Christiane Weber

The utility of texture analysis to improve per‐pixel classification for high to very high spatial resolution imagery

Earth observation data are becoming available at increasingly finer resolutions. Sensors already in existence (IKONOS, Quickbird, SPOT 5, Orbview) or due to be launched in the near future will reach 1–5 m resolution. These very high resolution (VHR) data will provide more details of the urban areas, but it seems evident that they will create additional problems in terms of information extraction using automatic classification. In this framework, this paper examines the potential of the spectral/textural approach to improve the classification accuracy of intra‐urban land cover types. The utility of the textural analysis was measured in comparison with multi‐spectral per‐pixel classifications. Haralicks second‐order statistics were applied to the co‐occurrence matrix. Four texture indices with six window sizes created from panchromatic images were tested on images at high to very high resolutions (10–1 m). The results show that the optimal index improving the global classification accuracy is the homogeneity measure, with a 7×7 window size. Moreover, for 1 m images, texture measure of homogeneity allows one to decrease the shadows.

Urbanization pressure and modeling of urban growth: example of the Tunis Metropolitan Area

Abstract Urbanization process is a major factor of change in the Mediterranean region where pre-urban cities and new urban settlements have raised over the past decades. Several cities rapidly became regional centres or international nodes according to economic and political pressures. Urbanization (and informal settlement) causes land cover changes which can lead to deeper social, economic and environmental changes. The main objective of this paper is to provide time-series information to define and locate the evolution trends of the Tunis Metropolitan Area. In a first step, satellite imagery has been used (1986–1996 SPOT XS) to extract the land cover, identify the urbanization processes and estimate the changes. One of the main aspects is to locate informal settlement areas that grow significantly along the roadway networks in the Tunisian capital. Results show a global progression of the built-up areas of 13% in 10 years. In a second step, the urban growth evolution has been approached by using a potential model that provides general trends of feasible urban expansion, taking into account protection laws of natural and agricultural land. This type of model has not been tested on developing cities and as such it corresponds to a new planning contribution for planners who have no concept of spatially how their urban areas have changed over time and where the growth is occurring. In this case, it has been calibrated over the period of 1986–1996, and then applied to predict the location of the built-up growth over the next 10 years (1996–2006). These results can provide local authorities and other stakeholders with information towards decision support documents for future planning and monitoring plans. Moreover, they can be updated systematically through the integration of remote sensing data.

Analysing the influence of different street vegetation on traffic-induced particle dispersion using microscale simulations

Urban vegetation can be viewed as compensation to the environmental drawbacks of urbanisation. However, its ecosystem function is not well-known and, for urban planning, vegetation is mainly considered as an element of urban design. This article argues that planning practice needs to re-examine the impact of vegetation cover in the urban fabric given our evaluation of vegetations effects on air quality, including the dispersion of traffic-induced particles at street level. Using the three-dimensional microclimate model ENVI-met®, we evaluate these effects regarding the height-to-width ratio of streets flanked by buildings and the vertical and horizontal density of street vegetation. Our results reveal vegetations effect on particle dispersion through its influence on street ventilation. In general, vegetation was found to reduce wind speed, causing inhibition of canyon ventilation and, consequently, an increase in particle concentrations. Vegetation was also found to reduce wind speed at crown-height and to disrupt the flow field in close vicinity to the canopy. With increasing height-to-width ratio of street canyons, wind speed reduction increases and the disturbance of the flow impacts across a canyons entire width. We also found that the effect is more pronounced in configurations with poor ventilation, such as the low wind speed, perpendicular inflow direction, and in deep canyons cases.

Some urban measurements from SPOT data: urban life quality indices

This paper reviews and illustrates the use of satellite remote sensing in urban analysis. Using the example of conventional population census data used together with SPOT imagery for Strasbourg, France, it is shown that landscape quality can be characterized and mapped with a detail that is not possible using the census alone.

Urban development in the Athens metropolitan area using remote sensing data with supervised analysis and GIS

In this study, a set of multi‐spectral satellites images were used to locate and identify the irregular settlements zones in the Athens metropolitan area. To achieve this goal, indexes—Brightness Index and Normalized Difference Vegetation Index—and supervised classifications are computed and applied to the images. In order to locate and identify these regions, common biophysical characteristics related to the urban and suburban landscape structures were identified. Five types of biophysical class were distinguished: (1) inner dense city with high buildings and absence of vegetation; (2) suburban areas with recent construction of buildings and absence of vegetation; (3) green suburban areas; (4) high‐density vegetation zones; and (5) recent forest fire regions. Some limitations are presented and discussed due to confusion of land‐cover types between bare land and recent constructed areas, or between various types of vegetation and some urban green zones. Results are integrated within a Geographical Information System (GIS), allowing the user to check the legal situation of the classified areas using the Urban Plan of Athens (1983–1995) documentation. This facilitates a proposal and representation of typology of irregular settlements. Such techniques might be very fruitful for developing countries or recently industrialized ones to identify specific irregular settlements.

