Topography GIS Data Sources PDF

Data Sources that GIS can handle GIS data is based on topographic features (the makeup of physical structures of the land surface). Topography includes the relief (difference in height from the surrounding terrain) of an area and the position of both natural and man-made features There are hundred...

Data Sources that GIS can handle GIS data is based on topographic features (the makeup of physical structures of the land surface). Topography includes the relief (difference in height from the surrounding terrain) of an area and the position of both natural and man-made features There are hundreds of data formats - some analogue and some digital -- that can be used in GIS A diagram of information on a blue background Description automatically generated 1)Raster The first type of raster data is **satellite imagery**. - Satellite imagery is captured by sensors on satellites orbiting the Earth. - It provides us with a bird's-eye view of the planet and helps us understand changes in land cover, monitor weather patterns, and analyze the Earth's surface. - Satellite imagery can be used for various applications, such as urban planning, disaster management, and environmental monitoring. The second type of raster data is the **Digital Elevation Model** (DEM). - DEM represents the elevation of the Earth's surface and is crucial for topographic mapping, watershed analysis, and terrain modeling. - It provides information about the height and slope of the land, allowing us to create accurate 3D visualizations of landscapes and study the flow of water across a given area. - LiDAR (Light Detection and Ranging) is commonly used to create Digital Elevation Models (DEMs). - LiDAR is an acronym for Light Detection and Ranging. In LiDAR, laser light is sent from a source (transmitter) and reflected from objects in the scene. The reflected light is detected by the system receiver and the time of flight (TOF) is used to develop a distance map of the objects in the scene. - LIDAR (Light Detection and Ranging) imagery is a remote sensing method that uses laser light to measure distances to the Earth's surface. LIDAR systems emit laser pulses and then measure the time it takes for the pulses to bounce back after hitting an object. - This information is used to create precise, three-dimensional maps of the terrain, vegetation, and other features.  **[Digital Orthophotos]**, the third type of raster data - They are aerial photographs that have been geometrically corrected to remove distortions caused by camera and terrain variations. - Orthophotos are commonly used for mapping purposes as they provide a geometrically accurate representation of the Earth's surface. - They are utilized in applications like land use planning, infrastructure development, and environmental studies. The fourth type of raster data is **Binary Scanned Files** A map of a city Description automatically generated - These files contain scanned versions of maps, drawings, or documents. - By converting analog materials into digital format, rasterizing them, we can analyze and integrate historical data into modern geographical information systems. - The term \"binary scanned map\" typically refers to a digital representation created by scanning a physical map and storing it in a binary file format. - Binary Scanned Files are particularly useful for research, archaeology, and preserving cultural heritage. 2\) Vector Contours are lines drawn on a map that connect points of equal elevation above a specified level, typically sea level.  - They represent the three-dimensional shape of the terrain on a two-dimensional map. - Contour lines are the lines that connect points of equal elevation. The contour lines on the map represent areas with equal elevation, that is, they are contours of equal altitude. - The two lines close together to show a mountain range in which all peaks have equal elevation, while the line far from them shows flat land with no mountains nearby. Here are some key features of contour lines: - Elevation Representation: Each contour line indicates a specific elevation. The spacing between lines indicates the steepness of the terrain; closely spaced lines suggest steep slopes, while widely spaced lines indicate gentler slopes. - Closed Loops: Contour lines often form closed loops, which can represent hills (if the lines are closed and have higher values toward the center) or depressions (if the lines are closed with hachures indicating lower values toward the center). - Index Contours: Some maps include thicker or darker lines, known as index contours, which are labeled with their elevation values. These help users quickly identify elevation changes and show elevation above sea level. - Contour Intervals: The vertical distance between adjacent contour lines is called the contour interval. It can vary depending on the map\'s scale and the level of detail required. In GIS, networks refer to interconnected systems of linear features that facilitate movement or flow between locations. Networks are commonly used to represent transportation systems, utility lines, and other types of connected infrastructure. A close-up of a map Description automatically generated Here are some key aspects of networks in GIS: Components of Networks: - Nodes: Points that represent intersections, endpoints, or connections within the network (e.g., intersections of roads, junctions in utility lines). - Edges: The linear features that connect nodes, representing pathways for movement or flow (e.g., roads, railways, rivers, or pipelines). Types of Networks: - **Transportation Networks**: Include roads, railways, and paths that enable movement of vehicles, pedestrians, or goods. - It is generally undirected network because the edge on a network may have a direction assigned to it. - The transportation route, the direction, speed, and destination of traversal can be decided by the person. - Transportation or road network model play key role in transportation planning, analysis of retail market, measurements of accessibility, allocation of service and more. - The