Gene Christopher P. Romuga | Jairus Noah L. Polintan | Mark Anthony Mercado | Rimmon Gerard A. Silvala
In predicting yield, there are different weather data needed. Weather variables consist of solar radiation, maximum temperature, minimum temperature, dew point, wind speed, and precipitation. As it is the case with other crop simulation models applications, the aim of the system was generally to prepare the input data to run the model. To run the model, merging and classifying of weather data are required to produce an input for yield prediction. Raw data have two sources, NSDSAS and TRMM. Naval Systems Data Support Activity (NSDSAS) weather data are available global weather data produced by NASA Langley Research Center Power Project funded through NASA Earth Science Directorate Applied Science Program. Tropical Rainfall Measuring Mission (TRMM) is a public available rainfall weather data produced by NASA and obtained from space-borne rain radar and microwave radiometric data covering precipitation over the tropics in a band between 35 degrees north and south latitudes. Both weather variables in NSDSAS and TRMM are needed for crop simulation model process. Being the tight spot on acquiring input to the model, the proponents created means for merging as well as the classifying weather data to provide acquired inputs for crop simulation. The system will be able to process weather data into acceptable inputs for the crop simulation process. After processing weather variables in NSDSAS and TRMM weather data, they are then merged to come up with an input for classifying data. The software will classify the merged data by cell id and automatically create a file container for each weather data until it is done. Classified weather data are the final output and serve as the input for crop simulation process. In general, this system automatically finds the matched cell id and year in a sequence of weather data in NSDSAS and TRMM weather data without the input from the user.
ISSN 1908-3874 (Print)
Philippine E-Journals
