Land Use Demands for the CLUE-S Spatiotemporal Model in an Agroforestry Perspective

Mamanis, Georgios; Vrahnakis, Michael; Chouvardas, Dimitrios; Nasiakou, Stamatia; Kleftoyanni, Vassiliki

doi:10.3390/land10101097

Cited by 24 publications

(12 citation statements)

References 23 publications

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“…Thus, it is increasingly necessary to explore the development of habitat quality from the perspective of simulation, which could bring lessons to ecosystem protection planning and habitat quality management. Predicting land use can be experimented on using a variety of models [ 27 , 28 ]. The study used a patch-generating land-use simulation model (PLUS) integrated with a Markov chain to predict land use in the future.…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Changes in Land Use and Habitat Quality of Hobq Desert along the Yellow River Section

Meng

Cai

Hui

et al. 2023

IJERPH

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As a key area in the Yellow River basin for sand control and management, the land change process in the Hobq Desert plays a crucial role in keeping the river and desert ecosystems and promoting the construction of ecological civilization in human systems. Based on multi-temporal remote sensing from 1991 to 2019 in the Hobq Desert along the Yellow River section, this study selected spatial statistical methods (land-use monitoring and landscape metrics) to examine land-use change dynamics. Then, we evaluated habitat quality using the InVEST model and quantitatively analyzed the factors causing spatial changes in habitat quality using geographic detectors. Finally, this paper predicted the pattern of land use and habitat quality in 2030 using the PLUS model. The results reveal that (1) from 1991 to 2019, the total area of forest grassland increased by 3572.5 km2, providing the most vegetation cover, and the sandy land and water area decreased continuously, while the cultivated land and construction land increased. There were 38.01% conversions of land types, with the land-use dynamic decreasing the greatest in sandy land (−12.66%) and increasing the greatest in construction land (9.26%); the comprehensive land-use dynamics were the highest in 2010–2019 (1.68%), which was the most active stage during our study period. (2) Both of the landscape indices NP and PD showed “N” type fluctuations during 1991–2019, and CONTAG and LSI rose from 69.19% to 70.29% and 36.01% to 38.89%, respectively, indicating that the land-use degree of landscape fragmentation increased, landscape connectivity turned better, and landscape dominance was enhanced, balanced, and developed evenly in overall landscape type. (3) From the overall region analysis, the average habitat quality in 1991, 2000, 2010, and 2019 was 0.3565, 0.5108, 0.5879, and 0.6482, respectively, with the overall habitat value showing a gradually increasing trend. Spatially, the habitat quality along the Yellow River section of the Hobq Desert has a certain regularity, and the overall pattern there is high in the south and low in the north, high in the east and west, and low in the middle. (4) The change in land use between 2019 and 2030 is similar to the previous period, but the change rate is generally lower. The habitat quality improved significantly, with the growth of high and medium habitat quality.

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Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Changes in Land Use and Habitat Quality of Hobq Desert along the Yellow River Section

Meng

Cai

Hui

et al. 2023

IJERPH

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“…In recent years, spatial-temporal forecasting has been used to help optimize the development direction of urban planning, so as to obtain the urban development dynamics and ES capacity in advance and provide timely feedback and adjustment, which has achieved good results [ 15 , 16 ]. Cellular Automata (CA), as one of the most important and widely used methods across many models, was the basis of many models, such as the Logistic-CA model [ 17 ], ANN-CA model [ 18 ], CLUE-S model [ 19 ] and FLUS model [ 20 ]. The CA-Markov model was a relatively successful simulation method, which combined the ability of the CA model to simulate the spatial changes of complex systems and the advantage of the Markov model in long-term prediction [ 21 , 22 , 23 ].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Evolution, Prediction and Optimization of LUCC Based on CA-Markov and InVEST Models: A Case Study of Mentougou District, Beijing

