Barjeece Bashir , Dong Liang , Rong Cai , Faisal Mumtaz , Lingyi Kong , Yahui Zou
{"title":"南极半岛雪藻华的光谱特性与遥感","authors":"Barjeece Bashir , Dong Liang , Rong Cai , Faisal Mumtaz , Lingyi Kong , Yahui Zou","doi":"10.1016/j.rse.2025.114839","DOIUrl":null,"url":null,"abstract":"<div><div>Snow algae, microscopic organisms thriving in snow-covered environments, significantly affect snow albedo and broader climatic processes. This study introduces the Algae Presence Index (API), a novel spectral tool using Sentinel-2 multispectral imagery to detect and classify red and green algae on King George Island, Antarctica. From 2019 to 2023, we analyzed temporal and spatial variations in algae presence during austral summers and observed corresponding reductions in surface albedo, demonstrating how algal blooms influence snowmelt. Green algae showed a stronger albedo reduction (up to 8.46 %) compared to red algae (5.33 %), emphasizing their greater role in accelerating snowmelt. The API outperformed traditional indices, such as the red/green band ratio and Red-Green Normalized Difference. It eliminated spectral overlap and accurately distinguished algae types from algae-free snow. These findings underscore the critical role of snow algae in climate feedback mechanisms and highlight the importance of monitoring their growth during Antarctic warming. This methodology provides a robust framework for assessing algae impacts on the cryosphere, with important implications for climate models and conservation.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114839"},"PeriodicalIF":11.4000,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spectral properties and remote sensing of snow algal blooms in the Antarctic Peninsula\",\"authors\":\"Barjeece Bashir , Dong Liang , Rong Cai , Faisal Mumtaz , Lingyi Kong , Yahui Zou\",\"doi\":\"10.1016/j.rse.2025.114839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Snow algae, microscopic organisms thriving in snow-covered environments, significantly affect snow albedo and broader climatic processes. This study introduces the Algae Presence Index (API), a novel spectral tool using Sentinel-2 multispectral imagery to detect and classify red and green algae on King George Island, Antarctica. From 2019 to 2023, we analyzed temporal and spatial variations in algae presence during austral summers and observed corresponding reductions in surface albedo, demonstrating how algal blooms influence snowmelt. Green algae showed a stronger albedo reduction (up to 8.46 %) compared to red algae (5.33 %), emphasizing their greater role in accelerating snowmelt. The API outperformed traditional indices, such as the red/green band ratio and Red-Green Normalized Difference. It eliminated spectral overlap and accurately distinguished algae types from algae-free snow. These findings underscore the critical role of snow algae in climate feedback mechanisms and highlight the importance of monitoring their growth during Antarctic warming. This methodology provides a robust framework for assessing algae impacts on the cryosphere, with important implications for climate models and conservation.</div></div>\",\"PeriodicalId\":417,\"journal\":{\"name\":\"Remote Sensing of Environment\",\"volume\":\"328 \",\"pages\":\"Article 114839\"},\"PeriodicalIF\":11.4000,\"publicationDate\":\"2025-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing of Environment\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0034425725002433\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing of Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0034425725002433","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Spectral properties and remote sensing of snow algal blooms in the Antarctic Peninsula
Snow algae, microscopic organisms thriving in snow-covered environments, significantly affect snow albedo and broader climatic processes. This study introduces the Algae Presence Index (API), a novel spectral tool using Sentinel-2 multispectral imagery to detect and classify red and green algae on King George Island, Antarctica. From 2019 to 2023, we analyzed temporal and spatial variations in algae presence during austral summers and observed corresponding reductions in surface albedo, demonstrating how algal blooms influence snowmelt. Green algae showed a stronger albedo reduction (up to 8.46 %) compared to red algae (5.33 %), emphasizing their greater role in accelerating snowmelt. The API outperformed traditional indices, such as the red/green band ratio and Red-Green Normalized Difference. It eliminated spectral overlap and accurately distinguished algae types from algae-free snow. These findings underscore the critical role of snow algae in climate feedback mechanisms and highlight the importance of monitoring their growth during Antarctic warming. This methodology provides a robust framework for assessing algae impacts on the cryosphere, with important implications for climate models and conservation.
期刊介绍:
Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing.
The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques.
RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.