Actual Land Use Research Articles

Effect of calculation unit division in distributed hydrological models on the analysis of hydrological effects of land use change

Numerous papers have utilized distributed hydrological models to assess the hydrological effects of land use changes. However, can these models reflect actual land use changes? This study focuses on the effect of calculation unit division in distributed hydrological models on the analysis of hydrological effects of land use change. The Soil and Water Assessment Tool (SWAT) model is tested here, using the Dongjiang headwater region in southern China as the study area. Thirteen calculation unit division schemes are developed to analyze the effects of land use generalization caused by calculation unit division on runoff and sediment load simulations by SWAT. Two indices, including Land Use Identification Accuracy (LUIA) and Land Use Change Identification Accuracy (LUCIA) are employed to quantify the model’s precision in describing land use and changes under various scenarios. In addition, this study examines how differences in land use descriptions, resulting from calculation unit division, influence the hydrological effect of land use changes in the SWAT model. The findings indicate that: (1) Calculation unit division leads to the generalization of land uses identified by the SWAT model. As the sub-watershed Drainage Area Threshold (DAT) increases, the small land use types tend to aggregate into the larger land use types. (2) Land use generalization, resulting from calculation unit division, significantly affects runoff and sediment load simulations. An increase in DAT induces a significant rise in simulated runoff and sediment load (P<0.001). (3) Calculation unit division substantially impacts the model’s description of land use. LUIA and LUCIA show a significant downward trend as DAT increases. (4) Calculation unit division significantly alters the analysis results of hydrological effects of land use changes. Different calculation unit division schemes yield different analysis results of hydrological effects of land use changes. These results demonstrate that the division of calculation units in the SWAT model leads to land use generalization, which impacts the model’s description of land use changes and subsequently affects the assessment of the hydrological effects of land use changes. The research results imply that when analyzing the hydrological effects of land use change, a more refined calculation unit division scheme should be adopted as far as possible to improve the accuracy of model’s description of land use change and reduce the uncertainty of model simulation results.

Urban land use simulation and carbon-related driving factors analysis based on RF-CA in Shanghai, China

As global climate change intensifies, climate protection is important for the sustainable development of human society. In the process of urbanization and industrialization, carbon dioxide emissions are an important factor contributing to global warming. Therefore, modelling projections of future urban land use under low-carbon scenarios are essential for sustainability policy development. Few studies have focused on the impact of carbon emissions on urban land use change in Shanghai, as current research has primarily concentrated on developing methods for urban land use modelling. This paper utilizes a cellular automata (CA) simulation model based on the Random Forest (RF) algorithm to select various spatial variables of carbon emissions as the driving factors that affect urban land use changes. These variables include traffic location factors, economic development factors, electricity consumption, and population density. In this study, remote sensing imagery of urban nighttime lighting is also used to construct a simulation model of land use types in Shanghai. The model is then used to analyze the contribution of carbon emission constraints to urban land use changes. Actual historical land use data from 2013 and 2019 are used for validation, and the prediction model is used to predict land use outcomes under different low-carbon scenarios in 2025. The model is validated by simulating multiple intra-city land use maps for 2019 (kappa = 0.88, OA=92.71 %). The method of out-of-bag error from the random forest is used to evaluate the significance of carbon emission constraints. Using the validated model, the constraints in the CA model are changed to predict the land use simulation results of Shanghai in 2025 under different low-carbon scenarios. In terms of significance, factors such as distance to power plants, distance to major roads, real GDP, and population density can all have a significant impact on changes in urban land use. By selecting the low-carbon scenario with the most appropriate thresholds for each driver, it is possible to obtain the land use simulation results of Shanghai in 2025 under the optimal low-carbon scenario, while ensuring the high accuracy of the RF-CA model and simultaneously reducing the impact of factors on the city’s overall carbon emissions. This paper provides a scientific base for urban planners and scholars to thoughtfully design urban land use while cutting down on carbon emissions. Furthermore, it can aid government agencies in establishing associated planning approaches.

