Processing historical NOAA AVHRR data with precise geometric correction

We published a new article in MDPI Remote Sensing journal on new method to accurately process time series of AVHRR Local Area Coverage (LAC) data. You can read the entire paper here:

We developed a new workflow which can read all the AVHRR LAC level 1B  data over all the NOAA satellites, calibrate them, applied clock drift corrections, geometrically correct them using automated feature matching technique called SIFT and finally applied split window technique to the thermal bands to derive lake surface water temperature as a case study. We found that the SIFT based geometric correction followed by gcp filter using m.gcp.filter addon in GRASS GIS 7 is very efficient in performing image to image corrections on thousands of images.

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Studying spatio-temporal changes in phytoplankton by means of remote sensing

The ocean is teeming with microscopic organisms called phytoplankton. Phytoplankton comprises two main groups: photosynthetic cyanobacteria and the single-celled algae that drift in the sunlit top layers of oceans. They provide food, directly or indirectly for virtually every other marine creature. They emit much of the oxygen that permeates our atmosphere and their fossilized remains, buried and compressed by geological forces, are transformed into oil. In addition, they play a huge role in the cycling of carbon dioxide from the atmosphere to the biosphere and back, cycling that helps to control Earth’s climate [1].air jordan 1

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Processing ERA-Interim dataset in ncdf using GDAL and GRASS GIS

Processing big data efficiently has become a necessity of the hour in ecological and climate change research. Now there are enormous number of public data available online, which demands high level of processing capabilities too.  In this post I will show you how we can process ESA-Interim data which is global atmospheric reanalysis from 1979 to present developed by ECMWF.

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GRASS GIS 7.0 RC1 is released

The first release candidate of feature rich GRASS 7.0 is released on January 14, 2015. The new candidate release is an output of 6 years of development after the last release of GRASS 6.4.0. One of the main feature in GRASS 7.0 is its new python user interface replacing the old tcl/tk based GUI.
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Changes and improvements on the latest version can be read here: GRASS 7.0 RC1
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