Detecting Ecosystem Disturbances and Land Cover Change using Data Mining

Remote sensing data that consists of satellite observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, combined with historical climate records and predictions from ecosystem models, offers new opportunities for understanding how the Earth is changing, for determining what factors cause these changes, and for predicting future changes. Data mining and knowledge discovery techniques can aid this effort by discovering patterns that capture complex interactions among ocean temperature, air pressure, surface meteorology, and terrestrial carbon flux. Specifically, in this paper we discuss the analysis of satellite observations of the land surface with two important goals: to detect large-scale ecosystem disturbances with natural and anthropogenic causes using low-resolution data, and to detect changing land cover patterns using high-resolution data.