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Znd GRSSDSPRS Joint Workshop on “Data Fusion and Remote Sensing over Urban Areas” ... remote sensing. urban areas. urban climate, multisensor analysis, hyperspectral analysis, data fusion, ... Changes in land use and land cover can be huge and ..... dell'edificata nell'area metropalitana Tonnew durante il deeennio.
Znd GRSSDSPRS Joint Workshop on “Data Fusion and Remote Sensing over Urban Areas”

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EVALUATION OF REMOTE SENSING DATA FOR URBANPLANNING. APPLICATIVE EXAMPLES BY MEANS OF MULTISPECTRAL AND HYPERSPECTRALDATA. Giulia Abbate **, Lorenza Fiumib,Christian De Lorenzob, Ruxandra Vintila‘

’ ENEA Progetto Clima Glohale, c/o ENEA Brindisi,

S.S. 7 Appia Km 714 72100 Brindisi, Italy Tel. +39 0831 507310, Fax: 0831 507 256, E-mail: siulia.abbate@br indisi .enea. i t ~

CNR- Istituto sull’hquinamento Atmosferico - L A M Laboratorio Aereo Ricerche Ambientali Via Monte D’oro, 11 - 00040 Pomeda (RM), Italy Tel. +39 069100312, Faxc39 0691601614, E-mail:[email protected]. it; ’ c.ddorenzo@la ra.rm.cnr.ir ‘Research Institute of Soil Science and Agrochemistry (ICPA) 61, Marasti Avenue 71 331 Bucharest, Romania E-mail : rviaicoa. rQ ~

KEY WORDS: Land remote sensing. urban areas. urban climate, multisensor analysis, hyperspectral analysis, data fusion, environmental monitoring

Abstract: Most city planners and managers already recognize that urban areas require careful desigdre-design and considered management, based on resource sustainability criteria. Involved aspects range from protection of natural and human resources. wise energy and water management, reduction of air pollution and traffic control, health and well-being of population, safeguard of cultural heritage, comfort standards in residential districts, industrial production, craftsmanship preservation, etc.. Advanced instruments for territorial planuiuglmanagemeut are required. Decisions should be based on “proper” information. Data set has to be accurate, objective, reliable, comprehensive and always up-to-date. Specific dataliuformatiou have to be extracted out of all available information but some dataliuformation have to be collected specifically for the purpose. This paper is part of a wider research effort to carry out a GIS (Geographical Information System) and a DSS (Decision Support System) for the city of Rome. Thematic maps will be derived from accurately geocoded remotely sensed images and used to draw “Guidance Tables for Urban Planning”. A multidisclpliuary team will carry out coordinated work to this scope. Application examples ad results for the cily of Rome are illustrated in this paper, based on integration of multispectral data from various satellites (ESA-ERS, Laudsat, SPOT) and MIVIS byperspectral data from aircraft. High complexity has been observed in land cover types, surface composition and morphology, which is directly interrelated with all phenomena taking place in urbanized areas (i.e. physical, chemical, social, economic, etc.). Attention has been focused on climate, urban elements, patterns and materials. I. INTRODUCTION

difficult to grasp when occurring gradually. In the long term they may lead to uncontrollable situations in terms of safety, quality of life, productivity of population, i.e. risks associated to pollution, climate changes and extreme climatic events, like intense beat/cool islands, intense/scarce precipitations, fires, etc. (Abbate, 2001). Need to understand complexity of urban environment has suggested new methods of investigation and urban planning, and has drawn an increasing interest toward multi-disciplinary studies. In the meanwhile, applied and fundamental researches have been supported and even stimulated to develop new technologies to understand these changes. Data obtained by means of remote sensing techniques are sometimes extremely significant and on occasion unique. They allow new spatial and temporal multi-scale approaches which are essential for multidisciplinary analyses of urban phenomena (Barret et al., 1992). Airclaft-home hyperspectral sensors, like MIVIS (Multispectral Infrared Visibile Imaging Spectrometer), besides improving spectral and spatial resolution of studies, allow to tune time interval between measurements over the same =a according to phenomena under study (Bianchi et al., 1996; Boardman et al., 1994). This is an advantage compared to satellite data where repetition time of measurements depends on the orbital parameters of the satellite and cannot be adapted at will. To remotely collect data for land monitoring and connected environmental implications by means of airbome platform National Research Council of Italy established LARA Project (Airborne Laboratory for Environmental Research) in 1990.

