Prediction of chlorophyll concentration in the ocean aids in assessing ecosystem health, advising fisheries management, and enhancing our understanding of Earth's biogeochemical processes. By employing deep learning methods, we will develop models to analyze the relationship between chlorophyll concentration and biogeochemical features
A Tkinter widget that fills your code with color
Sentinel-2 Crop Trait Retrieval Using Physiological and Phenological Priors from Field Phenotyping (Graf et al., 2023, RSE)
Search and fetch NASA Ocean Color data
An open-source Arduino based chlorophyll fluorometer for quantifying photosynthesis in photosynthetic organisms.
A highly-modular text editor
A web application that visualizes global coastal eutrophication trends by country and region from 2005 until 2021
Chl-tsm with C2RCC processor (OLCI-Sentinel 3). SNAP Guide
The influence of time scale on autocorrelation as an early warning indicator of regime shift
data template for temperature interference testing of Total Algae sensor for the National Science Collaborative Catalyst project, "Refining Techniques for High-Frequency Monitoring of Chlorophyll in the NERRS".
The Optical Reef and Coastal Area Assessment (ORCAA) tool in Google Earth Engine allows users to monitor, track, and evaluate water parameters in the Belize and Honduras Barrier Reefs from January 2013 to present using Landsat 8, Sentinel-2, and Aqua/Terra MODIS imagery.
Vorschwissenschaftliche Arbeit zum Thema "Direkte Analyse von Chlorophyllkataboliten"
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