**3. Case studies**

## **3.1 Characterization of Al Ain city urban growth using multi-temporal remote sensing data and GIS**

The population of the UAE rose exponentially from around 86,000 in 1961 to more than 4 million in 2005. This has resulted in enormously rapid emplacement of a modern infrastructure, including an extensive highway and road networks, residential areas, shopping malls, golf courses, airports, and industrial facilities. The scale of such ambitious developments (often referred to as 'mega-projects') has been amazing and unmatched on a world scale.

In this case study, an attempt has been undertaken to map 'urban areas' in Al Ain city from large and medium-scale Landsat imageries in three different dates spanning the period 1972–2000 and to characterize the urban growth of the city using three different approaches: qualitative (using milestone change trajectories in the city), quantitative (using spatial metrics), and GIS overlay analysis.

#### *3.1.1 Requirements for characterizing urban growth using remote sensing data*

Capturing and analyzing the landscape change of the UAE have become key components to planners and policy makers in order to identify causes and assess the consequences of these changes on the future development of the society. Here

**87**

**Figure 2.** *Study area.*

*Modeling the Environment with Remote Sensing and GIS: Applied Case Studies from Diverse…*

rises the challenge of finding an effective way of measuring and documenting this change, sometimes very rapid, for a sustainable development that augments the people welfare while preserving the environment. Measurement and analysis of urban growth using remote sensing and geographic information system (GIS)

The study area is located between 55°28′ E to 55°53′ E longitudes and 24°03′ N to 24°22′ N latitudes (**Figure 2**). Al Ain is situated 150 km from Abu Dhabi capital city and 160 km from Dubai on the feet of Hafeet Mountain to the south and bordering Oman international boundaries to the east. The city is a perfect example of a small desert oasis with primitive society and limited resources to transform into a well-developed large city with an urban center hosting more than half a million inhabitants within a quarter of a century, making it an ideal example for urban growth studies using new remote sensing and GIS techniques

A set of primary and secondary data is used in the research. Three Landsat

satellite images from 1972, 1990, and 2000 (i. e., MSS1972, TM1990, and ETM + 2000) are processed and analyzed using ERDAS Imagine for the extraction of LULC classes in the three dates. Large-scale historical aerial photographs besides other ancillary data are used as reference data for accuracy assessment as well as in the geo-database building for further spatial analysis in GIS (**Table 1**). All images are atmospherically calibrated and geometrically rectified to a common Universal Transverse Mercator (UTM) coordinate system, zone 40, and the

techniques have seen very limited application examples in the UAE.

*DOI: http://dx.doi.org/10.5772/intechopen.82024*

in the region.

*3.1.1.1 Datasets*

WGS84 Datum.

*Modeling the Environment with Remote Sensing and GIS: Applied Case Studies from Diverse… DOI: http://dx.doi.org/10.5772/intechopen.82024*

rises the challenge of finding an effective way of measuring and documenting this change, sometimes very rapid, for a sustainable development that augments the people welfare while preserving the environment. Measurement and analysis of urban growth using remote sensing and geographic information system (GIS) techniques have seen very limited application examples in the UAE.

The study area is located between 55°28′ E to 55°53′ E longitudes and 24°03′ N to 24°22′ N latitudes (**Figure 2**). Al Ain is situated 150 km from Abu Dhabi capital city and 160 km from Dubai on the feet of Hafeet Mountain to the south and bordering Oman international boundaries to the east. The city is a perfect example of a small desert oasis with primitive society and limited resources to transform into a well-developed large city with an urban center hosting more than half a million inhabitants within a quarter of a century, making it an ideal example for urban growth studies using new remote sensing and GIS techniques in the region.

#### *3.1.1.1 Datasets*

*Geographic Information Systems and Science*

**2.7 Visualizing and printing the results**

ated by other applications, or place them on your map. All the above steps are summarized in **Figure 1**.

been amazing and unmatched on a world scale.

techniques.

**3. Case studies**

**sensing data and GIS**

complex, multistep analytical models. Perhaps the simplest form of GIS analysis is presenting the geographic distribution of data. This is conceptually the same as sticking pins in a wall map, a simple but powerful method of detecting patterns. A second type of GIS analysis is querying, or selecting from, the database. Queries let you identify and focus on a specific set of features. There are two types of GIS queries, *attribute* queries (find features based on their attributes) and *location* queries (find features based on where they are). A third type of GIS analysis is finding what is near a feature (buffering); a powerful function of GIS analysis is that the output of one procedure can be used in another. Here, the buffered zone can be used in an attribute query. A fourth type of GIS analysis is overlaying different layers of features. You can create new information when you overlay one set of features with another. There are several types of overlay operations, but all involve joining two existing sets of features into a single new set of features. Finally, all these techniques and many others are combined into a more complex GIS analysis, thus creating detailed models of the world to solve complicated problems. It is possible to repeat an analysis using slightly different parameters several times and compare the results. This can allow you to refine your analysis

The last step in a GIS project is to present and communicate the results of your analysis. Your final product should effectively communicate your findings to your audience. The results of a GIS analysis can best be shown on a map. Nevertheless, they can also be disseminated through charts, reports, or videos and animated maps. You can print charts and reports separately, embed them in documents cre-

**3.1 Characterization of Al Ain city urban growth using multi-temporal remote** 

The population of the UAE rose exponentially from around 86,000 in 1961 to more than 4 million in 2005. This has resulted in enormously rapid emplacement of a modern infrastructure, including an extensive highway and road networks, residential areas, shopping malls, golf courses, airports, and industrial facilities. The scale of such ambitious developments (often referred to as 'mega-projects') has

In this case study, an attempt has been undertaken to map 'urban areas' in Al Ain city from large and medium-scale Landsat imageries in three different dates spanning the period 1972–2000 and to characterize the urban growth of the city using three different approaches: qualitative (using milestone change trajectories in the

city), quantitative (using spatial metrics), and GIS overlay analysis.

*3.1.1 Requirements for characterizing urban growth using remote sensing data*

Capturing and analyzing the landscape change of the UAE have become key components to planners and policy makers in order to identify causes and assess the consequences of these changes on the future development of the society. Here

**86**

A set of primary and secondary data is used in the research. Three Landsat satellite images from 1972, 1990, and 2000 (i. e., MSS1972, TM1990, and ETM + 2000) are processed and analyzed using ERDAS Imagine for the extraction of LULC classes in the three dates. Large-scale historical aerial photographs besides other ancillary data are used as reference data for accuracy assessment as well as in the geo-database building for further spatial analysis in GIS (**Table 1**). All images are atmospherically calibrated and geometrically rectified to a common Universal Transverse Mercator (UTM) coordinate system, zone 40, and the WGS84 Datum.

**Figure 2.** *Study area.*
