Mapping lichen abundance in ice-free areas of Larsemann Hills, East Antarctica using remote sensing and lichen spectra

IF 1.5 4区 地球科学 Q3 ECOLOGY Polar Science Pub Date : 2023-12-01 DOI:10.1016/j.polar.2023.100976
Chandra Prakash Singh , Harsh Joshi , Dhruvkumar Kakadiya , Malay S. Bhatt , Rajesh Bajpai , Ramya Ranjan Paul , D.K. Upreti , Shailendra Saini , Mirza Javed Beg , Anant Pande , Naveen Tripathi , Kiledar Singh Tomar , Sandip R. Oza , Mehul R. Pandya , Bimal K. Bhattacharya
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Abstract

Lichen communities are known to be most resistant and adapted organisms to the extreme environments; however, their abundance is not well mapped. Extensive lichen surveys were conducted as part of the 39th Indian scientific expedition and in-situ spectra (350 nm–2500 nm) of lichens were collected in the Larsemann Hills, East Antarctica during austral summer of 2020. Lichen abundance mapping was carried out with the help of Sentinel-2 MSI L2 data and surveyed records along with in-situ spectra. We generated feature collections for lichen, snow, water, bare surface and trained a random forest (RF) classification algorithms implemented in GEE and generated multi-class outputs. We finally merged all non-lichen classes and produced binary pixels with a confidence value (between 0 and 100) depicting similarity of its spectral response to that of a lichen pixel. Total 92 lichen points, 20 bare rock points, 26 points of water and 74 snow points were used to generate the probabilistic lichen abundance map. Resubstitution accuracy of 97.31% was obtained with 10 number of RF trees. Validation was done with geotagged ground photographs having 232 lichens, 20 bare rocks, 22 water and 69 snow points and achieved test accuracy of 82.44%.

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利用遥感和地衣光谱绘制南极洲东部拉尔森山无冰区地衣丰度图
众所周知,地衣群落是最能抵抗和适应极端环境的生物;然而,它们的丰度却没有得到很好的描绘。作为第 39 次印度科学考察的一部分,我们进行了广泛的地衣调查,并于 2020 年夏季在南极洲东部的拉尔斯曼山收集了地衣的原位光谱(350 nm-2500 nm)。在哨兵-2 MSI L2 数据和勘测记录以及原位光谱的帮助下,绘制了地衣丰度图。我们生成了地衣、雪、水和裸露地表的特征集合,并训练了在 GEE 中实施的随机森林(RF)分类算法,生成了多类输出结果。最后,我们合并了所有非地衣类别,并生成了二进制像素,其置信度值(介于 0 和 100 之间)表示其光谱响应与地衣像素的相似度。地衣丰度概率图共使用了 92 个地衣点、20 个裸岩点、26 个水域点和 74 个雪域点。使用 10 棵射频树的重置准确率为 97.31%。使用带有地理标记的 232 个地衣点、20 个裸岩点、22 个积水点和 69 个积雪点的地面照片进行了验证,测试准确率为 82.44%。
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来源期刊
Polar Science
Polar Science ECOLOGY-GEOSCIENCES, MULTIDISCIPLINARY
CiteScore
3.90
自引率
5.60%
发文量
46
期刊介绍: Polar Science is an international, peer-reviewed quarterly journal. It is dedicated to publishing original research articles for sciences relating to the polar regions of the Earth and other planets. Polar Science aims to cover 15 disciplines which are listed below; they cover most aspects of physical sciences, geosciences and life sciences, together with engineering and social sciences. Articles should attract the interest of broad polar science communities, and not be limited to the interests of those who work under specific research subjects. Polar Science also has an Open Archive whereby published articles are made freely available from ScienceDirect after an embargo period of 24 months from the date of publication. - Space and upper atmosphere physics - Atmospheric science/climatology - Glaciology - Oceanography/sea ice studies - Geology/petrology - Solid earth geophysics/seismology - Marine Earth science - Geomorphology/Cenozoic-Quaternary geology - Meteoritics - Terrestrial biology - Marine biology - Animal ecology - Environment - Polar Engineering - Humanities and social sciences.
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