Remotely sensed data can provide information about conditions on the ground that may affect food supply chains and food security during pandemics. Your challenge is to demonstrate the agricultural socio-economic impacts from COVID-19.
To combine Sentinel-3 and other satellite imagery of 5 types of food supply routes from Sentinel Hub's Earth Observation Browser App with the knowledge of how many supply chain workers it takes per million people to keep populations fed in times of Covid and other global disasters.
The stated End Product for the Agricultural supply-chain Challenge was two-fold:
1) taking already existing satellite capabilities of monitoring land and sea food supply-chain routes
2) adding a basic equation developed by combing through other public data to discover the minimum of workers needed to work those routes during food insecurity caused by times of pandemic and other possible disasters.
Though the US was used for data sources (because they were easier for me to find and cite), the intent was to create a basic and flexible equation that any country could use to keep food supply chains stabile -- and not just in times of disaster. Some countries have more coastlands, some are tinier with higher population concentrations per square mile. This concept hopefully will be useful to those more advanced in food-chain transportation work than me -- and they can take it farther in unique situations.
Further inspiration came from the idea that I would have a chance to present a project for social change that would be listened to by the space agencies if only I was willing to take the matter seriously. (Cite *everything* -- and work fast!)
The main tools that I used (because of lack of significant coding skills) that lead to personal achievements were:
1) A willingness to do long data-crawls where I went in with naive presumptions and came out with different fact-based ideas all together. (I didn't know how quickly truckers learn the rules of the road compared to airline pilots -- or that railroads divide food into three catergories of shipment speeds, or that if this freight transportation all stopped the supermarkets that I take for granted would feel the pinch in 3 days.) 2) Just about every government and academic and career website I could lay hands on -- plus Wikipedia (which I had already started donating to out of gratitude).
The main date used was from the Earth Observatory Browser in the Sentinel Hub, which I got access to through signing up for the EO Dashboard Hackathon. From there, I read up as much as I could in the time allotted on which satellites specialized doing what imagery. Towards the end, I realized Sentinel-3 was the main satellite I needed to capture imagery from -- and though I still have not figured out how to use all the filters as well as I think they could be employed, I came in with a decent (but rusty) knowledge of Google Earth and Google Maps, so I wasn't completely overwhelmed by a new user interface.
Here is the link to the 7-slide, publicly-accessable, PDF file in DropBox:
The Earth Observing Dashboard is already making available real-time data in raster (because vector *still* takes to much processing power -- sniffle!) that clearly shows the conditions of roads, seaports, river ports, airports, and railroad tracks that food transport supply-chains rely on. All the might be necessary to integrate my project into the dashboard would to be perhaps creating a special type o license seat for food supply chain managers, with a stripped-down, intuitive version for those actually doing to travel-time for transportation. That way, (for example) the managers of those licensed to drive 18-wheelers could adopt the technology with the least amount of stress, and keep on top of matters in time of any further crisis, and new workers coming in to replace those who might have been laid low by pandemic would not have to face a steep learning curve for yet another new skill when they are already trying to either a) learn or b) dust off abilities they never thought would be necessary except to save lives.
The shorter the time it takes to adapt to situations like Covid-19, the less possibility there is for food destabilization in affected nations.
(PUBLIC ROAD: “CORONADO FREEWAY”) https://sentinelshare.page.link/k1m5
(SEAPORT: “PORT OF SEATTLE, WA, DOCK YARDS”). https://sentinelshare.page.link/FC8w
(RIVER PORT: “AMERICA’S CENTRAL PORT”) https://sentinelshare.page.link/untr
(AIRPORT: “LOGAN INTERNATIONAL AIRPORT”) https://sentinelshare.page.link/GbNH
(RAIL TRACKS: “NORFOLK SOUTHERN RAIL YARD, NEW ORLEANS”) https://sentinelshare.page.link/hCVb
I (CORONA VIRUS) <a href="https://commons.wikimedia.org/wiki/File:Coronaviruses_004_lores.jpg">Photo Credit:Content Providers(s): CDC/Dr. Fred Murphy</a>, Public domain, via Wikimedia Commons
II ( FOOD) <a href="https://commons.wikimedia.org/wiki/File:Good_Food_Display_-_NCI_Visuals_Online.jpg">Unknown authorUnknown author</a>, Public domain, via Wikimedia Commons
III (SENTINEL-3) <a href="https://commons.wikimedia.org/wiki/File:Sentinel-3_spacecraft_model.svg">SkywalkerPL</a>, <a href="https://creativecommons.org/licenses/by/4.0">CC BY 4.0</a>, via Wikimedia Commons
IV (WAREHOUSE) <a href="https://commons.wikimedia.org/wiki/File:Pallet_racks.jpg">en:User:Jandrinov</a>, Public domain, via Wikimedia Commons
V (FCE MASK). <a href="https://commons.wikimedia.org/wiki/File:3M_N95_Particulate_Respirator.JPG">Banej</a>, <a href="https://creativecommons.org/licenses/by-sa/3.0">CC BY-SA 3.0</a>, via Wikimedia Commons
VI (WHEAT) <a href="https://commons.wikimedia.org/wiki/File:Wheat_close-up.JPG">User:Bluemoose</a>, <a href="http://creativecommons.org/licenses/by-sa/3.0/">CC BY-SA 3.0</a>, via Wikimedia Commons
#agricultural, #equation, #foodsupplyworkerspercitizenpopulation, #satelliteimagery, #sentinal3, #EODashboard, #feedamillion, #globalhunger, #crisisstabilization
This project has been submitted for consideration during the Judging process.