Spatial Analysis of LULC Changes and Suitability of Ngawi Regency on Spatial Regional Planning 2011-2031 Using Geographic Information System

Abstract This study analyzes land use change in Ngawi Regency, East Java, in 2011 and 2021 and examines the suitability of land use, Regional Spatial Plan, and Regional Medium-Term Development Plan. Qualitative descriptive analysis methods and spatial-temporal analysis are used to identify land-use change, land-use change, and land-use-related problems. The results showed a discrepancy between actual land use and RTRW in several sub-districts, such as Padas, Pangkur, Ngawi, Pitu, Kedunggalar, Ngrambe, Sine, Jogorogo, Kendal. This discrepancy includes changes in land functions from settlements to industries, tourism areas to settlements, industries to settlements, and vice versa. The total area of nonconformity reached 40,361 hectares or 28.93 % of the Ngawi area. GIS and map overlays provide an in-depth understanding of land change patterns, with settlements and industrial sectors being key focuses. Although the Regional Spatial Plan has been established to regulate land use, its implementation still needs to be improved in 2021. The development of tourism, industrial, agricultural, and residential areas sometimes goes differently than planned. This research highlights the need for coordination between Regional Medium-Term Development Plans and Regional Spatial Plans to achieve sustainable regional development.

Land Use Change Analysis and Remote Sensing-Based Spatial Evaluation In Kendal District, Indonesia in 2015 and 2020

Abstract Land use change in Kendal District, Indonesia, has become a crucial issue in spatial management. The mismatch between land use and spatial planning is one of the problems that often occurs. Limited land and rapid population growth have driven significant changes in land use, especially in the industrial sector, so an evaluation is needed by comparing actual land use in the area with the applicable Spatial Plan. This research aims to analyze land use change between 2015 and 2020 in Kendal District. Based on quantitative approaches and descriptive analysis, secondary data and interpretation of remote sensing imagery are used to understand land change. The results show that there were significant changes in spatial planning and land use in 2015 and 2020, so these results can make an important contribution to the government in regional planning and sustainable urban development. Changes in land use in Kendal Regency have not been in accordance with the Spatial Pattern Plan Map of the Kendal area. This is because changes will continue to occur, so changes in land use will also continue to change. It is not surprising that changes have not occurred significantly or in accordance with the planned pattern.

Unpacking conservation easements' assessed land use designations and their implications for realizing biodiversity protection

AbstractNative ecosystem and biodiversity loss from land use conversion into human‐modified landscapes are evident in the United States and globally. In addition to public land conservation, there is an increase in private land conservation through conservation easements (CEs) across exurban landscapes. Not every CE was established strictly for biodiversity protection and permitted land uses can increase human modification. No research of which we are aware has examined the actual tax assessor's land use designations (LUDs) through time. We constructed granular CE datasets (GCED) of CEs and their parcels' tax assessment LUDs for 1997–2008/2009, based on original data from 12 counties in six US states. Using the GCED, we examined patterns in the LUDs, with implications for land uses that could impact CE biological outcomes. We show that LUDs on exurban private conservation lands were predominately residential and agricultural, with increased residential over time. Critically, the LUDs lack a biological conservation exempt designation/category. There is no consistent trend in association between the primary CE reason and its parcel's LUD, suggesting that they coincide in some circumstances but in others, the CE may be a response to contravene the LUD. The majority of the first CE reasons are focused on open space preservation, except in some counties where agricultural land uses and agricultural CEs are associated. The economically and human‐focused LUD is one of many social factors that should be considered in a classification system for private land conservation and CEs more specifically. These results prompt the land conservation, conservation biology, and environmental planning communities to explore assessed land uses' impact on biodiversity conservation objectives.

A Multi-Feature Fusion Method for Urban Functional Regions Identification: A Case Study of Xi’an, China

Research on the identification of urban functional regions is of great significance for the understanding of urban structure, spatial planning, resource allocation, and promoting sustainable urban development. However, achieving high-precision urban functional region recognition has always been a research challenge in this field. For this purpose, this paper proposes an urban functional region identification method called ASOE (activity–scene–object–economy), which integrates the features from multi-source data to perceive the spatial differentiation of urban human and geographic elements. First, we utilize VGG16 (Visual Geometry Group 16) to extract high-level semantic features from the remote sensing images with 1.2 m spatial resolution. Then, using scraped building footprints, we extract building object features such as area, perimeter, and structural ratios. Socioeconomic features and population activity features are extracted from Point of Interest (POI) and Weibo data, respectively. Finally, integrating the aforementioned features and using the Random Forest method for classification, the identification results of urban functional regions in the main urban area of Xi’an are obtained. After comparing with the actual land use map, our method achieves an identification accuracy of 91.74%, which is higher than other comparative methods, making it effectively identify four typical urban functional regions in the main urban area of Xi’an (e.g., residential regions, industrial regions, commercial regions, and public regions). The research indicates that the method of fusing multi-source data can fully leverage the advantages of big data, achieving high-precision identification of urban functional regions.

