The relationship between temporal and spatial data is considered the major advantage of remote sensing in research related to biophysical characteristics. With temporally formatted remote sensing products, it is possible to monitor environmental changes as well as global climate change through time and space by analyzing vegetation phenology. Although a number of different methods have been developed to determine the seasonal cycle using time series of vegetation indices, these methods were not designed to explore and monitor changes and trends of vegetation phenology in Southeast Asia (SEA). SEA is adversely affected by impacts of climate change, which causes considerable environmental problems, and the increase in agricultural land conversion and intensification also adds to those problems. Consequently, exploring and monitoring phenological change and environmental impacts are necessary for a better understanding of the ecosystem dynamics and environmental change in this region. This research aimed to investigate inter-annual variability of vegetation phenology and rainfall seasonality, analyze the possible drivers of phenological changes from both climatic and anthropogenic factors, assess the environmental impacts in agricultural areas, and develop an enhanced visualization method for phenological information dissemination. In this research, spatio-temporal patterns of vegetation phenology were analyzed by using MODIS-EVI time series data over the period of 2001-2010. Rainfall seasonality was derived from TRMM daily rainfall rate. Additionally, this research assessed environmental impacts of GHG emissions by using the environmental model (DNDC) to quantify emissions from rice fields in Thailand. Furthermore, a web mapping application was developed to present the output of phenological and environmental analysis with interactive functions. The results revealed that satellite time-series data provided a great opportunity to study regional vegetation variability and internal climatic fluctuation. The EVI and phenological patterns varied spatially according to climate variations and human management. The overall regional mean EVI value in SEA from 2001 to 2010 has gradually decreased and phenological trends appeared to shift towards a later and slightly longer growing season. Regional vegetation dynamics over SEA exhibited patterns associated with major climate events such as El Niño in 2005. The rainy season tended to start early and end late and the length of rainy season was slightly longer. However, the amount of rainfall has decreased from 2001 to 2010. The relationship between phenology and rainfall varied among different ecosystems. Additionally, the local scale results indicated that rainfall is a dominant force of phenological changes in naturally vegetated areas and rainfed croplands, whereas human management is a key factor in heavily agricultural areas with irrigated systems. The results of estimating GHG emissions from rice fields in Thailand demonstrated that human management, climate variation, and physical geography had a significant influence on the change in GHG emissions. In addition, the complexity of spatio-temporal patterns in phenology and related variables were displayed on the visualization system with effective functions and an interactive interface. The information and knowledge in this research are useful for local and regional environmental management and for identifying mitigation strategies in the context of climate change and ecosystem dynamics in this region.
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