Remote sensing of the forest transition and its ecosystem impacts in mountain environments.

Land abandonment and forest recovery is often taking place on marginal lands, such as mountain environments. Assessing the rate, spatial patterns and ecosystem impacts of forest cover change in these environments is challenging given the ruggedness and inaccessibility of mountains. Remote sensing methods are the privileged tool, and yet suffer from methodological challenges due to topographical and shadowing effects. Recent techniques have been developed to correct high and very high resolution imagery for radiometric and geometric distortions, and illumination and shade effects on accidented surfaces. These sophisticated correction methods are not only highly labour intensive, but also demand site-specific calibration which makes it particularly difficult to apply them in streamlined processing schemes. At present, it is not clear what the added value of complex preprocessing techniques is compared to relative simple empirical methods and to what extent more sophisticated processing enhances results of subsequent analyses. This project will specifically address this methodological research question, and will develop an optimal preprocessing chain to be used for semi-automatic analyses of high resolution satellite data on mountainous terrain.
More specifically, the project will: (i) evaluate the sensitivity of the parameterization of biophysical attributes from remote sensing to the level of correction for possible distortions due to topographic effects, illumination and shadowing, and preceding rainfall, (ii) test and apply an optimal preprocessing chain for monitoring forest cover change and ecosystem services, (iii) provide new insights in the impact and feedback mechanisms of forest transitions on ecosystem services.
The results of this study on forest transition are very relevant for climate change policies and possible future obligations of countries with respect to limitations of GHG emissions from land cover activities (reforestation and avoided deforestation) as part of the Reduced Emissions from Deforestation and forest Degradation (REDD) scheme.
The research will be based on two or three mountain sites in very different geographic contexts, to allow for a rich comparative analysis: the Carpathian mountains in Eastern Europe; the Northern Andes in Ecuador; and, if the on-going process to obtain a research authorisation is successful, a valley in Bhutan, in the Himalayas. We have strong collaboration links with local scientists in each of these sites, and have good access to field sites and data.
This research will evaluate the potential of remote sensing tools for the identification of possible policy interventions aimed at accelerating land use transitions in forested mountain environments. It will also facilitate the identification and assessment of viable policy options addressing the drivers of forest-cover changes and their consistency with policy approaches on avoided deforestation, such as Reduced Emissions from Deforestation and degradation (REDD), currently being discussed in UNFCCC and other relevant international fora as part of post-2012 climate agreements.

Hostert, Patrick Prof. Dr. (Details) (Geomatik)

Projektstart: 01/2010
Projektende: 06/2014

Physische Geographie

Geofernerkundung, Landnutzung und Landnutzungswandel

Griffiths, P., Kuemmerle, T., Baumann, M., Radeloff, V. C., Abrudan, I. V., Lieskovsky, J., Munteanu, C., Ostapowicz, K., & Hostert, P. (2014). Forest disturbances, forest recovery, and changes in forest types across the Carpathian ecoregion from 1985 to 2010 based on Landsat image composites. Remote Sensing of Environment, 151(0), 72-88. doi:
Griffiths, P., Kuemmerle, T., Kennedy, R. E., Abrudan, I. V., Knorn, J., & Hostert, P. (2012). Using annual time-series of Landsat images to assess the effects of forest restitution in post-socialist Romania. Remote Sensing of Environment, 118(0), 199-214.
Griffiths, P., Müller, D., Kuemmerle, T., & Hostert, P. (2013). Agricultural land change in the Carpathian ecoregion after the breakdown of socialism and expansion of the European Union. Environmental Research Letters, 8(4), 045024.
Griffiths, P., van der Linden, S., Kuemmerle, T., & Hostert, P. (2013). A Pixel-Based Landsat Compositing Algorithm for Large Area Land Cover Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(5), 2088-2101. doi:10.1109/jstars.2012.2228167

Zuletzt aktualisiert 2020-13-03 um 23:07