A New Strategy for Planning Urban Park Green Spaces by Considering Their Spatial Accessibility and Distributional Equity

Urban park green spaces (PGSs) are crucial social public resources that provide various ecological services and enhance human health and well-being. However, with the acceleration of urbanization, the accessibility and equity of urban PGS resources are increasingly threatened. This study aims to propose an integrated framework that considers accessibility and equity simultaneously to optimize the planning and layout of urban PGS within the high-speed ring road of Hefei City. This study first used an improved two-step floating catchment area (2SFCA) method to quantify the level of accessibility of urban PGS within the ring road. Then, with the use of Lorenz curves, Gini coefficients, and bivariate correlation coefficients, the equity characteristics of these PGSs were quantified and evaluated, followed by an analysis of their relationships to the accessibility levels. Based on this comprehensive evaluation, the particle swarm optimization (PSO) algorithm was employed to the areas with low accessibility and equity levels to propose targeted PGS optimization strategies. The results showed that the accessibility of PGS was unevenly distributed, exhibiting a clear spatial difference of “east–west clustering”. The number of subdistricts with good (52.24–94.78) and best (94.79–283.58) accessibility was four, which was less than one-tenth of the total number of subdistricts in the study area. At the subdistrict level, the Gini coefficients for the accessible area of all types of PGSs were substantially higher than the international warning line of 0.4, indicating a substantial inequity in the population’s access to PGS. The implemented PSO algorithm resulted in eight new parks being planned at the specific optimized locations. Based on the actual land use status of the selected sites, recommendations are provided for the planning and layout of PGS. This proposed framework offers valuable data and theoretical insights for urban public green space planning and design in similar regions.

Monitoring of Cropland Abandonment and Land Reclamation in the Farming–Pastoral Zone of Northern China

The farming–pastoral zone in northern China is one of the most ecologically sensitive areas globally, having experienced extensive cropland abandonment and land reclamation over decades, primarily influenced by policy adjustment and global warming. However, the spatiotemporal patterns and suitability of long-term cropland change remain poorly understood. Using the annual China land cover dataset (CLCD), we provide a cropland abandonment and land reclamation mapping approach based on actual land use processes (rather than land cover conditions) to investigate spatiotemporal features of abandonment and reclamation and evaluate the rationality. Our findings show that: (1) Returning farmland to forest and grassland has been a clear trend in the study area over the past 30 years. Specifically, cropland use has undergone three phases of change, i.e., cropland contraction and expansion alternately (before 2000), followed by substantial abandonment (after 2000), and low-intensity reclamation (after 2010). (2) In the last decade, the intensity of the abandonment of cropland with high and moderate suitability is low. The rate of abandonment decreased, while the intensity of land reclamation was relatively high. The rate of the reclamation increased, and the spatial distribution of cropland tended to be reasonable. Our study emphasizes the importance of monitoring actual cropland changes based on land use processes, and this method can be effectively extended to regional or global long-term cropland monitoring.

Application of Satellite Images and Artificial Intelligence to Monitor Land Cover Changes in Hanoi Area During 2013-2023 Period

Artificial intelligence (AI) and remote sensing technology have now increasingly improved their efficiency and reliability in monitoring the changes in land cover. With the amendment of the Vietnamese Law on Land in 2013 and the administrative boundary expansion of Hanoi, Hanoi experiences significant changes in land use and land cover for the last ten years. To monitor the actual land use changes in the area, this study used the Random Forest (RF) machine learning algorithm to classify the basic land covers, monitor, and analyze the spatial variation of land use and land cover in the 2013 to 2023 period. The study findings indicate a relatively high rate of expansion of construction zone area and a decrease in land cover related to water bodies and vegetated area. Water bodies decrease by an average of 0.8% annually, whereas the construction zone area increased by 7% of the total area.&#x0D;

