AlgaeMAp: Algae Bloom Monitoring Application for Inland Waters in Latin America
نویسندگان
چکیده
Due to increasing algae bloom occurrence and water degradation on a global scale, there is demand for quality monitoring systems based remote sensing imagery. This paper describes the scientific, theoretical, methodological background creating cloud-computing interface Google Earth Engine (GEE) which allows end-users access related products with high spatial (30 m) temporal (~5 day) resolution. The proposed methodology uses Sentinel-2 images corrected atmospheric sun-glint effects generate an image collection of Normalized Difference Chlorophyll-a Index (NDCI) entire time-series. NDCI used estimate both Chl-a concentration, non-linear fitting model, Trophic State (TSI), tree-decision model classification into five classes. Once TSI algorithms had been calibrated validated they were implemented in GEE as App, entitled Algae Bloom Monitoring Application (AlgaeMAp). AlgaeMAp first online platform built within that offers resolution parameters. App benefits from huge processing capability any user internet easily extract detailed long information (from August 2015 every 5 days) throughout most important reservoirs São Paulo/Brazil. application will be adapted extend other relevant areas Latin America.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2021
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs13152874