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Measuring similarity or distance between two entities is a key step for several data mining and knowledge discovery tasks. The notion of similarity for continuous data is relatively well-understood, but for categorical data, the similarity computation is not straightforward. Several data-driven similarity measures have been proposed in the literature to(More)
The study of land cover change is an important problem in the Earth Science domain because of its impacts on local climate, radiation balance, biogeochemistry, hydrology, and the diversity and abundance of terrestrial species. Most well-known change detection techniques from statistics, signal processing and control theory are not well-suited for the(More)
Forests are a critical component of the planet's ecosystem. Unfortunately, there has been significant degradation in forest cover over recent decades as a result of logging, conversion to crop, plantation, and pasture land, or disasters (natural or man made) such as forest fires, floods, and hurricanes. As a result, significant attention is being given to(More)
It is well-known that forests play a vital role in maintaining biodiversity and the health of ecosystems across the Earth. This important ecological resource is under threat from both anthropogenic and biogenic pressures, ranging from insect infestations to commercial logging. Detecting, quantifying and reporting the magnitude of forest degradation are(More)
Mesoscale ocean eddies transport heat, salt, energy, and nutrients across oceans. As a result, accurately identifying and tracking such phenomena are crucial for understanding ocean dynamics and marine ecosystem sustainability. Traditionally, ocean eddies are monitored through two phases: identification and tracking. A major challenge for such an approach(More)
Mapping land cover change is an important problem for the scientific community as well as policy makers. Traditionally, bi-temporal classification of satellite data is used to identify areas of land cover change. However , these classification products often have errors due to classifier inaccuracy or poor data, which poses significant issues when using(More)
Reference based analysis (RBA) is a novel data mining tool for exploring a test data set with respect to a reference data set. The power of RBA lies in it ability to transform any complex data type, such as symbolic sequences and multi-variate categorical data instances, into a multivariate continuous representation. The transformed representation not only(More)
—Automatic identification of changes in land cover from remote sensing data is a critical aspect of monitoring the planet's ecosystems. We use time series segmentation methodology for detecting land cover changes from Moderate Resolution Imaging Spectroradiometer-based vegetation index. In this paper, we investigate segmentation scores based on difference(More)