WRM 362_Applied RS and GIS_GIS Data Models & Analysis.pdf

Kwame Nkrumah University of Science & Technology, Kumasi, Ghana Lecture 1 Geographic Information and Data Models Ing. G. Ashiagbor Dept. Wildlife and Range Management Faculty o...

Kwame Nkrumah University of Science & Technology, Kumasi, Ghana Lecture 1 Geographic Information and Data Models Ing. G. Ashiagbor Dept. Wildlife and Range Management Faculty of Renewable Natural Resources E-mail: [email protected] Office # : 115 FRNR  GIS data types GIS technology utilizes two basic types of data 1. Spatial data: describes the absolute and relative location of geographic features. 2. Attribute data : describes characteristics of the spatial features. These characteristics can be quantitative and/or qualitative in nature. Attribute data is often referred to as tabular data. The coordinate location of a forestry stand would be spatial data, while the characteristics of that forestry stand, e.g. cover group, dominant species, crown closure, height, etc., would be attribute data. spatial data models have evolved for storing geographic data digitally. These are referred to as: Vector and Raster/Images www.knust.edu.gh  Attribute data models A separate data model is used to store and maintain attribute data for GIS software. These data models may exist internally within the GIS software, or may be reflected in external commercial Database Management Software (DBMS). The most common are: 1. Tabular 2. Hierarchial 3. Network 4. Relational 5. Object Oriented www.knust.edu.gh Organizing and managing spatial data The main principle of data organization applied in a GIS is that of spatial data layers. A spatial data layer is either a representation of a continuous or discrete field, or a collection of objects of the same kind. Usually, the data are organized such that similar elements are in a single data layer. For example, all telephone booth point objects would be in one layer, and all road line objects in another. A data layer contains spatial data—of any of the types discussed above—as well as attribute (i.e. thematic) data, which further describes the field or objects in the layer. www.knust.edu.gh Organizing and managing spatial data Most GIS software organizes spatial data in a thematic approach that categorizes data in vertical layers. The definition of layers is fully dependent on the organization's requirements. Typical layers used in natural resource management agencies or companies include forest cover, soil classification, elevation, road network (access), ecological areas, hydrology, etc. The clear identification of the requirements for any GIS project is necessary before any data input procedures, and/or layer definitions, should occur. www.knust.edu.gh Spatial data layers Data layers can be laid over each other, inside a GIS package, to study combinations of geographic phenomena. www.knust.edu.gh  The temporal dimension Besides having geometric, thematic and topological properties, geographic phenomena also change over time and are thus dynamic. Some features or phenomena change slowly, e.g. geological features or land cover. Other phenomena change very rapidly, such as the movement of people or atmospheric conditions. For different applications, different scales of measurement will apply. 1. Where and when did something happen? 2. How fast did this change occur? 3. In which order did the changes occur? www.knust.edu.gh  The temporal dimension The way we represent relevant components of the real world in our models determines the kinds of questions we can or cannot answer. Examples of spatio- temporal phenomena: (a) expansion of a city, the area covered by the city grows over time, but the location of the city does not change; (b) a moving car will change position, but the object car does not change size or shape www.knust.edu.gh  Kwame Nkrumah University of Science & Technology, Kumasi, Ghana Lecture 2 GIS Analysis and Process modelling Ing. G. Ashiagbor Dept. Wildlife and Range Management Faculty of Renewable Natural Resources E-mail: [email protected] Office # : 115 FRNR  Four analytical functions of a GIS Classification functions allow the assignment of features to a class on the basis of attribute values or attribute ranges (definition of data patterns). Retrieval functions allow selective searching of data. We might, for example, retrieve all agricultural fields on which potato is grown. Measurement functions allow the calculation of distances, lengths or areas. All functions in this category are performed on a single (vector or raster) data layer, often using the associated attribute data. Generalization functions allow different classes of objects with common characteristics to be joined to form a higher-level (generalized) class. www.knust.edu.gh Measurement, retrieval and classification Overlay functions Neighbourhood functions Connectivity functions www.knust.edu.gh Overlay functions Overlay functions is one of the most frequently used functions in a GIS application. They combine two (or more) spatial data layers, comparing them position by position and treating areas of overlap—and of non- overlap—in distinct ways. Many GISs support overlays through an algebraic language, expressing an overlay function as a formula in which the data layers are the arguments. www.knust.edu.gh Overlay functions Standard overlay operators take two input data layers and assume that they are georeferenced in the same system and that they overlap in the study area. If either of these requirements is not met, the use of an overlay operator is pointless. The principle of spatial overlay is to compare the characteristics of the same location in both data layers and to produce a result for each location in the output data layer. The specific result to produce is determined by the user. It might involve a calculation or some other logical function to be applied to every area or location. www.knust.edu.gh Vector overlay operators The standard overlay operator for two layers of polygons is the polygon intersection operator. It is fundamental, as many other overlay operators proposed in the literature or implemented in systems can be defined in