Monthly Archives: October 2014

In-depth introduction to machine learning in 15 hours of expert videos

Chapter 1: Introduction (slidesplaylist)

Chapter 2: Statistical Learning (slidesplaylist)

Chapter 3: Linear Regression (slidesplaylist)

Chapter 4: Classification (slidesplaylist)

Read the rest of this entry

Convert rasters between Whitebox GAT and ArcGIS

Whitebox GAT is a powerful open-source GIS and remote sensing software package, which is developed by Dr. John Lindsay at University of Guelph. It provides many useful geoprocessing tools that ArcGIS does not have. Sometimes it is desirable to convert rasters between Whitebox GAT and ArcGIS, In particular, when you have to deal with hundreds of files, scripting is the way to go. See below for some scripting examples using Whitebox Scripter (Whitebox–>Tools–>Scripting) and  ArcPy (ArcMap–>Geoprocessing–>Python). You can customize the file path and make it your own.

Whitebox GAT can be freely downloaded at You can also check out the Whitebox blog for more information.

Happy Geoprocessing!

Import GeoTIFF (*.tif ) to Whitebox format (*.dep) using Whitebox Scripter

import os
import glob

path = r”C:\temp\*.tif”

fileNames = glob.glob(path)

inputFiles = “”

for fileName in fileNames:
inputFiles = inputFiles + “;” + fileName

inputFiles = inputFiles[1:]

#print inputFiles

args = [inputFiles]
pluginHost.runPlugin(“ImportGeoTiff”, args, False)

Export the Whitebox results (*.dep) to ArcGIS ASCII Grid format (*.txt) using Whitebox Scripter

import os
import glob

path = r”C:temp\*.dep”
fileNames = glob.glob(path)
inputFiles = “”
for fileName in fileNames:
inputFiles = inputFiles + “;” + fileName

inputFiles = inputFiles[1:]
#print inputFiles
args = [inputFiles]
pluginHost.runPlugin(“ExportArcAsciiGrid”, args, False)

Convert ArcGIS ASCII Grid format (*.txt) to GeoTIFF(*.tif) using ArcPy

import os
import glob

path = r”C:\temp\*.txt”
fileNames = glob.glob(path)
outPath = r”C:\output”

for file in fileNames:
outRaster = os.path.splitext(base)[0] + ‘.tif’
outFileName = os.path.join(outPath,outRaster)

Displaying LAS LiDAR point clouds in the Whitebox map area

Whitebox Geospatial Analysis Tools

I enjoy working with LiDAR data whenever I can because of its remarkable topographic detail and unique characteristics. More often then not, I work with LiDAR data interpolated onto a raster grid. Lately, however, I’ve been working with terrestrial laser scanner data and having a means of quickly visualizing the point data itself has become important to my workflows. Did you know that as of the latest release of Whitebox GAT (v. 3.2.1) you can now add LAS files, the commonly used standard format for storing LiDAR point clouds, into the map area?

Adding LAS layers to a map area Adding LAS layers to a map area

The LAS point cloud will be added to the Whitebox map area in the same way that you can overlay other vector or raster geospatial data. Here’s an example of a LAS dataset overlaid on top of a raster hillshade image.

Example LAS point cloud Example LAS point cloud (click to enlarge)

The display properties, including…

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NASA Soil Moisture Mapper Arrives at Launch Site | NASA

NASA Soil Moisture Mapper Arrives at Launch Site | NASA.

A NASA spacecraft designed to track Earth’s water in one of its most important, but least recognized forms — soil moisture — now is at Vandenberg Air Force Base, California, to begin final preparations for launch in January.

NASA's Soil Moisture Active Passive (SMAP) spacecraft is delivered by truck to the Astrotech payload processing facility at Vandenberg Air Force Base in California on Wednesday, Oct. 15, 2014.
NASA’s Soil Moisture Active Passive (SMAP) spacecraft is delivered by truck to the Astrotech payload processing facility at Vandenberg Air Force Base in California on Wednesday, Oct. 15, 2014.
Image Credit:

The Soil Moisture Active Passive (SMAP) spacecraft arrived Wednesday at its launch site on California’s central coast after traveling from NASA’s Jet Propulsion Laboratory (JPL) in Pasadena, California. The spacecraft will undergo final tests and then be integrated on top of a United Launch Alliance Delta II rocket in preparation for a planned Jan. 29 launch.

SMAP will provide the most accurate, highest-resolution global measurements of soil moisture ever obtained from space and will detect whether the ground is frozen or thawed. The data will be used to enhance scientists’ understanding of the processes that link Earth’s water, energy and carbon cycles.

