New publication: LecoS now with own reference

As I can see my QGIS plugin LecoS is still widely used and downloaded from the QGIS plugin hub. I have noticed that some people already started referencing ether my blog or the QGIS repository in their outputs, which is fine, but after thinking about it for a while I thought why not make a little descriptive article out of it (being an upstart PhD scholar and scientist an’ all). I am now happy to announce that this article has passed scientific peer-review and is now been published in early view in the Journal of Ecological Informatics.

LecoS — A python plugin for automated landscape ecology analysis

The quantification of landscape structures from remote-sensing products is an important part of many analyses in landscape ecology studies. This paper introduces a new free and open-source tool for conducting landscape ecology analysis. LecoS is able to compute a variety of basic and advanced landscape metrics in an automatized way. The calculation can furthermore be partitioned by iterating through an optional provided polygon layer. The new tool is integrated into the QGIS processing framework and can thus be used as a stand-alone tool or within bigger complex models. For illustration a potential case-study is presented, which tries to quantify pollinator responses on landscape derived metrics at various scales.

The following link provided by Elsevier is still active until the 23 of January 2016. If you need a copy later on and don’t have access to the journal (sorry, I didn’t have the money to pay for open-access fees), then feel free to ether contact me or you can read an earlier prePrint of the manuscript on PeerJ.

http://dx.doi.org/10.1016/j.ecoinf.2015.11.006
So if you are using LecoS in any way for your work, it would be nice if you could reference it using the citation below. That shows me that people are actively using it and gives me incentives to keep on developing it in the future.

Martin Jung, LecoS — A python plugin for automated landscape ecology analysis, Ecological Informatics, Volume 31, January 2016, Pages 18-21, ISSN 1574-9541, http://dx.doi.org/10.1016/j.ecoinf.2015.11.006.

The full sourcecode of LecoS is released on github.