A new assessment framework to forecast land use and carbon storage under different SSP-RCP scenarios in China

The vision of achieving “carbon neutrality” has created new requirements for the projection of land use and land cover (LULC), as well as the carbon storage (CS) of terrestrial ecosystem. Global-scale LULC scenario assessments with coarser resolution introduces uncertainties to national and regional-scale studies, which in turn has a negative impact on CS analysis based on land use perspective. Therefore, we proposed a new framework for scenario-based assessment that integrates the global-scale Land Use Harmonization (LUH2) dataset, Patch-generating Land Use Simulation (PLUS) model, and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, which we called LUH2-PLUS-InVEST (LPI) model. Our aim is to investigate the potential impacts of the combinations of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) on China's future LULC and CS. By calibrating the demands, we generated structural predictions that were consistent with the actual land use. Furthermore, we explored the spatial heterogeneity of potential land use changes using 500 m × 500 m downscale simulations. Additionally, we developed a quantitative evaluation of CS from a spatiotemporal perspective and made recommendations on potential ecological threats. Our findings indicate that the basic characteristics of LULC and CS are determined by the natural context and that the prospects of land use distribution and carbon sequestration capacity are influenced by global emission pressure, regional competition, and China's unique development pattern. The results demonstrate that the LUH2-PLUS-INVEST model can provide an effective method for modeling the feedbacks of LULC and CS to the climate-society system.

Land use planning implementation and its effect on the ecosystem in Addis Ababa, Ethiopia

Land use planning plays a pivotal role in the enhancement of urban ecosystems. However, very few studies evaluate the implementation of land use planning in Ethiopia and the subsequent effects on ecosystems. This study aimed to assess the efficiency and constraints of the implementation of the land use plans of Addis Ababa and their effects on the enhancement of the ecosystem. The data were collected from the Urban Planning and Development Commission, satellite images, and expert surveys. GIS, descriptive statistics, and expert judgment are employed to analyze the data. The model used for evaluating land use planning was the conformance approach, while the benefit transfer method was employed to assess the ecosystem service values. The findings revealed a disparity between the two land use plans. Both plans failed to align with the actual land use, converting the proposed land for ecosystems into physical structures. Comparing the 2006 land use plan with the 2011 land cover, it was observed that 68 %, 62.8 %, 48.8 %, and 35.2 % of proposed agriculture, urban green, waterbodies, and forest lands were transformed into built-up structures, respectively. A similar trend was observed when comparing the 2017 land use plan with the 2023 land cover, with 41 %, 25 %, 52.1, and 59 % of agricultural, forest land, urban green, and water bodies, respectively, transformed into physical structures, mainly settlements. This inconsistency between the land use plans and the actual land use hurts ecosystem services due to the encroachment by built-up structures. The lack of adherence to proposed land use plans in Addis Ababa can be attributed to poor planning projection, the proliferation of informal settlements, and interference by local governments and developers. Inadequate implementation results from the proliferation of informal settlements, a lack of proper prosecution of land violations, interference from stakeholders, a lack of synergy, and the absence of an effective legal framework. Addressing these issues requires effective security services, the involvement of relevant agencies, a land use plan review, and stringent enforcement and monitoring of the land use plan.

Model of WebGIS Based Sustainable Smart Land Use for Merauke Regency South Papua

This Smart and sustainable land use is the key to answering development challenges in the modern era. In the context of Merauke Regency, South Papua, rapid economic growth and significant environmental changes demand an integrated approach to managing land use. This research presents an innovative WebGIS-based model that combines geospatial information technology with land use analysis to provide sustainable solutions. Through the integration of spatial data, predictive analysis and stakeholder participation, this model enables stakeholders to explore alternative land use scenarios and evaluate their environmental, economic and societal impacts. The performance evaluation stage of the model shows its ability to accurately represent existing land use patterns. Validation with actual land use data confirms the ability of the model to reproduce the distribution of agricultural areas and protected forest areas. Furthermore, the evaluation of the environmental impact of the model results indicates that the model is capable of predicting the environmental impact of alternative land use scenarios. Consultation sessions with stakeholders proved the importance of their participation in the validation and adaptation of sustainable solutions. The results of this study indicate that WebGIS-based Smart Land Use model has great potential in assisting sustainable planning and decision-making in Merauke Regency. However, further validation and improvement of the model is needed to strengthen its accuracy and validity. This research provides valuable insights on the integration of geospatial information technology in sustainable development and provides guidance for the development of similar models in other regions.

