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land cover and change - GOFC-GOLD LC-IT Office - Wageningen UR

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Advancements on GEO SB-02 Global L<strong>and</strong> Cover <strong>and</strong> L<strong>and</strong><br />

Cover Change task<br />

The <strong>GOFC</strong>-<strong>GOLD</strong> L<strong>and</strong> Cover Project<br />

<strong>Office</strong> keeps playing a leading<br />

role in the specification of the<br />

GEO SB-02 Global L<strong>and</strong> Cover <strong>and</strong><br />

L<strong>and</strong> Cover Change task coordinating<br />

<strong>and</strong> contributing to the redaction<br />

of the document in conjunction<br />

with the GEO Secretariat. The current<br />

objectives of the task are to:<br />

Accuracy assessment of global <strong>l<strong>and</strong></strong><br />

<strong>cover</strong> (G<strong>LC</strong>) map products is an important<br />

part of the mapping procedure.<br />

Assessing the accuracy of a map can<br />

be done for different purposes such as<br />

providing overall measure of the quality<br />

of map, evaluating the utility of different<br />

algorithms, helping to underst<strong>and</strong><br />

how mapping errors are generated, or<br />

just selecting the best map for a particular<br />

region. Accuracy assessment also<br />

can be conducted to evaluate the utility<br />

of the maps for specific applications,<br />

particularly in the case of G<strong>LC</strong> maps.<br />

Reference data for accuracy assessments<br />

is commonly assumed to be accurate<br />

representation of reality, but, in<br />

many cases, particularly in G<strong>LC</strong> validation<br />

efforts, reference data are just<br />

another classification which are not<br />

error free. This issue is well known in<br />

the validation of <strong>l<strong>and</strong></strong> <strong>cover</strong> classification.<br />

The issues of positional accuracy,<br />

variability <strong>and</strong> bias in the image inter-<br />

3<br />

Newsletter N˚ 21 | 2012<br />

• Provide a suite of global<br />

<strong>l<strong>and</strong></strong>-<strong>cover</strong> <strong>and</strong> <strong>l<strong>and</strong></strong>-<strong>cover</strong><br />

<strong>change</strong> datasets, based on improved<br />

<strong>and</strong> validated moderate<br />

resolution <strong>l<strong>and</strong></strong>-<strong>cover</strong> maps.<br />

• Develop

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