Extreme weather events such as typhoons, floods, heavy rainfall and droughts impacted lots of areas in the world, and so as in Taiwan. The Council of Agriculture reported the agricultural damage has increased owing to unusual weather, estimated at an accumulated NT$13.5 billion over the past five years. In order to confirm the influences of extreme climate toward agriculture, we compare the changes in all kind of fruit production, choosing the top 10 species with the most reduction and analyze the reasons by interview the fruit farmers, the researchers of the Agricultural Research and Extension Station, and the government.
Instead of interviewing the fruit farmer randomly, we figure out which fruit yields are decreased the most at first. After that, we combine the data of the temperature change and the rainfall change in the major production areas, trying to find out the weather factor that affected directly, and then we start the interviews. The feature try to use data as evidences to confirm whether the phenomenon of “Extreme Climate in Taiwan” is true rather than just seeing other media reports individual farmer claiming the decrease of production.
For the data visualization, we use Adobe Illustrator to design graphs and charts. We use React and Web Components to implement web page.
What was the hardest part of this project?
We can filter the species by comparing the change of production, but the cause might be plural or have nothing to do with climate. For example, the production of “Honey tangerine”, which is a kind of citrus fruit, is decreasing year by year. The corp researcher said the fruit has too little water, so consumers don’t like it and rather choosing the other kind of citrus fruit. Therefore, we have to seek experts’ advice of every crop we choose.
What can others learn from this project?
The feature is a convincingly demonstrate to confirm that the agriculture in Taiwan is being severely affected by extreme weather by cross analyzing the fruit production and the weather factor such as temperature or rainfall. we start from examining data, asking questions from the data, trying to figure out different factors of the causes. We then consulted experts and fruit farmers with data we found, trying to be an alternative model of investigative reporting.