Design methodology for a raster database
Designing and implementing a GIS using raster data is no different than it would be for any other GIS. The only difference is that you use raster data instead of, or in addition to, vector feature data.
When working with raster data, your workflow could be the following:
Identify purpose or objective
You can use raster data in either one or both of the following ways: for display purposes, and for analysis analysis purposes. Raster data for display is quite common, especially using orthophotos as a background for a map. Raster data for analysis can be implemented in many ways, such as: a watershed analysis or terrain analysis, updating some topographic features in other datasets, or updating land-cover classes to assess the location of a new housing development.
Identify the data
If you’re looking to extract information from imagery, consider the resolution you require and whether you need one or more spectral bands. You might consider whether the data comes from an aircraft or satellite. If you’re going to work with elevation data, you might consider the most appropriate methods for collection, such as lidar , contour lines, or radar interferometry. If you intend to create a collection of scanned maps, you need to identify what those maps are, such as scanned documents, CAD drawings, or topographic maps.
Refine the requirements
Determine more detailed requirements based on the following:
- Cost—What are your budget limits? Can you afford the data you want? Is there an alternative within your budget?
- Availability—Does the data already exist? How often is the data updated? Will you receive updates as individual tiles or a single update with complete coverage? Can you receive this data in a timely manner?
- Licenses—Can you share or distribute this data? Can you use this data in multiple projects? What can you do with the information or data derived from the original data? Can you serve this to the public using the Internet?
- Resolution—Will the available level of detail provide the required information?
- Storage—What database or file formats will be used? How large is each file? Will you use pyramids? How much total disk space is needed?
- Extent—Can you cover the area of interest with one raster image or will you need multiple raster datasets?
- Accuracy—Will the available data resolution provide you with the required spatial accuracy? What is the level of accuracy promoted by the data vendor? How will the data be verified and validated?
- Accessibility and pricing—Is the data accessible or will it be accessible on a network? Will you charge fees for usage or downloads? Who will have access to the data? How will you control access and sales?
Acquire and review data
This can involve placing orders for the data with a company capable of providing it, scanning the maps you need, or acquiring the source data and building the corresponding raster datasets. It is important that you have a system for checking the quality of the data, whether created in-house or acquired from outside sources. You might have to check for missing data (such as dropped lines or pixels), for poorly represented data, or whether the data is georeferenced for your area of interest.
Prepare the data
Building the database could require the prior extraction or conversion from one data format to another, such as from lidar elevation points to a DEM. It could also involve some preprocessing, such as georeferencing or rubber sheeting.
Design and build the database
This could involve one of several choices:
- Building a large, seamless raster dataset (mosaic) from multiple images
- Building a separate, distinct raster dataset from each source image (Essentially, each dataset would be accessed independently of the others.)
- Building a raster catalog containing all the imagery
- Building a mosaic dataset that contains links to the separately stored image files
- Retaining the data in separate image files
Additional considerations include which compression method to use, whether to use a personal geodatabase or a multiuser geodatabase management system, and what your data dissemination will include. For example, if you will be serving your imagery, you might consider a mosaic dataset since it is optimized for this type of dissemination.
You will need to create some level of metadata, depending on your intended distribution and access to the data. For example, what kinds of queries should users expect to perform to find your raster data over the web? If using raster catalogs or mosaic datasets, you might consider additional catalog fields to allow more extensive querying capabilities.
Deploy and maintain the geodatabase
One of the main reasons for going through this entire loading process is to enable many people to use the data for various purposes and projects. This requires administration and management.
In most situations, you will plan on reusing your dataset or database. You will need to plan for updates, modifications, and the ability to build on your initial implementation.
Database fragmentation and frequent data manipulation may increase the size of your mosaic dataset dramatically. If your database size is inflated due to constant transactions, you should run the Compact tool.