understanding of road network patterns provide the idea about the human mobility behaviour. - **Utility Networks**: Represent the flow of resources like water, electricity, or telecommunications, including pipes and cables. - It includes water mains, sewage lines, and electrical circuits. These networks are generally directed. Its path is predetermined. It can be changed, but not by agent. - **Hydrological Networks**: Depict the movement of water through rivers, streams, and drainage systems. - It is directed network because of the natural flow. - This type of modelling is perform for the analysis of drainage based on terrain or digital elevation. It shows the detail information about the connectivity of landscape and land use and land cover pattern. - It measures the various attribute related to linear, areal, relief features of stream. Stream network model analyse the geometry (shape, size, drainage density, landforms etc.) - It helps in understanding the dynamic behaviour of river flow that reduces the impact of floods and helps in socio-economic condition of human, supply of hydroelectricity energy etc. Network Analysis: an operation in GIS which analyses the datasets of geographic network or real world network. Network analysis examine the properties of natural and man-made network to understand the behaviour of flows within and around such networks and locational analysis. It focuses on edge-node topology to represent real life networks of information. Its function based on the mathematical sub disciplines of graph theory and topology. GIS allows for various analyses on networks, such as: - Routing: Finding the shortest or fastest path between points. - Service Area Analysis: Determining areas that can be reached within a certain distance or time from a location. - Connectivity Analysis: Assessing how well different parts of the network are connected. Boundaries  In GIS, boundaries refer to the lines or surfaces that delineate the limits or extents of geographic features, areas, or jurisdictions. - These boundaries can be physical or administrative and are crucial for spatial analysis, mapping, and resource management. Here are the main types of boundaries in GIS: Administrative Boundaries: - These define the limits of governmental or organizational units, such as countries, states, counties, municipalities, and school districts. - They are essential for understanding jurisdictional areas and governance. Natural Boundaries: - These are defined by physical features of the landscape, such as rivers, mountains, or lakes. Natural boundaries can influence human activities and ecological processes. Cadastral Boundaries: - These represent the legal divisions of land, such as property lines and parcels. They are important for land ownership, zoning, and real estate management. Statistical Boundaries: - Used for data collection and analysis, these boundaries define areas for statistical reporting, such as census tracts or electoral districts. Thematic Boundaries: - These may represent areas based on specific themes or characteristics, such as land use zones (residential, commercial, industrial) or environmental management areas (conservation zones, wetlands). Applications of Boundaries in GIS: - Mapping: Boundaries are essential for visualizing geographic information and understanding spatial relationships. - Spatial Analysis: They help analyze demographic data, resource distribution, and environmental impacts within defined areas. - Planning and Management: Boundaries play a key role in urban planning, resource management, and policy-making by clearly defining areas of interest. Instances A collage of maps Description automatically generated In GIS, the term \"instances\" typically refers to specific occurrences or examples of geographic features or entities represented within a GIS dataset. Each instance is a distinct representation of a feature that possesses particular attributes. Here are some key points about instances in GIS: Feature Instances: - Each instance represents a unique geographic feature, such as a specific building, tree, or road segment. For example, in a dataset of parks, each individual park would be an instance. Attributes: - Instances have associated attributes that provide additional information about the feature. For example, a building instance might have attributes like its height, year built, and owner. Data Models: - In GIS data models, such as vector or raster, instances help structure the data. In vector data, each feature (point, line, or polygon) is an instance of its respective type. Spatial Relationships: - Instances can interact with one another in various ways. For example, a road instance might intersect with a river instance, which can be analyzed for planning or environmental studies. Query and Analysis: - GIS allows users to query instances based on their attributes and spatial relationships. For example, you can retrieve all instances of parks larger than a certain size or find all instances of buildings within a specific distance from a school. Visualization: - Instances are visualized on maps or in 3D representations, allowing users to understand spatial patterns, distributions, and relationships between features. Data Input A diagram of a computer Description automatically generated Digitising Data -- manual digitisation In GIS, various types of data can be input to create, analyze, and visualize geographic information. There are at least 4 procedure for inputting spatial data  A white text on a black background Description automatically generated  A white paper with black text Description automatically generated  Errors  Here are the main types of data input in GIS: Spatial Data: - Vector Data: Represents geographic features using points, lines, and polygons. Examples include roads (lines), boundaries (polygons), and landmarks (points). - Raster Data: Represents information as a grid of cells or pixels, often used for continuous data like elevation, temperature, or satellite imagery. Attribute Data: - Associated information that describes the characteristics of spatial