Modelling land use change and environmental impact

Land use change models are tools for understanding and explaining the causes and consequences of land use dynamics. Recently, new models, combining knowledge and tools from biophysical and socio-economic sciences, have become available. This has resulted in spatially explicit models focussed on patterns of change as well as agent-based models focused on the underlying decision processes. These developments improve the use of land use change models in environmental impact studies. This special issue documents these developments: (i) analysing the system properties in a biophysical and socio-economic context at multiple scales; (ii) integrating spatially explicit land use change models in integrated assessment models; (iii) visualising and quantifying the potential effects of land use change in trade-off curves, to support land users and policy makers in their decisions; and (iv) modelling of the actual decision making process with agent-based modelling. A new promising future development is the incorporation of dynamic feedbacks between changing land use and changing environmental conditions and vice versa. Unfortunately such dynamic feedbacks between the socio-economic and biophysical model components are still not or only partially operational in current models and are therefore the most important challenge for land use and environmental modellers.     

CLUE-S模型及其在奈曼旗土地利用时空动态变化模拟中的应用

在对目前常用的土地利用变化模型进行调研的基础上,认为CLUE-S模型是众多模型中适用于区域土地利用变化研究的一种较好的模型;它是根据系统论的观点,在深刻理解土地利用系统内土地利用变化特征(包括关联性、竞争性、稳定性以及等级性等)的基础上构建而成,具有同步模拟不同土地利用变化的能力。论文以奈曼旗为例,根据1985年的空间图形数据,结合道路、居民点、城镇、水域的分布、以及地形和土壤等驱动因素,对其2000年的土地利用变化格局进行模拟;并用2000年的土地利用现状图对模拟结果进行检验。结果显示,在基本单元(500m×500m栅格)的水平上,模拟的正确率为85%,Kappa指数值是0.80。说明CLUE-S模型具有成功模拟区域土地利用时空动态变化的能力,是值得向国内同行推荐的一种较好的LUCC模型。     

Combining remote sensing and household level data for regional scale analysis of land cover change in the Brazilian Amazon

Land cover change in the Brazilian Amazon depends on the spatial variability of political, socioeconomic and biophysical factors, as well as on the land use history and its actors. A regional scale analysis was made in Rondônia State to identify possible differences in land cover change connected to spatial policies of land occupation, size and year of establishment of properties, accessibility measures and soil fertility. The analysis was made based on remote sensing data and household level data gathered with a questionnaire. Both types of analyses indicate that the highest level of total deforestation is found inside agrarian projects, especially in those established more than 20 years ago. Even though deforestation rates are similar inside and outside official settlements, inside agrarian projects forest depletion can exceed 50% at the property level within 10–14 years after establishment. The data indicate that both small-scale and medium to large-scale farmers contribute to deforestation processes in Rondônia State encouraged by spatial policies of land occupation, which provide better accessibility to forest fringes where soil fertility and forest resources are important determinants of location choice.     

An agent-based approach to explore the effect of voluntary mechanisms on land use change: A case in rural Queensland,Australia

In rural regions, land use changes (LUC) are often the result of the decision-making of individual farmers. To influence this decision-making, compulsory and voluntary mechanisms are implemented. However, farmers’ decision-making is a heterogeneous process that depends on their ability and willingness to take certain decisions. Discrepancies between farmers’ ability and willingness and the design of voluntary mechanisms occur frequently. This makes it necessary to understand how farmers’ participation in these mechanisms can affect LUC. The aim of this paper was to demonstrate an agent-based approach to analyse and explore how voluntary mechanisms can influence LUC processes in rural regions. This approach was applied to a rural region in Australia, where clearing of native vegetation has occurred for agricultural development. Historical land cover data and semi-structured interviews were used to parameterise an agent-based model. Factors that influence farmers’ ability and willingness to participate in these mechanisms were identified. Three scenarios were simulated with the model to explore how the implementation of different voluntary mechanisms can affect the landscape structure of the region. This paper identifies how the diversity of farmers’ decision-making can influence the landscape structure in the region. The advantages and limitations of an agent-based approach in relation to LUC research and policy are discussed.     

Improving National-Scale Carbon Stock Inventories Using Knowledge on Land Use History

National-scale inventories of soil organic carbon (SOC) and forest floor carbon (FFC) stocks have a high uncertainty. Inventories are often based on the interpolation of sampled information, often using a number of covariables to help such interpolation. The rationale for the choice of these covariables is not always documented, despite the fact that many local-scale studies have identified the factors explaining spatial variability of SOC and FFC stocks. These studies indicate, among others the importance of long-term land use history. Despite this, information on the effects of land use history has never been used to explain variability of carbon stocks in national-scale inventories. We designed an alternative method to improve national-scale inventories of SOC and FCC for the Dutch sand area that takes stock of the findings of detailed case studies. Determinants for SOC and FFC stocks derived from landscape-scale case studies were used to map national-scale spatial variability and to calculate national totals. The resulting national-scale spatial distribution was compared with the SOC stock map from the current Dutch greenhouse gas inventory. Using land use history to explain SOC variability decreased the error of the SOC stock estimate in 60 % of the area. The error in FFC stocks decreased in half of the forest area after including soil fertility, tree species, and forest age as explanatory factors. Estimates with reduced uncertainty will make land use and land management a more attractive and acceptable mitigation option to reduce emissions of greenhouse gases for the LULUCF sector.     

基于土地利用变化模型的退耕还林还草决策分析——以通辽地区为例

通过综合考虑影响退耕还林还草的自然和社会因素,结合土地利用规划和遥感影像解译结果,论文以通辽地区为例,介绍了利用土地利用变化模型确定退耕还林还草区域的方法和过程。根据对2010年模型模拟结果和2000年通辽地区土地利用现状的对比分析,结果发现2000～2010年该地区进行退耕还林还草的合适区域应该主要位于研究地区的中部、南部,以及北中部。研究地区中部属于科尔沁沙地的腹地,土地沙漠化最为严重,同时城镇和农村居民点分布较密,退耕还林还草是政府用于减缓风沙对城镇和农村居民点危害程度的重要生态措施;而南部和北中部属于丘陵和山区,由于过度开垦,水土流失较为严重,是实施退耕还林还草的重点区域。此外,与退耕还林区相比,退耕还草区距城镇、农村居民点以及道路相对较远,具有可达性较差、地理位置较为偏僻的特点。论文得出的结果可为今后通辽地区退耕还林还草工程的实施提供科学依据,同时,该文提出的确定退耕还林还草区域的方法对其它地区具有一定的借鉴意义。     

Representing large-scale land acquisitions in land use change scenarios for the Lao PDR

Regional Environmental Change - Agricultural large-scale land acquisition (LSLA) is a process that is currently not captured by land change models. We present a novel land change modeling approach...     

A cross-scale impact assessment of European nature protection policies under contrasting future socio-economic pathways

Regional Environmental Change - Protection of natural or semi-natural ecosystems is an important part of societal strategies for maintaining biodiversity, ecosystem services, and achieving overall...