Image Analysis with ArcGIS

Strictly by pre-registration only

What is this course about?

This course covers dynamic raster processing options available in ArcGIS and takes you on an in-depth exploration of image classification. Learn best practices and workflows to enhance visualisation and extract meaningful information from satellite imagery, LiDAR, and other remotely sensed data. This course covers dynamic raster processing options available in ArcGIS and takes you on an in-depth exploration of image classification. You will use three classification methods to categorise land cover features and learn how to determine which method is appropriate for a given project and dataset.

This course is designed for GIS professionals, image analysts, and others who work with imagery for mapping and analysis. Those working in the forestry, hydrology, environmental management, urban planning, defence, intelligence, and mining industries may find the course of particular benefit.

Course details

Price

9,300,000.00 IDR

Location

Jakarta

Duration

2 days

Level

Intermediate

Category

Visualisation, Editing and Analysis Course

Are there any prerequisites?

Completion of ArcGIS 2: Essential Workflows or equivalent knowledge is required

What skills will I learn?

  • Apply dynamic raster processing functions to enhance raster display, prepare data for analysis, and quickly create multiple products from a single data source
  • Create a time-series mosaic dataset to visually identify and document areas of change
  • Support change detection, risk assessment, and other types of analysis by performing unsupervised, supervised, and object-oriented classification
  • Assess the accuracy of classification results

What can I expect?

  • Course topics

    Raster function chains and templates

    • Applying raster functions
    • Image Analysis window basics
    • Using a LAS database in a mosaic dataset

    Visually analysing change over time

    • Determining areas of change
    • Sources of raster data
    • Improving the display of raster data

    Introduction to image classification

    • Exploring remotely sensed change
    • Image classification history
    • Types of image classification
    • Classification outputs

    Change detection through unsupervised classification

    • Unsupervised classification review
    • Characteristics of coarse-resolution data
    • Landsat bands exploring
    • Landsat data

    Supervised classification of developed areas

    • Supervised classification review
    • Creating a spectrally pure training sample

    Accuracy assessment of classified results

    • Using accuracy assessments
    • Components of an accuracy assessment

    Impervious surface analysis with object-oriented classification

    • Image segmentation
    • Segmentation configuration
    • Object-oriented training samples