Evaluation of UAV and satellite-derived NDVI to map maritime Antarctic vegetation

Sotille, Maria Eliza; Bremer, Ulisses Franz; Vieira, Gonçalo; Velho, Luiz Felipe Machado; Petsch, Carina; Simões, Jefferson Cárdia

doi:10.1016/j.apgeog.2020.102322

Cited by 38 publications

(29 citation statements)

References 37 publications

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“…Therefore, NDVI should be used preferably in the studies focused on metabolic/physiological activity of vegetation than in the classification of vegetation component and their coverage area. It is because of the fact that some cryptogamic species exhibit low reflectance in the near-infrared region and are not easily detected by NDVI (Sotille et al 2020). This may complicate NDVI-based determination of species or vegetation functional groups (e.g.…”

Section: Ndvi Msr CI Greenmentioning

confidence: 99%

Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts.

Váczi¹,

Barták²,

Bednaříková³

et al. 2020

Czech Polar Rep.

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In this study, we investigated the utility of spectral remote sensing data gathered by a multispectral camera for estimating of vegetation cover in Antarctic vegetation oasis and Arcto-Alpine tundra. The surveys exploiting unmanned aerial vehicles (UAV) and multispectral camera were done in an Antarctic vegetation oasis located at the Northern shore of James Ross Island (Antarctica), and arcto-alpine tundra located in the Jeseníky Mts. (NE Czech Republic, 1 420 m a.s.l.). For the two locations, false colour images of spectral indices (VARI, NGRDI, GLI, RGVI, ExG, NDVI, PRI) were taken and analysis of vegetation types and components of vegetation cover done. Additionally, field research was performed by handheld instruments measuring NDVI, PRI and of selected vegetation components: Bryum pseudotriquetrum, Nostoc commune colonies (Antarctica), lichens grown on flat stones and boulders (the Jeseníky Mts.). The results show UAV photo surveys and imaging of spectral reflectance indices can be used to monitor vegetation types forming Antarctic vegetation oases and arcto-alpine tundra.

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Section: Ndvi Msr CI Greenmentioning

confidence: 99%

Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts.

Váczi¹,

Barták²,

Bednaříková³

et al. 2020

Czech Polar Rep.

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show abstract

“…2). For the similarity analysis based on the presence or absence of penguin influence, two areas were defined: A1 (biotic influence) and A2 (no influence), which were delimited from the Operational Land Image (OLI)/Thermal Infrared Sensor (TIRS) image Landsat 8/2014 RGB (bands 5 4 3 infrared composite) (Sotille et al 2020), where the colouring reflected from this composition was used to locate the area of the penguin influence using QGis ® v 3.0.3 software. In addition, the area of penguin influence was also visually identified during the field survey, corroborating the RGB composition.…”

Section: Methodsmentioning

confidence: 99%

Section: Data Analysesmentioning

confidence: 99%

Patterns of moss richness in Admiralty Bay, King George Island, cannot be explained by geological or ornithogenic drivers alone

et al. 2022

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We set out to document the diversity and distribution of bryophytes in Admiralty Bay and thereby enable the identification of patterns in local diversity and their possible drivers. Combining data extracted from different sources and recent collections, we documented the presence of 63 species. Similarity analyses of moss species diversity in relation to underlying geology and ornithogenic influence identified an identical cophenetic correlation coefficient of 0.744 for both factors. The Sørensen index was < 0.6, indicating that the groups share < 60% of the species recorded. The data showed that the selected filters (ornithogenic soils, non-ornithogenic soils and different geological extracts) did not underlie consistent species groupings, and we conclude that other environmental and topographical factors are likely to be responsible for shaping the moss community structure in Admiralty Bay. To enable effective management of Antarctic Specially Managed Area (ASMA) No. 1 and Antarctic Specially Protected Area (ASPA) No. 128, robust assessments of the local ecosystem and biodiversity are necessary to assist in the decision-making processes mandated under the Antarctic Treaty System, one of whose founding principles is the preservation of the Antarctic ecosystem.

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“…Fretwell et al [20] and Casanovas et al [21,22] studied the distribution of Antarctic vegetation using the Normalized Difference Vegetation Index (NDVI) and the matched filtering (MF) approach derived from Landsat images, but the research were unable to identify a pattern between the NDVI values and the vegetation types. Sotille et al [23] assessed the ability of the NDVI from unmanned aerial vehicle (UAV), Sentinel-2, and Landsat 8 to identify vegetated areas in the ice-free environment of Hope Bay, Antarctic Peninsula, and showed that the NDVI values provided by different sensors were not identical for the same vegetation class. More problematically, because polar vegetation clusters are usually very small [24], a pixel with a decameter spatial resolution usually includes a mix of plants, rocks, soil, and snow backgrounds, leading to poor classification results.…”

Section: Introductionmentioning

confidence: 99%

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

Sun

et al. 2021

Remote Sensing

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In polar regions, vegetation is especially sensitive to climate dynamics and thus can be used as an indicator of the global and regional environmental change. However, in Antarctica, there is very little information on vegetation distribution and growth status. To fill this gap, we evaluated the ability of both linear and nonlinear spectral mixture analysis (SMA) models, including a group of newly developed modified Nascimento’s models for Antarctic vegetated areas (MNM-AVs), in estimating the abundance of major Antarctic vegetation types, i.e., mosses and lichens. The study was conducted using WorldView-2 satellite data and field measurements over the Fildes Peninsula and its surroundings, which are representative vegetated areas in Antarctica. In MNM-AVs, we introduced secondary scattering components for vegetation and its background to account for the sparsity of vegetation cover and reassigned their coefficients. The new models achieved improved performances, among which MNM-AV3 achieved the lowest error for mosses (lichens) abundance estimation with RMSE = 0.202 (0.213). Compared with MNM-AVs, the linear model performed particularly poor for lichens (RMSE = 0.322), which is in contrast to the case of mosses (RMSE = 0.212), demonstrating that spectral signals of lichens are more prone to mix with their backgrounds. Abundance maps of mosses and lichens, as well as a map of moss health status for the entire study area, were then obtained based on MNM-AV3 with around 80% overall accuracy. Moss areas account for 0.7695 km2 in Fildes and 0.3259 km2 in Ardley Island; unhealthy mosses amounted to 40% (49%) of the area in the summer of 2018 (2019), indicating considerable environmental stress.

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Evaluation of UAV and satellite-derived NDVI to map maritime Antarctic vegetation

Cited by 38 publications

References 37 publications

Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts.

Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts.

Patterns of moss richness in Admiralty Bay, King George Island, cannot be explained by geological or ornithogenic drivers alone

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

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