NDLI: Modeling land use and land cover changes in a vulnerable coastal region using artificial neural networks and cellular automata

Content Provider	Springer Nature Link
Author	Qiang, Yi Lam, Nina S. N.
Copyright Year	2015
Abstract	As one of the most vulnerable coasts in the continental USA, the Lower Mississippi River Basin (LMRB) region has endured numerous hazards over the past decades. The sustainability of this region has drawn great attention from the international, national, and local communities, wanting to understand how the region as a system develops under intense interplay between the natural and human factors. A major problem in this deltaic region is significant land loss over the years due to a combination of natural and human factors. The main scientific and management questions are what factors contribute to the land use land cover (LULC) changes in this region, can we model the changes, and how would the LULC look like in the future given the current factors? This study analyzed the LULC changes of the region between 1996 and 2006 by utilizing an artificial neural network (ANN) to derive the LULC change rules from 15 human and natural variables. The rules were then used to simulate future scenarios in a cellular automation model. A stochastic element was added in the model to represent factors that were not included in the current model. The analysis was conducted for two sub-regions in the study area for comparison. The results show that the derived ANN models could simulate the LULC changes with a high degree of accuracy (above 92 % on average). A total loss of 263 km2 in wetlands from 2006 to 2016 was projected, whereas the trend of forest loss will cease. These scenarios provide useful information to decision makers for better planning and management of the region.
Starting Page	1
Ending Page	16
Page Count	16
File Format	PDF
ISSN	01676369
Journal	Environmental Monitoring and Assessment
Volume Number	187
Issue Number	3
e-ISSN	15732959
Language	English
Publisher	Springer International Publishing
Publisher Date	2015-02-03
Publisher Place	Cham
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Coastal sustainability Land use land cover change Coupled natural-human dynamics Artificial neural network Cellular automata Environmental Monitoring/Analysis Environmental Management Ecotoxicology Atmospheric Protection/Air Quality Control/Air Pollution Ecology
Content Type	Text
Resource Type	Article
Subject	Pollution Medicine Management, Monitoring, Policy and Law

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