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Lund Earth Observation research group

Remote sensing and Earth observation

Remote sensing is the technique of observing and analyzing objects from a distance without being in direct contact with them. When studying the Earth we often use the term Earth observation, which covers also the gathering of information about Earth by supplementary surveying techniques. Earth observation data are used for mapping the spatial and temporal distribution of Earth surface objects and features and for estimating the distribution of properties such as land vegetation biomass and land or ocean surface temperature.

About the LEO research group

The Lund Earth Observation (LEO) research group uses Earth observation data in a wide variety of environmental research projects, particularly focusing on the distribution and functioning of land vegetation.

Examples of our work include:
  • Estimating carbon uptake by land vegetation
  • Monitoring vegetation conditions in African drylands
  • Developing methods for assessing the impact of insect damage on forest vegetation
  • Extracting vegetation phenology information from satellite time series data
  • Monitoring biodiversity in semi-arid grasslands
You find more information via the link More about Earth observation in the left menu.

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More about Earth observation

Earth observation and the LEO group

Earth observation techniques allow us to view the ground using data from satellites or airplanes. Sensors and cameras on-board these platforms collect data about the atmosphere, land surface and oceans. The most common Earth observation systems measure reflected visible light, but they can also measure electromagnetic radiation that is invisible to the human eye, e.g. ultraviolet (UV), infrared (IR) or microwave radiation. The fact that satellites measure in different spectral wavelengths is utilized for obtaining information about the objects, features or properties under study.

Some meteorological satellites are located at about 36000 km above the equator, whereas other meteorological and Earth resource satellites circle Earth at about 800 km altitude. Some satellites image Earth frequently with low spatial detail, whereas others view Earth infrequently with very high spatial resolution, in some cases less than a meter. Data sets derived from satellites exist from the 1960s. Today, a large number of satellites generate data at a variety of spatial and temporal resolutions. These are useful for studying different parts of our environment, such as the atmosphere, land vegetation, oceans or ice masses.

The LEO group works with Earth observation applications for land resources, primarily vegetation and land cover/land use. Issues that interest us are:
  • Monitoring changes in vegetation cover in different climate regions
  • Extracting information about vegetation structure, such as the leaf area index (LAI)
  • Extracting information about carbon uptake by vegetation, e.g. through estimation of the fraction of incoming photosynthetically active radiation absorbed by vegetation (FAPAR)
  • Improving current methods for quantitative Earth observation of vegetation, e.g. handling different viewing and sun angles
  • Developing methods for handling time series of Earth observation data
  • Integrating Earth observation data with ecosystem models describing the development of plant stands

How do I learn more about Earth observation (remote sensing)?

Check this link or visit the department educational pages for more information.

 

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Education and training in Earth observation

Courses

The department offers several courses in Earth observation (remote sensing), both for students in physical geography and ecosystems analysis and for students in other science fields, such as land surveying, environmental science, forestry, agronomy and biology. Teaching is given in Lund or via Internet. Our Earth observation courses (called remote sensing courses at the department educational pages) are oriented towards land applications and include analysis of digital optical satellite data and aerial imagery. Among other we offer campus courses at full time (NGEN08: 15 ECTS) and half time (NGEN09: 7.5 ECTS).

Apart from academic courses we can offer tailored hands-on training courses according to client specifications.

See the department educational pages for more information.

We also offer post-graduate training in Earth observation. All open positions are advertised at the main Lund University web pages and can be applied for on-line. Search for jobs for doctoral students from these pages.

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People and publications

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

Researchers

Ph.D. students

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.
 

External links

Swedish National Space Board (SNSB, Swedish: Rymdstyrelsen)

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European Space Agency (ESA)

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National Aeronautics and Space Administration (NASA)

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