Discover and read the best of Twitter Threads about #modis

Most recents (4)

Happy New Year๐ŸŽ† You can now create sea surface temperature timelapse with a colorbar using the #streamlit web app in <60 seconds ๐Ÿ‘‡


#EarthEngine #geemap #eochat #gischat #oceancolor #dataviz #geospatial
Here is a demo using the @streamlit web app for creating ocean color timelapse with #MODIS Aqua data @chris_harrod

Keep in mind that you can create timelapse by selecting a yearly, quarterly, weekly, or daily frequency
Read 3 tweets
๐Ÿ”ฅ THREAD: global fire patterns ๐Ÿ”ฅ

Recent drought-related #wildfires have underscored how #climate change can increase fire risks regionally.
But various factors (e.g. human ignitions/suppression, vegetation growth) control fire, making regional fire patterns horribly complex!
It's tough to distill all these complexities into general statements, so here's a thread to showcase what ๐Ÿ›ฐ observations can reveal about ๐Ÿ”ฅ trends at various regional scales.

I invite you to get lost in the maps that follow and appreciate the complexity in all its glory! ๐Ÿค˜
First up, a basic question: Where do most fires happen?

๐Ÿ‘‡ Plot shows mean annual burned area during 2001-2020, summed within regions and mapped thematically.

(Note: log colour scale)
Read 25 tweets
Massive new #QGIS plugin: #GEE Timeseries Explorer offers instant access to #EarthEngine image collections! Fetch #Landsat, #Sentinel2, or #MODIS #timeseries for any location and visualize images: ๐Ÿงต
Choose from our predefined collections, for instance merged & #cloud masked #Landsat TM, ETM+, OLI surface reflectance, cloud masked Sentinel2AB L2A, or just define your awesome custom collection in the built-in #Python editor.
Extract time series profiles for #training / #validation by clicking on map, or by navigating through vector point file. Download raw time series data for #sample-based workflows efficiently with parallel download.
Read 6 tweets
Farmers in NW India are about to begin harvesting rice crop. #Aqua #MODIS NDVI for Sep historically largest this year--indicating a whooping crop prod>12 m tons. Given traditional crop residue burning practice, it means an intense fire season with ~16000 incidences in Oct & Nov
@NASAEarth @NASAGoddard @moesgoi @rajeevan61 @jayashreenandi @VishnuNDTV @parthaabosu @airqualityindia @m_parrington @robertdfield @UrbanEmissions @iainmarlow @USRAedu @SmokeyBot @urbansciencesIN @avoiland @vinoj_iisc @jmccarty_geo This is an initial estimate based on 16-day Sep data from #Aqua #MODIS. I will revise it with monthly observations once they are available (likely in 2nd week of Oct), however not expecting major change in results.
Read 32 tweets

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