Skip to main content

Lund University

Lund University,
Dept. Phys. Geography & Ecosystem Science
Sölvegatan 12,
SE-223 62 Lund,


Lund University - Department of Physical Geography and Ecosystem Science (INES)

Lund University (LU) is the largest University in Scandinavia with 46000 students and 6000 staff with research and education within faculties of science, technology, law, social sciences, humanities and theology, medicine, economics and theatre and arts. Department of Physical Geography and Ecosystem Science employ about 50 researchers and 40 PhD candidates working within a range of topics including meteorology, climatology, GIS-science, remote sensing, biogeophysics, dynamic vegetation modelling and in-situ observations. Focus on research related to the carbon cycle and climate change.

Physical geography is the study of the Earth and the processes connected to it in the natural environment - in the atmosphere, hydrosphere, biosphere and geosphere. Important to many of these processes is the climate, and the study of the effects of climate and changes in climate is an important part of our research. Storms, bark beetle damage to forests and spring temperature backlashes. The carbon cycle from the Arctic to Africa. Mathematical modeling of vegetation and ecosystems, and the role of water in climate change. These are just some of the many different interdisciplinary areas where INES has excellent research. The department's research is mainly focused on interdisciplinary studies of how climate and environmental changes affect the function and composition of terrestrial ecosystems. We combine field studies in many different places in the world with work in laboratories and computer simulations . The goal is to increase understanding of the processes that take place in the exchange between the biosphere and atmosphere, hydrosphere and geosphere, not least under different climatic and environmental changes. The GIS Centre is professional in developing and applying GIS, which can be used for everything from visualization of map data for environmental monitoring to analysis of spatial and temporal patterns of economic wealth /poverty.

Scroll to top