Riparian marshland composition and biomass mapping using Ikonos imagery

Abstract

The Ontario Wetland Evaluation System (OWES) employs mostly field-based visual assessments of wetland extent, composition, and productivity as primary indicators in determining which wetlands should be considered provincially significant and protected. A given wetland is generally assigned single attributes that are assumed to represent the whole wetland extent. High spatial resolution satellite remote sensing offers potential to map and monitor spatial variability of given attributes within a wetland. In this study, Ikonos imagery was used to map vegetation composition and biomass in three riparian marshes near Ottawa, Ontario. For vegetation composition mapping, separability and correlation analyses aided the selection of an optimum set of spectral and texture input variables. Several maximum likelihood classification tests for sets of terrestrial and aquatic vegetation classes gave best accuracies from 61% for seven classes to 88% for five classes. As an alternative, neural network classification was tested using various configurations of input variables and data. However, the best results did not match those from the maximum likelihood classification. For biomass mapping, dried green and senescent biomass collected at 75 locations were modelled using stepwise forward multiple regression. The best model produced was the logarithm of green biomass against a combination of texture and spectral variables (R2 = 0.61). It was applied to the image data to map green biomass with an absolute error of 213 g/m2, or approximately 40% of the mean field-measured biomass. Based on this error magnitude, the output map was aggregated into three classes of biomass (high, medium, and low) that showed a strong visual correspondence with the spatial distributions observed in the field. These results indicate strong potential for monitoring of vegetation composition and biomass changes within wetlands which may contribute to improvement of wetlands evaluation and monitoring in Ontario.