Sam Jantz

Graduate Student

Email:

sjantz@umd.edu

Supervisor:

Matthew Hansen

Thesis Title:

Multiscale, Multitemporal Assessment of Chimpanzee (Pan troglodytes) Habitat Using Remotely Sensed Datasets

I am particularly interested in utilizing remotely sensed data and geo-spatial modeling to support conversation projects. My current work is in support of a collaborative project with the Jane Goodall Institute entitled "Monitoring and Forecasting Chimpanzee Habitat Health in Africa to Inform Conservation Actions, Strategies and Measure Success". My contribution to this project involves the creation of a range wide chimpanzee habitat suitability model driven by remotely sensed datasets and the simulation of future deforestation scenarios.

Projects: Graduate Researcher

Integrating earth observation and forest inventory data in quantifying biomass in degraded forests of the Republic of Congo
Monitoring and forecasting chimpanzee habitat health in Africa to information conservation actions, strategies & measure success

Publications:

Pickering, J., Stehman, S.V., Tyukavina, A., Potapov, P., Watt, P., Jantz, S.M., Bholanath, P., Hansen, M.C. (2019) Quantifying the trade-off between cost and precision in estimating area of forest loss and degradation using probability sampling in Guyana. Remote Sensing of Environment 221, 122-135.
Jantz, S.M., Pintea, L., Nackoney, J., Hansen, M.C. (2018) Global forest maps in support of conservation monitoring. In: Satellite Remote Sensing for Conservation Action - Case Studies from Aquatic and Terrestrial Ecosystems (A. Leidner & G. Buchanan, Eds.). Cambridge, U.K.: Cambridge University Press.
Jantz, S.M., Pintea, L., Nackoney, J., Hansen, M.C. (2016) Landsat ETM+ and SRTM Data Provide Near Real-Time Monitoring of Chimpanzee (Pan troglodytes) Habitats in Africa. Remote Sensing, 8(5), 427.
Jantz, S. M., Barker, B., Brooks, T. M., Chini, L. P., Huang, Q., Moore, R. M., Noel, J. and Hurtt, G. C. (2015) Future habitat loss and extinctions driven by land-use change in biodiversity hotspots under four scenarios of climate-change mitigation.Conservation Biology. 29(4):1122-1131.

GLAD