Image_2_Semi-Automated Analysis of Digital Photographs for Monitoring East Antarctic Vegetation.tif
Climate change is affecting Antarctica and minimally destructive long-term monitoring of its unique ecosystems is vital to detect biodiversity trends, and to understand how change is affecting these communities. The use of automated or semi-automated methods is especially valuable in harsh polar env...
Main Authors: | , , , , , , |
---|---|
Format: | Still Image |
Language: | unknown |
Published: |
2020
|
Subjects: | |
Online Access: | https://doi.org/10.3389/fpls.2020.00766.s002 https://figshare.com/articles/Image_2_Semi-Automated_Analysis_of_Digital_Photographs_for_Monitoring_East_Antarctic_Vegetation_tif/12451229 |
id |
ftfrontimediafig:oai:figshare.com:article/12451229 |
---|---|
record_format |
openpolar |
spelling |
ftfrontimediafig:oai:figshare.com:article/12451229 2023-05-15T14:01:32+02:00 Image_2_Semi-Automated Analysis of Digital Photographs for Monitoring East Antarctic Vegetation.tif Diana H. King Jane Wasley Michael B. Ashcroft Ellen Ryan-Colton Arko Lucieer Laurie A. Chisholm Sharon A. Robinson 2020-06-09T04:57:54Z https://doi.org/10.3389/fpls.2020.00766.s002 https://figshare.com/articles/Image_2_Semi-Automated_Analysis_of_Digital_Photographs_for_Monitoring_East_Antarctic_Vegetation_tif/12451229 unknown doi:10.3389/fpls.2020.00766.s002 https://figshare.com/articles/Image_2_Semi-Automated_Analysis_of_Digital_Photographs_for_Monitoring_East_Antarctic_Vegetation_tif/12451229 CC BY 4.0 CC-BY Botany Plant Biology Plant Systematics and Taxonomy Plant Cell and Molecular Biology Plant Developmental and Reproductive Biology Plant Pathology Plant Physiology Plant Biology not elsewhere classified Antarctica moss vegetation cover vegetation health climate change monitoring OBIA RGB Image Figure 2020 ftfrontimediafig https://doi.org/10.3389/fpls.2020.00766.s002 2020-06-10T22:54:10Z Climate change is affecting Antarctica and minimally destructive long-term monitoring of its unique ecosystems is vital to detect biodiversity trends, and to understand how change is affecting these communities. The use of automated or semi-automated methods is especially valuable in harsh polar environments, as access is limited and conditions extreme. We assessed moss health and cover at six time points between 2003 and 2014 at two East Antarctic sites. Semi-automatic object-based image analysis (OBIA) was used to classify digital photographs using a set of rules based on digital red, green, blue (RGB) and hue-saturation-intensity (HSI) value thresholds, assigning vegetation to categories of healthy, stressed or moribund moss and lichens. Comparison with traditional visual estimates showed that estimates of percent cover using semi-automated OBIA classification fell within the range of variation determined by visual methods. Overall moss health, as assessed using the mean percentages of healthy, stressed and moribund mosses within quadrats, changed over the 11 years at both sites. A marked increase in stress and decline in health was observed across both sites in 2008, followed by recovery to baseline levels of health by 2014 at one site, but with significantly more stressed or moribund moss remaining within the two communities at the other site. Our results confirm that vegetation cover can be reliably estimated using semi-automated OBIA, providing similar accuracy to visual estimation by experts. The resulting vegetation cover estimates provide a sensitive measure to assess change in vegetation health over time and have informed a conceptual framework for the changing condition of Antarctic mosses. In demonstrating that this method can be used to monitor ground cover vegetation at small scales, we suggest it may also be suitable for other extreme environments where repeat monitoring via images is required. Still Image Antarc* Antarctic Antarctica Frontiers: Figshare Antarctic |
institution |
Open Polar |
collection |
Frontiers: Figshare |
op_collection_id |
ftfrontimediafig |
language |
unknown |
topic |
Botany Plant Biology Plant Systematics and Taxonomy Plant Cell and Molecular Biology Plant Developmental and Reproductive Biology Plant Pathology Plant Physiology Plant Biology not elsewhere classified Antarctica moss vegetation cover vegetation health climate change monitoring OBIA RGB |
spellingShingle |
