Remote Sensing for Sustainable Development

Phosphorus flowing via rivers into the Baltic Sea is a major source of nutrients, and in some cases the limiting factor for the growth of algae which causes the phenomenon known as eutrophication. Remote sensing of phosphorus, here using Landsat TM-data, can help to give a better understanding of the process of eutrophication. Since Landsat TM-data is used, this could form a basis for further spatio-temporal analysis in the Baltic Sea region. A method originally described and previously applied for the Quantang River (China) is here transferred and applied to three different rivers flowing into the Baltic Sea. The results show that by measuring the proxy variables of Secchi Depth and Chloryphyll-a the remote sensing model is able to explain 41% of the variance in total phosphorus for the rivers Dalälven, Norrström and Gavleån (Sweden) without any consideration taken to CDOM, turbidity or other local features. The study is based upon a multiple regression model that uses three proxies for total phosphorus. 1. Secchi Depth, here modeled as the ratio between TM band 1 and TM band 3 2. Chlorophyll-a, here modelled as the ratio between TM band 3 and TM band 2 3. The reflectance in wavelengths 0.45 – 0.52 μm (TM band 1) The results are validated against water chemistry data as provided by SLU where the total phosphorus is measured for different catchments at different intervals.