Image Sources for Informal Settlement Management

Informal settlements are a common feature of developing countries. In South Africa the improvement of living conditions in these settlements and the upgrading to formal housing types are regarded as being of central importance to the nation's development. Effective settlement improvement and upgrading activities, which we here term "management", require adequate spatial data. To date, the acquisition of spatial models of informal settlements has been based on conventional mapping techniques, and mostly on photogrammetry. Data are compiled using analogue or analytical methods. These are manual and hence require both considerable expertise and expensive equipment. Moreover, these methods are uneconomical over the often relatively small, densely populated areas covered by informal settlements and are also too expensive to employ with a regularity required to support such tasks as change detection. Alternative imaging sources and mapping techniques are therefore needed.
In this article we examine the problem of spatial information acquisition for informal settlement management from three perspectives: spatial information requirements, the role which imagery can play in satisfying these spatial information requirements, and effective imaging options. We focus on the potential of high resolution satellite imaging, small format digital aerial imagery and digital multispectral video systems for rapid mapping. We also discuss the example of automated shack extraction from aerial imagery.     

Mobile GIS occupancy audit of Ulana informal settlement in Ekurhuleni municipality,South Africa

ABSTRACT

Relocating people in informal settlements and upgrading the lives of those people require consistent commitment, good strategies, and supporting systems. In South Africa, in order to allocate subsidized housing to beneficiaries of an informal settlement, beneficiary administration needs to determine the number of people who qualify for subsidized houses. Without geo-spatial data-based technical verification, conventional methods of occupancy audits are often cumbersome, are unreliable, and do not promote smart and evidence-based decision making. Accordingly, the aim of this study is to propose and develop an Oracle-based mobile GIS tool to conduct an occupancy audit for Ulana, an informal settlement in Ekurhuleni Municipality in South Africa. Android-based tablets were used to collect the geographic and socio-economic attributes of the informal dwelling units (DU). Spatial analysis (in ArcGIS software and geo-spatial modeling environment) and statistical analysis were conducted to produce the occupancy audit. The results indicated that the use of mobile GIS provides up-to-date, accurate, comprehensive, and real-time data so as to facilitate the development of smart and integrated human settlements. The results of this audit also indicated that only 57% of the households residing in Ulana could potentially benefit from receiving a subsidized house. Accordingly, the occupancy audit enables planners to plan appropriate upgrading and housing development strategies for informal settlement. This study demonstrates that successful planning of housing delivery for post independent integrated neighborhoods is not a mere political rhetoric but is viable when it is based on reasonable geo-spatial techniques and information. The use of mobile GIS therefore needs to be extended to other informal settlement upgrading projects in South Africa as well as other cities in the global south. However, proper professional training is required to ensure the successful usage of smart mobile GIS tools.     

Modeling Urban Growth Using GIS and Remote Sensing

Based on remote sensing and GIS, this study models the spatial variations of urban growth patterns with a logistic geographically weighted regression (GWR) technique. Through a case study of Springfield, Missouri, the research employs both global and local logistic regression to model the probability of urban land expansion against a set of spatial and socioeconomic variables. The logistic GWR model significantly improves the global logistic regression model in three ways: (1) the local model has higher PCP (percentage correctly predicted) than the global model; (2) the local model has a smaller residual than the global model; and (3) residuals of the local model have less spatial dependence. More importantly, the local estimates of parameters enable us to investigate spatial variations in the influences of driving factors on urban growth. Based on parameter estimates of logistic GWR and using the inverse distance weighted (IDW) interpolation method, we generate a set of parameter surfaces to reveal the spatial variations of urban land expansion. The geographically weighted local analysis correctly reveals that urban growth in Springfield, Missouri is more a result of infrastructure construction, and an urban sprawl trend is observed from 1992 to 2005.     

