Monitoring biodiversity in cultural landscapes: development of remote sensing- and GIS-based methods

Abstract: In this thesis, I explore the relationships between structural and compositional landscape properties, and species diversity, using remotely sensed data on a variety of spatial scales. The thesis shows that increased landscape heterogeneity, measured using environmental and spectral variables that were used both separately and combined, is generally positively related to plant species richness. I further found that plant species richness could be predicted with <20% deviance in species numbers, in approximately 80% of the study area within the province of Scania, using a combination of environmental and spectral descriptors of landscape heterogeneity. Further, I used Landsat satellite data, aided by ancillary data on topography and a spectral proxy of seasonal variation in vegetation phenology, to classify historical (ca 1975) and contemporary (ca 2001) land-cover data within the province of Scania, with +85% accuracy. The produced land use/land cover (LULC) data showed correlations with levels of plant species richness, with the proportion of cropland generally being negatively correlated to levels of plant species richness, and the proportion of LULC classes such as grazed grassland, wetland and deciduous forest being positively correlated to levels of plant species richness. Further, the positive change between the historical and contemporary landscapes in the proportion of deciduous forest, and in the number of unique LULC patches, were positively correlated with contemporary levels of plant species richness. I modeled the importance of non-crop habitat types for plant species richness within the province of Scania, and showed that for the promotion of plant species richness, the most wide-spread non-crop LULC types were most important within the most simplified landscapes, while the amount of non-crop small biotopes were most important in more complex landscapes.In a series of studies on grazed grasslands on the Baltic island of Öland, I showed that dissimilarity in Worldview-2 satellite spectral reflectance was related to plant species dissimilarity within a set of grassland plots, and then used spectral dissimilarity to predict levels of plant species richness in other grassland plots. I used HySpex hyperspectral aerial reflectance data to predict plant species diversity (species richness and Simpson’s diversity), using the full range of wavebands and also using a reduced set of wavebands. Finally, I classified grassland plots into age classes using reflectance data from the HySpex hyperspectral sensor, and achieved better classification results when using a reduced set of wavebands compared to using the full range of wavebands.In summary, the findings of this thesis demonstrate that remote sensing and GIS-based methods can be useful tools in the monitoring of cultural landscapes, because of their combined ability to model landscape properties and relate those measures to species diversity, at a range of spatial scales and within a range of habitats.