A. Motivation and aim

Most metropolitan areas face increasing problems connected to urban expansion, loss of natural vegetation, decreasing of open space. Towns have turned from small isolated centers to big settlements. The new key-words are world-wide expansion, globalization and environmental sustainability (Avecedo et al., 1996). Changes in land use and land cover can be huge and

B. Overview of satellite studies for urban land-cover and climate Cities were observed as heat islands on meteorological satellite infrared images since the beginning of the Seventies, with relatively poor spatial resolution (7-8 Km). Several studies, based on NOAA AVHRR (National Oceanic and

Znd GRSSLlSPRS Joint Workshop on "Data Fusion and Remote Sensing over Urban Areas"

Atmospheric Administration Advanced Very High Resolution Radiometer) data (spatial resolution 1,1 !a),pointed out temperature variations across metropolitan areas (Balling et al., 1988; Gallo et al., 1996). Direct correlation was found between satellite derived surface temperahue values and incidence of residential, commercial and industrial areas in each pixel, while indirect correlation was observed with values of NDVI (Normalized Difference Vegetation Index), that is with vegetation biomass (urban-green land use). HCMM satellite (Heat Capacity Mapping System, Goddard Space Flight Center, 1978) allowed to acquire thermal data near the time of diumal maximum, at a spatial resolution of 500 m, which ww proven useful for placement of air quality monitoring stations in cities and for realistic spatial interpolation between such sites (Price, 1979). Only fifteen years ago, it was commonly believed that satellite images were just adequate for comparing urban-rural temperature differences and that inner structures of urban areas could not be studied by means of this technology, at least at that stage of development. Weather and climate studies in urban areas were carried out by theoretical approaches (even with applicability limitations of available models in urban environment) and, in some cases, by experimental campaigns to obtain point measurements and vertical profiles. Despite continuous progress in technologies of Earth observation from space, only a few attempts ww made of using Landsat TM data, with spatial resolution of 120 m in the thermal infrared hand and 30 m in the other bands (Kim,1992). Just recently these data were processed in combination with other types of spatial information and with accurate ground-truth measurements, by means of GIS technique (Nichol, 1994). This allowed to identify thermal characteristics of urban features down to the scale of a city block, a single row of trees, an individual building, etc. (Nichol, 1996). At the same time, ERS-SAR data (spatial resolution 12,s m) have been exploited to derive information about tri-dimensional structure, roughness (Abbate et al., 1995; Parlow, 1996; Scherer et al., 1996) and humidity (Borgeaud et al., 1994) of urban surfaces, parameters which play a fundamental role in urban climate. More accurate surface temperature measurements than with AVHRR could be obtained by ERS-ATSR data, at the same spatial resolution of 1.1 Km. As new satellite sensors become available, new research directions open up for this field, like use of high spatial resolution satellite data, i.e. IKONOS and QUICK BIRD, and synergistic use of data from ESA ENVISAT and ERS satellites. As above mentioned, hyper-spectral data from airbome sensors offer important advantages, like high spectral and spatial resolution and proper tuning of acquisition and repetition time of measurements, while perhaps costs for regular acquisition campaigns have to be carefully evaluated (Fiumi, 1997).

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11. LAND-COVER IN THE CITY OF ROME: WATERPROF SURFACES AND MATERIALS

