Monthly Archives: November 2014
Another tutorial for deriving brightness temperature from Landsat 8 using ArcGIS
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!
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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Nice tutorial for dealing with Landsat 8 imagery using scripting
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 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).”
- Any individual developer can use Visual Studio Community to create their own free or paid apps.
- 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.
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()