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People and publications

Please use Lund University Publications (LUP) or click on the names to the right to find our remote sensing publications

Ph.D. theses (2007-today)

  • Sjöström M., 2012: Satellite remote sensing of primary production in semi-arid Africa.
  • Schubert, P., 2011: Model development for estimating carbon dioxide exchange in Nordic forests and peatlands with MODIS time series data.
  • Tagesson, T., 2011: Land-atmosphere exchange of carbon in a high-Arctic wet tundra ecosystem.
  • Johansson, L., 2008: Semi-natural grasslands: landscape, history and plant species diversity.
  • Eriksson, H., 2007: Leaf Area Index of Scandinavian Forests Methods Using in situ and Remotely Sensed Data.
  • Olofsson, P., 2007: Remote Sensing of Carbon Balance across Scandinavian Forests.

M.Sc. theses (2007-today)

  • Gevaert, C., 2014: Combining hyperspectral UAV and mulitspectral FORMOSAT-2 imagery for precision agriculture applications.
  • Javid, H., 2014: Snowmelt and runoff assessment of Talas River Basin using remote sensing approach.
  • Nekrasov, O., 2014: Processing of MODIS Vegetation Indices for analysis of agricultural droughts in the southern Ukraine between the years 2000-2012.
  • Persson, S., 2014: Estimating leaf area index from satellite data in deciduous forests of southern Sweden.
  • Van Tiggelen, J., 2014: Assimilation of satellite data and insitu data for the improvement of global radiation maps in the Netherlands.
  • Veysipanah, M., 2014: Polynomial trends of vegetation phenology in Sahelian to equatorial Africa using remotely sensed time series from 1983 to 2005.
  • Löfgren, O., 2013: Using Worldview-2 satellite imagery to detect indicators of high species diversity in grasslands.
  • Morin, K., 2013: Mapping moth induced birch forest damage in northern Sweden, with MODIS satellite data.
  • Palm, E., 2013: Finding a method for simplified biomass measurements on Sahelian grasslands.
  • Shendryk, I., 2013: Integration of LiDAR data and satellite imagery for biomass estimation in conifer-dominated forest.
  • Zhou, Y., 2013: Inter-annual memory effects between soil moisture and NDVI in the Sahel.
  • Ahmed, M., 2012: Significance of soil moisture on vegetation greenness in the African Sahel from 1982 to 2008.
  • Alwesabi, M., 2012: MODIS NDVI satellite data for assessing drought in Somalia during the period 2000-2011.
  • Zhang, N., 2012: Automated plane detection and extraction from airborne laser scanning data of dense urban areas.
  • Ghezahai, S. B., 2011: Assessing vegetation changes for parts of the Sudan and Chad during 2000-2010 using time series analysis of MODIS-NDVI.
  • Sallaba, F., 2011: The potential of support vector machine classification of land use and land cover using seasonality from MODIS satellite data.
  • Timiza, W., 2011: Climate variability and satellite : observed vegetation responses in Tanzania.
  • Gunlycke, N. & Tuomaala, A., 2011: Detecting forest degradation in Marakwet district, Kenya, using remote sensing and GIS : in cooperation with SCC-Vi Agroforestry : a minor field study.
  • Jahan, R., 2010: Vegetation indices, FAPAR and spatial seasonality analysis of crops in southern Sweden.
  • Arfat, Y., 2010: Land use / land cover change detection and quantification : a case study in eastern Sudan.
  • Jin, H., 2010: Drivers of global wildfires - statistical analyses.
  • Guzinski, R., 2010, Comparison of vegetation indices to determine their accuracy in predicting phenology of Swedish ecosystems.
  • Bergman, C., 2009, En undersökning av samband mellan förändringar i fenologi och temperatur 1982-2005 med hjälp av GIMMS datasetet och klimatdata från SMHI.
  • Persson, P., 2007: Investigating the impact of ground reflectance on satellite estimates of forest leaf area index.
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Department of Physical Geography and Ecosystem Science
Lund University
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