Modem settlements are characterized by an indiscriminate use of asphalt and cement, so that most urban land cover types are waterproof surfaces. This has serious consequences on water and energy balances at city scales, with drastic effects for instance on rain water flows, regeneration of underground water layers and microclimate. The impact is evident even at regional scales, where the so called "urban heat island" effect is observed (Stull, 1991). In the formation of heat islands, responses of building materials to sun radiation a~ determining. Within LARA research activities, information on a great deal of covering surfaces and materials for extensions of several Kmz were collected with unique definition and precision. A methodology was developed which, by means of airbome MIVIS (Multispectral Infrared Visibile Imaging Spectrometer) data, allows automatic collection of this information and additional parameters, i.e. surface temperature of roads, squares and green areas. Methodology was also tested for IKONOS satellite data (Rossi, 1999). A flight over the city of Rome allowed to collect MIVIS data during summertime, at 12.30 p.m. Through analysis of spectral response of elements and materials in the study area, a classification methodology was produced, able to discriminate and quantify even spectrally similar urban land cover types, elements, and materials, like i.e. various roofing, road paving, surface coating, non-covered structures, urban buildings, depots at open air, vegetation, bare soil and dry grass, rivers, mobile elements and materials, shaded and sunny areas (Fiumi, 1997). A wide range of sub-classes could be obtained, stressing the typological characteristics of covering materials, i.e. bricks, grits, copper, lead, etc., (Bruno, 1981). An estimated classification accuracy of classification of 95% was obtained. Analysis of statistical files and classification maps produced by processing MIVIS data, highlighted numerous aspects, some immediate, some obvious, other surprising (Rossi, 1999). Buildings in proper sense (covered surface) reach high density values in the districts of Prati-MazziniTrionfale (mean of 47%). with a maximum in a test a m within Prati district (57%). Also the area of MonteverdeCirconvallazione Gianicolense shows a remarkable building density with a mean of 35%. Value reached in some areas of Magliana is really incredible: 72%. The problem of excessive density of buildings is worsened by the presence of asphalted or paved road network, (Fiumi, 2000) so that large areas are practically waterproof and cannot directly absorb rain waters. Waterproof areas reach often more than 90% of the total test district, sometimes almost 100% in the test area of PratiTrionfale-Monteverde. Situations like these should at least assume that drainage network works perfectly, which seldom occurs in practice (Fiumi, 2001). Surfaces covered by meadows are always rather small, while high trunk trees are apparently present with a certain diffusion even in densely built areas, though exclusively along treelined well paved avenues (Rossi, 1999). Ground temperature values at ground (channel 93, thermal infrared, 8.200-8.600 pm), in

Znd GRSSDSPRS Joint Workshop on "Data Fusion and Remote Sensing over Urban Areas" comparison with land cover maps produced by classification of MIVIS data set, show that surfaces recognized respectively as Water, Bare Soil, Meadows and Trees, record lower temperatures. Permeable areas always record lower temperatures both during day and night; vegetation reflects more sun radiation than it absorbs. On the contrary, surfaces classified as Buildings and Variously Paved Roads, record higher temperatures, from 32 "C onwards, and 10% of analyzed surfaces exceed 40' (MIVIS data were collected in June, 12.30 p.m.). This phenomenon is due to the great capability of waterproof surfaces to absorb sun heat and beat produced by human activities in sihl. As a matter of fact, high thermal values, over 40 "C, are recorded along main roads, near crossroads, or anyhow in correspondence with extended surfam which receive greater sun radiation, like St. Peter Square, the courtyards of the former barracks of Milizie Avenue, and the roofs of the industrial sheds in Idrovore Str. at Magliana district (bituminous material) (Fiumi 2001). By this type of analysis - never canied out up to now indicative tables for urban planning have been produced. 111. 3. INTEGRATING CLIMATE KNOWLEDGE INTO SOUND URBAN PLANNING AND MANAGEMENT

When considering setting up measures for the sustainable development of our cities, climate has certainly to be regarded as a high-value natural resource (Bitan, 1992). Its influence on health and most human activities is more than evident, while the influence of human activities on climate begins on a very local level and extends to larger and larger scales. In order to alleviate the impact of human activity on the environment before experiencing some unforeseen non-linearity in the climate system, remedial action will have to he considered in the processes that surround our everyday life. Through drastic modifications to the natural land-cover, urban activities impose localized changes on the Earth's energy budget, which lead to complex atmospheric phenomena (Stull, 1991). A very large set of variables and effects interact to lead to highly specific climates at the level of each town or district or even at that of smaller areas (Hertig, 1993). Scales of p h c X " a range from synoptic (i.e. generalized conditions in a region, due to the presence of city, which acts as a heat and roughness island) to local, up to the very detailed. Remote sensing can provide valuable data and information to support decisions aimed at achieving resource sustainability. It forms part of an approach in which we initially observe from afar and gradually move closer, until starting to test how it responds to our actions. Thus studies of urban areas and related phenomena require an ecological outlook and data with a wide variety of spatial scales, rather than just one single scale at the best possible detail (Abbate, 1997). This approach is being followed in the study of the city of Rome. A wide multi-band and multi-temporal Landsat TM (Thematic Mapper) and ERS SAR (European Remote Sensing Satellite - Syntetic Aperhm Radar) data set has been exploited, showing up thermal and roughness features of city from synoptic to local scale (Abbate et al., 2000). A SPOT

