Conversion Of Land Use And Its Effects Research Articles

Land Management Drifted: Land Use Scenario Modeling of Trancura River Basin, Araucanía, Chile

Modeling land use scenarios is critical to understand the socio-environmental impacts of current decisions and to explore future configurations for management. The management of regulations and permits by central and local governments plays an important role in shaping land use, with different complexities arising from site-specific socioeconomic dynamics. In Chile, the complexity is even more evident due to insufficient binding land regulations, fragmented government procedures, and the primacy of cities over rural areas. Yet land use must be managed to support sustainable development. This research integrates several state management dynamics into scenario modeling to support decision making at the basin scale through 2050. We employed a mixed qualitative-quantitative approach using interviews with state officials and local stakeholders as the basis for the Conversion of Land Use and its Effects (CLUE) model, which resulted in three scenarios with spatially explicit maps. Key findings indicate that opportunities for developing normative planning tools are limited, leaving state management without clear direction. However, current management practices can address problematic activities such as second-home projects and industrial monocultures while promoting small-scale agriculture. Scenario modeling is useful for understanding how the specifics that arise from the scalar dynamics of state management affect land use change and how existing management resources can be leveraged to achieve positive outcomes for both the ecosystem and society.

The projected impacts of smart decline on urban runoff contamination levels

There has been mounting interest about how the repurposing of vacant land (VL) through green infrastructure (the most common smart decline strategy) can reduce stormwater runoff and improve runoff quality, especially in legacy cities characterized by excessive industrial land uses and VL amounts. This research examines the long-term impacts of smart decline on both stormwater amounts and pollutants loads through integrating land use prediction models with green infrastructure performance models. Using the City of St. Louis, Missouri, USA as the study area, we simulate 2025 land use change using the Conversion of Land Use and its Effects (CLUE-S) and Markov Chain urban land use prediction models and assess these change’s probable impacts on urban contamination levels under different smart decline scenarios using the Long-Term Hydrologic Impact Assessment (L-THIA) performance model. The four different scenarios are: (1) a baseline scenario, (2) a 10% vacant land re-greening (VLRG) scenario, (3) a 20% VLRG scenario, and (4) a 30% VLRG scenario. The results of this study illustrate that smart decline VLRG strategies can have both direct and indirect impacts on urban stormwater runoff and their inherent contamination levels. Direct impacts on urban contamination include the reduction of stormwater runoff and non-point source (NPS) pollutants. In the 30% VLRG scenario, the annual runoff volume decreases by 11%, both physical, chemical, and bacterial pollutants are reduced by an average of 19%, compared to the baseline scenario. Indirect impacts include reduction of the possibility of illegal dumping on VL through mitigation and prevention of future vacancies.

Assessment of the Impacts of Land Use Change on Non-Point Source Loading under Future Climate Scenarios Using the SWAT Model

The Miyun Reservoir is an important source of surface drinking water in Beijing. Due to climate change and human activities, the inflow of Miyun Reservoir watershed (MRW) has been continuously reduced in the past 30 years, which has seriously affected the safety of Beijing’s water supply. Therefore, this study aimed to assess the mitigation measures based on the quantification of the integrated impacts of climate and land use change in MRW. The non-point source (NPS) model (soil and water assessment tool, SWAT) was used for the development of future climate scenarios which were derived from two regional climate models (RCMs) under two representative concentration pathways (RCPs). Three land use scenarios were generated by the land use model (conversion of land-use and its effects (CLUE-S)): (1) historical trend scenario, (2) ecological protection without consideration of spatial configuration scenario and (3) ecological protection scenario. Moreover, the reduction of sediment and nutrients under three future land use patterns in future climate scenarios was evaluated. The results showed that an appropriate land use change project led to the desired reduction effect on sediment and nutrients output under future climate scenarios. The average reduction rates of sediment, total nitrogen and total phosphorus were 11.4%, 6.3% and 7.4%, respectively. The ecological protection scenario considering spatial configuration showed the best reduction effect on sediment, total nitrogen and total phosphorus. Therefore, the addition of region-specific preference variables as part of land use change provides better pollutant control effects. Overall, this research provides technical support to protect the safety of Beijing’s drinking water and future management of non-point source pollution in MRW.

