Future Scenarios of Land Use/Land Cover (LULC) Based on a CA-Markov Simulation Model: Case of a Mediterranean Watershed in Morocco

Abstract

Modeling of land use and land cover (LULC) is a very important tool, particularly in the agricultural field: it allows us to know the potential changes in land area in the future and to consider developments in order to prevent probable risks. The idea is to give a representation of probable future situations based on certain assumptions. The objective of this study is to make future predictions in land use and land cover in the watershed “9 April 1947”, and in the years 2028, 2038 and 2050. Then, the maps obtained with the climate predictions will be integrated into an agro-hydrological model to know the water yield, the sediment yield and the water balance of the studied area by 2050.The future land use and land cover (LULC) scenarios were created using a CA-Markov forecasting model. The results of the simulation of the LULC changes were considered satisfactory, as shown by the values obtained from the kappa indices for agreement (κstandard) = 0.73, kappa for lack of information (κno) = 0.76, and kappa for location at grid cell level (κlocation) = 0.80. Future scenarios modeled in LULC indicate a decrease in agricultural areas and wetlands, both of which can be seen as a warning of crop loss. There is, on the other hand, an increase in forest areas that could be an advantage for the biodiversity of the fauna and flora in the “9 April 1947” watershed.

Integrating climate change adaptation policies in spatial development planning in hyperarid regions of Kerman province, Iran

“…In this regard, CA is one of the best methods for simulating LCCs over time, but it may have limitations that combining it with other models such as MCM will lead to better results [ 37 ]. Also, the combination of Patch-Generating Land Use Simulation (PLUS) with CA has a high ability for modeling LCCs [ 38 ].…”

Basin-Scale Streamflow Projections for Greater Pamba River Basin, India Integrating GCM Ensemble Modelling and Flow Accumulation-Weighted LULC Overlay in Deep Learning Environment

“…The CA-Markov Model is an effective technique for the simulation and projection of LULC [40][41][42].To represent the spatiotemporal dynamics of LULC, it integrates ideas from cellular automata and Markov chain modelling. The research region is represented by a grid in the model, with each grid cell corresponding to a land unit.…”

An Improved Future Land-Use Simulation Model with Dynamically Nested Ecological Spatial Constraints

“…Stability means that the change process tends to be stable, and no aftereffect means that the situation at a certain moment is not affected The Markov model is a raster scale-based model with strong quantitative prediction ability, which has stability and no aftereffect. Stability means that the change process tends to be stable, and no aftereffect means that the situation at a certain moment is not affected by the past and the future, being only related to the current situation [39,40]. The application of the Markov model in land-use simulation is mainly to predict the number of grids of each land-use type, so as to make up for the deficiency of the ordinary spatial model in quantitative prediction [41].…”