Spatio-temporal Patterns Of Crop Phenology And Climate Controls Of Pakistan From 1982-2015

Long term,time series of satellite remote sensing data NDVI can be used as crop phenology in broad range of research topics as climate change,crop dynamics,and desertification.Phenology plays an important role in plant productivity and functioning of the ecosystem.Long term observations of crop phenology are being used in tracking vegetation response of climate change.In this thesis,34 years Advanced Very HighResolution Radiometer(AVHRR),NDVI3 g satellite dataset from 1982 to 2015 with spatial resolution of 8 km and temporal resolution of 15 days,were used to examine the spatial temporal patterns of vegetation.The phenological aspect such as the Start of Season(SOS),End of Season(EOS),and its variability has been studied using the time series of NDVI for Pakistan.Quantitative contribution of climate variable,namely temperature and precipitation acquired from NOAA were analyzed for determining the seasonal variability in crop phenology.First we extract seasonality parameters SOS and EOS,SOS defines from April to August and EOS from August to December of all the years respectively.The four parameters logistic function method were used to process SOS and EOS,the function found stages emerged to harvest,then we correlate and significant test used between climate and phenology shift over the period of analysis,ttest determined the significance of the correlation.The study indicates a wider spatial as well as temporal variation in the different phenological characteristic of crops within the country throughout the study period.The phenology stages such as green-up SOS and harvest EOS dates are found from the NDVI time series.The length of growing season coincides well with the on-set and withdrawal of monsoon showing a high positive correlation in moist northern part of the study area unlike semi-arid areas in the south,where a low positive correlation has been experienced.Temperature in spring primarily controlled early SOS and warmer autumn delayed EOS.Results indicate the crops are influenced by climate and increases of temperature shows uncertainty in the crop phenology estimated from remote sensing images.Crop monitoring through spatial scale is essential to development outcomes and reducing exposure risks in future.