M.Sc. handed in: Quantifying land cover change using remote sensing data in a transboundary protected area

M.Sc. handed in: Quantifying land cover change using remote sensing data in a transboundary protected area

Henrike Schulte to Bühne handed in her M.Sc. thesis “Quantifying land cover change using remote sensing data in a transboundary protected area” supervised by Nathalie Pettorelli (ZSL) and me. From the abstract: Biodiversity is declining at unprecedented rates as a result of global environmental change, threatening ecosystem stability and resilience, on which human well-being ultimately depends. Transboundary 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, this thesis quantified loss and fragmentation of natural vegetation across the W-Arly-Pendjari transboundary protected area complex, a key biodiversity hotspot in West Africa. Land cover maps for 2000, 2006 and 2013 were generated by combining open source optical remote sensing data with spectral change analyses and supervised classification algorithms to quantify loss and fragmentation of natural vegetation as a result of agricultural expansion. There was widespread agricultural expansion outside protected areas between 2000 and 2013, whereas expansion was limited inside protected areas. Additionally, natural vegetation was less fragmented inside than outside protected areas. Protected areas with high protection status appeared considerably more effective at preventing land conversion, and had less fragmented natural vegetation, than other protected areas. There were marked differences in cropland expansion rates between countries, which might be linked to differences in rural population growth. Altogether, these results indicate that transboundary protected areas can be relatively successful at reducing human pressure on biodiversity. However, there can be considerable spatial heterogeneity in anthropogenic pressure across transboundary protected area complexes, which highlights the need for more comprehensive assessments of this mode of biodiversity protection; these assessments could capitalise on the current  availability of remote sensing information.

M.Sc thesis: Agent-based modeling to understand Mediterranean wetland dynamic based on multiple remote sensing data

M.Sc thesis: Agent-based modeling to understand Mediterranean wetland dynamic based on multiple remote sensing data

M.Sc thesis (+ a two-month internship):

Agent-based modeling to understand Mediterranean wetland (former saltworks) dynamic based on multiple remote sensing data


UAV imagery over a portion of the study site. Image courtesy Cyril Fleurant (Uni Angers)

The Camargue’s former saltworks is a 6500-ha site located at the Mediterranean coast in southern France. The site has been recently purchased by the Conservatoire du Littoral, a public organization created in 1975 to ensure the protection of outstanding natural areas along the coast. The ongoing management of the area has been entrusted to the natural regional parc (PNR camargue), the national reserve of Camargue and the Tour du Valat. The site comprises a wide range of habitats. It has traditionally been home to the single colony of Flamingos nesting in France and is used by thousands of shorebirds during breeding and migration. Various construction works such as embankments (to control circulation of pumped sea-water through lagoons) and sea-front dike (to prevent uncontrolled flooding by the sea) together with salt exploitation and sea-level rise led to profound changes in the landscape that in turn call for the restoration of natural processes of coastal lagoon ecosystems. However, the conservation and management measures are restricted to be timely done as a result of difficult access for ground survey. Very high resolution remote sensing can introduce alternatives to this by providing continuous and objective surface coverage.

In this context, this M.Sc project aims at developing predictive tools on the basis of remote sensing data to follow habitat dynamics in order to help adaptive ecosystem management. The objective is to develop a method to understand the fast changes of the habitats using very high resolution remote sensing data. To this aim, LiDAR and very high resolution optical data (WorldView 2) and other GIS layers will be analyzed to produce spatially-continuous input for a state-of-the-art agent-based model. Few studies have applied this modeling approach to image analysis but the first results are promising .

Agent-based modeling will allow considering multiple non parametric factors that characterize the landscape dynamics. This approach will allow taking complex spatial and temporal processes as well as changing factors into account. The GAMA agent-based simulation platform (Taillandier et al. 2014, http://gama-platform.org/)  was initially developed to integrate GIS data in the  simulation. Within the envisaged M.Sc work this platform will be used for prediction based on the layers created from remote sensing data.

The M.Sc thesis is planned to be ideally started with a preliminary phase of two-month internship at the LETG, University of Angers . During the internship the M.Sc student will encompass a NetLogo and GAMA learning phase and gets to know the area and data.  A site visit at Tour du Valat research centre may help to understand the management objective of the area. The second phase would be the M.Sc thesis, during which the candidate will spend time at both Universities of Würzburg (4 months) and Angers (2 months). The stay in Angers is supported by an existing ERASMUS agreement between the two universities.

Interested candidates are wellcome to send an Email to Dr. Hooman Latifi.


Dr. Aurélie Davranche (University of Angers, France)

Dr. Hooman Latifi (University of Würzburg)

Dr. Brigitte Poulin (Tour du Valat, France)

new M.Sc. program: applied EArth Observation and Geoanalysis for the Living Environment

new M.Sc. program: applied EArth Observation and Geoanalysis for the Living Environment

eagle_master_full_noTextAre you interested to learn how to apply remote sensing for a variety of topics? Check out our EAGLE study program.

