IEEE Geoscience and Remote Sensing Magazine - December 2015 - 30

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6080000 6060000 6040000 6020000 6000000
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k-Means Clustering

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ity and magnetic airborne surveys. B) Result of k-Means cluster analysis based on 11 partitions displaying pseudo-geology. C) Result of Fuzzy c-Means cluster analysis (see text for a more detailed
explanation of the algorithms).

x

(c)

x

(b)

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FIguRE 1. (Continued) KNIME workflow developed to classify geological discontinuities in a selected region. A) KNIME nodes used to perform unsupervised classification of a combination of grav-

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Fuzzy c-Means

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machine learning algorithms and data
mining in geoscience related problems
and case studies.
2. THE KNIME ENVIRONMENT
The KNIME Graphic User Interface
(GUI) is relatively simple to use with
seven windows facilitating direct interaction with the modelling environment: (1) the KNIME Explorer, helps
with pre-built examples available on
the public KNIME server and also has
links to the local workspace where
all existing user built workflows can
be easily retrieved; (2) the Favorite
Nodes window allows to retrieve most
frequently used nodes; (3) the Node
Repository window, equipped with a
search tool, allows to rapidly select a
module (node) that executes a specific
task, and lets you explore visually also
the numerous nodes options; (4) any
node can be dragged into a WorkflowBench window where multiple nodes
can be connected with arrows that indicate a data/model flow to form a data
processing pipeline (more formally a
DAG, Directed Acyclic Graph), see [4]
and Fig. 1. (5) A Node Description window, which provides detailed descriptions of a selected node, its use, and
other functionalities are reported in the
panel. (6) The Outline window, which
allows to visualize the entire workflow
and facilitates zooming and panning
for detailed views of the work-bench.
(7) The Console window, which represents the command line panel where
KNIME processing errors are displayed
for troubleshooting and also other
information related to plug-in installations is provided. Workflows can be
run from the command line if desired,
this is done for iterative/repetitive tasks.
The way data processing works is
very much similar to ESRI, ArcGIS
Model-Builder although KNIME represents a generalization of the functionality offered by this ESRI GIS
tool, in essence it can handle more
data-types. Furthermore, some of
the nodes allow to manipulate data
using other programming languages
making it also a tool that can pipeline and automate the execution of
processes that are carried out using

ieee Geoscience and remote sensing magazine

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