دورية أكاديمية

Leveraging multimission satellite data for spatiotemporally coherent cyanoHAB monitoring

التفاصيل البيبلوغرافية
العنوان: Leveraging multimission satellite data for spatiotemporally coherent cyanoHAB monitoring
المؤلفون: Kate C. Fickas, Ryan E. O’Shea, Nima Pahlevan, Brandon Smith, Sarah L. Bartlett, Jennifer L. Wolny
المصدر: Frontiers in Remote Sensing, Vol 4 (2023)
بيانات النشر: Frontiers Media S.A., 2023.
سنة النشر: 2023
المجموعة: LCC:Geophysics. Cosmic physics
LCC:Meteorology. Climatology
مصطلحات موضوعية: cyanobacteria, remote sensing, Sentinel-2/MSI, Sentinel-3/OLCI, machine learning, public health, Geophysics. Cosmic physics, QC801-809, Meteorology. Climatology, QC851-999
الوصف: Cyanobacteria harmful algal blooms (cyanoHABs) present a critical public health challenge for aquatic resource and public health managers. Satellite remote sensing is well-positioned to aid in the identification and mapping of cyanoHABs and their dynamics, giving freshwater resource managers a tool for both rapid and long-term protection of public health. Monitoring cyanoHABs in lakes and reservoirs with remote sensing requires robust processing techniques for generating accurate and consistent products across local and global scales at high revisit rates. We leveraged the high spatial and temporal resolution chlorophyll-a (Chla) and phycocyanin (PC) maps from two multispectral satellite sensors, the Sentinel-2 (S2) MultiSpectral Instrument (MSI) and the Sentinel-3 (S3) Ocean Land Colour Instrument (OLCI) respectively, to study bloom dynamics in Utah Lake, United States, for 2018. We used established Mixture Density Networks (MDNs) to map Chla from MSI and train new MDNs for PC retrieval from OLCI, using the same architecture and training dataset previously proven for PC retrieval from hyperspectral imagery. Our assessment suggests lower median uncertainties and biases (i.e., 42% and -4%, respectively) than that of existing top-performing PC algorithms. Additionally, we compared bloom trends in MDN-based PC and Chla products to those from a satellite-derived cyanobacteria cell density estimator, the cyanobacteria index (CI-cyano), to evaluate their utility in the context of public health risk management. Our comprehensive analyses indicate increased spatiotemporal coherence of bloom magnitude, frequency, occurrence, and extent of MDN-based maps compared to CI-cyano and potential for use in cyanoHAB monitoring for public health and aquatic resource managers.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2673-6187
Relation: https://www.frontiersin.org/articles/10.3389/frsen.2023.1157609/full; https://doaj.org/toc/2673-6187
DOI: 10.3389/frsen.2023.1157609
URL الوصول: https://doaj.org/article/23bf0674d2bb48b2becc3b91db01b3fb
رقم الأكسشن: edsdoj.23bf0674d2bb48b2becc3b91db01b3fb
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:26736187
DOI:10.3389/frsen.2023.1157609