Shuai Yuan, Juepeng Zheng, Lixian Zhang, Runmin Dong, Yile Xing, Yuhan She, H. Fu, Ray C. C. Cheung
{"title":"冰川融化:乞力马扎罗山37年(1984-2020)高分辨率冰川覆盖记录","authors":"Shuai Yuan, Juepeng Zheng, Lixian Zhang, Runmin Dong, Yile Xing, Yuhan She, H. Fu, Ray C. C. Cheung","doi":"10.1109/IGARSS46834.2022.9883229","DOIUrl":null,"url":null,"abstract":"Commonly recognized as an important symbol of the tropics and global warming, the glacier loss on Mt. Kilimanjaro has received worldwide attention for decades. In this paper, we propose a high-resolution glacier-cover (GC) record of Mt. Kilimanjaro over the period from 1984 to 2020, using a novel deep learning-based semantic segmentation method and Google Earth images, as well as digital elevation model (DEM) and ERA5-Land (ERA5) for snowline and temperature variations analysis. Our method achieves an accuracy of 94.37%, which proves the model's capability to record the GC areas precisely. The results show that (1) the GC area dramatically decreases from 19.2 km2 to 3.6 km2 during 37 years, which decreases about 4% and 2% per year from 1984 to 2000 and from 2000 to 2020 respectively, (2) the snowline altitude rises from $4,651 m$ to $5,088 m$ by about $437 m$, and (3) the average $5,000 m$ air temperature on Mt. Kilimanjaro increases from −2.1 °C to −1.1 °C by about 1 °C. This study indicates that there will be no GC within a few decades if the current loss continues.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Melting Glacier: A 37-Year (1984–2020) High-Resolution Glacier-Cover Record of MT. Kilimanjaro\",\"authors\":\"Shuai Yuan, Juepeng Zheng, Lixian Zhang, Runmin Dong, Yile Xing, Yuhan She, H. Fu, Ray C. C. Cheung\",\"doi\":\"10.1109/IGARSS46834.2022.9883229\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Commonly recognized as an important symbol of the tropics and global warming, the glacier loss on Mt. Kilimanjaro has received worldwide attention for decades. In this paper, we propose a high-resolution glacier-cover (GC) record of Mt. Kilimanjaro over the period from 1984 to 2020, using a novel deep learning-based semantic segmentation method and Google Earth images, as well as digital elevation model (DEM) and ERA5-Land (ERA5) for snowline and temperature variations analysis. Our method achieves an accuracy of 94.37%, which proves the model's capability to record the GC areas precisely. The results show that (1) the GC area dramatically decreases from 19.2 km2 to 3.6 km2 during 37 years, which decreases about 4% and 2% per year from 1984 to 2000 and from 2000 to 2020 respectively, (2) the snowline altitude rises from $4,651 m$ to $5,088 m$ by about $437 m$, and (3) the average $5,000 m$ air temperature on Mt. Kilimanjaro increases from −2.1 °C to −1.1 °C by about 1 °C. This study indicates that there will be no GC within a few decades if the current loss continues.\",\"PeriodicalId\":426003,\"journal\":{\"name\":\"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IGARSS46834.2022.9883229\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IGARSS46834.2022.9883229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Melting Glacier: A 37-Year (1984–2020) High-Resolution Glacier-Cover Record of MT. Kilimanjaro
Commonly recognized as an important symbol of the tropics and global warming, the glacier loss on Mt. Kilimanjaro has received worldwide attention for decades. In this paper, we propose a high-resolution glacier-cover (GC) record of Mt. Kilimanjaro over the period from 1984 to 2020, using a novel deep learning-based semantic segmentation method and Google Earth images, as well as digital elevation model (DEM) and ERA5-Land (ERA5) for snowline and temperature variations analysis. Our method achieves an accuracy of 94.37%, which proves the model's capability to record the GC areas precisely. The results show that (1) the GC area dramatically decreases from 19.2 km2 to 3.6 km2 during 37 years, which decreases about 4% and 2% per year from 1984 to 2000 and from 2000 to 2020 respectively, (2) the snowline altitude rises from $4,651 m$ to $5,088 m$ by about $437 m$, and (3) the average $5,000 m$ air temperature on Mt. Kilimanjaro increases from −2.1 °C to −1.1 °C by about 1 °C. This study indicates that there will be no GC within a few decades if the current loss continues.