Statistical Modeling of Impacts El Niño Southern Oscillations (ENSO) on Land Surface Temperature in Small Medium Size City: Case Study Kuching Sarawak
نویسندگان
چکیده
El Niño Southern Oscillation (ENSO) can affect the daily temperature and amount of rainfall extreme weather such as floods droughts. For that reason, scientists need to understand process developing ENSO develop statistical models predict impact land surface temperature. The remote sensing data provide spatial information allows analyzing influence on patterns. This study examines ability model for predicting effect Remote needs go through a pre-process digital Number conversion Land Surface Temperature (LST). To ensure accurate information, calibration is carried out using records from Meteorological Malaysia Department (MMD). next step conduct correlation analysis between LST Oceanic Index (ONI). final use linear regression in building forecasting LST. result found changes ONI values value Improving knowledge understanding ideas strategies reducing adapting human beings.
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ژورنال
عنوان ژورنال: JOURNAL OF SUSTAINABLE NATURAL RESOURCES
سال: 2022
ISSN: ['2716-7143']
DOI: https://doi.org/10.30880/jsunr.2022.03.01.002