The urban transition that has emerged over the past quarter century poses new challenges for mapping land cover/land use change (LCLUC). The growing archives of imagery from various earth-observing satellites have stimulated the development of innovative methods for change detection in long-term time series. We tested two different multi-temporal remote sensing datasets and techniques for mapping the urban transition.

Ulaanbaatar, the capital of Mongolia, has expanded rapidly over the past decade. Insufficient authority is in place to address this expansion, and many residential plots have been developed in the peripheral regions of the city. The aim of this study is to estimate changes in land cover within the central part of Ulaanbaatar, which has been affected by anthropogenic disturbances.

This research examines the integration and potential uses of linkages between climate dynamics, savanna vegetation and landscape level processes within a highly vulnerable region, both in terms of climate variability and social systems. We explore the combined applications of two time-series methodologies: (1) climate signals detected in tree ring growth, from published literature, chronologies from the International Tree-Ring Data Bank, and minimal preliminary field data; and (2) new primary production (NPP) data of vegetation cover over time derived from remotely sensed analyses.