Land use/land cover change detection and prediction in the north-western coastal desert of Egypt using Markov-CA

Detecting land-use change has become of concern to environmentalists, conservationists and land use planners due to its impact on natural ecosystems. We studied land use/land cover (LULC) changes in part of the northwestern desert of Egypt and used the Markov-CA integrated approach to predict future changes. We mapped the LULC distribution of the desert landscape for 1988, 1999, and 2011. Landsat Thematic Mapper 5 data and ancillary data were classified using the random forests approach. The technique produced LULC maps with an overall accuracy of more than 90%. Analysis of LULC classes from the three dates revealed that the study area was subjected to three different stages of modification, each dominated by different land uses. The use of a spatially explicit land use change modeling approach, such as Markov-CA approach, provides ways for projecting different future scenarios. Markov-CA was used to predict land use change in 2011 and project changes in 2023 by extrapolating current trends. The technique was successful in predicting LULC distribution in 2011 and the results were comparable to the actual LULC for 2011. The projected LULC for 2023 revealed more urbanization of the landscape with potential expansion in the croplands westward and northward, an increase in quarries, and growth in residential centers. The outcomes can help management activities directed toward protection of wildlife in the area. The study can also be used as a guide to other studies aiming at projecting changes in arid areas experiencing similar land use changes.     

A method to dynamically subdivide parcels in land use change models

Spatial simulation models have become a popular tool in studying land use/land cover (LULC) change. An important, yet largely overlooked process in such models is the land subdivision, which is known to govern LULC change and landscape restructuring to a large extent. To fill this gap, we propose an efficient and straightforward method to simulate dynamic land subdivision in LULC change models. Key features in the proposed method are implementing a hierarchical landscape where adjacent cells of the same LULC type form patches, patches form properties, and properties form the landscape and incorporating real subdivision layouts. Furthermore, we use a queue-based modified flood-fill algorithm to dynamically reset LULC patches following a subdivision. The proposed subdivision method is demonstrated in action using a prototype agent-based LULC model developed for an amenity landscape in Australia. Results show that it is computationally feasible to run the subdivision method even as spatial resolution is increased, thus providing a proven means for spatial simulation models to dynamically split parcel land.     

Optimal rural land use allocation in central China: Linking the effect of spatiotemporal patterns and policy interventions

Rural land use development is experiencing a transition stage of socioeconomic and land use development in China. Historic land use transition process and policy interventions have key influence on the applicability of land use allocation solutions in future land use management. Strategic land use allocation is therefore required to possess a good adjustment capability to the transition process. Although heuristic optimization methods have been promising to solve land use allocation problems, most of them ignored the spatially explicit effect of historic land use transition and policies. To help resolve this issue, this study aims to optimize future land use pattern in the context of rural land use development. We took Yunmeng County, one of the typical major grain producing and rapidly urbanizing areas in central China, as a case study and solved the sustainable land use allocation problem by using an improved heuristic optimization model. The model was constructed based on the integration of a spatial discrete particle swarm optimization and cellular automata-Markov simulation approach. The spatiotemporal land use patterns and policy interventions were represented by the CA-Markov as in spatially explicit transition rules, and then incorporated into the discrete PSO for optimal land use solutions. We examined the influence of the joint effect of spatiotemporal land use patterns and policy interventions on the land use allocation outcome. Our results demonstrate the robustness and potential of the proposed model, and, more importantly, indicate the significance of incorporating the spatiotemporal land use patterns and policy interventions into rural land use allocation.     

情景分析法在工业用地置换中的应用——以福建省长汀腾飞经济开发区为例

从土地综合价值出发, 将一般用于宏观研究的情景分析法引入微观领域, 根据社会、经济、环境效益的最佳、最差和最可能情景模式, 确定工业用地和居住用地开发的情景过程及其对比特征。研究表明, 福建省长汀腾飞经济开发区最可能情景下的工业收支比经过16 年才能达到平衡, 居住和商业用地最可能情景下收支比可以维持在3~5 左右的稳定发展水平, 在前5 年, 居住用地的收支比8~10 倍于工业用地, 然后差距逐步缩小, 降低到20 年期2 倍的水平。这一情景表明, 腾飞经济开发区要缩小规模, 分步、分阶段地把没有进行开发的闲置土地和3 年左右依然处于亏损的企业用地置换出来, 工业用地应该由目前的2.5 km² 缩减 到1~1.5 km²。     