Botany Plant Biology Plant Systematics and Taxonomy Plant Cell and Molecular Biology Plant Developmental and Reproductive Biology Plant Pathology Plant Physiology Plant Biology not elsewhere classified Antarctica moss vegetation cover vegetation health climate change monitoring OBIA RGB Diana H. King Jane Wasley Michael B. Ashcroft Ellen Ryan-Colton Arko Lucieer Laurie A. Chisholm Sharon A. Robinson Image_2_Semi-Automated Analysis of Digital Photographs for Monitoring East Antarctic Vegetation.tif |
topic_facet |
Botany Plant Biology Plant Systematics and Taxonomy Plant Cell and Molecular Biology Plant Developmental and Reproductive Biology Plant Pathology Plant Physiology Plant Biology not elsewhere classified Antarctica moss vegetation cover vegetation health climate change monitoring OBIA RGB |
description |
Climate change is affecting Antarctica and minimally destructive long-term monitoring of its unique ecosystems is vital to detect biodiversity trends, and to understand how change is affecting these communities. The use of automated or semi-automated methods is especially valuable in harsh polar environments, as access is limited and conditions extreme. We assessed moss health and cover at six time points between 2003 and 2014 at two East Antarctic sites. Semi-automatic object-based image analysis (OBIA) was used to classify digital photographs using a set of rules based on digital red, green, blue (RGB) and hue-saturation-intensity (HSI) value thresholds, assigning vegetation to categories of healthy, stressed or moribund moss and lichens. Comparison with traditional visual estimates showed that estimates of percent cover using semi-automated OBIA classification fell within the range of variation determined by visual methods. Overall moss health, as assessed using the mean percentages of healthy, stressed and moribund mosses within quadrats, changed over the 11 years at both sites. A marked increase in stress and decline in health was observed across both sites in 2008, followed by recovery to baseline levels of health by 2014 at one site, but with significantly more stressed or moribund moss remaining within the two communities at the other site. Our results confirm that vegetation cover can be reliably estimated using semi-automated OBIA, providing similar accuracy to visual estimation by experts. The resulting vegetation cover estimates provide a sensitive measure to assess change in vegetation health over time and have informed a conceptual framework for the changing condition of Antarctic mosses. In demonstrating that this method can be used to monitor ground cover vegetation at small scales, we suggest it may also be suitable for other extreme environments where repeat monitoring via images is required. |
format |
Still Image |
author |
Diana H. King Jane Wasley Michael B. Ashcroft Ellen Ryan-Colton Arko Lucieer Laurie A. Chisholm Sharon A. Robinson |
author_facet |
Diana H. King Jane Wasley Michael B. Ashcroft Ellen Ryan-Colton Arko Lucieer Laurie A. Chisholm Sharon A. Robinson |
author_sort |
Diana H. King |
title |
Image_2_Semi-Automated Analysis of Digital Photographs for Monitoring East Antarctic Vegetation.tif |
title_short |
Image_2_Semi-Automated Analysis of Digital Photographs for Monitoring East Antarctic Vegetation.tif |
title_full |
Image_2_Semi-Automated Analysis of Digital Photographs for Monitoring East Antarctic Vegetation.tif |
title_fullStr |
Image_2_Semi-Automated Analysis of Digital Photographs for Monitoring East Antarctic Vegetation.tif |
title_full_unstemmed |
Image_2_Semi-Automated Analysis of Digital Photographs for Monitoring East Antarctic Vegetation.tif |
title_sort |
image_2_semi-automated analysis of digital photographs for monitoring east antarctic vegetation.tif |
publishDate |
2020 |
url |
https://doi.org/10.3389/fpls.2020.00766.s002 https://figshare.com/articles/Image_2_Semi-Automated_Analysis_of_Digital_Photographs_for_Monitoring_East_Antarctic_Vegetation_tif/12451229 |
geographic |
Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic Antarctica |
genre_facet |
Antarc* Antarctic Antarctica |
op_relation |
doi:10.3389/fpls.2020.00766.s002 https://figshare.com/articles/Image_2_Semi-Automated_Analysis_of_Digital_Photographs_for_Monitoring_East_Antarctic_Vegetation_tif/12451229 |
op_rights |
CC BY 4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.3389/fpls.2020.00766.s002 |
_version_ |
1766271383928569856 |