Monthly Archives: November 2014

Deriving temperature from Landsat 8 thermal bands TIRS

Another tutorial for deriving brightness temperature from Landsat 8 using ArcGIS

Deriving temperature from Landsat 8 thermal bands TIRS.

You can use the thermal bands from Landsat 8 to calculate at-satellite brightness temperature. There are quite a few steps that I’ll walk you th­­rough to do this. What we’re going to do is:

–        Convert the raw bands into Top of Atmosphere Radiance (TOAr).

–        Convert TOAr into degrees kelvin.

–        Convert degrees kelvin into degrees Fahrenheit.

–        Save and export this workflow as a template that you can apply it to any other image.

Step 1 – The mise en place of GIS

A – Luck is where preparation meets opportunity

This is a fairly lengthy blog, so I’d recommend topping off that cup of coffee or perhaps stretching the legs before getting started.

B – Raster Function Template Editor

Open the Raster Function Template Editor from the toolbar. Right click on the raster and insert a Composite Band Function. Click on the plus sign and select Add copy of selected input. You have to do this because there are two thermal bands for Landsat 8. If you’re working with Landsat 5 or 7, you can omit this step.

[If you don’t have the Raster Function Template Editor loaded, you can add it through the customize window, and it will be under the Commands tab, in the raster section. Drag and drop it into the toolbar.]

raster function editor interface

C – Preview of the final output

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Working with Landsat 8, a tutorial. 3. conversion to radiance and brightness temperature at top-of-atmosphere

Useful tutorial for deriving brightness temperature from Landsat 8!

Scientia Plus Conscientia

In this third post of the Landsat 8 series we will implement, step by step, the procedures explained in the Landsat web site for converting the digital numbers in the satellite images to geophysical measurements of spectral radiance, as measured at the sensor and without atmospheric correction, called ‘top-of-atmosphere’ or simply TOA.

The images that we download as TIF files are coded into 16-bit unsigned integer images. These are referred to as digital numbers. For some simple purposes, as for example, measuring the extent of features identifiable by eye, these digital numbers are perfectly sufficient. However, when we need to assess the geophysical properties of the terrain or make studies of land cover change over time, we might find convenient to convert these raw digital numbers to their original values of radiance, mostly to be able to compute reflectance, and compare surfaces on a solid geophysical basis.

Converting to radiance…

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New peer-reviewed article on vernal pool detection

An Effective Method for Detecting Potential Woodland Vernal Pools Using High-Resolution LiDAR Data and Aerial Imagery

Qiusheng Wu 1,3,* , Charles Lane 2 and Hongxing Liu 3

Abstract: Effective conservation of woodland vernal pools—important components of regional amphibian diversity and ecosystem services—depends on locating and mapping these pools accurately. Current methods for identifying potential vernal pools are primarily based on visual interpretation and digitization of aerial photographs, with variable accuracy and low repeatability. In this paper, we present an effective and efficient method for detecting and mapping potential vernal pools using stochastic depression analysis with additional geospatial analysis. Our method was designed to take advantage of high-resolution light detection and ranging (LiDAR) data, which are becoming increasingly available, though not yet frequently employed in vernal pool studies. We successfully detected more than 2000 potential vernal pools in a ~150 km2 study area in eastern Massachusetts. The accuracy assessment in our study indicated that the commission rates ranged from 2.5% to 6.0%, while the proxy omission rate was 8.2%, rates that are much lower than reported errors of previous vernal pool studies conducted in the northeastern United States. One significant advantage of our semi-automated approach for vernal pool identification is that it may reduce inconsistencies and alleviate repeatability concerns associated with manual photointerpretation methods. Another strength of our strategy is that, in addition to detecting the point-based vernal pool locations for the inventory, the boundaries of vernal pools can be extracted as polygon features to characterize their geometric properties, which are not available in the current statewide vernal pool databases in Massachusetts.

Working with Landsat 8, a tutorial. 2. creating simple composites

Nice tutorial for dealing with Landsat 8 imagery using scripting

Scientia Plus Conscientia

In this second post of the Landsat 8 series, we have a look at how to create simple color composites with uncorrected data, a common and useful task that is often misunderstood by beginners. For this purpose, it is necessary to understand two concepts: how digital sensors register information and how color images are constructed.

The first key concept is that sensors on board satellites or air planes perform radiometric measurements in specific ranges of wavelength of the electromagnetic spectrum. Sensor elements capture a portion of the outgoing (from Earth) radiation in a given spectral window, which is then converted to digital numbers, stored and, together with the set of neighboring measurements, coded as regular image grids. Images acquired in specific windows of the spectrum are called ‘bands’. The spectral ranges in which they were acquired, measured in nanometers or micrometers, together with their nominal pixel size, are key properties…

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Microsoft Launches Free, Unrestricted Version Of Visual Studio Community 2013

“Microsoft today launched the Community 2013 edition of Visual Studio, which essentially replaces the very limited Visual Studio Express version the company has been offering for a few years now.

There is a huge difference between Visual Studio Express and the aptly named Visual Studio 2013 Community edition, though: The new version is extensible, so get access to the over 5,100 extensions now in the Visual Studio ecosystem. It’s basically a full version of Visual Studio with no restrictions, except that you can’t use it in an enterprise setting and for teams with more than five people (you can, however, use it for any other kind of commercial and non-commercial project).”


Q: Who can use Visual Studio Community?
A: Here’s how individual developers can use Visual Studio Community:
  • Any individual developer can use Visual Studio Community to create their own free or paid apps.
Here’s how Visual Studio Community can be used in organizations:
  • An unlimited number of users within an organization can use Visual Studio Community for the following scenarios: in a classroom learning environment, for academic research, or for contributing to open source projects.
  • For all other usage scenarios: In non-enterprise organizations, up to 5 users can use Visual Studio Community. In enterprise organizations (meaning those with >250 PCs or > $1MM in annual revenue), no use is permitted beyond the open source, academic research, and classroom learning environment scenarios described above.

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Google Developers R Programming Video Lectures

Google Developers recognized that most developers learn R in bits and pieces, which can leave significant knowledge gaps. To help fill these gaps, they created a series of introductory R programming videos. These videos provide a solid foundation for programming tools, data manipulation, and functions in the R language and software. The series of short videos is organized into four subsections: intro to R, loading data and more data formats, data processing and writing functions. Start watching the YouTube playlist here, or watch an individual lecture below:

1.1 – Initial Setup and Navigation
1.2 – Calculations and Variables
1.3 – Create and Work With Vectors
1.4 – Character and Boolean Vectors
1.5 – Vector Arithmetic
1.6 – Building and Subsetting Matrices
1.7 – Section 1 Review and Help Files
2.1 – Loading Data and Working With Data Frames
2.2 – Loading Data, Object Summaries, and Dates
2.3 – if() Statements, Logical Operators, and the which() Function
2.4 – for() Loops and Handling Missing Observations
2.5 – Lists
3.1 – Managing the Workspace and Variable Casting
3.2 – The apply() Family of Functions
3.3 – Access or Create Columns in Data Frames, or Simplify a Data Frame using aggregate()
4.1 – Basic Structure of a Function
4.2 – Returning a List and Providing Default Arguments
4.3 – Add a Warning or Stop the Function Execution
4.4 – Passing Additional Arguments Using an Ellipsis
4.5 – Make a Returned Result Invisible and Build Recursive Functions
4.6 – Custom Functions With apply()


Alex Tereshenkov

Programming and managing GIS

REDD+ for the Guiana Shield

Technical Cooperation Project

Dr. Qiusheng Wu @ University of Tennessee

Writing Science

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!