Landsat TM images in mapping of semi-natural grasslands and analysing of habitat pattern in an agricultural landscape in south-west Finland

Abstract

Decision-making in land-use and conservation planning requires relevant and good quality information over wide areas, collected in a cost-efficient manner. This study focuses on the use of medium-resolution satellite imagery in landscape level studies of habitat pattern, particularly in fragmented agricultural landscapes. We analysed the suitability of multi-temporal Landsat TM images in habitat mapping, in particular for the discrimination of semi-natural grasslands. The results showed that even patchy agricultural mosaics can be coarsely mapped with Landsat TM and that the use of multi-temporal imagery notably improves the classification results. The best classification result (total accuracy 89%) was achieved with early spring, midsummer and late summer images combined. The classification accuracy for semi-natural grasslands was relatively low overall (63%), but over 90% of large (> 1 ha) patches were discriminated. Furthermore, we compared a set of landscape composition and structure indices calculated from 1) a Landsat TM -based habitat classification (25 m resolution) and 2) a habitat map derived from aerial photographs (2 m resolution). The compositional indices, diversity index and patch sizes gave
similar results on both scales. Finally, the habitat pattern of the study area was described using the calculated compositional, structural and environmental indices, and three main landscape types were identified.