%0 Journal Article %1 Rocchini201757 %A Rocchini, Duccio %A Petras, Vaclav %A Petrasova, Anna %A Horning, Ned %A Furtkevicova, Ludmila %A Neteler, Markus %A Leutner, Benjamin %A Wegmann, Martin %D 2017 %J Ecological Informatics %K article Wegmann Leutner LSFE %P 57 - 61 %R https://doi.org/10.1016/j.ecoinf.2017.05.004 %T Open data and open source for remote sensing training in ecology %U http://www.sciencedirect.com/science/article/pii/S1574954117300237 %V 40 %X Abstract Remote sensing is one of the most important tools in ecology and conservation for an effective monitoring of ecosystems in space and time. Hence, a proper training is crucial for developing effective conservation practices based on remote sensing data. In this paper we aim to highlight the potential of open access data and open source software and the importance of the inter-linkages between these and remote sensing training, with an interdisciplinary perspective. We will first deal with the importance of open access data and then we provide several examples of Free and Open Source Software (FOSS) for a deeper and more critical understanding of its application in remote sensing.

@article{Rocchini201757, abstract = {Abstract Remote sensing is one of the most important tools in ecology and conservation for an effective monitoring of ecosystems in space and time. Hence, a proper training is crucial for developing effective conservation practices based on remote sensing data. In this paper we aim to highlight the potential of open access data and open source software and the importance of the inter-linkages between these and remote sensing training, with an interdisciplinary perspective. We will first deal with the importance of open access data and then we provide several examples of Free and Open Source Software (FOSS) for a deeper and more critical understanding of its application in remote sensing. }, added-at = {2020-09-11T12:04:50.000+0200}, author = {Rocchini, Duccio and Petras, Vaclav and Petrasova, Anna and Horning, Ned and Furtkevicova, Ludmila and Neteler, Markus and Leutner, Benjamin and Wegmann, Martin}, biburl = {https://www.bibsonomy.org/bibtex/2137454763a44dbafdb7dbdea8350008c/earthobs_uniwue}, doi = {https://doi.org/10.1016/j.ecoinf.2017.05.004}, interhash = {23ff08cca969fb610bf6ab9c11705ce2}, intrahash = {137454763a44dbafdb7dbdea8350008c}, issn = {1574-9541}, journal = {Ecological Informatics }, keywords = {article Wegmann Leutner LSFE}, pages = {57 - 61}, timestamp = {2020-11-18T22:08:33.000+0100}, title = {Open data and open source for remote sensing training in ecology }, url = {http://www.sciencedirect.com/science/article/pii/S1574954117300237}, volume = 40, year = 2017 }