Constantine – Algeria- informal expansion, private lands value at stake. Towards a preventive approach to informal land use

In this paper, we examine the informal expansion of Constantine from the perspective of land as a property asset and a regulation target and what it involves in terms of stakeholders’ interplays. The study was conducted on the southeastern expansion by drawing a parallel between land use regulation and the actual land use on large private landholdings. A qualitative survey was conducted to investigate the informal production and use of urban land through semi-structured interviews with relevant public and private stakeholders. The study shows that informal land use lies in the conflict between urban planners and landowners over the conversion and allocation of large private landholdings and the financial stakes it involves. Land transactions are engaged in the informal market when land use regulation does not converge with the owner’s logic of land value maximization. The informal land market allows the latter to circumvent land use regulation and to capture land added value on hypothetical uses, whether by informally converting agricultural lands or allocating urban ones. As to the resulting informal land use, it is not limited to housing issues but also meets the needs of private actors for tertiary real estate. It is also pointed out that land use policy and regulations failure in countering the phenomenon lies in ignoring the informal land market upstream of informal land use and urbanization. Finally, the study suggests that a preventive approach should address the conflict over land use with land management oriented towards local approach and consensus seeking with the private stakeholders. In this sense, we propose a tool to assess the likelihood of the emergence of informal land market as a decision aid for urban planners and policymakers in terms of land use.

A new decision-making method for the renewal of agricultural irrigation wells: A case study of Songzhuang town, Tongzhou District, Beijing

Pumping wells (PWs) lie at the core of agricultural irrigation infrastructure, and their spatial configuration is of great significance for the scientific management of regional agriculture and rational use of water resources. To solve the problems of unreasonable and unscientific spatial allocation of regional agricultural irrigation PWs, this paper proposes a new strategy for updating agricultural irrigation PWs based on a spatial decision model, using Songzhuang Town, Tongzhou District, Beijing as a case study. The model utilizes constraints based on local factors such as actual land use, and proposes a novel feasible solution strategy that combines random local search and abrupt jumps to increase the probability that feasible solutions will be found, addressing the performance issues of simulated annealing algorithms, influence of initial values, and parameter sensitivity. Finally, we used the proposed method to perform updated decision analysis on the spatial configuration of PWs in the study area. The results showed that most of the crops in the study area lack irrigation, and the currently available PWs cannot meet the needs for irrigation. The new PWs added based on this decision method can be more evenly distributed within the predefined optimization unit. The proposed number of PWs to be added is 166, the density of PWs is 0.04/ha, and the crop area covered by the PWs is 3350.43 ha. In contrast to the previous PW layout, the optimized PW configuration can meet the irrigation needs of residents, indicating that the new method proposed in this paper has good potential for extension and application.

Impacts of Land Use and Climate Change on Ecosystem Services in Agro-pastoral Ecotone

Land use and climate change are the most important factors driving the change in ecosystem services (ESs). It is critical to understand the mechanisms behind such changes for improving ESs. However, there is still a lack of accurate understanding of change and dominant influencing factors of ESs in the agro-pastoral ecotone. This study took Naiman Banner, a typical farming pastoral ecotone in China, as the case study area. Based on the InVEST model, the revised wind erosion equation (RWEQ) and the revised universal soil loss equation (RUSLE) were used to calculate water yield, soil retention, and windbreak and sand-fixing in Naiman Banner in 2005 and 2015. Finally, the impacts of land use and climate change on these three ecosystem services were analyzed by using contribution rate formula, Pearson correlation coefficient, and geodetector methods. The results indicate that:① from 2005 to 2015, water yield and soil retention in Naiman Banner showed an overall upward trend, increasing by 22.41% and 6.74%, respectively, and windbreak and sand-fixing decreased by 66.24%. ② The change in water yield and windbreak and sand-fixing was mainly affected by climate change, and the change in soil retention was mainly affected by land use change. ③ Actual evapotranspiration change and land use change were the main factors affecting the spatial differentiation of water yield, with the explanatory powers of 94.50% and 50.05%, respectively. The main factors influencing the spatial differentiation of windbreak and sand-fixing were actual evapotranspiration change and land desertification degree, with the explanatory power of 19.84% and 16.15%, respectively. ④ The correlation of ESs in Naiman Banner was weak, and only windbreak and sand-fixing and water yield showed a weak significant synergy. Based on the results, we recommend that managers increase the proportion of grassland in sandy areas, implement closed management in pastoral areas, and introduce drip irrigation and other water-saving technologies in farmland, and ecological protection should continue to be given priority in city.

