Bretton Woods -instituutioiden köyhyysdiskurssi ja sen rakentuminen : tapaustutkimus Tansanian vuosien 2000-2007 köyhyydenvähennysstrategiapapereista

What makes segmentation good? A case study in boreal forest habitat mapping

Segmentation goodness evaluation is a set of approaches meant for deciding which segmentation is good. In this study, we tested different supervised segmentation evaluation measures and visual interpretation in the case of boreal forest habitat mapping in Southern Finland. The data used were WorldView-2 satellite imagery, a lidar digital elevation model (DEM), and a canopy height model (CHM) in 2 m resolution. The segmentation methods tested were the fractal net evolution approach (FNEA) and IDRISI watershed segmentation. Overall, 252 different segmentation methods, layers, and parameter combinations were tested. We also used eight different habitat delineations as reference polygons agains…

Coupling high-resolution satellite imagery with ALS-based canopy height model and digital elevation model in object-based boreal forest habitat type classification

We developed a classification workflow for boreal forest habitat type mapping. In object-based image analysis framework, Fractal Net Evolution Approach segmentation was combined with random forest classification. High-resolution WorldView-2 imagery was coupled with ALS based canopy height model and digital terrain model. We calculated several features (e.g. spectral, textural and topographic) per image object from the used datasets. We tested different feature set alternatives; a classification accuracy of 78.0 % was obtained when all features were used. The highest classification accuracy (79.1 %) was obtained when the amount of features was reduced from the initial 328 to the 100 most imp…

Kiintoaineen ja kasviravinteiden vesistökuormituksen riskialuekartoitus Aurajoen valuma-alueella

Developing and comparing methods for mapping habitat types and conservation values using remote sensing data and GIS methods

Monitoring peatland water table depth with optical and radar satellite imagery

Peatland water table depth (WTD) and wetness have widely been monitored with optical and synthetic aperture radar (SAR) remote sensing but there is a lack of studies that have used multi-sensor data, i.e., combination of optical and SAR data. We assessed how well WTD can be monitored with remote sensing data, whether multi-sensor approach boosts explanatory capacity and whether there are differences in regression performance between data and peatland types. Our data consisted of continuous multiannual WTD data from altogether 50 restored and undrained Finnish peatlands, and optical (Landsat 5–8, Sentinel-2) and Sentinel-1 C-band SAR data processed in Google Earth Engine. We calculated rando…

Comparing Conservation Value Maps and Mapping Methods in a Rural Landscape in Southern Finland

We tested to what extent conservation value maps are different if the valuation and mapping method is changed. We compared 66 different conservation value and 4 different ecosystem service maps. Using remote sensing and other georeferenced data, we produced 2 different habitat type maps, which were 50 % similar. We valued each mapped habitat type based on rarity corrected potential number of vascular plant species and naturalness using 6 different valuation alternatives. We mapped habitat type connectivity and complementarity using 2 main approaches. The habitat type valuation alternatives were quite similar, but if the habitat type naturalness was taken into account, differences were large…

The role of landscape, topography, and geodiversity in explaining vascular plant species richness in a fragmented landscape

We explained vascular plant species richness patterns in a 286 km(2) fragmented landscape with a notable human influence. The objective of this study was two-fold: to test the relative importance of landscape, topography and geodiversity measures, and to compare three different landscape-type variables in species richness modeling. Moreover, we tested if results differ when only native species are considered. We used generalized linear modeling based variation partitioning and generalized additive models with different explanatory variable sets. Landscape and topography explained the majority of the variation but the relative importance of topography and geodiversity was higher in explainin…