A comparison of algorithms used to compute hill slope as a property of the DEM

The calculation of hill slope in the form of downhill gradient and aspect for a point in a digital elevation model (DEM), is a popular procedure in the hydrological, environmental and remote sensing. The most commonly used slope calculation algorithms employed on DEM topography data make use of a three by three search window, or kernel, centred on the grid point (grid cell) in question in order to calculate the gradient and aspect at that point. A comparison of eight frequently used slope calculation algorithms for digital elevation matrices has been carried out using both synthetic and real data as test surfaces. Morrison's surface III, a trigonometrically defined surface, was used as the synthetic test surface. This was differentiated analytically to give true gradient and aspect values against which to compare the results of the tested algorithms. The results of the best-performing slope algorithm on Morrison's surface were then used as the reference against which to compare the other tested algorithms on a real DEM. For both of the test surfaces residual gradient and aspect grids were calculated by subtracting the gradient and aspect grids produced by the algorithms on test from the true/reference gradient and aspect grids. The resulting residual gradient and aspect grids were used to calculate root-mean-square (RMS) residual error estimates that were used to rank the slope algorithms from “best” (lowest value of RMS residual error) to “worst” (largest value of RMS residual error). For Morrison's test surface, Fleming and Hoffer's method gave the “best” results for both gradient and aspect. Horn's method (used in ArcInfo GRID) also performed well for both gradient and aspect estimation. However, the popular maximum downward gradient method (MDG) performed poorly, coming last in the rankings. A similar pattern was seen in the gradient and aspect rankings derived using the Rhum DEM, with Horn's method performing well and the MDG method poorly.

A comparison of algorithms used to compute hill slope as a property of the DEM

Earth Point Tools for Google Earth

This is a very handy site for doing all sorts of things including conversions between many different coordinate systems.



Tools For Google Earth

Convert Coordinates

Lots of things are free but they do have some paid services as well.

It is pretty cheap to subscribe but free for some:

• Education/Humanitarian - No charge for students, teachers, or non-governmental charitable relief organizations. Approvals on a case-by-case basis.
• Governmental organizations in developed countries, except for schools and universities, are asked to get a paid subscription. If you have budgeting issues, I can approve a free trial subscription to get you through the current fiscal year.

GDAL - Geospatial Data Abstraction Library

GDAL - Geospatial Data Abstraction Library is a translator library for raster and vector geospatial data formats that is released under an X/MIT style Open Source license by the Open Source Geospatial Foundation. As a library, it presents a single raster abstract data model and vector abstract data model to the calling application for all supported formats. It also comes with a variety of useful command line utilities for data translation and processing.

GDAL: GDAL - Geospatial Data Abstraction Library

Nullege GDAL - Geospatial Data Abstraction Library Examples

GDAL - Geospatial Data Abstraction Library is a translator library for raster and vector geospatial data formats that is released under an X/MIT style Open Source license by the Open Source Geospatial Foundation. As a library, it presents a single raster abstract data model and vector abstract data model to the calling application for all supported formats. It also comes with a variety of useful commandline utilities for data translation and processing.

Nullege has some good examples of how to use GDAL in python.

gdal - Nullege Python Samples

DotSpatial geographic information system library written for .NET 4

DotSpatial is a geographic information system library written for .NET 4. It allows developers to incorporate spatial data, analysis and mapping functionality into their applications or to contribute GIS extensions to the community. DotSpatial provides a map control for .NET and several GIS capabilities including:

• Display a map in a .NET Windows Forms or Web application.
• Open shapefiles, grids, rasters and images.
• Render symbology and labels
• Reproject on the fly
• Manipulate and display attribute data
• Scientific analysis
• Read GPS data

DotSpatial - Home

Geographic Information Systems Stack Exchange

Geographic Information Systems Stack Exchange is a question and answer site for cartographers, geographers and GIS professionals. It's 100% free, no registration required.

Geographic Information Systems Stack Exchange

GeoExamples

This is a blog with some good example code and tips for doing geospatial, especially with python.


GeoExamples

pyshp

The Python Shapefile Library (pyshp) provides read and write support for the Esri Shapefile format. The Shapefile format is a popular Geographic Information System vector data format created by Esri.

GeospatialPython/pyshp · GitHub

InvisibleRoads.com

This is a somewhat strange collection of life advice, dance advice, tutorials on building geospatial web applications and using neural networks to classify satellite images and a few other geeky things.

Tutorials — invisibleroads-tutorials 1.2 documentation

Geospatial Python

This is a blog by a guy who is the CIO and "head python geek" at NVisionSolutions.com at Stennis Space Center.  He has a bunch of very useful posts on using python for geospatial tasks.

GeospatialPython.com