@inproceedings{264ad09e132d44049be534176fb84bde,
title = "Application of GIS and remote sensing for predicting land-use change in the French jura mountains with the lcm model: The impact of variables on the disturbance model",
abstract = "This research studies the land-use change for the Ain watershed in the Jura Mountains, in the East of France. Using the satellite images LANDSAT in 1975, 1992, 2000 and 2010, the land-use data for the four corresponding years was generated in the first place, and the diachronic land-use analysis from 1975 to 2010 was next carried out. In order to generate the four land-use maps, the satellite images were classified using the Maximum Likelihood supervised classification. The land-use map in 2010 is validated based on the observations from ground visits in 2011. Other land-use maps are validated by the ground truth data established from the auxiliary information layers taken in the area. Based on the trend in the past evolution of land-use, a prediction of future land-use is generated, using the Land Change Modeler (LCM). Next, the multi-temporal analysis of land-use change is carried out and the variables affecting the LCM are evaluated using Multi- Layer Perceptron and Markov transition probabilities. Two pairs of maps (1975, 1992) and (1992, 2000) are used to generate the predictive maps. Copyright",
keywords = "GIS, LCM, Land-use change, Markov chain, Remote sensing",
author = "Nghiem, {Van Tuan} and Rachid Nedjai and Le, {Van Anh} and Laure Charleux",
year = "2013",
month = jan,
day = "1",
language = "English (US)",
isbn = "9781629939100",
series = "34th Asian Conference on Remote Sensing 2013, ACRS 2013",
publisher = "Asian Association on Remote Sensing",
pages = "2598--2605",
booktitle = "34th Asian Conference on Remote Sensing 2013, ACRS 2013",
note = "34th Asian Conference on Remote Sensing 2013, ACRS 2013 ; Conference date: 20-10-2013 Through 24-10-2013",
}