Stockholm university

Jenny Marika WennbomResearch engineer

About me

My field of expertise is GIS and remote sensing (geomatics). In my role as research engineer I assist researchers and participate in research projects with GIS and Remote Sensing.

I also teach on most of the departments courses in GIS, remote sensing and cartography.

For GIS-analyses I mainly use ArcGIS Pro and QGIS with python but also other applications or programming languages that are suitable for the task at hand.

My remote sensing competence mainly encompass optical satellite imagery (e.g. Landsat and Sentinel 2) and aerial photographs.

Teaching

Other teaching 2024:

GIS for employees (1,5 days in vt)
 

Teaching on department courses 2024:

Cartography and graphic design (GE3021)

Cartography and graphic design (GE3012)

GE II Geographical methods II (GE4001) (remote sensing exercise)

Geographic information systems (GIS) - distance spring + autumn (GE4030)

Paleoglaciologi (GE7053)

Advanced remote sensing (GE7090)

Applied aerial photographic techniques for landscape analysis (GE7082)

Geographic information systems (GIS) (GE4035)

Geomorphological processes, natural hazards and risk assessments (GE5033)

Applied GIS and remote sensing (GE7088) ht A + B

Geographic analysis and visualization in GIS (GE7089)

Research projects

Publications

For more publications see my Researchgate profile:

https://www.researchgate.net/profile/Marika-Wennbom

A selection from Stockholm University publication database

  • An innovative use of orthophotos - possibilities to assess plant productivity from colour infrared aerial orthophotos

    2019. Rasmus Erlandsson (et al.). Remote Sensing in Ecology and Conservation 5 (4), 291-301

    Article

    Studies of ecological processes should focus on a relevant spatial scale, as crude spatial resolution will fail to detect small scale variation which is of potentially critical importance. Remote sensing methods based on multispectral satellite images are used to assess primary productivity and aerial photos to map vegetation structure. Both methods are based on the principle that photosynthetically active vegetation has a characteristic spectral signature. Yet they are applied differently due to technical differences. Satellite images are suitable for calculations of vegetation indices, for example Normalized Difference Vegetation Index (NDVI). Colour infrared aerial photography was developed for visual interpretation and never regarded for calculation of indices since the spectrum recorded and post processing differ from satellite images. With digital cameras and improved techniques for generating colour infrared orthophotos, the implications of these differences are uncertain and should be explored. We tested if plant productivity can be assessed using colour infrared aerial orthophotos (0.5 m resolution) by applying the standard NDVI equation. With 112 vegetation samples as ground truth, we evaluated an index that we denote rel‐NDVIortho in two areas of the Fennoscandian mountain tundra. We compared the results with conventional SPOT5 satellite‐based NDVI (10 m resolution). rel‐NDVIortho was related to plant productivity (Northern area: P = <0.001, R2 = 0.73; Southern area: P = <0.001, R2 = 0.39), performed similar to SPOT5 satellite NDVI (Northern area: P = <0.001, R2 = 0.76; Southern area: P = <0.001, R2 = 0.40) and the two methods were highly correlated (cor = 0.95 and cor = 0.84). Despite different plant composition, the results were consistent between areas. Our results suggest that vegetation indices based on colour infrared aerial orthophotos can be a valuable tool in the remote sensing toolbox, offering a high‐spatial resolution proxy for plant productivity with less signal degradation due to atmospheric interference and clouds, compared to satellite images. Further research should aim to investigate if the method is applicable to other ecosystems.

    Read more about An innovative use of orthophotos - possibilities to assess plant productivity from colour infrared aerial orthophotos
  • High-resolution bathymetric mapping reveals subaqueous glacial landforms in the Arctic alpine lake Tarfala, Sweden

    2019. Nina Kirchner (et al.). Journal of Quaternary Science 34 (6), 452-462

    Article

    In Arctic alpine regions, glacio-lacustrine environments respond sensitively to variations in climate conditions, impacting, for example,glacier extent and rendering former ice-contact lakes into ice distal lakes and vice versa. Lakefloors may hold morphological records of past glacier extent, but remoteness and long periods of ice cover on such lakes make acquisition of high-resolution bathymetric datasets challenging. Lake Tarfala and Kebnepakte Glacier, located in the Kebnekaise mountains, northern Sweden, comprise a small, dynamic glacio-lacustrine system holding a climate archive that is not well studied. Using an autonomous surface vessel, a high-resolution bathymetric dataset for Lake Tarfala was acquired in 2016, from which previously undiscovered end moraines and a potential grounding line feature were identified. For Kebnepakte Glacier, structure-from-motion photogrammetry was used to reconstruct its shape from photographs taken in 1910 and 1945. Combining these methods connects the glacial landform record identified at the lakefloor with the centennial-scale dynamic behaviour of Kebnepakte Glacier. During its maximum 20(th) century extent, attained c. 1910, Kebnepakte Glacier reached far into Lake Tarfala, but had retreated onto land by 1945, at an average of 7.9 m year(-1).

    Read more about High-resolution bathymetric mapping reveals subaqueous glacial landforms in the Arctic alpine lake Tarfala, Sweden

Show all publications by Jenny Marika Wennbom at Stockholm University