Integrating spectral and non-spectral data to improve urban settlement mapping in a large Latin-American city

ABSTRACT

Information on urban settlements is crucial for sustainability planning and management. While remote sensing has been used to derive such information, its applicability can be compromised due to the complexity in the urban environment. In this study, we developed a remote sensing method to map land cover types in a large Latin-American city, which is well known for its mushrooming unplanned and informal settlements. After carefully considering the landscape complexity there, we designed a data fusion method combining multispectral imagery and non-spectral data for urban and land mapping. Specifically, we acquired a cloud-free Landsat-8 image and two non-spectral datasets, i.e., digital elevation models and road networks. Then, we implemented a set of experiments with different inputs to evaluate their merits in thematic mapping through a supervised protocol. We found that the map generated with the multispectral data alone had an overall accuracy of 73.3% but combining multispectral imagery and non-spectral data yielded a land cover map with 90.7% overall accuracy. Interestingly, the thermal infrared information helped substantially improve both the overall and categorical accuracies, particularly for the two urban classes. The two types of non-spectral data were critical in resolving several spectrally confused categories, thus considerably increasing the mapping accuracy. However, the panchromatic band with higher spatial resolution and its derived textural measurement only generated a marginal accuracy improvement. The novelties of our work are with the successful separation between the two major types of urban settlements in a complex environment using a carefully designed data fusion approach and the insight into the relative merits of the thermal infrared information and non-spectral data in helping resolve the issue of class ambiguity. These findings should be valuable in deriving accurate urban settlement information which can further advance the research on socio-ecological dynamics and urban sustainability.     

利用水准数据的天津市地面沉降时空特征分析

地面不均匀沉降可能对城市的发展与人民的安全造成危害,天津市的地面沉降情况尤为严重。针对该问题,本文收集天津市2005—2012年、2016—2017年水准观测数据,以固定水准点位的沉降量、沉降速率、沉降加速率为状态向量,构建卡尔曼滤波模型,对天津市历年的水准观测数据进行滤波;根据滤波后的结果,本文利用多项式加权内插的方法,以距离、沉降速率、沉降加速率信息确定权值大小,对地面沉降情况进行内插;并以中误差作为精度评定参数,比较多种内插方法的精度。通过对内插结果的试验分析发现,2005—2017年天津市地面累计平均沉降量为394.477 5 mm,最大沉降量为1 143.5 mm;主要沉降区域为北辰、大港、塘沽等地区,且随着时间的增长,这些区域呈现漏斗式下沉。试验证明本文结合卡尔曼滤波与多项式加权内插的方式能够较好地反映地面沉降的时空特征分布情况并对未来一段时间的沉降情况进行预测,对天津市的城市发展及建设有一定的参考意义。     

Meeting the Need for GIS Skills in Developing Countries: The Case of Informal Settlements

Informal settlements are a chronic issue in developing countries. Management and formalisation processes require good spatial data and analytical tools. While software such as geographic information systems (GIS) are widely available, access to good data and skilled users may be limited. In this paper we suggest that digital multimedia learning tools, accessible via the World Wide Web (WWW) may be part of the solution. We present the rationale for, and structure of, a suite of prototype learning modules for neighbourhood operations. We illustrate the use of these operations by converting shack locations into population density maps for the Imizamo Yethu settlement near Cape Town, South Africa. This prototype forms a part of a larger web site that also includes background information, data sources and software.     

Applying multiple and logistic regression models to investigate periurban processes in Thessaloniki,Greece

The paper examines periurbanization processes in the region of Thessaloniki through the application of multiple regression and logistic regression models. A set demographic and socio-economic data are analysed through a principal component analysis, and results are mapped so as to highlight the distributional characteristics. In a next section, the multiple regression model is applied to the study area. The four variables entering the multiple regression model (population size and age characteristics, employment in the tertiary sector, new buildings), which reflect the indications stemming out from the PCA analysis, provide a relatively high multiple correlation coefficient (R = 0.852) accounting for about 72.5% of the population changes. Then, a logistic regression model is used to identify periurban communities presenting urban characteristics and to distinguish them from the rural ones. Results indicate that decentralization towards existing periurban settlements is mostly driven by the construction of new housing and employment in the tertiary sector.     

史前连续文化聚落的决策树分类挖掘研究——以郑州-洛阳地区为例

利用C4.5决策树分类算法和GIS组件Super Map Objects,开发实现了基于连续文化序列的空间数据挖掘系统,运用此系统对郑州-洛阳地区史前四个连续文化时期的聚落进行了数据挖掘,提取了聚落遗址面积的分类规则,并根据这些分类规则和聚落的空间分布情况对四个文化时期的I级聚落进行对比分析,得出了I级聚落的空间分布特点,即I级聚落中的一些特大面积的聚落朝着中心聚落的方向发展。     

Monitoring household upgrading in unplanned settlements with unmanned aerial vehicles

