When we first started to analyze and use the data from the Earthdata we realized how important for the data to have practical and simple access is. Overwhelming and difficult to decipher data must become easy to read and visually interpret. The main problem was to combine several data formats to build the model.
Our goal was to make an application which is simple in use but contains all of the needed information about any species. This will allow not only scientists to search for specific information about a certain region but also will allow us to learn more interesting facts for anyone how is just curious about biodiversity. The best way to do that is creating the species distribution model.
We decided to present our model on the example and endemic species would be the most illustrative one. We chose the American Alligator (Alligator mississippiensis) to show how all the data can be connected into one picture.
To begin with, InterBio will take into account environmental factors and how these factors affect the distribution and abundance of alligators in the south part of the USA. Our example includes the the analysis of temperature; the program will calculate average minimum temperature per coordinate and connect them to the coordinates of the alligators' occurences which allows to draw correlations using such machine learning algorithms such as clustering and k-means. In the future the program will be able to take into account such factors as CO2 levels, percentage tree cover of the land, topography and many more in order to make results as valid as possible. The data is presented by the illustration of on the map. This allows to interpret the connections visually.
In the future all the data collected and conclusions drawn will allow not only to track the variations in species occurences along with the environmental changes but also according to data analysis make predictions for the further changes. How will the increase in temperature affect the population size, species distribution, and population density in a hotspot? The InterBio will answer.
In conclusion, we believe that the main feature of InterBio is to provide everyone with a sufficient amount of information whether the program is used by a scientist or by a regular person such as a high school student. We want to bring awareness about the changes in the biosphere and their outcomes and this is the purpose of our project.
The challenge states that we need to find a way to use space agency data to advance the capability of understanding, processing, visualizing, and predicting the distribution and abundance of numerous species.
We are living in a world where we hear such news about the decrease in biodiversity regular. These are the news that break the hearts of many people but only a few want to learn more and find the cause behind the problem. Hence, we had an idea about creating a web about the species which is easily acceptable for everyone. At the same time, the program must be as informative as possible so that it can also be used for advanced researches.
The demo of InterBio consists of two code files: PlottingSpeciesDistribution and NetCD4Interpreter. The first one takes open available data from the web and plots them on the map of USA. The second one provides interpretation of .nc4 files in the form of value and corresponding coordinates.
Due to the vast volumes of data, it is impractical to combine them on the hardware available to us. In the future, however, using a clustering algorithm on the species occurrences data and combining it using k-means algorithm. In the demo, only minimum surface temperature is assessed, however in the future, with only slight alterations, the script will be able to assess all .nc4 data.
We used data from EARTHDATA to generate environmental data for our solution and we decided on the main format of our project (netcdf) by looking at the variety of data available and chose the format that a diverse range of datatypes concerning environmental data was available in.
We also used GBIF in our search for occurrences of species.
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