ANALISIS POLA PEMANFAATAN RUANG PADA KAWASAN RAWAN BANJIR DI KABUPATEN LOMBOK BARAT

West Lombok Regency often experiences floods. The flooding problem requires proper land use planning and management that is also integrated with the regional spatial strategy. However, in reality there are often inconsistencies between regional spatial plans and actual land use. The purpose of this research is to make a map of the distribution of flood-prone areas; to analyse the relationship between land use and spatial pattern plans in flood-prone areas; to analyse the relationship between spatial use patterns in flood-prone areas and existing land use. This research was conducted based on spatial analysis, multicriteria analysis, and descriptive analysis. There are six flood-prone factors used in this study, including rainfall intensity (I), slope (S), land use (U), soil type (ST), distance from drainage network/river (D) and altitude (E). The results of this study indicate that the area in West Lombok Regency based on the potential class of flood vulnerability is dominated by the mildly vulnerable class which is spread across all sub-districts, namely 47,624.24 Ha. (51.80%), not prone is 21,001.92 Ha (22.84%), and ± 25% of the remaining area is divided into medium prone 15,241.75 Ha (16.58%), prone 7,871.98 Ha (8.56%) and very prone 195.79 Ha (0.21%).

Soil erosion assessment by RUSLE model using remote sensing and GIS in an arid zone

ABSTRACT In this research, we used the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS) to predict the annual rate of soil loss in the District Chakwal of Pakistan. The parameters of the RUSLE model were estimated using remote sensing data, and the erosion probability zones were determined using GIS. The estimated length slope (), crop management (), rainfall erosivity (), soil erodibility (), and support practice () range from 0–68,227, 0–66.61%, 0–0.58, 495.99–648.68 0.15–0.25 , and 1 respectively. The results indicate that the estimated total annual potential soil loss of approximately 4,67,064.25 is comparable with the measured sediment loss of 11,631 during the water year 2020. The predicted soil erosion rate due to an increase in agricultural area is approximately 164,249.31 . In this study, we also used Landsat imagery to rapidly achieve actual land use classification. Meanwhile, 38.13% of the region was threatened by very high soil erosion, where the quantity of soil erosion ranged from 365487.35 . Integrating GIS and remote sensing with the RUSLE model helped researchers achieve their final objectives. Land-use planners and decision-makers use the result's spatial distribution of soil erosion in District Chakwal for conservation and management planning.

A comparative assessment of forest/green cover and the awareness of forestry district managers.

Urban forests are becoming more critical as climate-induced disasters and disturbances tend to increase and affect cities. Forest managers are the responsible technical people on the ground to implement forestry-related climate policies. There is limited knowledge on the capacities of forest managers related to climate change issues. In this study, we surveyed 69 forest district managers of 28 provinces and compared their responses with actual data to understand their perceptions of urban green areas and climate change issues. We used a set of digital maps of the 1990-2015 period to identify land cover changes. To calculate the urban forest cover in the city centers, we used the city limit delineation shapefiles produced by the EU Copernicus program. We also employed the land consumption rate/population growth rate metric and a principle component analysis (PCA) to identify and discuss the provinces' land and forest cover changes. The results showed that forest district managers were aware of the general condition of the forests in their provinces. Still, there was a considerable inconsistency between actual land use changes (i.e., deforestation) and their responses. The study also revealed that the forest managers were aware of the increasing influence of climate change issues but were not knowledgeable enough to establish the connection between their tasks and climate change. We concluded that the national forestry policy should prioritize the urban-forest interaction and develop the capacities of district forest managers to improve the efficiency of climate policies on a regional scale.

