Preparing input data

This section will discuss best practices and specifications for preparing your data when using the Managing Preprocessed Orthophotos workflow.

Imagery requirements

What imagery specifications are required for this workflow?

The Managing Preprocessed Orthophotos workflow is intended to work with specific types of data. The basic data requirements are listed in the table below.

Parameter	Requirement
Orthorectification?	Required
Acceptable file types	Multiple files (usually edge-match tiles) Single compressed file (large area mosaics)
Source	Typically an aerial camera system, though possibly a satellite sensor
Bit depth	Typically 8 bits per pixel per color, though possibly 16 bits
Color correction?	Typically yes, though not always
Acceptable band configurations	Single-band (panchromatic) Three-band (true-color RGB or false-color infrared) Four-band (RGB plus near-infrared)

Typical imagery types

How is my imagery likely to be formatted?

There are three common orthophoto formats you are likely to encounter. Specifications for each of these three types are listed here, which will help you set parameters correctly when using the workflow tools.

1. Tiled orthophotos

   The most common orthophoto format, these images are usually created by a data provider from a collection of images that are (1) orthorectified, (2) processed into a seamless mosaic, then (3) exported as image tiles.

   Parameter	Description
   Orthorectification?	Yes
   Acceptable file types	Multiple files. Tiles are usually edge-matched, though they may overlap in some cases.
   Image boundary / NoData	Regions of NoData are not present, with a few possible exceptions in a small number of tiles around the project boundary.
   Bit depth	Typically 8 bits per pixel per color, though possibly 16 bits
   Color correction?	Typically yes
   Acceptable band configurations	Usually three-band (true-color RGB or false-color infrared), though sometimes four-band (RGB plus near-infrared)

   See examples of tiled orthophotos depicting a contiguous project and a linear corridor, below.

   

   The first image is courtesy of USDA APFO (NAIP). The second image is courtesy of Montana State Library.

2. Multi-image mosaics

   These images are usually created by a data provider from a collection of images that are (1) orthorectified, (2) processed into a seamless mosaic, then (3) compressed and distributed as one file.

   Parameter	Description
   Orthorectification?	Yes
   Acceptable file types	A single file, typically compressed.
   Image boundary / NoData	Typically irregular boundaries surrounded by large areas of NoData. Due to compression, NoData values may be changed from zero to values near zero.
   Bit depth	Typically 8 bits per pixel per color, though possibly 16 bits
   Color correction?	Typically yes
   Acceptable band configurations	Typically three-band (true-color RGB or false-color infrared) or four-band (RGB plus near-infrared)

   Note:

   Setting the Footprint parameter in the Create Source Mosaics dialog box to "Remove black edges around imagery" will remove the NoData areas.

   Below, check out tiled orthophotos depicting a the black NoData around the edges of orthophotos (left) and the same mult-image mosaic with the NoData removed (right).

   

3. Individual orthorectified image frames

   This is the least common type of orthophoto format. In this case, images are (1) individually orthorectified, then (2) output as individual, orthorectified files.

   Parameter	Description
   Orthorectification?	Yes
   Acceptable file types	Multiple files depicting individual orthophotos.
   Image boundary / NoData	Usually uncropped, with NoData regions around the edge of each image.
   Bit depth	Typically 8 bits per pixel per color, though possibly 16 bits
   Color correction?	Possibly not color corrected
   Acceptable band configurations	Typically three-band (true-color RGB or false-color infrared) or four-band (RGB plus near-infrared)

   Below, find individual orthophotos, with black areas of NoData around the edge of each image.

   Setting the Footprint parameter in the Create Source Mosaics dialog box to "Remove black edges around imagery" will remove the NoData areas.

   

Data structure recommendations

How should I structure my directories?

• Store each collection of image files in a separate directory.
• Define a folder hierarchy that makes sense for the data, and plan ahead to provide sufficient granularity later.
  • For example: directories might be separated by year, with subdirectories for multiple dates in the same year. Alternately, for very large datasets, directories might also be organized by geographic region.
• To maximize performance, try to keep the number of files per directory under 1,000.

How should I manage my files?

• File names are generally defined by the data provider; keep the original names, if possible.
• Store metadata that comes with your imagery in the same location as the imagery files.
• Store main imagery files as read-only when possible. This helps ensure that the original files are not modified and that they are backed up multiple times.
• Don't set the directory in which the files are stored as read-only. Many of the workflows result in additional pyramid, statistics, or metadata files being written along with the source files. If the directories are read-only during the authoring processes, these files will be stored in separate locations disconnected from the originals.

How should I organize my mosaic datasets?

• Store mosaic datasets in a file geodatabase (most cases) or enterprise geodatabase (when multiple users need to edit the mosaic dataset at the same time).
• Typically, use one geodatabase for each mosaic dataset or for a small group of related mosaic datasets that define a project. This makes backup and restoring simpler.
• Use a standardized naming convention. Imagery Workflows use the following prefixes:
  • S_xxx-Source mosaic dataset
  • D_xxx-Derived mosaic dataset
  • R_xxx-Referenced mosaic dataset

Preparing metadata

How should I organize the metadata that came with my imagery?

Key metadata will be recorded in the attribute table of each mosaic dataset you create to support queries, sorting, and general data management.

• If metadata is readable by ArcGIS, view it in the mosaic dataset's properties.
• If metadata is not readable by ArcGIS, store it in a network-accessible location and record hyperlinks to that location in the mosaic dataset's attribute table.

Preprocessing

Do I need to create pyramids or generate statistics?

Yes, if pyramids are not provided with the original data (or the data is reformatted), pyramids should be created. (Multi-image mosaics typically have built-in pyramids, so you won't need to create them.)

Find more information about building pyramids and calculating statistics here.

In the majority of cases, pyramids can be compressed even if the original data sources contain no compressed data, since analysis is typically not performed on the pyramids themselves. For a table of pyramid sizes, see Raster pyramids.

When creating pyramids, there are environmental variables that control how they are generated. These include the following:

Variable	Description
Pyramid/Compression	In most cases you should compress the overviews. For natural color 3-band imagery, use JPEG YCBCR compression. For panchromatic or other imagery, use JPEG compression. Typically, the compression factor for JPEG can be set to 80.
Sampling method	For optical imagery, use bilinear sampling, since this generally provides better-quality imagery when viewed at smaller scales.

Check out the next section to learn more about best practices for creating mosaic datasets in the Managing Preprocessed Orthophotos workflow.