Modeling the spatial distribution of crop cultivated areas at a large regional scale combining system dynamics and a modified Dyna-CLUE: A case from Iran

Agricultural land use pattern is affected by many factors at different scales and effects that are separated by time and space. This will lead to simulation models that optimize or project the cropping pattern changes and incorporate complexities in terms of details and dynamics. Combining System Dynamics (SD) and a modified Conversion of Land Use and its Effects (CLUE) modelling framework, this paper suggests a new dynamic approach for assessing the demand of different crops at country-level and for predicting the spatial distribution of cultivated areas at provincial scale. As example, a case study is presented for Iran, where we have simulated a scenario of future cropping pattern changes during 2015–2040.The results indicated a change in the spatial distribution of cultivated areas during the next years. An increase in the proportion of rice is expected in northern Iran, whereas the proportion of wheat is increasing in the mountainous western areas. Wheat and barley crops are expected to become dominant within the cropping system throughout the country regions.

Urban expansion dynamics and modes in metropolitan Guangzhou, China

Urbanization changes urban landscapes and results in ecological and environmental problems. To solve these problems, it is essential to quantify the dynamics of urban expansion and better understand the modes of urban sprawl. This study evaluated urbanization in metropolitan Guangzhou, China from 1990 to 2020 and explored its modes of urban growth using Landsat Thematic Mapper images and simulated landscape maps based on the Conversion of Land Use and its Effects (CLUE) modeling framework. The results indicate that Guangzhou has experienced great expansion, characterized by the tripling of its total urbanized area within the last 20 years, and it is projected to continue expanding into less developed areas (agricultural and forest land). The results also show that adjusting the land-use structure sometime has a greater effect on the formation of the urban landscape than spatial restriction policies. Three urban expansion modes (infilling, edge expanding, and leapfrogging) were observed to occur simultaneously along with a shift in their relative dominance, which reveals a spiraling urban process.

Projected land use changes impacts on water yields in the karst mountain areas of China

Human-induced land use changes over short time scales have significant impacts on water yield, especially in China because of the rapid social economic development. As the biggest developing country of the world, China's economy is expected to continuously grow with a high speed in the next few decades. Therefore, what kind of land use changes will occur in the future in China? How these changes will influence the water yields? To address this issue, we assessed the water yields in the karst mountain area of China during the periods of 1990–2010 and 2010–2030 by coupling an Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and a Conversion of Land Use and its Effects (CLUE) model. Three different land use scenarios i.e. natural growth, economic development, and ecological protection, were developed in 2030 using the CLUE model. It was concluded that, given land use changes between 1990 and 2010, total water yields in the karst mountain area are characterized by a trend towards fluctuating reduction. However, total water yields of 2030 in the economic development scenario revealed an increase of 1.25% compared to the actual water yields in 2010. The economy development in karst mountain areas of China in the future has a slight positive influence on water yields.

Integrating Future Land Use Scenarios to Evaluate the Spatio-Temporal Dynamics of Landscape Ecological Security

Urban ecological security is the basic principle of national ecological security. However, analyses of the spatial and temporal dynamics of ecological security remain limited, especially those that consider different scenarios of urban development. In this study, an integrated method is proposed that combines the Conversion of Land Use and its Effects (CLUE-S) model with the Pressure–State–Response (P-S-R) framework to assess landscape ecological security (LES) in Huangshan City, China under two scenarios. Our results suggest the following conclusions: (1) the spatial and temporal dynamics of ecological security are closely related to the urbanization process; (2) although the average values of landscape ecological security are similar under different scenarios, the areas of relatively high security levels vary considerably; and (3) spatial heterogeneity in ecological security exists between different districts and counties, and the city center and its vicinity may face relatively serious declines in ecological security in the future. Overall, the proposed method not only illustrates the spatio-temporal dynamics of landscape ecological security under different scenarios but also reveals the anthropogenic effects on ecosystems by differentiating between causes, effects, and human responses at the landscape scale. This information is of great significance to decision-makers for future urban planning and management.

Simulation of Forestland Dynamics in a Typical Deforestation and Afforestation Area under Climate Scenarios

Forestland dynamics can affect the ecological security of a country and even the global environment, and therefore it is of great practical significance to understand the characteristics of temporal and spatial variations of forestland. Taking Jiangxi Province as the study area, this study first explored the driving mechanism of the natural environment and social economy on deforestation and afforestation using a simultaneous equation model. The results indicate that population size, topographic and geomorphologic factors, climate, and location play leading roles in influencing forestland density fluctuations. Specifically, the population size, economic development level, gross value of forestry production, climate conditions, and government policies are key influencing factors of afforestation. Deforestation is mainly influenced by agricultural population, non-agricultural economy, forestry production, forestry density, location, transportation, and climate. In addition, this study simulated the spatial distribution of land use and analyzed the spatial characteristics and variation trends of forestland area and quality under the Representative Concentration Pathways (RCPs) climate scenarios from 2010 to 2030 using the Conversion of Land Use and its Effects (CLUE) model. The results indicate that forestland declines under the Asia-Pacific integrated model (AIM) climate scenario. The environment tends to be heavily damaged under this kind of scenarios, and measures should be taken in order to protect the environment. Although the model for energy supply strategy alternatives and their general environmental impact (MESSAGE) scenario is to some extent better than the AIM scenario, destruction of the environment will still occur, and it is necessary to restrain deforestation and convert shrub land into forestland or garden land. These results can provide significant information for environmental protection, forest resource exploitation, and utilization in the areas experiencing deforestation and afforestation.

