Assessing of land use intensity (LUI) with remote sensing

Authors and Affiliations: 

Lausch, Angela *1/2; Wellmann, Thilo 2; Haase, Dagmar2; Knapp, Sonja3; Selsam, Peter4

1 Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research – UFZ, Permoserstr. 15, D-04318 Leipzig, Germany

2 Humboldt Universität zu Berlin, Department of Geography, Lab for Landscape Ecology, Rudower Chaussee 16, 12489 Berlin, Germany, Germany

3 Department of Community Ecology, Helmholtz Centre for Environmental Research – UFZ, Theodor-Lieser-Str. 4, D-06120 Halle (Saale), Germany

4 Department of Geography, Friedrich Schiller University, Friedrich Schiller University Jena, Loebdergraben 32, D-07743 Jena, Germany

Corresponding author: 
Angela Lausch
Email: 
angela.lausch@ufz.de
Abstract: 

Adding attributes of space and time to the spectral traits (ST) concept (Lausch et al., 2016, 2017) we developed a completely new way for the quantification and assessment of land use intensity and hemeroby of urban landscapes. With spectral traits variations (STV) from remote sensing (RS) data, we show how to approximate human land use intensity and the degree of hemeroby for large spatial areas with a dense temporal resolution.
With the presented modelling framework, types of land use cover could be separated according to their degree of hemeroby and the land use intensity, respectively. Moreover, since the concept of plant traits is a functional framework in which each trait can be assigned to one or more ecosystem functions, the assessment of STV is a promising step towards the assessment of functional diversity and related functions in an ecosystem. The usage of RS data thus opens up the opportunity of spatially continuous comparisons of whole landscapes over longer periods of time, independent of categorical land-use classifications (Wellmann et al., 2017).

References: 

Lausch, A., Bannehr, L., Beckmann, M., Boehm, C., Feilhauer, H., Hacker, J.M., Heurich, M., Jung, A., Klenke, R., Neumann, C., Pause, M., Rocchini, D., Schaepman, M.E.; Schmidtlein, S., Schulz, K., Selsam, P., Settele, J., Skidmore, A.K., Cord, A.F., 2016. Linking Earth Observation and taxonomic, structural and functional biodiversity: Local to ecosystem perspectives. Ecological Indicators 70., 317-339., doi: 10.1016/j.ecolind.2016.06.022.

Lausch, A., Erasmi, S., Douglas, J., King, Magdon, P., Heurich, M., 2016. Understanding forest health with remote sensing - Part I - A review of spectral traits, processes and remote sensing characteristics. Remote Sensing 8, 1029; doi:10.3390/rs8121029.

Wellmann, Thilo, Haase, Dagmar, Knapp, Sonja, Chistoph Salbach, Selsam, Peter, Lausch, Angela, 2017. Spatio-temporal spectral traits of earth observation for quantifying and assessing urban land use intensity. (subm. Ecological Indicators)

Symposium: 
Beyond the mosaic: a better characterisation of landscapes would help to understand ecological patterns and processes
Oral or poster: 
Oral presentation
Abstract order: 
4