features. This data can be stored in tables and linked to spatial data. For example, a dataset of buildings may include attributes such as height, use, and owner. - Attribute data is usually inputted by manual keying Tabular Data: - Data organized in rows and columns, often used for demographic information, survey results, or any non-spatial data that can be linked to spatial features through unique identifiers. Remote Sensing Data: - Information collected from aerial or satellite imagery. This data can be processed into both raster and vector formats and is useful for monitoring environmental changes, land use, and urban development. GPS Data: - Data collected from Global Positioning System (GPS) devices that provide precise location information. This data is often used for mapping, tracking, and field data collection. Survey Data: - Information gathered from ground surveys, which can include precise measurements of land, structures, and features. This data is critical for creating accurate maps and models. 3D Data: - Includes three-dimensional representations of features, often used in urban modeling, terrain analysis, and architectural design. This data can be represented in various formats, including 3D vector models and 3D raster data (like Digital Elevation Models). Geocoded Data: - Data that has been linked to geographic coordinates, allowing it to be placed on a map. This can include addresses, places of interest, or other location-based information. Web Services Data: - Data accessed from online services and APIs, such as Web Map Services (WMS) or Web Feature Services (WFS), allowing for the integration of external datasets into GIS applications. Data Sources 1. Collect primary data yourself (e.g. fieldwork) - Primary data are (New) data collected by the user for a specific purpose - Questionnaires, Field Observations, Field Surveys and Physical measurements are types of primary data collection. - You can use GPS, differential GPS and total stations to collect primary x (latitude), y (longitude), z (elevation) coordinate information relative to a spatial reference system - There are instances in which spatial data are collected without a formal, spatial reference but by locating known positions on an image it can be made to conform to a spatial reference system A diagram of a mountain range Description automatically generated with medium confidence 2. secondary data set: Data warehouses (e.g. Digimap) - Secondary data are (Existing) data collected by others that may provide useful information for a given purpose 3. Commercial data provides (e.g. Ordnance Survey, Department of Survey in Malaysia) 4. Government (e.g. Census, statistic, economics) A map scale is the relationship between the dimensions on the paper to the real distance on the ground Example: a building is 13m in the real world but on paper/map it is 13mm = scale is 1:1000. 1. Representation of Area: - The scale determines how distances and areas on the map correspond to their actual sizes in the real world. A larger scale (e.g., 1:10,000) shows a smaller area with greater detail, while a smaller scale (e.g., 1:250,000) covers a larger area but with less detail. 2. Accuracy of Measurements: - Accurate scaling ensures that measurements taken from the map (distances, areas, etc.) are reliable. Users can make informed decisions based on these measurements, whether for planning, navigation, or analysis. 3. Appropriate Detail Level: - Different scales are suitable for different purposes. For example, a detailed city map requires a larger scale for effective navigation, while a regional map may use a smaller scale to show broader trends and patterns. 4. Contextual Understanding: - Scaling helps convey the relationship between different features on the map. It allows users to understand how various elements (like roads, buildings, and natural features) fit into the larger landscape. 5. Comparison Across Maps: - When comparing different maps, consistent scaling helps ensure that users can accurately interpret and analyze spatial relationships. This is particularly important in multi-map analyses or when integrating data from various sources. Generalisation Generalization in GIS refers to the process of simplifying and reducing the complexity of spatial data to make it more understandable and usable for specific applications. This involves modifying the representation of geographic features to focus on the most relevant information while omitting less critical details. Key Concepts of Generalization: Purpose: - Generalization is used to create maps or datasets that are appropriate for different scales and audiences. For example, a detailed topographic map may be generalized to create a regional map for broader understanding. Techniques: Various techniques can be applied in the generalization process, including: - Simplification: Reducing the detail of shapes, such as smoothing curves or removing small features. - Aggregation: Combining multiple features into a single representation, such as grouping smaller lakes into one larger area. - Displacement: Adjusting the position of features to avoid overlap and improve clarity, such as moving labels or symbols apart. - Selection: Choosing only the most important features to represent at a given scale, omitting less significant ones. - The level of generalization required often depends on the scale of the map or the intended use. Larger scale maps may retain more detail, while smaller scale maps require more generalization to convey essential information clearly. - While generalization simplifies data, it\'s crucial to maintain the spatial relationships and characteristics of the features to ensure that the map remains useful and accurate. Benefits of Generalization: - Clarity: Simplified representations make it easier for users to understand the information being conveyed. - Focus: By highlighting essential features, generalization helps users focus on relevant data for their specific needs. - Improved Usability: Generalized maps are often more user-friendly, allowing for quicker decision-making and analysis. Scanning