Browsing by Subject "satellite"

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    Advances and limitations of using satellites to monitor cyanobacterial harmful algal blooms
    (Associação Brasileira de Limnologia, 2019-06) Ogashawara, Igor; Earth Sciences, School of Science
    The use of satellites for monitoring forests is common and well-known practice. However, the operational remote monitoring of water quality from space is still under development. In the United States of America (USA), the use of this type of data is just now being applied to operationally monitor cyanobacterial harmful algal blooms (CHABs). This powerful tool can be used to generate temporal and spatial assessments of CHABs, however the validation of the retrieved information is still a challenge - especially in tropical and equatorial countries. This commentary discusses the advantages and challenges of current initiatives that use Earth Observation data for managing CHABs such as “Lake Erie’s HAB Bulletin” and “Project CYAN” - both in the USA. Additionally, it was also discussed the application of remote sensing techniques to monitor CHABs in Brazilian inland waters.
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    Enhanced canopy growth precedes senescence in 2005 and 2010 Amazonian droughts
    (Elsevier, 2018-06) Liu, Yi Y.; van Dijk, Albert I. J. M.; Miralles, Diego G.; McCabe, Matthew F.; Evans, Jason P.; de Jeu, Richard A. M.; Gentine, Pierre; Huete, Alfredo; Parinussa, Robert M.; Wang, Lixin; Guan, Kaiyu; Berry, Joe; Restrepo-Coupe, Natalia; Earth Sciences, School of Science
    Unprecedented droughts hit southern Amazonia in 2005 and 2010, causing a sharp increase in tree mortality and carbon loss. To better predict the rainforest's response to future droughts, it is necessary to understand its behavior during past events. Satellite observations provide a practical source of continuous observations of Amazonian forest. Here we used a passive microwave-based vegetation water content record (i.e., vegetation optical depth, VOD), together with multiple hydrometeorological observations as well as conventional satellite vegetation measures, to investigate the rainforest canopy dynamics during the 2005 and 2010 droughts. During the onset of droughts in the wet-to-dry season (May–July) of both years, we found large-scale positive anomalies in VOD, leaf area index (LAI) and enhanced vegetation index (EVI) over the southern Amazonia. These observations are very likely caused by enhanced canopy growth. Concurrent below-average rainfall and above-average radiation during the wet-to-dry season can be interpreted as an early arrival of normal dry season conditions, leading to enhanced new leaf development and ecosystem photosynthesis, as supported by field observations. Our results suggest that further rainfall deficit into the subsequent dry season caused water and heat stress during the peak of 2005 and 2010 droughts (August–October) that exceeded the tolerance limits of the rainforest, leading to widespread negative VOD anomalies over the southern Amazonia. Significant VOD anomalies were observed mainly over the western part in 2005 and mainly over central and eastern parts in 2010. The total area with significant negative VOD anomalies was comparable between these two drought years, though the average magnitude of significant negative VOD anomalies was greater in 2005. This finding broadly agrees with the field observations indicating that the reduction in biomass carbon uptake was stronger in 2005 than 2010. The enhanced canopy growth preceding drought-induced senescence should be taken into account when interpreting the ecological impacts of Amazonian droughts.
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    Improving Remote Sensing Algorithms Towards Inland Water Cyanobacterial Assessment From Space
    (2021-09) Ogashawara, Igor; Li, Lin; Moreno-Madriñán, Max Jacobo; Druschel, Gregory K.; Hwang, Taehee; Wang, Lixin
    Water is an essential resource for life on Earth, and monitoring its quality is an important task for mankind. However, the amount of water quality data collected by the traditional method is insufficient for the conservation and sustainable management of this important resource. This challenge will be exacerbated by increasing harmful algal blooms at the global scale. To fill this gap, Earth Observations (EO) have been proposed to help stakeholders make their decisions, but the use of EO for monitoring inland water quality is still in development. In this context, the main objective of this study was to improve the estimation of cyanobacteria via remote sensing data. To achieve this goal, the water type classification was first used to identify the dominant optically active constituents within aquatic environments. This information is crucial for understanding the optical properties of inland waters and selecting the best remote sensing algorithm for specific optical water types. The next research question was to develop a universal structure for retrieval of the inherent optical properties of several important aquatic systems around the world, which can be used as a corner stone for developing a globally applicable remote sensing algorithm. The third research topic of this dissertation is about removing the interference of chlorophyll-a with the absorption strength at 620 nm where phycocyanin exhibits its diagnostic absorption so that the estimation of phycocyanin concentration can be improved. Despite the novelty of the proposed remote sensing algorithms which are able to accommodate distinct water optical properties, there are abundant opportunities for improving the parameterization of the proposed models to retrieve inland water quality and optical properties when a global database of optical and water quality measurements is available. Considering the current advancement in spaceborne technology and the existence of a coordinate effort for global calibration and validation of remote sensing algorithms for monitoring inland waters, there is a high potential for operational assessment of harmful cyanobacterial blooms using the remote sensing algorithms proposed in this dissertation.