Yang

Zhang²,

Zhu

et al. 2022

IJERPH

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With the rapid advancement of urbanization and industrialization, the contradiction between the social economy and resources and the environment has become increasingly prominent. On the basis of limited land resources, the way to promote multi-objective comprehensive development such as economic, social development and ecological and environmental protection through structure and layout regulation, so as to maximize regional comprehensive benefits, is an important task of current land spatial planning. Our aim is to obtain land-use-change data in the study area using remote-sensing data inversion and multiple-model simulation. Based on land suitability evaluation, we predict and optimize the land use structure of the study area in 2030 and evaluate and compare ecosystem services. Based on remote-sensing images and eco-environmental data from 1985 to 2014 in the study area, land use/land cover change (LUCC) and future simulation data were obtained by using supervised classification, landscape metrics and the CA-Markov model. The ecosystem services were evaluated by the InVEST model. The analytic hierarchy process (AHP) method was used to evaluate the land suitability for LUCC. Finally, the LUCC in 2030 under two different scenarios, Scenario_1 (prediction) and Scenario_2 (optimization), were evaluated, and the ecosystem service functions were compared. In the last 30 years, the landscape in the study area has gradually fragmented, and the built-up land has expanded rapidly, increased by one-third, mainly at the cost of cropland, orchards and wasteland. According to the suitability evaluation, giving priority to the land use types with higher environmental requirements will ensure the study area has a higher ecosystem service value. The rapid development of urbanization has a far-reaching impact on regional LUCC. Intensive land resources need reasonable and scientific land use planning, and land use planning should be based on the suitability evaluation of land resources, which can improve the regional ecosystem service function.

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“…Multi-scenario land-use change simulation can be predicted and analyzed by various models, and many models have been applied for future land-use change. These include the Markov chain model for calculating land demand [25,26], the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model for allocating land-use change demand space [27,28], the cellular automata(CA) model for simulating complex spatial patterns of land use [29,30], the artificial neural network (ANN) model for dealing with non-deterministic identification and classification [31], and coupled models that combine multiple advantages of different models [32][33][34][35]. The above models can achieve good simulation accuracy in applications but lack the comprehensive ability to simulate spatial and temporal changes in land use.…”

Section: Introductionmentioning

confidence: 99%

Multi-Scenario Simulation of Production-Living-Ecological Space in the Poyang Lake Area Based on Remote Sensing and RF-Markov-FLUS Model

Fang

Xia

et al. 2022

Remote Sensing

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With industrialization and urbanization, the competition among land production, living, and ecological (PLE) spaces has intensified. Particularly in ecological reserves, competition among various types of land use restricts the coordinated development of PLE space. To explore spatial sustainable development, this study starts from a PLE spatial perspective, based on Landsat long time series images. Object-based image analysis (OBIA) and landscape index analysis were selected to monitor the spatial and temporal land use and landscape pattern changes in the Poyang Lake region (PYL region) from 1989 to 2020. The RF-Markov-FLUS coupled model was used to simulate spatial changes in 2030 under four scenarios: production space priority (PSP), living space priority (LSP), ecological space priority (ESP), and an integrated development (ID). Finally, the goal-problem-principle was used to enhance PLE space. The results showed that: (1) production space and ecological spaces decreased in general from 1989 to 2020 by 3% and 7%, respectively; living space increased by 11%. (2) From 1989 to 2020, the overall landscape spread in the Poyang Lake (PYL) area decreased, connectivity decreased, fragmentation increased, landscape heterogeneity increased, and landscape geometry became more irregular. (3) Compared with the other three scenarios, the ID scenario maintained steady production space growth in 2030, the expansion rate of living space slowed, and the area of ecological space decreased the least. (4) Spatial pattern optimization should start with three aspects: the transformation of the agricultural industry, improving the efficiency of urban land use, and establishing communities of “mountains, water, forests, fields, lakes and grasses”. The results provide scientific planning and suggestions for the future ecological protection of Poyang Lake area with multiple scenarios and perspectives.

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Land Use Demands for the CLUE-S Spatiotemporal Model in an Agroforestry Perspective

Cited by 24 publications

References 23 publications

Spatio-Temporal Changes in Land Use and Habitat Quality of Hobq Desert along the Yellow River Section

Spatio-Temporal Changes in Land Use and Habitat Quality of Hobq Desert along the Yellow River Section

Spatio-Temporal Evolution, Prediction and Optimization of LUCC Based on CA-Markov and InVEST Models: A Case Study of Mentougou District, Beijing

Multi-Scenario Simulation of Production-Living-Ecological Space in the Poyang Lake Area Based on Remote Sensing and RF-Markov-FLUS Model

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