Link to Session Platform

Chairs(s):

Alana Rader, Deparment of Geography, Rutgers University

; Leonardo Calzada, Deparment of Geography, Rutgers University

Description:

Central to studying land transformation is the ability to characterize trends and spatial configurations of landscape change using long-term and multi-scalar data sets. Plenty of work has been produced by geographers looking at long-term changes and trends in landcovers such as vegetation distributions, agricultural expansion, and urban sprawl. Many of these studies relied on rich remotely sensed data repositories which are continually expanding across spatial and temporal scales. Meanwhile, biophysical field and parcel level measurements, while critical for understanding land transformation dynamics across scales, have not been as central to these long-term analyses, mostly due to the difficulty of collecting field data consistently through time. With the development of field-based biophysical monitoring networks and enhanced field data collection techniques, long-term and multi-scalar monitoring using ecological field and parcel level measurements is possible, facilitating further experimentation with temporal scales, dynamics, and trends. As such, combining both remotely sensed and in-situ field data across scales provides the opportunity to study the nuances of long-term changes and complex dynamics of land transformation, not only to common land transitions (e.g., deforestation or urban sprawl) but also complex transitions such as forest regeneration and landscape conditions after disturbances such as fires, droughts or hurricanes. From a methodological perspective, geographers are moving towards the development of analytical tools to measure and monitor long-term trends across scales and away from snapshot assessments.

Non-Presenting Participants Agenda