New M.Sc. started: Burn scar detection using polarimetric ALOS-2 time-series data

New M.Sc. started: Burn scar detection using polarimetric ALOS-2 time-series data

Susanne Karg started her M.Sc. thesis on „Burn scar detection using polarimetric ALOS-2 time-series data“ in cooperation with DLR-DFD (Günter Strunz, Sandra Martinis). The aim of this thesis is to develop a change-detection approach using polarimetric SAR (PolSAR) data and, if suitable data is available, interferometric SAR (InSAR) data to detect fire scars. Within this thesis different polarimetric decomposition approaches and pixel-based classifications will be tested for their suitability to detect a recently burned region of interest. The variables which perform best will then be used for an object-based post-classification refinement.

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.

EAGLE M.Sc. application deadline 2017 is approaching

EAGLE M.Sc. application deadline 2017 is approaching

The EAGLE MSc. application deadline for the upcoming winter term is approaching. Apply within the next 7 days: http://eagle-science.org/apply – all details about needed documents are listed on this page.

Learn within EAGLE how to apply remote sensing for a variety of environmental applications, explore new methods and collaborate with other disciplines. Also read the news by our EAGLE students on their webpage.

More details about the study program or the courses can be found here:

http://eagle-science.org/about/

http://eagle-science.org/courses/

http://eagle-science.org/specialization/

EAGLE students back to their second semester

EAGLE students back to their second semester

After the semester holidays, we welcome our EAGLE students back to their second semester!

Some of them already took the chance to take part in a short course on landscape ecology for wetland monitoring and management with QGIS given by the ERASMUS lecturer Dr. Aurelie Davranche (more) the last two days.
Today, the course   “Advanced spatial analysis for geoscientists – object-oriented image analysis” started. It is a hands-on-data-seminar jointly given by our colleagues Dr. Michael Thiel, who will teach eCognition during the summer term, and Dr. Christian Geiss who will be at our department until the end of the week. Christian is an invited guest lecturer from DLR’s Remote Sensing Data Center (Department: Geo-Risks and Civil Security) and he is working on mapping and characterization of urban areas with respect to risk and vulnerability assessment. If you want to learn more about Christian’s Team click here.

We wish all students and lecturers interesting seminars (full list) and a successfull summer term!

M.Sc. handed in on UAV-based monitoring of post-disturbed forest sites.

M.Sc. handed in on UAV-based monitoring of post-disturbed forest sites.

The M.Sc thesis by Marius Röder (Hochschule für Technik Stuttgart) was handed in. The thesis was supervised by Dr. Hooman Latifi and Prof. Eberhard Gülch and focuses on monitoring post-disturbed and heterogenuous forest sites by cost-effective methods from Unmaned Aerial Vehicle (UAV) domain. The advantage of normalized digital surface models extracted from UAV dta was initially compared to the products derived from standard aerial photography. Subsequently, the suitability of UAV-based inventory was compared to traditional eld methods . For this purpose, reference and UAV data were compared in terms of quality, quantity and cost eectiveness. In addition, an algorithm for automatic tree detection was compared to the manual detection on the UAV-imagery. The extent to which the results differ for certain forest heterogeneity as well as for single and grouped tree individuals was addressed., followed by a cost and benefit analysis of UAV-based forest inventory compared to traditional field-based methods.

 

UAV-based point cloud (left) and UAV-based nDSM (right) of an examplified sample plot in Bavarian Forest National Park

 

the results showed that the UAV inventory can not fully replace the eld methods in terms of quality and quantity due to the general disadvantages of photogrammetric methods in the small-scale forest sites consisting of dense rejuvenation stocks. However, from a purely economic point of view, the advantages over the eld method predominate. Improvements could be achieved by combining field and UAV-methods or a simulteanous use of digital camera and laser scanner mounted on UAV.

M.Sc. handed in on animal movement and remote sensing

M.Sc. handed in on animal movement and remote sensing

The M.Sc. thesis “Can animal movement and remote sensing data help to improve conservation efforts?” by Matthias Biber M.Sc. student within the Global Change Ecology program handed in his thesis. He explored the potential of remote sensing data to explain animal movement patterns and if these linkages can help to improve conservation efforts. He used Zebra as study animal in Southern and Eastern Africa. The second supervisor of his M.Sc. was Prof. Thomas Müller from BIK-F.

 

abstract:
Climate and land-use change have a growing influence on the world’s ecosystems, in particular in Africa, and increasingly threaten wildlife. The resulting habitat loss and fragmentation can impede animal movement, which is especially true for migratory species. Ungulate migration has declined in recent years, but its drivers are still unclear. Animal movement and remote sensing data was combined to analyse the influence of  various vegetation and water indices on the habitat selection of migratory plains zebras in Botswana’s Ngamiland. The study area experienced a more or less steady state in normalised difference vegetation index (NDVI) over the last 33 years. More than half of the study area was covered by PAs. NDVI increased stronger in PAs compared to areas that were not protected. NDVI was always higher in the Okavango Delta  compared to the Makgadikgadi Pans. Although zebras are thought to select for areas with high NDVI, they experienced a lower NDVI in the Makgadikgadi grasslands during wet season. Step selection functions (SSFs) showed that NDVI derived from Landsat as well as NDVI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) were significant drivers of habitat selection across all individuals. Migration  seems to be driven by the high nutritional value of the Makgadikgadi grasslands and not seasonal resource limitation. Landsat imagery was shown to provide different environmental information compared to MODIS data. This highlights not only the importance of NDVI for explaining animal movement, but also the importance of Landsat imagery for monitoring habitat extent and fragmentation. Incorporating the animal’s  behavioural state and memory into SSFs will help to improve our ecological understanding of animal movement in the future.