Creating Raster dataset - MapInfo_Pro_Advanced - 2023

MapInfo Pro Advanced Help

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MapInfo
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MapInfo > MapInfo Pro
Version
2023
Language
English
Product name
MapInfo Pro Advanced
Title
MapInfo Pro Advanced Help
First publish date
2016
Last updated
2023-09-20
Published on
2023-09-20T15:00:50.875000

MapInfo Pro Advanced supports a wide variety of interpolation methods that allow you to create continuous raster surfaces from point, line and polygon data. There are various interpolation algorithms available which provide different approaches for converting your point data into a raster. For best result you should choose an interpolation method which is appropriate for the type of input data you have and the type of raster surface you need, to perform your analysis.

MapInfo Pro Advanced supports the following input file formats for creating a raster surface:

  • TAB - MapInfo TAB Files (*.tab)
  • LAS - LIDAR ASPERS LAS Files (*.las) - The LIDAR point cloud data.
  • LAZ - The compressed version of LAS files (*.laz)
  • ASCII
  • ZIP Files (*.zip, *.7z)
Note: All interpolation methods that use the LAS/LAZ files as input are now able to read projection information if available in the selected LAS/LAZ files and select it in the projection dialogue automatically.

Limitation: CRS, if stored as a WKT string inside LAS/LAZ file (Most common for LAS/LAZ files on version 1.4 specification), cannot be read.

Interpolation Method

MapInfo Pro Advanced supports several methods to create Heatmap and surface raster from point data. These methods have been grouped into logical categories. There are categories for Heatmap, Assignment, and Interpolation. Each category has multiple options under them. When you select any method from a category, the dialog box title displays the category name instead of selected method name.

Click the links below to know more about the supported methods and their properties.

Heatmap

Heatmap supports the following methods. Heatmap supports an MRR output only.

  1. Estimate
  2. Weighted Estimate
  3. Sample Count
  4. Sample Density
  5. Advanced

Assignment

  1. Stamp
  2. Nearest Neighbor
  3. Distance

Interpolation

  1. Triangulation
  2. Natural Neighbor
  3. Inverse Distance Weighting
  4. Minimum Curvature

LiDAR

  1. Surface Analysis
  2. Tree Canopy Analysis