Soil moisture is critical for plant growth and supplies aquifers, which are underground water supplies contained in layers of rock, sand or dirt. Through evaporation, water in the soil cools the land surface and lower atmosphere while seeding the upper atmosphere with moisture that forms clouds and rain. High-resolution global maps of soil moisture produced from SMAP will allow scientists to understand how regional water availability is changing and inform water resource management decisions.

“Water is vital for all life on Earth, and the water present in soil is a small but critically important part of Earth’s water cycle,” said Kent Kellogg, SMAP project manager at JPL. “The delivery of NASA’s SMAP spacecraft to Vandenberg Air Force Base marks a final step to bring these unique and valuable measurements to the global science community.”

SMAP data also will aid in predictions of plant growth and agricultural productivity, improve weather and climate forecasts, and enhance our ability to predict the extent and severity of droughts and where floods may occur. SMAP’s freeze/thaw data will also be used to detect changes in the length of the growing season, which is an indicator of how much carbon plants take up from the atmosphere each year.

Among the users of SMAP data will be hydrologists, weather forecasters, climate scientists, and agricultural and water resource managers. Additional users include fire hazard and flood disaster managers, disease control and prevention managers, emergency planners and policy makers.

To make its high-resolution, high-accuracy measurements, SMAP will combine data from two microwave instruments — a synthetic aperture radar and a radiometer — in a way that uses the best features of each. The instruments can peer through clouds and moderate vegetation cover day and night to measure water in the top 2 inches (5 centimeters) of the soil.

SMAP will fly in a 426-mile (685-kilometer) altitude, near-polar, sun-synchronous orbit that crosses the equator near 6 a.m. and 6 p.m. local time. SMAP is designed to operate for at least three years, producing a global map of soil moisture every two to three days.

SMAP is managed for NASA’s Science Mission Directorate in Washington by JPL with participation by NASA’s Goddard Space Flight Center, Greenbelt, Maryland. JPL is responsible for project management, system engineering, instrument management, the radar instrument, mission operations and the ground data system. Goddard is responsible for the radiometer instrument. Both centers collaborate on the science data processing and delivery of science data products to the Alaska Satellite Facility and the National Snow and Ice Data Center for public distribution and archiving. NASA’s Launch Services Program at NASA’s Kennedy Space Center in Florida is responsible for launch management. JPL is managed for NASA by the California Institute of Technology in Pasadena.

For more information about SMAP, visit:

SMAP is planned to be the final of five NASA Earth science missions launched into space in a 12-month period, the most new NASA Earth-observing mission launches in that timespan in more than a decade. NASA monitors Earth’s vital signs from land, air and space with a fleet of satellites and ambitious airborne and ground-based observation campaigns. NASA develops new ways to observe and study Earth’s interconnected natural systems with long-term data records and computer analysis tools to better see how our planet is changing. The agency shares this unique knowledge with the global community and works with institutions in the United States and around the world that contribute to understanding and protecting our home planet.

For more information about NASA’s Earth science activities, visit:


Steve Cole
Headquarters, Washington

Alan Buis
Jet Propulsion Laboratory, Pasadena, Calif.

1-m Resolution NAIP Image Layers updated with 2013 Imagery

NAIP Image Layers updated with 2013 Imagery

Earlier this year, Esri published a new set of image layers featuring recent 1m resolution, multispectral imagery for the continental United States made available by the USDA Farm Service Agency. The National Agriculture Imagery Program (NAIP) acquires aerial imagery during the agricultural growing seasons in the continental United States. The image layer published by Esri provides access to NAIP imagery for each state in 4-bands (RGB and Near Infrared) with the option to display the imagery as false color or to display the NDVI showing relative biomass of an area.

The image layers initially included NAIP 2010–2012 imagery to provide complete coverage for the continental United States. The image layers now are updated to also include the NAIP 2013 imagery that is available for 23 states (as shown below). In some cases, imagery for a state is available from multiple years and can be used for comparison purposes. You can discover and access these layers through the Living Atlas: Imagery collection as well as through the NAIP Imagery group.

NAIP 2013 Imagery Added for 23 States

NAIP 2013 Imagery Added for 23 States

The NAIP image layer is currently in Beta release. The NAIP image layer is available to users with an ArcGIS Organizational subscription at no additional cost. To access the NAIP imagery maps and layers, you’ll need to sign in with an account that is a member of an organizational subscription. If you don’t already have an organizational subscription, you can create a new account and then sign up for a 30 day trial of ArcGIS Online.

GIS tools for connectivity, corridor, or habitat modeling

GIS tools for connectivity, corridor, or habitat modeling

While CorridorDesigner provides one method of modeling wildlife corridors with ArcGIS, it’s not the only game in town. Here are some other free tools you may find handy for modeling wildlife or ecological corridors, connectivity, or habitat. For updates on connectivity and corridors in peer-reviewed literature and the news, make sure to check out Conservation Corridor.