terms of it. The result of this operator is the collection of all possible polygon intersections; the attribute table result is a join—in the relational database sense. www.knust.edu.gh  Vector overlay operators Three polygon overlay operators are illustrated 1. Intersect 2. Clip 3. Overwrite www.knust.edu.gh Raster overlay operators Raster overlays perform their computations cell by cell, and thus they are fast. GISs that support raster processing—as most do—usually have a language to express operations on rasters. These languages are generally referred to as map algebra or, sometimes, raster calculus. They allow a GIS to compute new rasters from existing ones, using a range of functions and operators. – Arithmetic operators – Comparison and logical operators – Conditional expressions – Overlays using a decision table www.knust.edu.gh Raster overlay operators Examples of arithmetic map www.knust.edu.gh Raster overlay operators Example of logical expression in map algebra. Green cells represent true values, white cells represent false values. www.knust.edu.gh  Raster overlay operators Examples of complex logical expressions in map algebra. A is a classified raster for land use, and B holds elevation values www.knust.edu.gh  Raster overlay operators Examples of conditional expressions in map algebra. Here A is a classified raster holding land use data, and B is an elevation- value raster. www.knust.edu.gh  Raster overlay operators Consider a suitability study in which a land use classification and a geological classification must be used NB: forests on alluvial terrain and grassland on shale are considered suitable combinations, while any others are not. The use of a decision table in a raster overlay. www.knust.edu.gh  Case application question Problem Background Mole National Park holds the largest population of elephants in the Northern Savannah zone of Ghana. Park managers in Mole National Park (MNP) conducts regular patrols, surveillance and monitoring operations against any illegal activities within the park as to safeguard its ecological integrity. curbing poaching and other illegal activity in protected areas predominantly depends on resource allocation for law enforcement, in terms patrol effort and capital. However, funds allocations for protected area in Ghana, have been consistently low limiting the enforcement of wildlife laws and the efficiency of anti-poaching activities. To avoid unnecessary waste of conservation resources and help prioritize areas for conservation efforts, You are contracted as a resource manager to identify regions of suitable habitat use by elephants in the park. Terms of Engagement Using the following predictor variables (Environmental variables), Identify data needs and the data type www.knust.edu.gh Case application question Variables Variable Hypothesis Elevation/Altitude & Elephants avoid high elevation areas and steep slopes (Slope Slope >14) due to the risk of injury Distance to Waterholes Elephants stay closer to open water sources NDVI (vegetation Prefer regions of high forage productivity and forage availability) Distance to Saltlicks Elephants supplement diets from mineral licks. Therefore prefer staying closer to saltlicks www.knust.edu.gh Neighbourhood functions Neighbourhood functions evaluate the characteristics of an area surrounding a feature’s location. A neighbourhood function “scans” the neighbourhood of the given feature(s), and performs a computation on it(them). – Search functions – Buffer zone generation (or buffering) – Interpolation functions – Topographic functions www.knust.edu.gh Neighbourhood functions The principle is to find out the characteristics of the vicinity, of a location. Many suitability questions, for instance, depend not only on what is at a location but also on what is near the location. Thus, the GIS must allow us “to look around locally”. To perform neighbourhood analysis, we must: – state which target locations are of interest to us and define their spatial extent; – define how to determine the neighbourhood for each target; and – define which characteristic(s) must be computed for each neighbourhood. www.knust.edu.gh Neighbourhood functions For instance, our target might be a forest reserve. Its neighbourhood could be defined as: – an area within 2 km travelling distance; or – all roads within 500 m travelling distance; or – all communities within 10 minutes travelling time; – all other reserves within 100km distance. Next is to discover about the phenomena that exist or occur in the neighbourhood. – how many people live in the communities; – what is their average household income; – are any illegal activities within the neighbourhood. www.knust.edu.gh Neighbourhood functions Search functions allow the retrieval of features that fall within a given search window. This window may be a rectangle, circle or polygon. Buffer zone generation (or buffering) is one of the best-known neighbourhood functions. It determines a spatial envelope (buffer) around a given feature or features. The buffer created may have a fixed width or a variable width that depends on characteristics of the area. Interpolation functions predict unknown values using the known values at nearby locations. This typically occurs for continuous fields, e.g. elevation, when the data actually stored does not provide a direct answer for the location/locations of interest. Topographic functions determine characteristics of an area by also looking at the immediate neighbourhood. www.knust.edu.gh  Classification Classification is a technique for purposely removing detail from an input data set in the hope of revealing important patterns. It allow the assignment of features to a class on the basis of attribute values or attribute ranges (definition of data patterns). In the process, we produce an output data set, so that the input set can be left intact. This output set is produced by assigning a characteristic value to each element in the input set, which is usually a collection of spatial features that could be raster cells or vector (points, lines or polygons). www.knust.edu.gh  Kwame Nkrumah University of Science & Technology, Kumasi, Ghana THANK YOU