Analysis of Land Use Change Using RCP-Based Dyna-CLUE Model in the Hwangguji River Watershed

The objective of this study was to predict land use change based on the land use change scenarios for the Hwangguji river watershed, South Korea. The land use change scenario was derived from the representative concentration pathways (RCP) 4.5 and 8.5 scenarios. The CLUE (conversion of land use and its effects) model was used to simulate the land use change. The CLUE is the modeling framework to simulate land use change considering empirically quantified relations between land use types and socioeconomic and biophysical driving factors through dynamical modeling. The Hwangguji river watershed, South Korea was selected as study area. Future land use changes in 2040, 2070, and 2100 were analyzed relative to baseline (2010) under the RCP4.5 and 8.5 scenarios. Binary logistic regressions were carried out to identify the relation between land uses and its driving factors. CN (Curve number) and impervious area based on the RCP4.5 and 8.5 scenarios were calculated and analyzed using the results of future land use changes. The land use change simulation of the RCP4.5 scenario resulted that the area of urban was forecast to increase by 12% and the area of forest was estimated to decrease by 16% between 2010 and 2100. The land use change simulation of the RCP8.5 scenario resulted that the area of urban was forecast to increase by 16% and the area of forest was estimated to decrease by 18% between 2010 and 2100. The values of Kappa and multiple resolution procedure were calculated as 0.61 and 74.03%. CN (III) and impervious area were increased by 0-1 and 0-8% from 2010 to 2100, respectively. The study findings may provide a useful tool for estimating the future land use change, which is an important factor for the future extreme flood.

Integrated assessment of cropping patterns under different policy scenarios in Quzhou County, North China Plain

Agricultural land use is affected by government policies and leads to different consequences of regional sustainability. In this work, changes in cropping patterns including acreage, cropping locations and management-related environmental impacts were simulated under various policy scenarios for Quzhou County, China. This county is in China's major agricultural region, the North China Plain. Four dominant crop systems were categorized (winter wheat/summer maize, winter wheat/summer maize/spring maize, cotton, and vegetables) and analyzed, following two alternative policy scenarios that either prioritized government funding to subsidize crop production (“subsidy” scenario) or promoted advanced irrigation techniques (“technique” scenario). Input–output coefficients for all four crop systems were determined, mainly irrigation demand, yield, and price of produce, but other factors like a limited area of arable land and scarce regional water resources were also considered. For the simulation, a LINDO Inc. system was linked with the CLUE (Conversion of Land Use and its Effects) model. Temporal changes of crop systems were simulated with the LINDO system, whereas spatial dynamics of cropping patterns were simulated with the CLUE model, based on land suitability maps. The results show that crop patterns changed variably with time under the two scenarios, and water availability was the primary constraint on sustainability of land use. Under the subsidy scenario, winter wheat/summer maize/spring maize became dominant across the entire county, replacing other crop systems. In contrast, the vegetable system gradually occupied farmland surrounding the township under the technique scenario. The different policies produced opposite consequences for regional sustainability. Although a “subsidy” policy contributed to farmers’ income, it did not encourage water conservation for sustainable crop production, leading to land abandonment because of water shortage. In contrast, the “technique” policy partially cut direct financial benefits to farmers, but promoted water conservation and made a substantial contribution to agricultural sustainability.

The impact of soybean expansion on mammal and bird, in the Balsas region, north Brasilian Cerrado

In order to analyse the impact of land use change, it is particularly important to know how organisms use resources distributed across a heterogeneous landscape. The main objective of this study is to analyse the potential impact of land use change on bird and mammal fauna, by using a coupled model approach. The CLUE (Conversion of Land Use and its Effects) model has been applied to obtain the spatial pattern of land use change for a scenario with soybean expansion in the Cerrado of Maranhão State in Brazil. These land use change maps were used as the input for the LEDESS (Landscape Ecological Decision and Evaluation Support System) model to evaluate the impact of habitat fragmentation on mammal and bird species. The scenarios demonstrated that high quality habitat for all studied species will be lost in the future when current trends in agricultural expansion continue, but these changes will have species-specific impacts. The most relevant ecological impact under the explored scenarios was habitat fragmentation expressed by the increase the number of habitat clusters. The coupled model approach of LEDESS and CLUE made it possible to project the spatial impact of soybean expansion on habitat dynamics in the studied region. This model approach can help to design effective ecological infrastructure to facilitate species survival and to implement an effective habitat network in the Balsas region.