Connectivity and corridor GIS tools


Linkage Mapper is a GIS tool designed to support regional wildlife habitat connectivity analyses. Linkage Mapper uses GIS maps of core habitat areas and resistances to identify and map linkages between core areas. Each cell in a resistance map is attributed with a value reflecting the energetic cost, difficulty, or mortality risk of moving across that cell. Resistance values are typically determined by cell characteristics, such as land cover or housing density, combined with species-specific landscape resistance models. As animals move away from specific core areas, cost-weighted distance analyses produce maps of total movement resistance accumulated.


Circuitscape is a stand-alone Python program which borrows algorithms from circuit theory to predict patterns of movement, gene flow, and genetic differentiation among populations in heterogeneous landscapes. It uses raster habitat maps as input, and predicts connectivity and movement patterns between user-defined points on the landscape. Circuitscape is distributed by Brad McRae of the National Center for Ecological Analysis and Synthesis (NCEAS) at University of California, Santa Barbara.


The Connectivity Analysis Toolkit provides conservation planners with newly-developed tools for both linkage mapping and landscape-level ‘centrality’ analysis. Centrality refers to a group of landscape metrics that rank the importance of sites as gatekeepers for flow across a landscape network. The Toolkit allows users to develop and compare three contrasting centrality metrics based on input data representing habitat suitability or permeability, in order to determine which areas, across the landscape as a whole, would be priorities for conservation measures that might facilitate connectivity and dispersal. The Toolkit also allows application of these approaches to the more common question of mapping the best habitat linkages between a source and a target patch.


Conefor Sensinode quantifies the importance of habitat areas for the maintenance or improvement of landscape connectivity. It is conceived as a tool for decision-making support in landscape planning and habitat conservation, through the identification and prioritization of critical sites for ecological connectivity.


Connect is a set of tools that helps researchers and conservation planners model landscape connectivity for multiple wildlife species in complex heterogeneous landscapes. Connect also allows users to combine single-species models of animal movement to identify areas of the landscape that facilitate the movement of multiple species. Connect packages Circuitscape, NetworkX, and Zonation into a user-friendly geoprocessing toolbox for ESRI ArcGIS 9.3.


UNICOR implements Dijkstra’s shortest path algorithm for any number of landscapes and distributions of species. The model’s features include a graphical user interface, parallel-processing, kernel path-buffering, connectivity maps, and various formatted outputs ready for graph and patch theory metrics.


FunConn is a functional connectivity modeling toolbox for ArcGIS, distributed by Dave Theobald and the Natural Resource Ecology Laboratory at Colorado State University. The goal of the functional connectivity model is to allow landscape connectivity to be examined from a functional perspective. Functional connectivity recognizes that individuals, species or processes respond functionally (or behaviorally) to the physical structure of the landscape. From this perspective, landscape connectivity is specific to a landscape and species/individual/process under investigation.


Path Matrix is a tool for ArcView 3 to compute matrices of effective geographic distances among samples, based on a least-cost path algorithm. It was developed by Nicholas Ray of the Computational and Molecular Population Genetics Lab, University of Bern, Switzerland.

Habitat suitability and species occurrence modeling GIS tools


openModeller aims to provide a flexible, user friendly, cross-platform environment where the entire process of conducting a fundamental niche modeling experiment can be carried out. The software includes facilities for reading species occurrence and environmental data, selection of environmental layers on which the model should be based, creating a fundamental niche model and projecting the model into an environmental scenario.


StatMod is an extension for ArcView 3.3 that helps users create logistic regression and CART models using the statistical packages SAS and S-PLUS. It is distributed by Chris Garard of Utah State University.


Maxent provides a maximum-entropy approach for species habitat modeling. The software takes as input a set of layers or environmental variables (such as elevation, precipitation, etc.), as well as a set of georeferenced occurrence locations, and produces a model of the range of the given species. It is distributed by Princeton University.


BioMapper is a stand-alone package for developing ecological niche and habitat suitability models using only a species presence data. It is distributed by Alexandre Hirzel of the Laboratory For Conservation Biology, University of Lausanne, Switzerland.


DesktopGarp is a software package for biodiversity and ecologic research that allows the user to predict and analyze species distributions using presence data. The package is distributed by the University of Kansas Natural History Museum.


Spatial Data Modeler is a collection of geoprocessing tools for adding categorical maps with interval, ordinal, or ratio scale maps to produce a predictive map of where something of interest is likely to occur. The tools include the data-driven methods of Weights of Evidence, Logistic Regression, and two supervised and one unsupervised neural network methods, and a knowledge-driven method Fuzzy Logic.


PatchMorph is an extension for ArcMap which delineates habitat patches from a habitat suitability or land cover map.