Simulating multiple scenarios of land use/cover change using a coupled model to capture ecological and economic effects

AbstractThe conflict between the demands of ecological protection and economic development is increasingly prominent. Land use change is sensitive to whether economic or ecological profits dominate, and prediction of future land use changes has become an important scientific issue. This article constructs a coupled model that comprises the grey model (GM), the fuzzy multiple objective linear programming model (FMOLP) and the future land use simulation model (FLUS). We used this model to calculate a macro‐scale quantitative forecast using the top‐down GM‐FMOLP model, and calculated micro‐scale spatial simulations of land use/cover change (LUCC) using the bottom‐up FLUS model under three dissimilar future scenarios, with different emphases on ecological and economic benefits. The scenarios were designed to meet different planning requirements in Chongqing: ecological benefits maximization, economic benefits maximization, and combined ecological and economic benefits maximization. The proposed model, FLUS, was applied to a LUCC simulation for Chongqing in 2015, beginning from verified historical land use data from 2010. The results show that the simulation agrees well with the actual land use in 2015. The overall accuracy and kappa coefficient are 85.92% and 0.76, respectively, which indicates the model performs well. The three land use types with the highest producer and user accuracies are forest, cropland and water areas. The GM‐FMOLP model was used to forecast future LUCC quantity demand, and the FLUS model was then used to calculate spatial predictions for the three scenarios for 2040. The prediction results for the six land use types were significantly different under the three different scenarios. The total areas of forest, urban land and water increased by different degrees under the three scenarios, and the unused land area dwindled. Cropland areas were largely converted into forest, urban land and water areas. The increases in forest and urban land areas generally represents internal gap‐filling between disparate areas and peripheral expansion of areas of the same land use type. The increase in water area results from increased surface runoff in mountainous valleys with severe terrain. Areas of unused land are fully transformed into other land use types. The outcomes from the designed scenarios demonstrate that the proposed models are reliable and effective for future LUCC simulation, and highlight key areas where land use changes differently according to the scenario. In summary, in the predictions for the scenario that combined ecological and economic benefits maximization, each land use type tried to maximize ecological and economic benefits under the constraints, taking into account ecological safety and economic growth, which is in line with the coordination, comprehensiveness and binding requirements in Chongqing's development plan. Therefore, this scenario becomes the optimal scenario for land use optimization in Chongqing in the future. This study provides an example of the application of simulation and forecast models in land use management, remediation and urban planning, and addresses the growing requirement for low‐cost and effective tools for prediction of dynamic land use succession patterns.

FLUS Based Modeling of the Urban LULC in Arid and Semi-Arid Region of Northwest China: A Case Study of Urumqi City

Modeling land use and land cover (LULC) change is important for understanding its spatiotemporal trends and plays a crucial role in land use planning and natural resources management. To this end, this study assessed the spatiotemporal characteristics of the LULC changes in Urumqi city between 1980 and 2020. In addition, future LULC was successfully projected for 2030 and 2050 under different scenarios based on the FLUS model. This model was validated using actual and simulated land use data for 2020. The kappa coefficient and figure of merit of the simulation results for 2020 were 0.87 and 0.114, respectively, indicating that the simulation accuracy was satisfactory. The results demonstrated that grassland was the major land use type, with the area accounting for more than 50% of the study area. From 1980 to 2020, urban land greatly expanded, while grassland decreased significantly. Urban land increased from 353.51 km2 to 884.27 km2, while grassland decreased from 7903.4 km2 to 7414.92 km2 from 1980 to 2020. In addition, significant transitions mainly occurred between grasslands, cultivated lands and urban lands. Grassland and cultivated land were converted into urban land, resulting in rapid urban expansion over the last 40 years. From 1990 to 2000, grassland was converted into urban land with an area of 341.08 km2. Finally, the simulation results of the LULC showed that urban land is expected to increase under all three scenarios, and cultivated land, grassland and forest land are effectively protected under the Cultivated Land Protection Scenario (CPS) and Ecological Protection Scenario (EPS) compared to the Baseline Scenario (BLS). This study assessed the spatiotemporal characteristics and transitions of LULC between 1980 and 2020, and successfully projected LULC for 2035 and 2050 in Urumqi City in the arid and semi-arid regions of northwest China based on the FLUS model, which has not been investigated in previous studies.