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(SystBme Pour I' Observation de la Terre) panchromatic image and a map have been used as reference. Landsat images were selected for different seasons, while S A R data were selected to cover different meteorological conditions. Data set also included a DEM (Digital Elevation Model), CORINE (COoRdination of INformation on Environment) land cover layer and air temperature data at 14 meteorological stations. Useful parameters to characterize microclimatic aspects of Rome were derived, suitable to be included in a GIS as spatial layers (Abbate at al., 1998). Parameters include: NDVI (Normalized Difference Vegetation Index), from Landsat TM bands 3 and 4; brightness temperature at ground, from Landsat TM band 6; urban thermal emissivity, derived from brightness temperature values and ambient temperatures from meteorological networks at ground; radar backscattering coefficient annual average and standard deviation range, from SAR images. By means of accurately geereferenced and coregistered maps of these parameters, SPOT image, map and CORINE land-cover, relation between urban land-cover and ambient temperature was studied. Temperature relative differences up to IO "C have been observed within Rome during spring and summer, while a relatively uniform distribution of temperature is observed in winter images of city in the presence of strong northerly winds, maximum relative differences being about 3 "C. High correlation values between temperature values as derived from satellite data and measured at monitoring stations (height: 1.5 m, practically temperature of air we breath) encourage to perform accurate tothe-pupose measurements at ground. Classifications of urban a m by means of these parameters could allow to improve positioning of air quality monitoring stations, spatial resolution of ground data, and to obtain a more realistic interpolation among monitoring sites.

Iv. ADDITIONAL RESEARCH EXAMPLES FOR APPLICATION IN URBAN PLANNING

A "Digital atlas of urban mas and elements" research project is being camed to fully explore potentialities of MIVIS hyperspectral data for urban areas (Fiumi, 2001). Some results have been described in session 2. An additional purpose of project is to develop easy-to-use procedures for Local Authorities' staff to look after: Temtory image and data storage; Temtory monitoring and systematic control. Contiguous pixels in urban areas can be extremely different (Cracknell,l998); by using this extreme variability it has been possible to identify structures presenting few pixels with similar values. Through pixel samples with homogeneous spectral characteristics, ROI (Regions Of Interest), wide ranges of subclasses have been determined stressing i.e. roofs, bricks, grit paving, tiles, travertine, copper and asbestos (Fiumi. 2000). In order to assess reliability of this method, a ground-truth field campaign was camed out. For every class and subclass a certain number of samples were selected and photographed for a total of 20 test sites. The results of this field campaign have

Zna GRSSLlSPRS Joint Workshop on “Data Fusion and Remote Sensing over Urban Areas”

