SatHDSS
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Algae Dataset

Every data hub, dataset, sensor, variable, paper and limitation in one tree — and for each: where it comes from, how far back it goes, how often it captures, why it belongs in a cholera study, and why it does not work everywhere.

Highlight site All three Chakaria HDSS Matlab HDSS Dhaka City Choosing a site greys out everything that does not apply there.

2. Inland/coastal high-res

AL18 · Sentinel-2 Level-1C + ACOLITE Dark Spectrum Fitting
ESA (data) + RBINS (processor)
B Usable FREE (both) ACCOUNT NEEDED

Source · duration · capture cadence

Data source
ESA (data) + RBINS (processor)
Access route
CDSE download + local ACOLITE run
Endpoint / asset
github.com/acolite/acolite
Duration
2015-06 → present
Capture cadence
5 days
Resolution
10-20 m
Delivers
Publication-grade Rrs → NDCI, MCI, FAI, phycocyanin, TSM over turbid inland water
Command
07_algae_api_download.py --sources cdse
Why it is used for cholera. DSF is the peer-reviewed standard for turbid inland/coastal water · used by Anas et al. 2021 at Vembanad
Why not — catalogue limitation. Requires local compute and disk (~1 GB per scene). Slow. But GEE's Sen2Cor L2A is NOT trustworthy over dark turbid water, so for any published concentration you need this.

Site applicability

SiteVerdictWhy
Chakaria HDSS YES THE RIGOROUS ROUTE for shrimp ponds
Matlab HDSS YES THE RIGOROUS ROUTE for village ponds
Dhaka City YES THE RIGOROUS ROUTE for urban lakes

Reliable · accessible · authentic

B Usable
Reliability tier
REGISTER
Accessible
ESA (data) + RBINS (processor)
Authentic — operator

Typed limitations (1)

HIGH ACOLITE is roughly 1 GB per scene and weeks of processing access

The rigorous route to real reflectance requires downloading L1C scenes and running Dark Spectrum Fitting locally. For a multi-year archive across three sites this is a serious computing commitment.

What to do: Do it AFTER the ordinal pipeline works end to end. Filter to under 20 percent cloud first, and consider reprocessing only the bloom-season scenes.