Abstract

The present study used the official Portuguese land use/land cover (LULC) maps (Carta de Uso e Ocupação do Solo, COS) from 1995, 2007, 2010, 2015, and 2018 to quantify, visualize, and predict the spatiotemporal LULC transitions in the Beja district, a rural region in the southeast of Portugal, which is experiencing marked landscape changes. Here, we computed the conventional transition matrices for in-depth statistical analysis of the LULC changes that have occurred from 1995 to 2018, providing supplementary statistics regarding the vulnerability of inter-class transitions by focusing on the dominant signals of change. We also investigated how the LULC is going to move in the future (2040) based on matrices of current states using the Discrete-Time Markov Chain (DTMC) model. The results revealed that, between 1995 and 2018, about 28% of the Beja district landscape changed. Particularly, croplands remain the predominant LULC class in more than half of the Beja district (in 2018 about 64%). However, the behavior of the inter-class transitions was significantly different between periods, and explicitly revealed that arable land, pastures, and forest were the most dynamic LULC classes. Few dominant (systematic) signals of change during the 1995–2018 period were observed, highlighting the transition of arable land to permanent crops (5%) and to pastures (2.9%), and the transition of pastures to forest (3.5%) and to arable land (2.7%). Simulation results showed that about 25% of the territory is predicted to experience major LULC changes from arable land (−3.81%), permanent crops (+2.93%), and forests (+2.60%) by 2040.

Highlights

  • In many areas of the globe, the scale and extent of land use/land cover (LULC) changes have been affected by socioeconomic and biophysical factors (e.g., [1,2])

  • Over the last decade, for dynamic visualization and quantification of the spatial patterns of the LULC changes, Geographic Information Systems (GIS) have been widely used, since they allow for the use of vector or remote sensing data, expressed spatially and temporally [6,7,8]

  • This region is characterized by a vast landscape of wheat, cork oaks, and olive trees, where the dominant land use is mixed agrosilvopastoral

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Summary

Introduction

In many areas of the globe, the scale and extent of land use/land cover (LULC) changes have been affected by socioeconomic and biophysical factors (e.g., [1,2]). This region is characterized by a vast landscape of wheat, cork oaks, and olive trees, where the dominant land use is mixed agrosilvopastoral. In order to specify the major changes in croplands and characterize the type of agricultural activity in this region, we used the second hierarchical level of the COS nomenclature of the agriculture mega class, namely arable land, permanent crops, pastures, and heterogeneous areas.

Spatiotemporal LULC Change Analysis
LULC Change Detection
States Transition Probability of the Markov Chain
Classification States and Simulating Future States
Uncertainty of Future States
LULC Spatiotemporal Evolution and Distribution
Classification States
Simulating Future States
About the Dominant LULC Transitions
About the LULC Future Changes
Main Conclusions and Future Studies
Full Text
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