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Untangling the Interactions Between Rural Outmigration, Grassland Degradation, and Sustainable Land Use in Mongolia
Project Start Date
03/01/2022
Project End Date
03/01/2025
Region
Solicitation
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Team Members:

Person Name Person role on project Affiliation
Qiongyu Huang Principal Investigator Smithsonian Institution, Front Royal, USA
Melissa Songer Collaborator Smithsonian Conservation Biology Institute, Front Royal, US
Peter Leimgruber Collaborator Smithsonian Institution, Front Royal, US
Nicole Motzer Co-Investigator National Socio-Environmental Synthesis Center, Annapolis, USA
Ginger Allington Co-Investigator Natural Resources and the Environment , Cornell University, Ithaca, NY, USA
Abstract

The objectives of the proposal are to: 1. Assess changes in household demographics, livestock management practices, and opportunities of sustainable livelihoods related to rural outmigration; 2. Develop and assess novel algorithms for quantifying fractional grass cover, fractional vegetational functional types, and a synthetic grassland resilience index by leveraging medium-resolution satellite imagery and UAV data, and 3. Use statistical matching method to systematically assess the differences of fractional grass cover and resilience at the district level as a function of changing human and social capital.

We will evaluate changes to rural demographics and livelihoods associated with rural outmigration through a household survey administered across multiple districts in three Mongolian provinces. Survey questions will focus on the rural herding labor force, finances, and associated decisions, and potential impact on opportunities for a sustainable livelihood. We will use Landsat-8 data to model fractional grass cover in two periods between 2013 and 2022. The model will be trained using UAV-derived vegetation functional type information based on object-based segmentation and classification algorithm. We will use the Harmonized Landsat and Sentinel-2 (HLS) data to create a fractional vegetation functional types product circa 2020 and, subsequently, a synthetic grassland resilience index map. The resulting metrics will be compared between regions using a statistical matching method to systematically assess the social drivers of degradation.

Project Research Area