refers to the process of digitizing physical maps, documents, or other forms of spatial data into a digital format. This process allows for the preservation, analysis, and manipulation of geographic information that was originally in a non-digital format Automated digitalising: - Vector-based data uses automatic line tracing algorithms - Much quicker than manual approach - Wholly dependent on the quality of the algorithm - Features less than the resolution of the data set will be lost - Algorithm has no concept of the context of the information being digitised - Usually requires a great deal of cleaning  1. **Digitization Process**: - Scanning involves using a scanner or specialized imaging equipment to capture the details of a physical map or document. The result is a raster image, which can be stored in various formats (e.g., TIFF, JPEG). - It is also an automated digitisation technique - Digitizing is very time consuming because every single point or vertex must be captured individually - Digitizing attaches attribute information to features. Eg. its type and shape 2. **Types of Scanning**: - **Flatbed Scanning**: Used for scanning maps and documents that are flat and can be placed on a scanner bed. - **Drum Scanning**: Provides high-resolution images, suitable for detailed cartographic maps. - **3D Scanning**: Captures three-dimensional objects or landscapes, useful for creating detailed models. 3. **Georeferencing**: - After scanning, the raster image needs to be georeferenced to provide a spatial reference across the raster, which involves aligning the image with real-world coordinates. This process ensures that the scanned data can be accurately overlaid with other GIS data layers. Vectorization in GIS is the process of converting raster data (which represents information in a grid format) into vector data (which uses points, lines, and polygons). - This transformation allows for more precise representation and analysis of geographic features. - Various techniques can be used for vectorization, including manual digitization (where a user traces features), automated edge detection, or contour tracing using software tools. Remote sensing in GIS refers to the acquisition of information about the Earth\'s surface without direct contact. This is typically done through the use of satellites, aircraft, or drones equipped with sensors that capture data across various wavelengths of the electromagnetic spectrum. 1. Data Collection: - Remote sensing involves collecting data using sensors that can capture images or measurements of the Earth\'s surface. These sensors can detect visible light, infrared radiation, thermal energy, and more. Types of Sensors: - Passive Sensors: Detect natural energy reflected or emitted from the Earth\'s surface (e.g., cameras capturing sunlight). - Active Sensors: Emit their own signals (such as radar or LiDAR) and measure the energy that returns after interacting with the surface. 2. Image Processing: - The raw data collected by remote sensors often requires processing to enhance image quality, correct for atmospheric effects, and extract meaningful information. This can include filtering, classification, and transformation techniques. 3. Applications: - Land Use and Land Cover Mapping: Analyzing changes in vegetation, urban development, and natural resources. - Environmental Monitoring: Tracking changes in ecosystems, deforestation, and pollution. - Disaster Management: Assessing damage from natural disasters, such as floods and wildfires. - Agriculture: Monitoring crop health, soil moisture, and land management practices. Topology and topography Topography Definition: Topography refers to the arrangement of natural and artificial physical features of an area. It includes elevation, terrain relief, landforms (like mountains, valleys, and plains), and surface characteristics. Usage: Topographic maps depict these features, often using contour lines to show elevation changes. They are useful for activities like hiking, land-use planning, and environmental studies. Topology Definition: Topology in GIS refers to the spatial relationships and connections between features, regardless of their exact geometric shape or size. It focuses on how features relate to each other (e.g., adjacency, connectivity, and containment). Usage: Topological models are crucial for spatial analysis and maintaining data integrity. They help in understanding how features interact, such as determining which areas are accessible from one another or identifying overlapping regions. Summary Topography = Physical features and their elevation. Topology = the spatial relationships between adjacent or neighboring features. Link-node topology A diagram of a constellation Description automatically generated - Refers to a network representation in which the relationships between features are defined by their connectivity. - This concept is often used in the context of transportation or utility networks, where links represent connections (like roads or pipelines) and nodes represent junctions or endpoints. **Key Features of Link Node Topology:** 1. **Links and Nodes**: - **Links**: These are the pathways or connections between nodes (e.g., roads, railways, or pipes). - **Nodes**: Points where links intersect or terminate, such as intersections or junctions. 2. **Directional Flow**: - In some cases, links may have directionality, indicating the flow of traffic, water, or other materials. 3. **Network Analysis**: - Link mode topology is essential for analyzing routes, accessibility, and network efficiency. It allows for understanding how different parts of a network interact. 4. **Spatial Relationships**: - This topology emphasizes how the physical layout and relationships of links influence overall network behavior. **Applications:** - **Transportation Planning**: Evaluating traffic flow, optimizing routes, and understanding congestion. - **Utility Management**: Analyzing the flow of water, electricity, or telecommunications through a network. - **Urban Planning**: Assessing connectivity and accessibility within urban environments.