Here is an in-depth English summary of the presentation *“Overview: Geographic
Information Systems (GIS) and Remote Sensing”* by Thomas Bauer and Franz Suppan
from the University of Natural Resources and Life Sciences Vienna. 

This is Part 1.1 of the Geodata Management Course.

### **Course Objectives and Learning Outcomes**

The aim of the course is to impart foundational knowledge in the areas of
Geographic Information Systems (GIS) and Remote Sensing. Students will:

-   Learn about the acquisition, storage, and processing of geospatial data.

-   Understand the potentials of geodata.

-   Be able to independently conduct small GIS-related projects.

### **Key Concepts and Definitions**

#### **Geoinformatics Relevance**

-   Around 90% of everyday decisions rely on spatial information.

-   80–90% of all information has a spatial reference and can thus be considered
    geodata.

#### **Geodata and Related Scientific Fields**

Geoinformatics intersects with:

-   Remote sensing (data acquisition without physical contact),

-   Photogrammetry,

-   Cartography,

-   Surveying,

-   GIS (data analysis and visualization systems).

### **Geographic Information Systems (GIS)**

#### **Definition**

GIS involves the **acquisition**, **storage**, **processing**, **analysis**, and
**representation** of geodata.

#### **Information System Structure**

-   Composed of a database, data, and software tools for data processing.

#### **Data Analysis in GIS**

GIS allows spatial queries and overlays, enabling complex queries like:

-   "Show all districts in Vienna with \>10,000 population."

-   "Display forests \>10 years old with slopes between 15–25°."

#### **Data Structure in GIS**

Each spatial element includes:

-   **Geometry**: The shape and location (points, lines, polygons).

-   **Attributes**: Descriptive data (e.g., age of a tree).

-   **Topology**: Spatial relationships like containment or adjacency.

### **Models of Spatial Data**

#### **Vector Model**

-   Represents data as points, lines, or polygons.

-   Suitable for logical structure and object references.

-   Smaller data volume, longer acquisition time.

#### **Raster Model**

-   Data is structured in pixels (grids).

-   Simplifies data collection and processing.

-   Suitable for continuous data (e.g., satellite imagery).

-   Demands high computing power and large storage.

#### **Hybrid GIS**

-   Combines vector and raster data models for comprehensive analysis.

### **Geodata Types**

#### **By Content**

-   Physical (e.g., soil),

-   Ecological (e.g., air quality),

-   Legal (e.g., property),

-   Economic (e.g., land value),

-   Demographic (e.g., population).

#### **By Occurrence**

-   **Discrete**: Values at specific points (e.g., measurement stations).

-   **Continuous**: Values interpolated across areas (e.g., temperature maps).

-   **Statistical**: Values represent defined zones (e.g., census blocks).

### **Sources of Geodata**

#### **Primary Sources**

-   Field surveys

-   GNSS

-   Remote sensing

-   Manual digitization

#### **Secondary Sources**

-   Public institutions (e.g., INSPIRE, open government data portals)

-   Private companies (e.g., Google Maps, OpenStreetMap)

### **Geodata Quality**

Quality depends on:

-   **Fitness for use**

-   Criteria: Accuracy, completeness, resolution, timeliness, metadata
    availability, legal use rights.

### **Spatial Resolution and Precision**

-   **Raster**: Determined by pixel size.

-   **Vector**: Depends on object detail and discretization.

-   **Precision**: Depends on measurement and identification accuracy.

### **Metadata**

-   Metadata describes geodata, including its origin, quality, and spatial
    reference system.

-   Standards such as ISO 19115 (in Austria: ÖNORM A 2270) define metadata
    structures.

### **Legal and Cost Aspects**

#### **Legal Framework**

Covers public procurement, data protection, copyright, and licensing. Example:
AMA data licensed under CC-BY-AT 3.0.

#### **Costs**

-   Vary based on data source and resolution.

-   Open data: Mostly free (e.g., Sentinel, Landsat).

-   Commercial data: Priced based on use and resolution (e.g., infrared
    orthophotos, LiDAR).

### **Final Notes**

The course is provided by the Institute of Geomatics at BOKU, emphasizing
practical knowledge of geodata, spatial thinking, and legal/technical frameworks
for managing and using spatial information systems.

Let me know if you'd like this as a Word document or summarized even further for
presentation or exam prep.
