Multitemporal histogram matching - a new approach of moss and lichen change detection from landsat in datapoor antarctica environments

Abstract

Mosses and lichens are important components of Antarctic ecosystems. Maps of these vegetation are needed to improve our understanding of ecosystem dynamics. This requires species distribution to be mapped repeatedly over time, a critical task that becomes extremely challenging in data-poor Antarctic regions, where the lack of field data, logistics, coupled with scarcity of cloud free, quality multitemporal Landsat imagery are major intrinsic constraints to time-series analysis for change detection. This study firstly analyzes the spectral curves of moss and lichen generated by field-based spectroradiometer and then proposes an innovative histogram matching technique where historical Landsat data is modified such that its histogram matches that of present (reference) dataset. This has made it possible to mapping multitemporal Landsat data in the Antarctic Peninsula. The results demonstrate an overall accuracy of 90.5%. Mapping of Arctic vegetation facilitated by histogram matching of Landsat image, according to the results, seems to be an advisable image processing technique for application in a data-poor context.