**2. Urban remote sensing and urban climate**

A variety of remote sensors, satellite and airborne, detect and measure energy patterns from different portions of the electromagnetic spectrum, which are useful to quantify several parameters essential for urban studies. The great number of EO data from satellite and airborne systems presents an opportunity to extract a great wealth of information via remote sensing, relevant to the urban and peri-urban environments at various spatial, temporal, and spectral scales. With recent innovations in sensor technologies, urban applications of remote sensing, i.e., urban remote sensing, has rapidly gained popularity among a wide variety of communities.

spatial variability is likely to be reduced and less difference is expected among two land-use classes in a city for example, than between a north and south-facing wall of an individual building. Urban climatology studies this heterogeneity and complexity, either explicitly, in terms of detailed mapping of urban morphology, or in interpreting observations at aggregate

The urban surface is composed of a large number of man-made materials arranged in a complex three-dimensional (3D) structure. Cities are built with artificial materials, such as cement, asphalt, brick, pebbles, or aggregates, which absorb and store radiation throughout the day and slowly release heat through the night. Moreover, streets, sidewalks, and parking lots are generally impervious, meaning that they do not allow the water to infiltrate into the soil. Since the urban environment is predominantly covered by artificial pavement, it is important to study the types of materials used and their individual characteristics. Impervious surfaces not only absorb high heat loads, which increase air temperatures through heat convection, but

While land changes from forests, grasslands, and croplands to impervious surfaces, the energy balance changes. The larger amount of solar radiation reaching the Earth's surface is reflected, absorbed, and transformed into sensible and latent heat. A small percentage of the solar radiation is also used in photosynthesis. The atmosphere close to the surface is mainly heated by energy radiating off the Earth's surface and not by direct solar heating. The surface materials affect largely the amount of solar radiation reflected or absorbed and, thus, they affect the heat flux from the surface to the atmosphere. The impervious surfaces alter the local energy balances through changes in the albedo, the emissivity, the specific heat capacities, and the thermal conductivities of the surfaces, as well as the ratio of sensible to latent heat fluxes from the surface to the atmosphere. Therefore, this impacts the temperature and humidity of the overlying air. Cool pavements are made from advanced materials and surface types that are used for decreasing the surface temperature in urban environments. These are mainly based on the use of materials with high albedo combined and high emissivity or techniques that exploit the latent heat to decrease the surface and ambient temperature [6]. Nevertheless, not only the materials, but also the 3D structures of the city have important impact on its radiational balance and thus its temperature. The shape of the cities can be described by several measures, each of which has effect on the city climate. The buildings and trees height affects the reflectivity, the flow regimes, and the heat dispersion above ground. The surface properties as well as the 3D structure of the cities can both be assessed using remote sensing methods

A variety of remote sensors, satellite and airborne, detect and measure energy patterns from different portions of the electromagnetic spectrum, which are useful to quantify several

also increase the rate and temperature of runoff during storms [5].

**2. Urban remote sensing and urban climate**

scales [4].

and EO data.

**1.2. Urban surface and morphology**

128 Multi-purposeful Application of Geospatial Data

Environmental scientists are increasingly relying upon EO data to derive, for example, urban land cover information as a primary boundary condition used in many spatially distributed models [7]. The climate change community has also recognized remote sensing as an enabling and acceptable technology to study the spatiotemporal dynamics and consequences of urbanization as a major form of global changes [8]. Lately, more urban researchers are also using remote sensing to extract information for studying the urban surface and geometry [9, 10]. Finally, urban and regional planners are increasingly using EO data to derive information on cities in a timely, detailed, and cost-effective way to accommodate various planning and management activities [11].

Urban remote sensing can help improve our understanding of cities and many benefits of using EO data for urban studies that can be identified. The largest benefit of remote sensing, its capability of acquiring images that cover a large area, applies also for urban studies, where synoptic views allow identifying objects, patterns, and human-land interactions. Identifying the urban processes that operate over a rather large area and quantifying the differences in an intra-urban level is essential for understanding the urban environment. Remote sensing provides a great asset on information gathering on the entire mosaic of an urban phenomenon, while knowledge and expertise from multiple disciplines can lead to full understanding and modeling the urban processes.

Remote sensing holds an advantage as well, and complements the field measurements. Field measurements in most cases in urban sites do not represent the broader area. To cover large areas a lot of field measurements are needed, dense in both temporal and spatial terms and this can become prohibitively expensive in most cases. Moreover, data collected from field surveys and measurements can suffer from biases in the sampling design. Remote sensors can collect data in an unbiased and cost-effective way and thus provide better insights on the spatial and temporal evolution of processes. Field measurement can complement the remote sensing ones and combined methods and products hold great potential in terms of accuracy, spatial, and temporal coverage.

