Geospatial mapping of vegetation in the Antarctic environment using very high-resolution WorldView-2 imagery

Abstract

A robust monitoring of the changes in the distribution and density of cryospheric plant species requires accurate and high-resolution baseline maps of vegetation. Mapping such change at the landscape scale is often problematic, particularly in remote areas, such as Antarctica. Vegetation mapping of plant communities at fine spatial scales is increasingly supported by remote sensing technology in cryospheric regions. Less frequent imaging with high spatial resolution satellite sensors enable more detailed analyses of vegetation change frequently. This study is the first to use high-resolution WorldView-2 (WV-2) imagery to classify vegetation communities on Antarctic oases and to provide semi-automated means to map vegetation, as an imperative indicator for environmental change. Multispectral imagery (MSI) and panchromatic imagery (PAN) from very high resolution WV-2 have been used for mapping of vegetation in different forms in Antarctic environment. A range of supervised classification methods have been executed using pansharpened WV-2 data. This study comparatively and statistically evaluates vegetation mapping results using supervised and unsupervised classification methods to extract vegetation in Larsemann Hills and Schirmacher oasis, east Antarctica. We also discuss on the use of supervised pixel-based classifiers and textural measures, in addition to standard multispectral information, to improve the classification of Antarctic vegetation communities. Classification results were validated with independent reference datasets. This work indicates that the overall accuracy of mapping vegetation using WV-2 imagery and semiautomated target extraction methods ranged from 90% to 94%.

Snow Albedo Seasonality and Trend from MODIS Sensor and Ground Data at Johnsons Glacier, Livingston Island, Maritime Antarctica

“…Landsat images were, first, converted to Top of Atmosphere (TOA) reflectance. Subsequently, the DOS (Dark Object Subtraction) algorithm [43] was applied to homogenize the TOA reflectance image, as previously done in snow-covered areas with World View-2 data in Antarctica [44] and Landsat 7 images over Patagonia [45]. Dark pixels were selected from the Drake Passage, where depths above 4000 m are reached in several areas.…”

Cambios climáticos y aumento de la vegetación en la Península Fildes, Antártica

“…Alguns dos fatores ambientais que afetam o crescimento da vegetação na Antártica são, de acordo com Jawak et al (2016), água disponível, riqueza de nutrientes, exposição a ventos, spray marinho e solos. Para o caso da península Fildes, dos 6 maiores campos de vegetação encontrados com a técnica de mapeamento por NDVI, 5 encontram-se na porção voltada para o estreito de Drake.…”

Vegetation Abundance and Health Mapping Over Southwestern Antarctica Based on WorldView-2 Data and a Modified Spectral Mixture Analysis

“…UAV with hyperspectral sensor and higher spatial resolution was used to measure the reflectance spectroscopic characteristics of mats in McMurdo Dry Valleys to determine whether mats' presence, types, and activities could be mapped at a spatial scale sufficient to characterize their interannual changes [28]. Relevant studies obtained vegetation distribution maps based on supervised classification methods including support vector machines [29], neural net classifiers [30], and spectral index ratios [31]. However, large training and verification datasets are difficult to collect in this region due to the harsh environmental conditions, severely limiting classification accuracy.…”