A meta-modeling approach for spatio-temporal uncertainty and sensitivity analysis: an application for a cellular automata-based Urban growth and land-use change model

The paper presents a computationally efficient meta-modeling approach to spatially explicit uncertainty and sensitivity analysis in a cellular automata (CA) urban growth and land-use simulation model. The uncertainty and sensitivity of the model parameters are approximated using a meta-modeling method called polynomial chaos expansion (PCE). The parameter uncertainty and sensitivity measures obtained with PCE are compared with traditional Monte Carlo simulation results. The meta-modeling approach was found to reduce the number of model simulations necessary to arrive at stable sensitivity estimates. The quality of the results is comparable to the full-order modeling approach, which is computationally costly. The study shows that the meta-modeling approach can significantly reduce the computational effort of carrying out spatially explicit uncertainty and sensitivity analysis in the application of spatio-temporal models.     

沿海经济发达地区农村居民点整理适宜性研究——以福清市为例

以福建省沿海经济较发达的福清市为例,通过对样本区域农村居民点用地的现状进行调查,并在调查数据的基础上测算出农村居民点用地的整理潜力,以此为基础,选取福清市土地利用现状、自然因素、社会因素、经济因素等方面12个指标,采用因子分析和聚类分析方法对农村居民点整理的适宜性进行评价,根据聚类结果将18个评价单元划分为4个不同的适宜性类型区,结合实际情况和定量分析过程提出各类型区的整理途径和整理对策.     

沿海经济发达地区农村居民点整理适宜性研究——以福清市为例

以福建省沿海经济较发达的福清市为例,通过对样本区域农村居民点用地的现状进行调查,并在调查数据的基础上测算出农村居民点用地的整理潜力,以此为基础,选取福清市土地利用现状、自然因素、社会因素、经济因素等方面12个指标,采用因子分析和聚类分析方法对农村居民点整理的适宜性进行评价,根据聚类结果将18个评价单元划分为4个不同的适宜性类型区,结合实际情况和定量分析过程提出各类型区的整理途径和整理对策.     

石家庄市农村居民点用地集约利用潜力评价

近年来,石家庄市农村居民点用地增长过快对土地持续利用、经济和社会发展构成严重制约,农村居民点用地集约利用势在必行。该文在农村居民点用地集约利用潜力评价内涵界定和集约利用分区的基础上,构建了农村居民点用地集约利用潜力评价指标体系,建立了评价模型。以县为评价单元,对石家庄市农村居民点用地集约利用潜力进行了实证研究,按综合评价分值高低将18个评价单元划分为集约利用潜力很大、较大、较小3个级别。在上述研究基础上,提出石家庄市农村居民点用地集约利用的有效途径。     

Comparison of land cover maps using fuzzy agreement

A generic problem associated with different land cover maps that cover the same geographical area is the use of different legend categories. There may be disagreement in many areas when comparing different land cover products even though the legend shows the same or very similar land cover class. To capture the uncertainty associated with both differences in the legend and the difficulty in classification when comparing two land cover maps, expert knowledge and a fuzzy logic framework are used to map the fuzzy agreement. The methodology is illustrated by comparing the Global Land Cover 2000 data set and the MODIS global land cover product. Overall accuracy measures are calculated, and the spatial fuzzy agreement between the two land cover products is provided. This approach can be used to improve the overall confidence in a land cover product, since areas of severe disagreement can be highlighted, and areas can be identified that require further attention and possible re-mapping.     

Reconstructing the historical spatial land use pattern for Jiangsu Province in mid-Qing Dynasty