A framework of monitoring, synthesis, and modeling in the urban environment can be achieved with synergies of EO data integrated with relevant geospatial technologies, like spatial analysis and dynamic modeling. This framework can then be used to support the development of a spatio-temporal perspective of the urban processes and phenomena across scales and also to relate the different human and natural variables for understanding the direct and indirect drivers of urbanizations.

Last, remote sensing is ideal for connecting different scales for urban studies. Urban science disciplines have their own preferred scales of analysis. For example, urban planners tend to work at street and neighborhood scales, while regional planners deal with larger entities such as metropolitan areas, even a whole city, or country region. Urban ecologists work at many spatial scales defined by the ecological units, and so as urban geographers, depending upon the specific topics under investigation. Urban meteorologists define the scales by the different physiographical features of the city. EO data can provide global coverage with spatial resolution ranging from sub-meter to a few kilometers and with varying temporal resolutions. The different urban researchers use different temporal scales depending on their application, varying from hourly, daily, weekly, monthly, seasonally to annual or decal basis. EO data allow work at any scale depending on the urban phenomenon being examined and they also offer the unique potential for linking different scales.

Remote sensing improves our understanding of urban areas in several ways, although the complexity of the urban environment challenges the realistic potential for making these improvements. Despite the profound benefits of using EO data for urban studies, the great inhomogeneity of urban environments obstructs the applicability and robustness of remote sensing methods. The presence of manmade materials and structures and the variety of vegetation cover, along with the 3D nature of cities, cause substantial inter-pixel and intra-pixel variations, complicating the characterization of urban landscapes. A great scientific challenge lies in the combination of EO data from different sensors, both in terms of scales and type of measurements. Moreover, it is always a challenge to integrate satellite data with other types of geospatial data in urban environmental analyses, like field measurement data, and cope with the fundamental differences in data sampling and measurement.

on urban remote sensing, since 1995. There is a published literature on urban remote sensing since the 1970s, but a highly increasing rate is observed around 2002. This period coincides with the advent of very high spatial resolution satellite images (higher than 5 m) and the first spaceborne hyperspectral images. Thus, enhanced image processing techniques were developed such as the object-based image analysis, data mining, and data and image fusion of dif-

**Figure 2.** The number of journal articles (including review articles) including the key words urban remote sensing (line), urban remote sensing climate (first set of bars), urban remote sensing thermal (second set of bars), urban remote sensing

Earth Observation for Urban Climate Monitoring: Surface Cover and Land Surface Temperature

http://dx.doi.org/10.5772/intechopen.71986

131

The same trend can be noticed in the literature of urban remote sensing for climate (first set of bars in **Figure 2**), which has been following similar rate of increase in these years. It is interesting though to observe that the pattern of urban thermal remote sensing (second set of bars in **Figure 2**) follows very close the one of urban heat island (third set of bars in **Figure 2**). Although expected, this graph is a strong indication that, so far, when referred to urban climate monitoring from space, the main focus is usually in thermal remote sensing. It is indeed true that thermal remote sensors provide indispensable information for the surface temperature, with their great advantage being the spatial cover of large areas. Yet, remote sensing can contribute much more than that into our understanding of the biophysical properties, the patterns and the processes of urban landscapes using all ranges of electromagnetic wavelength and active sensors as well. In fact, the last year (2015–2016) seems that the remote sensing community has started publishing studies related to urban climate, which are not necessarily

From the wealth of available and upcoming EO data, detailed information on the urban surface cover and quantitative estimates of the biophysical parameters related to the urban climate can be extracted. Methodologies that exploit and combine satellite data from different sources and of various spatial, spectral, and temporal resolutions can give insights on the evolution in space and time of the urban climatic phenomena. Current and upcoming satellite sensors may provide great wealth of information for our understanding of the cities climate. Remote sensing provides a wealth of data of different spatial, spectral, and temporal resolutions that can cope with the spatial and temporal scale requirements of urban climate studies.

ferent sensors, wavelength regions and spatial, spectral, and temporal resolutions.

using thermal data or are referring to the urban heat island.

heat island (third set of bars). Source: Scopus search on August 18, 2017.

The ability to map, monitor, and analyze the complex and dynamic attributes of urban environments from EO data greatly depends on the characteristics of the remote sensing imaging instrument. Operational satellite EO systems are designed for specific missions, and thus have different operational principles and technical characteristics depending on the specifications of the missions. Currently, no EO system is specifically designed for monitoring urban areas. Airborne imaging systems are more flexible, but the cost of airborne campaigns limits the frequency of acquisitions and the area of coverage.
