Network panel
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.
- +DATA HUBSwhere the data physically comes from
- +DATASET TYPESgrouped by what kind of water they see
- +SITE-WISEwhat actually applies at each site
- +DURATION & CAPTURE CADENCEdaily · weekly · 10-day · 16-day · monthly
- +VARIABLESwhat is computed from the bands
- −LIMITATIONSwhy not — typed and severity-ranked
- +VALIDATION2 limitations · 1 critical
- +ACCESS6 limitations · 4 critical
- +SPATIAL6 limitations · 3 critical
- +TEMPORAL7 limitations · 2 critical
- +ALGORITHMIC3 limitations · 1 critical
- −COVERAGE6 limitations · 1 critical
- ·Dhaka has almost no pre-2015 algae observationCRITICALsite level
- ·Copernicus LWQ300 lake mask may exclude all three sitesHIGHdataset AL09
- ·Landsat 7 SLC-off stripes after May 2003HIGHdataset AL05
- ·IRI is a strong climate archive but a thin ocean-colour o…HIGHdataset AL17
- ·Multiple testing across the lag gridMEDIUMstudy level
- ·Dhaka polygon is a GADM level-3 unit labelled TejgaonMEDIUMsite level
- +ATMOSPHERIC1 limitations
- +SPECTRAL2 limitations
- +PAPERSthe evidence, DOI-linked
MEDIUM Multiple testing across the lag grid coverage
34 variables x 14 lag steps x 3 sites is 1,428 cross-correlations. At p<0.05 roughly 70 will clear significance by chance alone, and the strongest of those will look publishable.
What to do: Pre-register the expected lag per variable before looking at the heatmap. Treat the rest of the surface as exploratory and say so.