This study is proposed to reconstruct a high-resolution spatial distribution of historical land use pattern with all land use types to overcome low-accuracy and/or the monotonic land use type in current historical land use reconstruction studies. The year of 1820 is set as the temporal section and the administrative area of Jiangsu Province is the study area. Land use types being reconstructed include farmland, residential land (including both urban land and rural residential land), water body, and other land (including forest land, grassland, and unused land). Data sources mainly refer to historical documents, historical geographic research outcomes, contemporary statistics, and natural environmental data. With great considerations over regional natural resources and social and economic conditions, a few theoretical assumptions have been proposed to facilitate the adjustment on prefecture farmland, urban land, and rural residential land. Upholding the idea that the contemporary land use pattern has been inherently in sequence with the historical land use pattern as well as the land use pattern shall be consistent to its accessibility, this study reconstructs the land use pattern in Jiangsu Province in 1820 with 100 m*100 m grids based on accessibility analysis and comprehensive evaluation. The outcome has been tested as valid by regionalization and correlation analysis. The resulted spatial distribution shows that back in 1820 in Jiangsu Province: (1) farmland, urban land, rural residential land, water body, and other land take about 48.49%, 4.46%, 0.16%, 15.03%, and 31.86% of the total land area respectively; (2) the land use pattern features high proportion of land in farming while low-proportion land in non-farming uses while population, topography, and the density of water body lead to great spatial variations; and (3) the reconstruction methodology has been tested as reasonable based on significant positive correlations between 1820 data and 1985 for both farmland and rural residential land at the prefecture level.     

转型期农村宅基地边际化的内涵、特征与诊断指标

本文主要考察城乡转型发展与农村空心化背景下,农村宅基地利用形态的演变与边际化问题。在剖析农村宅基地边际化概念和内涵的基础上,探讨了宅基地边际化的类型及其在区域土地利用中的表现特征,提出了相应的诊断标准。农村宅基地的边际化是一种在现有的土地利用和社会经济结构条件下,农村宅基地原始的居住保障功能不断弱化、衰退或被其他用途取代的现象。农户对宅基地边际化的行为响应,将导致区域农村宅基地在利用程度、功能与使用制度等方面发生重大变化。农村宅基地的“利用率诊断”、“自住面积比例诊断”与“利用成本诊断”是诊断农村宅基地边际化类型、测度农村宅基地边际化趋势的三个主要步骤。一般而言,该宅基地的利用率明显下降是显性边际化的重要标志;而在宅基地多功能利用过程中,自住面积比例的不断降低,体现了农村宅基地的隐性边际化;最后,农村宅基地现有自住用途下利用成本的增加,是其边际化趋势预测的重要依据。本文可为城乡发展转型期农村宅基地利用形态和功能变化提供新的研究视角。     

Using multiple scale spatio-temporal patterns for validating spatially explicit agent-based models

Spatially explicit agent-based models (ABMs) have been widely utilized to simulate the dynamics of spatial processes that involve the interactions of individual agents. The assumptions embedded in the ABMs may be responsible for uncertainty in the model outcomes. To ensure the reliability of the outcomes in terms of their space-time patterns, model validation should be performed. In this article, we propose the use of multiple scale spatio-temporal patterns for validating spatially explicit ABMs. We evaluated several specifications of vector-borne disease transmission models by comparing space-time patterns of model outcomes to observations at multiple scales via the sum of root mean square error (RMSE) measurement. The results indicate that specifications of the spatial configurations of residential area and immunity status of individual humans are of importance to reproduce observed patterns of dengue outbreaks at multiple space-time scales. Our approach to using multiple scale spatio-temporal patterns can help not only to understand the dynamic associations between model specifications and model outcomes, but also to validate spatially explicit ABMs.     

农村居民点土地整理潜力研究方法述评

结合我国农村居民点土地整理潜力研究现状,将农村居民点土地整理研究归纳为综合潜力评价与农村居民点土地整理潜力计算方法两项主要研究内容;评述政策指标测算法、闲置宅基地抽样调查法和建筑容积率法3种农村居民点土地整理潜力计算方法,并探讨农村居民点土地整理潜力理论缺乏系统性、综合潜力研究中土地整理适宜性评价与综合潜力评价重叠及农村居民点土地整理潜力计算方法尚不完善等问题;提出农村居民点土地整理潜力研究应与耕地整理等其他土地整理领域相结合,使农村居民点土地整理潜力计算方法更系统、更精确。     

Urban Expansion Pattern and Land Use Dynamics in Dhaka, 1989–2014

Rapid change in land use and land cover (LULC) and unplanned urban expansion in Dhaka City, Bangladesh, receives continuous attention from local policymakers and the international community. This study employed a supervised classification procedure and postclassification change detection technique to estimate major changes between different LULC classes. The study revealed that built-up area increased significantly from 1989 to 2014. The total urban growth of 81.54 percent resulted in a substantial decrease in natural vegetation cover and agricultural land. In addition, water bodies have declined consistently over the last twenty-five years. The overall accuracy of LULC change maps produced from Landsat data ranged from 89.72 percent to 92.97 percent. The results should contribute to ongoing LULC information updates while forecasting possible future LULC change and sustainable development under greater population density.     

