ANALYZING THE EFFECT OF CLIMATE CHANGE (RAINFALL AND TEMPERATURE) ON VEGETATION COVER OF NEPAL USING TIME SERIES MODIS IMAGES
- 1Department of Civil and Geomatics Engineering, Kathmandu University, Dhulikhel, Nepal
- 2Department of Photogrammetry and Remote Sensing, Land Management Training Centre, Government of Nepal
Keywords: MODIS image, NDVI, CHIRPS, Vegetation change pattern, Climate change, Time series data
Abstract. Climate change and so its effect on terrestrial ecosystem has been a focus point for a while now. Among them, rainfall and temperature changes happen to exert a strong influence on the condition of vegetation cover. So, it is imperative to analyze the variation and inter-relationship between vegetation cover and climate pattern, especially country like Nepal having a dynamic ecosystem. This paper aims to analyze the spatial-temporal distribution of vegetation cover, temperature, and rainfall, and to examine the relationship of the latter two with vegetation for entire Nepal. Primary data used were vegetation and temperature data from Moderate Resolution Imaging Spectroradiometer (MODIS) and rainfall data from Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data product. The relationship analysis was carried out in three phases; first, the trend of vegetation with respect to rainfall and land surface temperature (LST) was inspected over entire study area by creating a time series of Normalized Difference Vegetation Index (NDVI) monthly means for six months, averaged over the whole study period. However, vegetation change pattern across various ecological regions of Nepal also needed to be considered, for the three different regions are profoundly different from each other in a number of factors like altitude and soil type. Finally, the variation of vegetation with climatic parameters, i.e. rainfall and temperature, along the eleven-year study period was also portrayed, to depict how the vegetation cover has been fluctuating over the years. During the study period, the correlation coefficient between vegetation index and rainfall was the highest in October in Terai while that with temperature was in July in Hilly region. Overall, vegetation was influenced greater by the temperature than rainfall in all three ecological regions with the highest correlation coefficient of vegetation with temperature and rainfall, being −0.937 and 0.556 respectively.