In-situ slum upgrading projects include infrastructural improvements such as new roads, which are perceived to improve the quality of life for the residents and encourage structural improvements at a household level. Although these physical changes are easily visible in satellite imagery, it is more difficult to track incremental improvements undertaken by the residents – which are perhaps more closely linked to the socio-economic development of the households themselves. The improved detail provided by imagery obtained from Unmanned Aerial Vehicles (UAVs) has the potential to monitor these more subtle changes in a settlement. This paper provides a framework which takes advantage of high-resolution imagery and a detailed elevation model from UAVs to detect changes in informal settlements. The proposed framework leverages expert knowledge to provide training labels for deep learning and thus avoids the cost of manual labelling. The semantic classification is then used to interpret a change mask and identify: new buildings, the creation of open spaces, and incremental roof upgrading in an informal settlement. The methodology is demonstrated on UAV imagery of an informal settlement in Kigali, Rwanda, successfully identifying changes between 2015 and 2017 with an Overall Accuracy of 95 % and correctly interpreting changes with an Overall Accuracy of 91 %. Results reveal that almost half the buildings in the settlement show visible changes in the roofing material, and 61 % of these changed less than 1m². This demonstrates the incremental nature of housing improvements in the settlement.     

基于高分辨率遥感影像的城市小区交通可达性评价——以厦门市为例

居住小区是与人们生活密切相关的单元,居住小区交通可达性是衡量小区环境好坏的一项重要指标。高分辨率遥感影像的空间分辨率可达到0.6m甚至更高,使得从居住小区的尺度研究交通可达性成为可能。本文从区域交通环境、路网可达性和设施可达性三个影响因子出发,根据高分辨率遥感影像的特点构建了居住小区交通可达性评价的指标体系,并对厦门市的实际情况进行实证分析,最后对选取的50个居住小区的交通可达性做出了综合评判。结果表明,利用高分辨率影像进行城市交通可达性评价是一种简便可行的方法。     

澜沧江流域居民点空间分布格局及影响因素研究

居民点空间分布是区域自然、社会、经济以及历史发展的综合反映,影响着区域经济发展的规模、方向以及发展的可能性。区域自然环境是居民点形成和发展的基础,社会经济因素也对居民点的分布产生重要影响。基于澜沧江流域数字高程模型(DEM)提取坡度、坡向和地形起伏度,结合1∶5万地名数据库的居民点及国家1∶25万基础地理信息数据库的河流、道路信息,研究了澜沧江流域居民点的空间分布格局,并对澜沧江流域居民点分布的影响因素进行定量了分析。研究结果显示,海拔、坡度、坡向、地形起伏度对居民点的分布有显著影响,居民点倾向于分布在海拔较低、坡度和起伏度较小、东南坡向的地区,各级居民点沿河流、道路分布明显。另外,较高级别的居民点更趋向于分布在自然条件较好的区域。研究结果可为澜沧江流域综合开发和生态环境保护提供科学依据。     

New urban settlements in a perspective of public and private interests. Case study: a Swedish municipality within the hinterland of the Stockholm city

The changes of land use patterns and urban structures could be seen as the dynamic result of the trade off between public and private interests. Thereby the land use change is to some extent unpredictable. The focus in the current study is to measure the importance of spatial location factors regarding new residential and commercial buildings in relation to existing urban amenities and political guidelines. The relative importance of the location factors was studied by multinomial regression analysis. Results from this study reveal that the location profiles of new urban object types attained here indicate strong correspondence with local political land use guidelines and to clustering. The spatial distribution of new urban settlements does not in general correspond to the monocentric urban scheme where firms and residents locate in spatial proximity to urban centres.      

基于GIS技术的武夷山市农村居民点空间分布特征

农村居民点形成和发展与区域的自然环境有着密切的关系。利用GIS空间分析功能,定量分析农村居民点与海拔高度、坡度、坡向、交通、河流等自然环境因子的关系,结果表明:①武夷山市农村居民点的分布格局受海拔、坡度、坡向、道路、河流的影响比较明显。②农村居民点呈数量多、质量低、大散居、小聚居的空间分布特征,部分居民点分布在不适宜人们居住的区域,有待调整。因此本研究能为武夷山市农村居民点整理、农村居民点规划提供一定的决策支持。     

Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model’s parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China’s Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model’s parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.     