Land Use Diversification in the Elite Residential Sector of Quito,Ecuador*

It is generally assumed that older mansions in the elite residential sector of Latin American cities filter down to the middle classes once their residents migrate to modern suburban homes. Five land use maps compiled between 1975 and 1999 show that the elite residential sector of Quito (Mariscal Sucre) experienced a much more complex fate. Diffusion of nonresidential land uses from the city center and its associated spine transformed the residential neighborhood into a vibrant upper‐scale business district. Sophisticated businesses subsequently moved on to modern suburban facilities, but Mariscal Sucre became a major hub for business, nocturnal entertainment, and tourism. Diversification of land use in Mariscal Sucre confirms the Crowley hypothesis of complexity in Latin American urban land use patterns ( Crowley 1995 ).     

评析西方城市土地利用的理论研究

综述了西方城市土地利用理论研究的最新进展,较深入地评析了各种研究方法与理论派系的独到功力及其局限性。并结合中国城市土地利用的研究进展,提出今后应加强城市土地利用区位经济的理论与实证研究及城市土地开发过程的政治经济分析     

大渡河上游地区土地利用动态模拟分析

基于1967、1987和2000年三期遥感数据和1:25万数字高程模型,通过Logistic逐步回归分析,在地形、海拔、水系、道路交通、城镇和居民点分布等多种自然地理和社会经济因素中,筛选出不同时期对大渡河上游地区主要土地利用类型空间分布及其变化具有决定作用的驱动因子,并生成相应的土地利用空间分布概率适宜图,然后采用CLUE-S模型,模拟分析了1987年和2000年两个时点上金川、壤塘和马尔康三县18665 km2范围内的土地利用状况。用当年的现状图检验对比的结果表明,模拟取得了较为理想的结果,Kappa值分别达到0.86和0.89。在此基础上,针对三种政策情景,应用相同模型模拟预测了研究地区2010年时的土地利用时空变化。     

Rural sustainability under threat in Zimbabwe – Simulation of future land use/cover changes in the Bindura district based on the Markov-cellular automata model

Spatially explicit land use/cover models are indispensable for sustainable rural land use planning, particularly in southern African countries that are experiencing rapid land use/cover changes. Using Zimbabwe as an example, we simulated future land use/cover changes up to 2030 based on a Markov-cellular automata model that integrates Markovian transition probabilities computed from satellite-derived land use/cover maps and a cellular automata spatial filter. A multicriteria evaluation (MCE) procedure was used to generate transition potential maps from biophysical and socioeconomic data. Dynamic adjustments of transition probabilities and transition potential map thresholds were implemented in the Markov-cellular automata model through a multi-objective land allocation (MOLA) procedure. Using the normalised transition probabilities, the Markov-cellular automata model simulated future land use/cover changes (up to 2030) under the 2000 calibration scenario, predicting a continuing downward trend in woodland areas and an upward trend in bareland areas. Future land use/cover simulations indicated that if the current land use/cover trends continue in the study area without holistic sustainable development measures, severe land degradation will ensue.     

Land change in the central Albertine rift: Insights from analysis and mapping of land use-land cover change in north-western Rwanda

Land change was assessed in the Albertine rift region (ARR) using its central section of north-western Rwanda as case study. This region is one of Africa's most ecologically sensitive environments under severe pressure from human activities. The study maps and quantifies the spatial extent of land use-land cover (LULC) changes between 1987 and 2016 from Landsat images. Transitions between five major land classes were identified in order to understand the trajectory of observed changes. In terms of gains, the forest class, the urban built-up and bare land class increased by 9% and 4% respectively over the study period. The gains of forest were mainly derived from the afforestation of some agricultural lands in the southern part, whereas the gains of built-up and bare lands were mostly from cultivated land which was a net losing class. Forest increase is in line with government's policy to increase the national forest cover to 30% by 2020. Forest losses occurred mostly outside protected areas due to land conversion for settlement and agricultural purposes. Much needed information about changes in LULC over the last three decades is provided. This study demonstrates in a timely manner how to analyse and monitor LULC change and the drivers in an environment where field based research is a challenge due to the mountainous terrain. The ecological richness of the region, which coincides with heightened human population pressure, necessitates the monitoring of land change as input for improving land use planning with focus on conserving biodiversity.