Reserve and protected area GIS tools


Marxan delivers decision support for reserve system design. Marxan finds reasonably efficient solutions to the problem of selecting a system of spatially cohesive sites that meet a suite of biodiversity targets.


Zonation identifies areas important for retaining habitat quality and connectivity for multiple species, indirectly aiming at species’ long-term persistence. The computational strategy of Zonation can be characterized as maximal retention of weighted, range size normalized (rarity corrected) richness. Zonation produces a complementarity-based priority ranking.


PANDA is a stand-alone application developed to provide a user friendly framework for systematic protected areas network design to ArcGIS users. Through the use of P.A.N.D.A. the designer can explore different hypothetical configurations of a system of protected areas in the planning area.


CLUZ is an ArcView GIS interface that allows users to design protected area networks and conservation landscapes. It can be used for on-screen planning and also acts as a link for the MARXAN conservation planning software. It is currently being developed at DICE and is funded by the British Government through their Darwin Initiative for the Survival of Species.


LINK is a set of ArcGIS tools designed to analyze habitat patterns across a landscape. LINK uses species habitat matrices to model potential species habitat and habitat diversity. What sets LINK apart from its predecessors is that it uses raster data sources—raster data sources allow LINK to model habitat over a much larger area than its vector based ancestors.

General GIS tools


Jenness Enterprises has created many extensions for ArcView 3.3 useful to ecological applications. Jeff Jenness created the CorridorDesigner ArcMap extension.


Hawth’s Analysis Tools is an extension for ArcGIS (specifically ArcMap). It is designed to perform spatial analysis and functions that cannot be conveniently accomplished with out-of-the-box ArcGIS. Most of these analysis tools have been written within the context of ecological applications such as movement analysis, resource selection, predator prey interactions and trophic cascades.

The Nile River Basin from SRTM data

Well done, Whitebox!

Whitebox Geospatial Analysis Tools

Someone asked the other day whether the cross-platform, free and open-source GIS Whitebox GAT can handle watershed delineation from massive, regional-scale DEMs. They had a particular interest in the Nile River basin. Heck, if you’re going to go big, why not go huge, right? So I decided to give it a go. First off, I used the Retrieve SRTM Data tool to download the approximately 800 SRTM 3-arcsecond (approximately 90 m) tiles that make up the Nile River basin. This required a bit of experimentation because my first attempt at doing so hit the boundary of the basin and I had to give it a second try. The tool downloaded each of the tiles and mosaicked them into a single large DEM. The final DEM was 45,601 rows by 25,201 columns (a little over 1.1 billion grid cells) and was 4.28 GB in size. I then used the new Breach…

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ESA released a new generation of satellite-derived global land cover products

First official release of a new generation of satellite-derived global land cover products

 The CCI Land Cover (LC) team is proud to announce the release of its 5 key products to its climate and LC communities:
  1. the full archive (2003-2012) of MERIS Full Resolution time series pre-processed in 7-day composites,
  2. three global LC maps representative for the 1998-2002, 2003-2007 and 2008-2012 epochs,
  3. three global land cover seasonality products describing the vegetation greenness, the snow and the burned areas occurrence dynamics,
  4. a global map of open and permanent water bodies at 300m spatial resolution,
  5. a user tool for sub-setting, re-projecting and re-sampling the products.

All products can be freely visualized and accessed online at

Additional information can also be found in the last edition of the project newsletter.

Windows 10 Technical Preview Available for Download

Follow these steps to download Technical Preview:

  1. Sign up for the Windows Insider Program.

  2. Read the system requirements.

  3. Click one of the Download links on this page to download a special file—it’s called an ISO file—that you can use to install the preview.

  4. When the download is complete, transfer the ISO file to installation media such as a DVD or USB flash drive.

  5. Double-tap or double-click setup.exe from the installation media, and then follow the steps.

Alex Tereshenkov

Programming and managing GIS

REDD+ for the Guiana Shield

Technical Cooperation Project

Dr. Qiusheng Wu @ University of Tennessee

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How to write papers that get cited and proposals that get funded

GIS In Ecology

Providing Training, Advice And Consultation On The Use Of GIS In Ecology


On cities, land, ...

Scientia Plus Conscientia

Thoughts on Science and Nature


Learning hydrology with R

Karl Hennermann

GIS at the University of Manchester

GIS and Science

Applications of geospatial technology for scientific research and understanding.

Whitebox Geospatial Analysis Tools

Open-source GIS development and spatial analysis with Whitebox GAT


MATLAB-based software for topographic analysis

Anything Geospatial

Dr. Qiusheng Wu @ University of Tennessee

Dr. Qiusheng Wu @ University of Tennessee

Another GIS Blog

Dr. Qiusheng Wu @ University of Tennessee

ArcPy Café

Get all your ArcGIS Python Recipes here!