利用 Landsat-8 号卫星图像评估环礁湖内温度的空间变异性

IF 3.8 Q2 ENVIRONMENTAL SCIENCES
Simon Van Wynsberge , Robin Quéré , Serge Andréfouët , Emmanuelle Autret , Romain Le Gendre
{"title":"利用 Landsat-8 号卫星图像评估环礁湖内温度的空间变异性","authors":"Simon Van Wynsberge ,&nbsp;Robin Quéré ,&nbsp;Serge Andréfouët ,&nbsp;Emmanuelle Autret ,&nbsp;Romain Le Gendre","doi":"10.1016/j.rsase.2024.101340","DOIUrl":null,"url":null,"abstract":"<div><p>Sea Surface Temperature (SST) maps are necessary for managing marine resources in a climate change context, but are lacking for most of the 598 world's atolls. We assessed the feasibility of using the Landsat-8 (L8) satellite to infer SST maps for four French Polynesia atolls of aquaculture interest in Tuamotu Archipelago, namely Takaroa, Raroia, Tatakoto, and Reao. Specifically, we (1) used sensors to measure <em>in situ</em> the range of spatial temperature differences recorded in these four atoll lagoons; (2) calibrated and assessed the performances of SST algorithms to estimate lagoon temperature from L8 signals; (3) generated temperature maps for the lagoons and compared spatial patterns of temperature obtained from these maps with patterns highlighted by <em>in situ</em> sensors. Good agreements between satellite and <em>in situ</em> temperature data were obtained, with better results achieved when using an atoll-by-atoll optimization (average bias = −0.26 °C; RMSE = 0.55 °C). However, we also show that the range of temperature inside atoll lagoons is low, and of the same order of magnitude than RMSE achieved with SST algorithms. Because of the L8 overpass time (∼9 a.m.) and the revisit time (16 days), L8 SST could not capture the entire range of spatial differences measured <em>in situ</em> in the four lagoons, but could capture spatial gradients and fronts better than with few <em>in situ</em> sensors. Considering the achieved accuracies and the actual temperature differences at the four study sites, we discuss the usefulness of L8 derived SST maps to assist fishery and aquaculture management in atoll lagoons, as well as the possible generalization to other lagoons.</p></div>","PeriodicalId":53227,"journal":{"name":"Remote Sensing Applications-Society and Environment","volume":"36 ","pages":"Article 101340"},"PeriodicalIF":3.8000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatial variability of temperature inside atoll lagoons assessed with Landsat-8 satellite imagery\",\"authors\":\"Simon Van Wynsberge ,&nbsp;Robin Quéré ,&nbsp;Serge Andréfouët ,&nbsp;Emmanuelle Autret ,&nbsp;Romain Le Gendre\",\"doi\":\"10.1016/j.rsase.2024.101340\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Sea Surface Temperature (SST) maps are necessary for managing marine resources in a climate change context, but are lacking for most of the 598 world's atolls. We assessed the feasibility of using the Landsat-8 (L8) satellite to infer SST maps for four French Polynesia atolls of aquaculture interest in Tuamotu Archipelago, namely Takaroa, Raroia, Tatakoto, and Reao. Specifically, we (1) used sensors to measure <em>in situ</em> the range of spatial temperature differences recorded in these four atoll lagoons; (2) calibrated and assessed the performances of SST algorithms to estimate lagoon temperature from L8 signals; (3) generated temperature maps for the lagoons and compared spatial patterns of temperature obtained from these maps with patterns highlighted by <em>in situ</em> sensors. Good agreements between satellite and <em>in situ</em> temperature data were obtained, with better results achieved when using an atoll-by-atoll optimization (average bias = −0.26 °C; RMSE = 0.55 °C). However, we also show that the range of temperature inside atoll lagoons is low, and of the same order of magnitude than RMSE achieved with SST algorithms. Because of the L8 overpass time (∼9 a.m.) and the revisit time (16 days), L8 SST could not capture the entire range of spatial differences measured <em>in situ</em> in the four lagoons, but could capture spatial gradients and fronts better than with few <em>in situ</em> sensors. Considering the achieved accuracies and the actual temperature differences at the four study sites, we discuss the usefulness of L8 derived SST maps to assist fishery and aquaculture management in atoll lagoons, as well as the possible generalization to other lagoons.</p></div>\",\"PeriodicalId\":53227,\"journal\":{\"name\":\"Remote Sensing Applications-Society and Environment\",\"volume\":\"36 \",\"pages\":\"Article 101340\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing Applications-Society and Environment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352938524002040\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing Applications-Society and Environment","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352938524002040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

海洋表面温度(SST)地图是在气候变化背景下管理海洋资源所必需的,但世界上 598 个环礁中的大多数环礁都缺少 SST 地图。我们评估了使用 Landsat-8(L8)卫星推断法属波利尼西亚图阿莫图群岛四个水产养殖环礁(即塔卡罗阿、拉罗亚、塔塔克托和雷奥)的 SST 地图的可行性。具体来说,我们(1)使用传感器实地测量这四个环礁湖记录到的空间温差范围;(2)校准和评估 SST 算法的性能,以便根据 L8 信号估算环礁湖温度;(3)生成环礁湖温度图,并将从这些图中获得的温度空间模式与实地传感器突出显示的模式进行比较。卫星温度数据与原地温度数据之间取得了良好的一致,在逐环礁优化时取得了更好的结果(平均偏差 = -0.26 °C;均方误差 = 0.55 °C)。不过,我们也发现环礁湖内的温度范围较小,与利用 SST 算法获得的均方误差处于同一数量级。由于 L8 的越过时间(上午 9 点)和重访时间(16 天),L8 SST 无法捕捉到四个环礁湖内原地测量到的全部空间差异,但能比使用少量原地传感器更好地捕捉到空间梯度和前沿。考虑到所达到的精度和四个研究地点的实际温差,我们讨论了 L8 导出的 SST 地图在协助环礁湖渔业和水产养殖管理方面的实用性,以及推广到其他环礁湖的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial variability of temperature inside atoll lagoons assessed with Landsat-8 satellite imagery

Sea Surface Temperature (SST) maps are necessary for managing marine resources in a climate change context, but are lacking for most of the 598 world's atolls. We assessed the feasibility of using the Landsat-8 (L8) satellite to infer SST maps for four French Polynesia atolls of aquaculture interest in Tuamotu Archipelago, namely Takaroa, Raroia, Tatakoto, and Reao. Specifically, we (1) used sensors to measure in situ the range of spatial temperature differences recorded in these four atoll lagoons; (2) calibrated and assessed the performances of SST algorithms to estimate lagoon temperature from L8 signals; (3) generated temperature maps for the lagoons and compared spatial patterns of temperature obtained from these maps with patterns highlighted by in situ sensors. Good agreements between satellite and in situ temperature data were obtained, with better results achieved when using an atoll-by-atoll optimization (average bias = −0.26 °C; RMSE = 0.55 °C). However, we also show that the range of temperature inside atoll lagoons is low, and of the same order of magnitude than RMSE achieved with SST algorithms. Because of the L8 overpass time (∼9 a.m.) and the revisit time (16 days), L8 SST could not capture the entire range of spatial differences measured in situ in the four lagoons, but could capture spatial gradients and fronts better than with few in situ sensors. Considering the achieved accuracies and the actual temperature differences at the four study sites, we discuss the usefulness of L8 derived SST maps to assist fishery and aquaculture management in atoll lagoons, as well as the possible generalization to other lagoons.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
8.00
自引率
8.50%
发文量
204
审稿时长
65 days
期刊介绍: The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信