Available with Image Analyst license.
The ArcPy Image Analysis module provides a set of image analysis and modeling geoprocessing functions for both raster (cell-based) and feature (vector) data.
The capabilities of the ArcPy Image Analysis module are grouped into categories of related functionality. Knowing the categories will help you identify which geoprocessing function to use. The table at the end of this section lists all the available analytical categories with a description of the capabilities offered by the geoprocessing functions in each.
For most geoprocessing functions that generate a raster output, the output is a temporary raster object on disk. To make it permanent, you can call the raster object's save method. Based on the workspace and the extension specified, the output format will vary; see Output raster formats and names for more information.
The geoprocessing functions in the ArcPy Image Analysis module require the ArcGIS Image Analyst extension.
Image Analysis geoprocessing functions
The functional categories of the ArcPy Image Analysis module are described below.
|Geoprocessing functional category||Description|
The Change Detection geoprocessing function category contains a function for extracting change information from multiple rasters over time. Additional capabilities for detecting change across a time series of images are available in the Multidimensional Analysis geoprocessing functions.
The Deep Learning geoprocessing functions allow you to train a deep learning model, detect specific features in an image, classify pixels in a raster dataset.
The Extraction geoprocessing functions allow you to extract a subset of pixels from a raster by the pixels' attributes or their spatial location.
Map Algebra is a way to perform spatial analysis by creating expressions in an algebraic language. With the Raster Calculator geoprocessing function, you can create and run Map Algebra expressions that output a raster dataset.
The general Math geoprocessing functions apply a mathematical function to the input. These geoprocessing functions fall into several categories. The arithmetic geoprocessing functions perform basic mathematical operations, such as addition and multiplication. There are geoprocessing functions that perform various types of exponentiation operations, which includes exponentials and logarithms in addition to the basic power operations. The remaining geoprocessing functions are used either for sign conversion or for conversion between integer and floating point data types.
The Conditional geoprocessing functions allow you to control the output values based on the conditions placed on the input values. The conditions that can be applied are of two types, those being either queries on the attributes or a condition based on the position of the conditional statement in a list.
The Logical Math geoprocessing functions evaluate the values of the inputs and determine the output values based on Boolean logic. The geoprocessing functions are grouped into four main categories: Boolean, Combinatorial, Logical, and Relational.
The Trigonometric Math geoprocessing functions perform various trigonometric calculations on the values in an input raster.
The Motion Imagery geoprocessing functions can be used for managing, processing, and analyzing motion imagery, including full-motion video data.
The Multidimensional Analysis geoprocessing functions allow you to perform various multidimensional analyses on scientific raster data across multiple variables and dimensions.
The Overlay geoprocessing functions can be used to weight and overlay several rasters to create a single summary raster.
The geoprocessing functions in the Segmentation and Classification category can be used to perform classification workflows, including accuracy assessment. Capabilities include multispectral image segmentation, training sample generation and evaluation, pixel and object-oriented machine learning classification, and quantitative accuracy assessment of results.
The Statistical geoprocessing functions perform statistical operations on raster data.