Abstract
The present paper proposes a novel fuzzy-VORS (vigor, organization, resilience, ecosystem services) model by integrating fuzzy logic and a VORS model to predict ecosystem health conditions in Abha city of Saudi Arabia from the past to the future. In this study, a support vector machine (SVM) classifier was utilized to classify the land use land cover (LULC) maps for 1990, 2000, and 2018. The LULCs dynamics in 1990–2000, 2000–2018, and 1990–2018 were computed using delta (Δ) change and Markovian transitional probability matrix. The future LULC map for 2028 was predicted using the artificial neural network-cellular automata model (ANN-CA). The machine learning algorithms, such as random forest (RF), classification and regression tree (CART), and probability distribution function (PDF) were utilized to perform sensitivity analysis. Pearson’s correlation technique was used to explore the correlation between the predicted models and their driving variables. The ecosystem health conditions for 1990–2028 were predicted by integrating the fuzzy inference system with the VORS model. The results of LULC maps showed that urban areas increased by 334.4% between 1990 and 2018. Except for dense vegetation, all the natural resources and generated ecosystem services have been decreased significantly due to the rapid and continuous urbanization process. A future LULC map (2028) showed that the built-up area would be 343.72 km2. The new urban area in 2028 would be 169 km2. All techniques for sensitivity analysis showed that proximity to urban areas, vegetation, and scrubland are highly sensitive to land suitability models to simulate and predict LULC maps of 2018 and 2028. Global sensitivity analysis showed that fragmentation or organization was the most sensitive parameter for ecosystem health conditions.
Highlights
With economic prosperity, demographic growth, and land use land cover (LULC) transition, urbanization is the primary driver of social and ecological transformation [1]
We incorporated fuzzy logic knowledge with the vigor–organization–resilience–ecosystem service (VORS) model to improve the accuracy of Ecosystem health (EH) models, which can be considered the unique work in the domain
These findings do not mean that the environmental conditions have been the hugeecosystem area from health moderate ecosystem improved, becausebeen the improved, huge area because from moderate conditions hashealth been condition been shifted to very poor and poor ecosystem health condition zones
Summary
Demographic growth, and LULC transition, urbanization is the primary driver of social and ecological transformation [1]. 2021, 13, 2632 socio-economic growth, the growing population and urbanization necessitate higher ecological services [4], which leads to the emergence of a commonly affecting nexus between urbanization and ecology [3]. Urban expansion has resulted in the conversion of land fragmentation and LULC patterns from initial to built land, which has a significant impact on ecosystems, such as habitat loss, decreases in agro-forest productivity, and the reduction of plants’ climate-regulating role [5]. Continuous ecosystems monitoring and impact assessments on urban ecosystems have become a scientific theme for sustainable urban landscape planning and environmental policy implication
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