Our MEE paper on the r.pi GRASS package is now available online: “r.pi: a GRASS GIS package for semi-automatic spatial pattern analysis of remotely sensed land cover data”. This package allows a wide range of spatial pattern analysis from individual based dispersal models to graph theory or omni-directional connectivity metrics. It is part of the GRASS software and all outputs are provided in spatial formats and can be used for further processing in any spatial software such as GRASS, QGIS or R.
The full publication can be accessed here:
Wegmann, M., Leutner, B. F., Metz, M., Neteler, M., Dech, S. and Rocchini, D. (), r.pi: a GRASS GIS package for semi-automatic spatial pattern analysis of remotely sensed land cover data. Methods Ecol Evol.
The r.pi GRASS extension is now published and available through the GRASS extension repository. It provides a range of functionality and allows to easily analyze spatial patch attributes in GRASS. Patches are expected to be raster objects derived from remote sensing data and their spatial characteristics is written into a new spatial file for further analysis.
The list of functions outlined in our recent publication in MEE can be seen here. More functions are available in the r.pi package but not specifically mentioned.
Our former M.Sc. student Henrike published her work “Protection status and national socio-economic context shape land conversion in and around a key transboundary protected area complex in West Africa” where she outlined the capabilities of remotely sensed land cover information and its change over time to inform conservation activities. From the abstract: “ransboundary cooperation is being promoted as an effective way to conserve biodiversity that straddles national borders. However, monitoring the ecological outcomes of these large-scale endeavours is challenging, and as a result, the factors and processes likely to shape their effectiveness remain poorly identified and understood. To address this knowledge gap, we tested three hypotheses pertaining to natural vegetation loss across the W-Arly-Pendjari protected area complex, a key biodiversity hotspot in West Africa. Using a new methodology to compare land cover change across large remote areas where independent validation data is unevenly distributed across time, we demonstrate widespread agricultural expansion outside protected areas over the past 13 years.”
read more here:
Schulte to Bühne, H., Wegmann, M., Durant, S. M., Ransom, C., de Ornellas, P., Grange, S., Beatty, H., Pettorelli, N. (2017), Protection status and national socio-economic context shape land conversion in and around a key transboundary protected area complex in West Africa. Remote Sensing in Ecology and Conservation. doi: 10.1002/rse2.47
Our article in MEE got accepted “r.pi: a GRASS GIS package for semi-automatic spatial pattern analysis of remotely sensed land cover data” by Martin Wegmann, Benjamin Leutner, Markus Metz, Markus Neteler, Stefan Dech, Stefan and Duccio Rocchini. It outlines the capabilities of the r.pi package to analyze spatial patterns derived from remote sensing land cover data to inform about landscape conditions and changes. Such fragmentation measures are relevant for ecology or conservation as well as for remote sensing to produce value-added landcover maps that provide details on the spatial structure of the landscape.
Our EAGLE MSc. student Jakob Schwalb-Willmann just published a neat animal movement and remote sensing animation package called “moveVis“. It allows to animate movement tracks with corresponding or static remote sensing environmental data. Jakob is currently working to implement some more functionality. These will allow more customization and also some more information retrieval of resource use of single individuals. This new package will be used in the upcoming science schools AniMove and already got a lot of attention by people working in the interdisciplinary field of remote sensing and animal movement.
Our new publication “Open data and open source for remote sensing training in ecology” lead by Duccio Rocchini is now online covering the potential of open-access and open-source within training Earth Observation applications in other disciplines such as ecology. It is related to the special issue on remote sensing training for ecology and conservation published earlier this year and highlights the importance to embrace open-access and -source in remote sensing training.
read the full article here:
Duccio Rocchini, Vaclav Petras, Anna Petrasova, Ned Horning, Ludmila Furtkevicova, Markus Neteler, Benjamin Leutner, Martin Wegmann (2017) Open-access and open-source for remote sensing training in ecology, Ecological Informatics