**2. Research approach**

Remote sensing and GIS are incorporated into environmental modeling for addressing environmental issues and problems. The core of this approach is to use the power embedded in these geospatial techniques to develop and implement a GIS project. Remote sensing here is treated as the science, technology, and techniques used to acquire the wanted data concerning the study area, processing those data, extracting relevant information about the studied area, and exporting the resulting file into a geodatabase.

A typical GIS project includes (1) stating the problem; (2) defining the study area; (3) acquiring, preparing, and automating the data; (4) processing the data; (5) building the geodatabase; (6) analyzing; and (7) visualizing, mapping, and report writing.

#### **2.1 Stating the problem**

The first step of implementing a GIS project is to state the problem and identify the objective of the analysis. The following questions need be addressed: What is the problem to solve? How is it solved now? Are there alternate ways to solve it using a GIS? What are the final products of the project—reports, working maps, and presentation-quality maps? Will the data be used for other purposes? What are the requirements for these? This step is important because the answers to these questions determine the scope of the project as well as how you implement the analysis.

#### **2.2 Defining the study area**

This step delineates a narrowed boundary of an area of interest. The information from *Step* 2.1 tells us about the proper location where the problem occurred and addresses the possible questions and answers under interest.

GIS possesses many and convenient ways for demarkation of a project's boundary. ERDAS IMAGINE® and ArcGIS®, worldwide used GIS software packages, allow

**83**

**Table 1.**

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

users to work with geographic information data by inputting and manipulating map layers in a comprehensive manner. In this chapter, we use ERDAS Imagine 2014 and

Before locating and acquiring the needed data, a list of criteria should have been set to address the identified objectives of the problem to be solved in the study area.

Example 1: Landfill Locations for Waste Management of the City of Abu Dhabi

Furthermore, the methodology needs to be analyzed to establish what kind of data is needed. The most important question that needs to be answered is Why do I need these data? If the data are truly needed, then this question is easily answered. If not, then the data are most likely not necessary to solve the

To be able to work with data in GIS, you need to understand the nature and procedural steps of working with GIS data such as dataset formats, dataset attributes, dataset completeness, coordinate systems, and dataset sources (see

> January 1972

> > 1990

2000

1983

2006

2000 and 2000– 2015

1995, 2001, and 2005

Primary 2008 ــــــــ) TPSS)

Al Ain land use map Secondary 2000 30 m UAEU

Secondary 1986–

**Date Resolution/**

**accuracy**

1:5000 and 1:50,000

**Source**

Al Ain Town Planning and Surveying Sector

57 m UAEU

28.5 m UAEU

15 and 30 m UAEU

1 m (TPSS)

(TPSS (ــــــــ

& (TPSS (ــــــــ

UAEU

Example 2: GIS-based wind farm site selection model offshore Abu Dhabi

ArcGIS 10.6 for implementing all remote sensing and GIS processes.

Consider the following two real-world examples:

**secondary**

Landsat MSS Primary 29

Landsat TM Primary 28 august

Landsat ETM+ Primary 23 March

Aerial photos Secondary 1976 and

IKONOS Secondary 2000 and

Demographic data Secondary 1989,

*List of primary and secondary data used in the research.*

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

**2.3 Acquiring the data**

Using GIS (**Table 4**) and,

problem.

**Tables 1** and **5**).

Master Plan of the Al Ain region

Al Ain administrative boundary map

Emirate, UAE (**Tables 7** and **8**)*.*

**Data type Primary/**

users to work with geographic information data by inputting and manipulating map layers in a comprehensive manner. In this chapter, we use ERDAS Imagine 2014 and ArcGIS 10.6 for implementing all remote sensing and GIS processes.