Prediction of paddy field change based on climate change scenarios using the CLUE model

This study simulated land-cover change using the Conversion of Land Use and its Effects (CLUE) model and predicted future changes in paddy field area under climate change scenarios A1B, A2, B1, and B2 of the Special Report on Emissions Scenarios (SRES). The CLUE model is a dynamic spatial land-use simulation model considering competition among land-use types in relation to socioeconomic and biophysical driving factors. Yongin, Icheon, and Anseong, South Korea, were selected as study areas, and scenarios were developed for regional-level simulation of land-use change. Binary logistic regressions were also conducted to evaluate the relationships between land uses and its driving factors. Finally, the simulation results suggested future changes of paddy field area under the scenario conditions. In all the scenarios, demand for cropland, including paddy and upland, decreased continuously throughout the simulation period of 2000–2100. The decrease in cropland area was particularly steep in scenario A2 in 2050. The receiver operating characteristic (ROC) values indicated that the spatial patterns of land-cover types based on the regressions were reasonably explained by the driving factors. According to the scenarios developed and location characteristics, in scenario A1B, paddy field areas were mainly transformed into built-up areas, while in the other scenarios paddy field areas were mainly transformed into forest. The approach used in this study is expected to enable exploration of future land-use changes under other development constraints and detailed scenarios.

A method and application of multi-scale validation in spatial land use models

The majority of the large number of existing land use models lack a proper validation, often because of data problems. Moreover, despite recognition of the necessity to incorporate a multi-scale analysis, scale dependencies are normally not considered during validation. In this paper, a multi-scale land use change modelling framework, conversion of land use and its effects (CLUE), is calibrated for Costa Rica and validated at five spatial resolutions for Honduras and Costa Rica. Both countries experienced locally very strong actual land use changes. Calibration runs show that the model is very sensitive to changes in the autonomous development parameter, which defines the influence of the finest resolution. Validation results are very satisfactory for both countries. Especially, changes in major land use types are reproduced with the model. Changes in localised land use types are more difficult to project. The magnitude of gains and magnitude of losses are slightly underestimated in all cases. The multi-scale validation demonstrates that results improve strongly, and exponentially, with decreasing spatial resolution. Strong reduction of the number of observations results in a correlation between actual and modelled changes that approximates the perfect value of 1. The study demonstrates that the CLUE modelling framework can reproduce changes as they took place in Central America in the 1970s and 1980s, and shows how conclusions can differ depending on the scale at which validation is performed.

The Need for Scale Sensitive Approaches in Spatially Explicit Land Use Change Modeling

This paper introduces some of the issues that are relevant to the spatially explicit modeling of land use systems. A short overview is given of the ways and means in which a number of different land use change models describe the land use system. Specific attention is given to the empirical modeling approach used in the CLUE (Conversion of Land Use and its Effects) modeling framework. This approach is demonstrated for three case studies in China, Ecuador and the Atlantic Zone of Costa Rica. These case-studies illustrate the methodology for multi-scale analysis of land use driving factors and their application in spatially explicit modeling exercises. Model functioning, performance and limitations are discussed. The presented case-studies indicate that empirical modeling results can contribute to a better theoretic imbedding of land use change research in scale sensitive and integrated theories.

CLUE: a conceptual model to study the Conversion of Land Use and its Effects

A dynamic model to simulate Conversion of Land Use and its Effects (CLUE) is presented. For an imaginary region, CLUE simulates land use conversion and change in space and time as a result of interacting biophysical and human drivers. Within CLUE regional land use changes only if biophysical and human demands cannot be met by existing land use. After a regional assessment of land use needs, the final land use decisions are made on a local grid level. Important biophysical drivers are local biophysical suitability and their fluctuations, land use history, spatial distribution of infrastructure and land use, and the occurrence of pests and diseases. Important human land use drivers in CLUE are population size and density, regional and international technology level, level of affluence, target markets for products, economical conditions, attitudes and values, and the applied land use strategy. Initial CLUE simulations suggest that the integrated land use approach of CLUE can make a more realistic contribution to predictions of future land cover than currently used biophysical equilibrium approaches.