EAGLE: “applied EArth Observation and Geoanalysis for the Living Environment”


EAGLE is an international English language M.Sc. program offered at the University of Würzburg, Germany. It is focusing on Applied Earth Observation and Geoanalysis for the environment. The goal of EAGLE is to strengthen the practical use of applied Earth Observation in research, planning, and decision making, and to unlock the full potential of remote sensing data analyses in your desired field of application.

EAGLE lectures, seminars, and practicals provide in depth methodological knowledge and practical skills, and additionally provide a comprehensive overview of the range of remote sensing applications. The potential of Earth Observation data analyses for research on and management of forest-, agro-, or coastal ecosystems or the urban sphere – to name only a few examples – will be illuminated. Please browse through our courses in order to get a good overview of content and aims.

EAGLE students are subsequently encouraged to further develop and deepen their knowledge and skills tailored to their personal interests during internships and innovation laboratories at international partner institutions of the EAGLE network.

The EAGLE study program is a joint initiative of the Institute of Geography and Geology at the University of Würzburg, led by the Department of Remote Sensing in collaboration with the Earth Observation Center at the German Aerospace Center (DLR-EOC). The courses are taught in English by a team of internationally recognized researchers from diverse backgrounds.

The accredited (120 ECTS) University degree is open for students from a variety of disciplines such as geography, geology, hydrology, ecology, biology, and other fields in environmental sciences and studies.


Internship at Bavarian Forest National Park

Internship at Bavarian Forest National Park

The Department of Conservation and Research of the Bavarian Forest National Park (BFNP) is seeking highly motivated B.Sc and M.Sc students for internships starting in September 2015. The BFNP is located at the German/Czech border in eastern part of the state of Bavaria, and is home to a portion of most spectacular mixed temperate forest landscapes across central Europe.

Source: http://www.bayerischer-wald.de

Source: http://www.bayerischer-wald.de

The announced internship will start from 15th of September 2015 and will normally take 3 months of reearch work , mostly with a strong focus on GIS and remote sensing (LiDAR, hyperspectral and multispectral). The main areas of research will be biodiversity and forest management. The candidates should be highly motivated for the topics, related field works, and should additionally be familiar with basic skills of GIS. Programming skills in R or Python would be seen as assets.

The internship application is open to all potential candidates, and the selected candidates will be supported by an amount of 200 EURO per month as well as free of charge accomodation within BFNP housing facilities.

Please send your applications directly to Dr. Marco Heurich from BFNP.

New MSc. student – LiDAR for species distribution modeling

New MSc. student – LiDAR for species distribution modeling

Lidar_Bay_Forest_remote-sensing_euA new MSc. student started her thesis “Suitability of Light detection and ranging (LiDAR) data and texture measures of aerial images to model the species distribution of Glaucidium passerinum (Pygmy Owl) in Vercors, French Alps”. Wanda Graf is using LiDAR data to describe the three dimensional habitat structure of Glaucidium passerinum at different scales. Moreover texture measures of aerial images will be used to describe the habitat structure of Glaucidium passerinum at different scales. It is assumed that LiDAR data are more suitable to model the distribution of Glaucidium passerinum than texture measures of aerial images. The thesis is supervised by Dr. Björn Reineking and Dr. Martin Wegmann

Topic for M.Sc thesis: Application of multi-seasonal RapidEye satellite imagery for inventory of private and municipal forests in the northern Black Forest

Topic for M.Sc thesis: Application of multi-seasonal RapidEye satellite imagery for inventory of private and municipal forests in the northern Black Forest

In this M.Sc thesis, a set of multi-seasonal satellite imagery from RapidEye will be applied to develop algorithms and improve the existing ones in tree species mapping across a portion of mixed forest stands in northern Black Forests in the state of Baden-Württemberg in Germany. The focus of the research will be on small private forest patches, for which conducting regular forest inventories has always been a major challenge. For most private forests (i.e. more than 30% of the forest area in Baden-Württemberg) there is a shortage of accurate and up-to-date forest inventory data.

To this aim, a set of multi seasonal RapidEye satellite imagery with a spatial resolution of about 5m are obtained from the Black Bridge company. The data cover 4 seasonally different times of the year, including March 2014, May 2013, July 2014, September 2013, and October 2012. Based on the fact that the tree species show phonological (and in turn spectral) differences during the year, these comprehensive dataset will be used here to map different tree species and other important forest characteristics, such as needle fall, storm effects or effects caused by bark beetles.


Both the results of the single tree-based aerial photo interpretation as well as those from a small area in which all pine trees have been mapped will be used as reference data. In addition, validation data can also be achieved from a number of aerial photo-interpreted stands dominated by Scots pine. The data for the neighboring public forests can also be accessed via the local forest enterprises.

The work will be carried out in close cooperation between University of Würzburg and the LandConsult company (Dr Markus Weidenbach). A Visit to the study area in the northern Black Forest is supported by the LandConsult company.

Moreover, Dr. Piotr Tompalski from the University of British Columbia (Canada) will give advices as an external supervisor.

For questions on this topic, please contact Dr. Hooman Latifi at the Dept. of remote sensing of the University of Würzburg (hooman.latifi@uni-wuerzburg.de).  A more comprehensive description of this topic can be found at following address: