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RSS FeedsRemote Sensing, Vol. 14, Pages 4906: A Simple Procedure to Preprocess and Ingest Level-2 Ocean Color Data into Google Earth Engine (Remote Sensing)

 
 

30 september 2022 17:02:40

 
Remote Sensing, Vol. 14, Pages 4906: A Simple Procedure to Preprocess and Ingest Level-2 Ocean Color Data into Google Earth Engine (Remote Sensing)
 


Data from ocean color (OC) remote sensing are considered a cost-effective tool for the study of biogeochemical processes globally. Satellite-derived chlorophyll, for instance, is considered an essential climate variable since it is helpful in detecting climate change impacts. Google Earth Engine (GEE) is a planetary scale tool for remote sensing data analysis. Along with OC data, such tools allow an unprecedented spatial and temporal scale analysis of water quality monitoring in a way that has never been done before. Although OC data have been routinely collected at medium (~1 km) and more recently at higher (~250 m) spatial resolution, only coarse resolution (≥4 km) data are available in GEE, making them unattractive for applications in the coastal regions. Data reprojection is needed prior to making OC data readily available in the GEE. In this paper, we introduce a simple but practical procedure to reproject and ingest OC data into GEE at their native resolution. The procedure is applicable to OC swath (Level-2) data and is easily adaptable to higher-level products. The results showed consistent distributions between swath and reprojected data, building confidence in the introduced framework. The study aims to start a discussion on making OC data at native resolution readily available in GEE.


 
73 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 14, Pages 4902: A Novel Algorithm Modelling for UWB Localization Accuracy in Remote Sensing (Remote Sensing)
Remote Sensing, Vol. 14, Pages 4907: Updating Inventory, Deformation, and Development Characteristics of Landslides in Hunza Valley, NW Karakoram, Pakistan by SBAS-InSAR (Remote Sensing)
 
 
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