proven that the classification obtained by MIVIS data processing corresponds to samples collected in situ. with 95% accuracy. For different types of covering materials (i.e. bricks, tiles, fired brick or travertine paving, marble), pictures of Rome Capital were used. They were taken on September 12“. 1990, at scales 1: 2000, 1: 1000 and 1: 500, by Zeiss camera RMKA 30/23, f=305,38 mm. Critic observation of MIVIS scenes taken over some Italian towns constitutes an occasion to deepen some considerations and examine possible further research developments. Urban landscape, mainly in historical centres, is very often characterized by the presence of local materials. From an architectonic point of view the use of local materials has always been a very important feature for the characterization of the urhan landscape as a whole, down to the smallest element of it. The centuries-old historical centres of Italian towns, characterized by natural colours of local materials, homogeneity and continuity of materials and styles, are opposed to outskirts, which appear as no man’s lands, results of causality, often ignored by town planners, where chimney, parabolic aerials, exalters, prevail with an indiscriminate and chaotic use of materials like bituminous surfaces, cormgated coatings, sheet metals, etc. (Scarpa et al., 1999). Local Authorities need cities overviews, as well as processed products to help understanding of nrhan temtory and related dynamics. v . RESULTS AND DISCUSSION In Europe there are 365 cities of more than 100,000 inhabitants and about 80% of Europeans live in agglomerationsof more than 10,000 people (Citiesnet, 1998). While being among the most vulnerable areas on the planet (WMO, 1997j, cities continue to attract people, as they are perceived as offering more opportunities, not just in terms of survival but also of satisfaction and fulfillment. It is thus clear that real wealth of cities is their people, with their enormous patrimony of personal and collective progress obtained through the effort, work and creativity of generations (Abhate, 2001). People well-being therefore has to be regarded as a resource, and improving it has to he accepted as a challenge for the future. Planning and management of large cities can receive benefit from technologies previously not used in this field, like advanced remote sensing techniques from satellite and aircraft, digital image processing, large data base management and GIS technologies, computer networks and telecommunications, and the like (Lavalle, C. et al., 2000). Studies for the city of Rome, based on remote sensing techniques and GIS approach, have been shortly reported in previous sections. Well informed and considered planninglmanagement even at local scale could lead to “sustainable” impact of urban activities on hydrological and climatic phenomena and extreme weather events in urbanized areas. Wise and expert location of green areas, vegetal species, water surfaces, structural elements and building materials within a city area is fundamental to reach harmony with natural cycles with regulate weather and climate (McPherson, 1992). On the other hand, weather conditions are a matter of considerable interest to the public. Day-to-day experience builds-up to a personal perception of climate, accompanied by feelings of comfort or discomfort. Daily weather forecasts on

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TV and in the newspapers have made us familiar with some concepts of meteorological science and with images from weather satellites, so that there is considerable public awareness of meteorology and climatology. Even if mostly acquired at larger scales than a city, there is also in-depth scientific knowledge and technical experience available. Planninghanagement work to improve quality of life in cities could well start from weather and climate.

VI. CONCLUSIONS AND FURTHER RESEARCH Remote sensing data from satellite and aircraft sensors have been demonstrated to be very appropriate for operational management of urban microclimate quality and associated risks in urban areas (i.e. pollution, intense precipitations, fires, etc.j, especially if processeUfused in multi-band, multisensor, multi-temporal combinations. Some climate-related parameters have been derived and a GIS approach defined. Data sets from new sensors (i.e. ESA ENVISAT, European Space Agency ENVIronmental SATellite) will be analyzed to search for other parameters andlor improve accuracies of estimations. MIVIS hyper-spectral data were used to characterize urban and sub-urban covering surfaces. Coverings in asbestos-cement are worth a special mention (Carlini a! al., 1996; Fiumi at al, 2001). If results are further confrmed for wider areas, operational use of these data could suhstitutehtegrate conventional systems to locate pollution due to askstoscement and other polluting covering surfaces, in different conditions of use. MIVIS data could he used for instance to assess wear condition of road asphalt, or to obtain quantitative information on different covering surfaces present in uban

area Characteristicsof complex and chaotic urban systems, like the city of Rome, do not allow to overlook any factor. Present instruments of territorial management seem to be in general inefficacious towards the anthropogenic risk. Also specific problems related to thermal characteristics in Rome urban a m have to be taken into account. Research activity will funher proceed towards development of a GIS. It will be designed to formulate complex assessments in short time, so as to plan suitable actions before urban system evolves towards undesired stages (Gomarasca, 1996). By means of shapes (lines, points, and polygons) extracted from gec-coded remotely sensed images and from digital maps, as well as through the superimposition and interpolation of other data in a data base, it will be able to produce thematic maps with same graphic precision characteristics of traditional cartography (Gomarasca, 1997). A multidisciplinary research work will draw “Guidance Tables for Urban Planning ”.

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ACKNOWLEDGEMENTS

Scientific work has been carried out with SAR and Landsat data from ESA, under AOI-102fi Project “Heat Island Study in the area of Rome by integrated use of remote sensing techniques”, P.I. Dr. G. Abbate. Cooperation by Prof. Sara Rossi - Chair of Urban Planning, Faculty of Architecture, Reggio Calabria University of Meditemean Studies - in the development of methodology based on MIVIS data is gratehlly acknowledged.