publication: Remote Sensing in Ecology and Conservation: three years on

publication: Remote Sensing in Ecology and Conservation: three years on

Our editorial “Remote Sensing in Ecology and Conservation: three years on” is out. from the abstract: In 2014, Wiley and the Zoological Society of London launched Remote Sensing in Ecology and Conservation, an open-access journal that aims to support communication and collaboration among experts in remote sensing, ecology and conservation science. Remote sensing was from the start understood as the acquisition of information about an object or phenomenon through a device that is not in physical contact with the object, thus including camera traps, field spectrometry, terrestrial and aquatic acoustic sensors, aerial and satellite monitoring as well as ship-borne automatic identification systems (Pettorelli et al. 2015). The primary goals of this new journal were, and still are, to maximize the understanding and uptake of remote sensing-based techniques and products by the ecological and conservation communities, prioritizing findings that advance the scientific basis of, and applied outcomes from, ecology and conservation science; and to identify ecological challenges that might direct development of future remote sensors and data products. read more:

Pettorelli, N., Nagendra, H., Rocchini, D., Rowcliffe, M., Williams, R., Ahumada, J., De Angelo, C., Atzberger, C., Boyd, D., Buchanan, G., Chauvenet, A., Disney, M., Duncan, C., Fatoyinbo, T., Fernandez, N., Haklay, M., He, K., Horning, N., Kelly, N., de Klerk, H., Liu, X., Merchant, N., Paruelo, J., Roy, H., Roy, S., Ryan, S., Sollmann, R., Swenson, J. and Wegmann, M. (2017), Remote Sensing in Ecology and Conservation: three years on. Remote Sens Ecol Conserv, 3: 53–56. doi:10.1002/rse2.53

new publication: r.pi a GRASS package for semi-automatic spatial pattern analysis

new publication: r.pi a GRASS package for semi-automatic spatial pattern analysis

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.

 

 

new GRASS extension: spatial pattern analysis

new GRASS extension: spatial pattern analysis

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.

new publication: land conversion in and around a transboundary protected area

new publication: land conversion in and around a transboundary protected area

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

article accepted: remote sensing spatial pattern analysis

article accepted: remote sensing spatial pattern analysis

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.