Interaction model application for urban planning

Urban growth is a terrific issue for the next centuries. Monitoring the urban development in order to assure sustainable cities in the future is an absolute necessity. Decision support in this domain needs some spatial information enabling to forecast the urban development trends. Satellite imagery may provide reliable information assessing the different states of urban growth, but it is necessary to anticipate where future built areas might be located. This paper presents the interest of interaction models, more precisely the potential model, to define future development zones. This model is applied to the Strasbourg area (France) using remotely sensed data. Two images are used, one to initiate the model processing and the other to validate the results. GIS capabilities are applied to refine the results, adding traffic network in the study.

A new approach to building identification from very-high-spatial-resolution images

The extent and rapidity of the urban growth induce a number of socio‐economic and environmental conflicts everywhere. In order to reduce these problems, urban planners need to integrate spatial information in planning tools. High expectations are placed on very‐high‐spatial‐resolution (VHSR) imagery. However, conventional interpretation methods do not seem to be adapted to this new type of images. The aim of our study is to develop a new approach for semi‐automatic building identification, more specifically to individual housing, from VHSR images. The proposed methodology has been applied to Ikonos and Quickbird images in urban areas. Results show the capacity of our method for building identification, in spite of some limitations.

Spatial heterogeneity of the relationships between environmental characteristics and active commuting: towards a locally varying social ecological model

BackgroundAccording to the social ecological model of health-related behaviors, it is now well accepted that environmental factors influence habitual physical activity. Most previous studies on physical activity determinants have assumed spatial homogeneity across the study area, i.e. that the association between the environment and physical activity is the same whatever the location. The main novelty of our study was to explore geographical variation in the relationships between active commuting (walking and cycling to/from work) and residential environmental characteristics.Methods4,164 adults from the ongoing Nutrinet-Santé web-cohort, residing in and around Paris, France, were studied using a geographically weighted Poisson regression (GWPR) model. Objective environmental variables, including both the built and the socio-economic characteristics around the place of residence of individuals, were assessed by GIS-based measures. Perceived environmental factors (index including safety, aesthetics, and pollution) were reported by questionnaires.ResultsOur results show that the influence of the overall neighborhood environment appeared to be more pronounced in the suburban southern part of the study area (Val-de-Marne) compared to Paris inner city, whereas more complex patterns were found elsewhere. Active commuting was positively associated with the built environment only in the southern and northeastern parts of the study area, whereas positive associations with the socio-economic environment were found only in some specific locations in the southern and northern parts of the study area. Similar local variations were observed for the perceived environmental variables.ConclusionsThese results suggest that: (i) when applied to active commuting, the social ecological conceptual framework should be locally nuanced, and (ii) local rather than global targeting of public health policies might be more efficient in promoting active commuting.

The Utility of Very High Spatial Resolution Images to Identify Urban Objects

Abstract With the diversity of new digital geographic information products and in particular the near future Very High Spatial Resolution images (1 to 5m), an evaluation of the capacity of these new data source is necessary in the framework of urban studies. This article aims at assessing the utility of VHSR sensors to provide reliable and useful information for the end‐users (city councils, urban community, county) in urban planning, monitoring and management. The capacity of this new source of information to answer to the end‐users needs have to be investigated. In fact, which type of end‐users must these resolution satisfy, what are the potential applications of these images, what are the characteristics of the information required and finally what type of extraction methods are efficient? An analysis of the capacities of these new sensor to extract urban objects have been carried out for different resolutions and with several extraction methods. This analysis allows on the one hand to define a “Minimal” and a “Functional” spatial resolution able to satisfy the needs of the end‐users, and on the other hand to determine if this future sensors would provide additional capabilities to study the urban environment.

Exploring trade-offs between air pollutants through an Integrated Assessment Model.

When designing air pollution reduction policies, regional decision makers face a limited budget to choose the most efficient measures which will have impacts on several pollutants in different ways. RIAT+ is a regional integrated assessment tool that supports the policy maker in this selection of the optimal emission reduction technologies, to improve air quality at minimum costs. In this paper, this tool is formalized and applied to the specific case of a French region (Alsace), to illustrate how focusing on one single pollutant may exacerbate problems related to other pollutants, on top of conflicts related to budget allocation. In our case, results are shown for possible trade-offs between NO2 and O3 control policies. The paper suggests an approach to prioritize policy maker objectives when planning air pollution policies at regional scale.