SATELLITE-BASED AGRICULTURAL MODELING
An online agricultural system manages and optimizes interactions of entities within the system to enable the execution of transaction and the transportation of crop products. The online agricultural system accesses historic and environmental data describing factors that may impact crop product transactions and/or transportation to determine market prices for crop products and crop product transportation. Responsive to receiving a request from an entity, the online agricultural system determines an optimal transaction for the entity, such as a price for selling a crop product, an available crop product for purchase, or a transportation opportunity to transport a crop product.
1 . A method for predicting future crop characteristics in an online agricultural system comprising:
receiving, from a crop producer, a request to list a crop product within an online agricultural system, the first request identifying a type of the crop product, a first quantity of the crop product, and a location of the crop product;
accessing current crop product information comprising:
a current available quantity and current price of the type of the crop product associated with the location of the crop product within the online agricultural system; and
current satellite data representative of the location of the crop product;
accessing historic crop product information comprising:
historic quantities and historic prices of the type of the crop product associated with the location of the crop product within the online agricultural system; and
historic satellite data representative of the location of the crop product;
training a price model for the crop product using the accessed current crop product information and the accessed historic crop product information;
predicting a future price of the type of the crop product using the price model; and
presenting, within an interface of the online agricultural system displayed by a client device of the crop producer, the predicted future price of the type of the crop product.
2 . The method of claim 1 , wherein the price model comprises one of a neural network, a k-means clustering machine learning model, and a reinforcement learning model.
3 . The method of claim 1 , wherein the price model is configured to predict future prices for the type of the crop product based at least in part on a correlation between the historic quantities of the type of the crop product within the online agricultural system and historic prices of the type of the crop product within the online agricultural system.
4 . The method of claim 1 , wherein the price model is configured to predict future prices for the type of the crop product based at least in part on a correlation between estimates of historic availability of the type of the crop product determined from the historic satellite data and historic prices of the type of the crop product within the online agricultural system.
5 . The method of claim 1 , wherein the price model is configured to predict future prices for the type of the crop product based at least in part on a correlation between the historic quantities of the type of the crop product within the online agricultural system and a current available quantity of the type of the crop product within the online agricultural system.
6 . The method of claim 1 , wherein the price model is configured to predict future prices for the type of the crop product based at least in part on a correlation between estimates of historic availability of the type of the crop product determined from the historic satellite data and an estimate of current availability of the type of the crop product determined from the current satellite data.
7 . The method of claim 1 , wherein the price model is configured to predict future prices for the type of the crop product based at least in part on a correlation between historic prices of the type of the crop product within the online agricultural system and the current price of the type of the crop product within the online agricultural system.
8 . The method of claim 1 , wherein the price model is configured to predict future prices for the type of the crop product based at least in part on a correlation between historic weather conditions and historic prices of the type of the crop product within the online agricultural system.
9 . The method of claim 1 , wherein presenting the predicted future price of the crop product within the interface comprises presenting a maximum or mean expected price of the crop product if the crop product is sold before a threshold date.
10 . The method of claim 9 , wherein presenting the predicted future price of the crop product within the interface further comprises presenting an uncertainty associated with the presented future price.
11 . The method of claim 10 , wherein presenting the uncertainty associated with the presented future price comprises presenting a confidence interval.
12 . The method of claim 1 , wherein presenting the predicted future price of the crop product within the interface comprises presenting an indication that the future price is expected to be higher or lower than the current price of the crop product.
13 . The method of claim 12 , wherein presenting the predicted future price of the crop product within the interface further comprises presenting an explanation of why the future price is expected to be higher or lower than the current price of the crop product, the explanation based at least in part on one or both of the current crop product information and the historical crop product information.
14 . The method of claim 13 , wherein presenting the explanation comprises presenting a narrative explanation of why the future price is expected to be higher or lower than the current price, presenting an icon associated with a future higher price or a future lower price, or presenting a color representative of a future higher price or a future lower price.
15 . The method of claim 1 , wherein presenting the predicted future price of the crop product within the interface comprises presenting a recommendation to the crop producer to sell the crop product before a threshold date.
16 . The method of claim 1 , wherein presenting the predicted future price of the crop product within the interface comprises presenting a recommendation to the crop producer to delay selling the crop product until after a threshold date.
17 . The method of claim 1 , wherein presenting the predicted future price of the crop product within the interface comprises presenting a recommendation to the crop producer to sell the crop product between a first date and a second date.
18 . The method of claim 1 , further comprising presenting one or both of the current price of the type of the crop product and historic prices of the type of the crop product within the interface.
19 . The method of claim 1 , further comprising:
in response to the predicted future price being less than a threshold future price, sending a notification to the client device indicating a potential future price decrease.
20 . The method of claim 1 , further comprising:
in response to the predicted future price being greater than a requested listing price received from the crop producer by more than a threshold price difference, modifying the interface to suggest increasing the requested listing price.
21 . The method of claim 1 , further comprising:
in response to the predicted future price being less than a requested listing price received from the crop producer by more than a threshold price difference, modifying the interface to suggest decreasing the requested listing price.
22 . The method of claim 1 , wherein the crop product comprises one of: wheat, rice, barley, buckwheat, rye, millet, oats, corn, sorghum, triticale, spelt, cotton, tomato, lettuce, peppers, cucumber, endive, melon, potato, squash, rapeseed, canola, mustard, flax, palm, sunflower, safflower, soybean, peas, and beans.
23 . The method of claim 1 , wherein the crop product comprises one of: oil, protein, starch, meal, fiber, flour, juice, frozen crop tissue, and dried crop tissue.
24 . The method of claim 1 , wherein the current satellite data comprises satellite image data captured within a previous threshold of time.
25 . (canceled)
26 . A system for predicting future crop characteristics in an online agricultural system, comprising:
a non-transitory computer-readable storage medium storing executable instructions that, when executed, cause steps to be performed comprising:
receiving, from a crop producer, a request to list a crop product within an online agricultural system, the first request identifying a type of the crop product, a first quantity of the crop product, and a location of the crop product;
accessing current crop product information comprising:
a current available quantity and current price of the type of the crop product associated with the location of the crop product within the online agricultural system; and
current satellite data representative of the location of the crop product;
accessing historic crop product information comprising:
historic quantities and historic prices of the type of the crop product associated with the location of the crop product within the online agricultural system; and
historic satellite data representative of the location of the crop product;
training a price model for the crop product using the accessed current crop product information and the accessed historic crop product information;
predicting a future price of the type of the crop product using the price model; and
causing display, within an interface of the online agricultural system displayed by a client device of the crop producer, the predicted future price of the type of the crop product; and
a hardware processor configured to execute the executable instructions.
27 . A method for predicting future crop characteristics in an online agricultural system comprising:
receiving, from a crop producer, a request to list a crop product within an online agricultural system, the first request identifying a type of the crop product, a first quantity of the crop product, and a location of the crop product;
accessing current crop product information comprising:
a current available quantity and current profitability of the type of the crop product associated with the location of the crop product within the online agricultural system; and
current satellite data representative of the location of the crop product;
accessing historic crop product information comprising:
historic quantities and historic profitabilities of the type of the crop product associated with the location of the crop product within the online agricultural system; and
historic satellite data representative of the location of the crop product;
training a price model for the crop product using the accessed current crop product information and the accessed historic crop product information;
predicting a future profitability of the type of the crop product using the price model; and
presenting, within an interface of the online agricultural system displayed by a client device of the crop producer, the predicted future profitability of the type of the crop product.