Characterization and spatial modeling of urban sprawl in the Wuhan Metropolitan Area,China

Urban sprawl has led to environmental problems and large losses of arable land in China. In this study, we monitor and model urban sprawl by means of a combination of remote sensing, geographical information system and spatial statistics. We use time-series data to explore the potential socio-economic driving forces behind urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions. The methodology is applied to the city of Wuhan, China, for the period from 1990 to 2013. The results reveal that the built-up land has expanded and has dispersed in urban clusters. Population growth, and economic and transportation development are still the main causes of urban sprawl; however, when they have developed to certain levels, the area affected by construction in urban areas (Jian Cheng Qu (JCQ)) and the area of cultivated land (ACL) tend to be stable. Spatial regression models are shown to be superior to the traditional models. The interaction among districts with the same administrative status is stronger than if one of those neighbors is in the city center and the other in the suburban area. The expansion of urban built-up land is driven by the socio-economic development at the same period, and greatly influenced by its spatio-temporal neighbors. We conclude that the integration of remote sensing, a geographical information system, and spatial statistics offers an excellent opportunity to explore the spatio-temporal variation and interactions among the districts in the sprawling metropolitan areas. Relevant regulations to control the urban sprawl process are suggested accordingly.     

山地丘陵与平原地区城乡聚落空间分布分形特征研究

本文以河南省区域系统的不同地域单元为例,运用城镇体系研究的空间关联维数模型对山地丘陵区及平原地区城乡聚落体系空间结构进行分析,结果表明农村聚落具有与城市聚落相同的空间分布分形特征;山地丘陵城市的城乡聚落空间可达性不及平原城市;城乡聚落空间分布的乌鸦维数集中在1左右,差别不大,表明河南省作为中原地区所具有的城乡聚落空间布局的总体均衡性。基于此提出了中部农区城乡聚落空间优化、撤乡并镇、新农村社区建设应结合地域城乡聚落分布特点制定适宜的规划方案等有益的建议。     

Electricity consumption patterns within cities: application of a data-driven settlement characterization method

ABSTRACT

Urban areas presently consume around 75% of global primary energy supply, which is expected to significantly increase in the future due to urban growth. Having sustainable, universal energy access is a pressing challenge for most parts of the globe. Understanding urban energy consumption patterns may help to address the challenges to urban sustainability and energy security. However, urban energy analyses are severely limited by the lack of urban energy data. Such datasets are virtually non-existent for the developing countries. As per current projections, most of the new urban growth is bound to occur in these data-starved regions. Hence, there is an urgent need of research methods for monitoring and quantifying urban energy utilization patterns. Here, we apply a data-driven approach to characterize urban settlements based on their formality, which is then used to assess intra-urban urban energy consumption in Johannesburg, South Africa; Sana’a, Yemen; and Ndola, Zambia. Electricity is the fastest growing energy fuel. By analyzing the relationship between the settlement types and the corresponding nighttime light emission, a proxy of electricity consumption, we assess the differential electricity consumption patterns. Our study presents a simple and scalable solution to fill the present data void to understand intra-city electricity consumption patterns.     

基于GIS的大连市沙河口区城市绿地公平性研究——以可持续人居环境为视角

我国快速城市化进程正在遭受着环境污染、交通拥挤、住房紧张等一系列的城市问题,城市生态环境质量持续下降。城市绿地对城市碳氧平衡的调节具有重要作用,大力发展城市绿化将有助于改善城市环境问题。但目前我国城市绿地建设缺乏具体的空间分布规划,只注重绿地覆盖率和人居绿地面积,绿地服务功能的公平性问题没有得到充分重视。本文利用ArcGIS对大连市沙河口区的绿地可达性进行了研究,通过对比绿地可达性与沙河口区人居环境类型发现,高收入社会群体拥有比低收入社会群体更高的绿地可达性。城市规划者应该注意到这些问题,并在今后的建设中关注社会各阶层对绿地的需要,使城市居民在享受公共服务资源上更为公平。     

顾及方向关系的农村居民地聚类方法

农村居民地空间分布具有独特的规律性和复杂性,Voronoi图在表达居民地分布特征方面有显著优势。针对当前空间聚类较少考虑实体方向关系的问题,基于Voronoi图提出一种顾及方向关系的农村居民地聚类方法。首先,构建距离约束的Voronoi图,并构建居民地实体间的Voronoi邻近图;然后,利用无向特征与有向特征来综合评价居民地实体间的聚集强度;最后,消除聚集强度小于阈值的实体对的邻近关系,得到聚类结果。采用浙江省宁波地区部分农村居民地数据进行实验,结果表明,所提方法能够有效聚类不同分布模式的居民地,聚类结果符合人的认知习惯。