**2.1. Satellite data in urban studies**

A large variety of satellite data can be used for urban studies. The selection of a particular data source is a compromise among data availability, costs, and the required spatial, spectral, and temporal resolution. The majority of urban phenomena are scale-dependent, which means that urban patterns change with the scale of observation. Urban processes appear to be hierarchical in pattern and structure [12]. Therefore, studies of the relationship between the patterns at different levels in the hierarchy are urgently needed in obtaining a better understanding of the scale and resolution requirements in urban areas and in finding the optimal scale for examining the relationship between urban landscape pattern and process.

Over the past decade, urban remote sensing has emerged as a new frontier in the EO technology by focusing primarily on mapping and monitoring of the urban land cover and its spatial extent. The line in **Figure 2** shows the number of journal articles (including review articles)

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

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

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

A large variety of satellite data can be used for urban studies. The selection of a particular data source is a compromise among data availability, costs, and the required spatial, spectral, and temporal resolution. The majority of urban phenomena are scale-dependent, which means that urban patterns change with the scale of observation. Urban processes appear to be hierarchical in pattern and structure [12]. Therefore, studies of the relationship between the patterns at different levels in the hierarchy are urgently needed in obtaining a better understanding of the scale and resolution requirements in urban areas and in finding the optimal scale for

Over the past decade, urban remote sensing has emerged as a new frontier in the EO technology by focusing primarily on mapping and monitoring of the urban land cover and its spatial extent. The line in **Figure 2** shows the number of journal articles (including review articles)

offer the unique potential for linking different scales.

130 Multi-purposeful Application of Geospatial Data

with the fundamental differences in data sampling and measurement.

examining the relationship between urban landscape pattern and process.

the frequency of acquisitions and the area of coverage.

**2.1. Satellite data in urban studies**

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

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

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

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.
