the present study aims to simulate the spatial pattern of land use change in lisar protected area,iran. land cover maps for 1989, 2000, and 2007 were depicted using tm, etm+, and irs liss-iii images ofthe area at stake. images were classified using a merge of unsupervised and supervised classification. camarkov model was used to predict land cover maps as a top-down approach in investigating la...

Research on the uncertainty of Land Use Cover Change (LUCC) models is still limited. Through this paper, we aim to globally characterize structural four common software packages (CA_Markov, Dinamica EGO, Modeler, Metronamica) and analyse options that they offer for management. The have been compared qualitatively, based their structures tools, quantitatively, through a study case city Cape Town...

During the last decades, a diversity of models has been developed to simulate future land use and land cover changes (LUCC). In this paper, we compared four modeling tools: CLUE-S, DINAMICA EGO, CA_MARKOV and Land Change Modeler. We assessed the methods and tools available for each modeling tool within these models based on the six steps necessary for a generic framework of LUCC modeling: 1) es...

Land use/cover change (LUCC), as an important factor in global change, is a topic that has recently received considerable attention in the prospective modeling domain. There are many approaches and software packages for modeling LUCC, many of them are empirical approaches based on past LUCC such as CLUE-S, DINAMICA EGO, CA_MARKOV and Land Change Modeler (both available in IDRISI). This study re...

This paper applies different methods of map comparison to quantify the characteristics of three different land change models. The land change models used for simulation are termed as ―Stochastic Markov (St_Markov)‖, ―Cellular Automata Markov (CA_Markov)‖ and ―Multi Layer Perceptron Markov (MLP_Markov)‖ models. Various model validation techniques such as per category method, kappa statistics, co...

The primary objective of this research is to predict and analyze the future urban growth of Dhaka City using the Landsat satellite images of 1989, 1999 and 2009. Dhaka City Corporation (DCC) and its surrounding impact areas have been selected as the study area. At the beginning, a fisher supervised classification method has been applied to prepare the base maps with five land cover classes. In ...

Modeling and predicting land use/cover change (LUCC) identifying its drivers have been a focus of research over the past few decades. In order to solve problem resource degradation in typical pastoral areas, reveal temporal spatial evolution characteristics LUCC, contradiction between man sustainable development, we analyze Gurvanbulag area Bulgan province, Mongolia, where grassland is relative...