Image Analysis Techniques
Introduction
Before beginning any geospatial analysis and remotes sensing project you need to plan, obtain and process data. Not all project have the same the data or processing requirements.
Select and Acquire Data
The first step in starting a project is to research, select and obtain data. You need to consider the scope of the project, resolution needs and financial constraints. You will also need to research and find what data is available. You will also want to consider what other types of data, including vector data and and tabular data.
Process Data
This is one of the most important steps in the geospatial analysis process. As we learned in previous modules pre-processing is an integral part of analysis. Pre-processing improves the quality and accuracy of the data. This step is also very important when analyzing changes over time. The most common pre-processing techniques needed are georeferencing, radiometric calibration and atmospheric correction. After pre-processing, various image enhancement techniques, including contrast stretches and pansharpening may be applied.
Mosaic and/or Subset Data
Before beginning the analysis it is important to create a seamless, focused dataset. To achieve this you may need to mosaic multiple data sets and subset the data. Raster files can be large and processing can be time consuming. Therefore to save time and disk space subsetting data is an important step.
Analyze Data
There are many different analysis techniques and it is important to select an appropriate technique. Some of the interpretation and analysis techniques we will cover are:
- Digitizing and Measurements
- Sampling Techniques
- Spatial Analysis Techniques
- Spatial Statistics
- Image Classification