inventory, monitoring and classification of land use and land cover are a fundamental step in the land use planning process, in evaluating and comparing alternatives and in choosing the best and sustainable use of land for development, accomplishment economic and social well-being. Remote sensing and Geographic Information System provided advantages that conventional methods could not provide for surveys and monitoring of natural and human resources, and classification of agricultural land uses and land cover in the area of the Al-Sad Al-Adhim sub District – Iraq. Depending on the Anderson system and others to classify land uses and land cover, through the integration of digital interpretation with the use of Digital Image Processing (ERDAS IMAGINE) software, and visual interpretation using ArcGIS software. Classification of agricultural land use and land cover up to the third level, with over all accuracy of the map 90%. the percentage distribution of the areas shows that the agricultural lands ranked first and occupy 52%, then grassland occupies 19%, barren land is occupied 17%, urban areas and built up occupy 9% water is ranked last occupy 3% of the total area of the study area.


2019 ◽  
Vol 3 (2) ◽  
pp. 204-210
Author(s):  
Harnawan Nurul Asna ◽  
Frederik Samuel Papilaya

The purpose of this study was to find out how much area of agricultural land was converted because of the high property business activities in Semarang City, the data used for this study were taken from 1999 to 2018. The classification method used in this study was the remote sensing method using the unsupervised classification technique. Output of this study is the extensive data of agricultural land cover change obtained from 1999 to 2018. The results of this study can prove that the Geographic Information System can be used to find out how much agricultural land cover change in Semarang City from 1999 to 2018. The area of agricultural land that has been converted is from 1999 to 2009 around 3072 ha and from 2009 to 2018 around 1071.4 ha.


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