Expanding Remote Sensing through Collaboration

Full Title

Expanding access to data-intensive remote sensing algorithms through collaboration with the SES research community


Protected ecosystems, temperate zones, and wealthier countries receive a disproportionate amount of research attention. Fragmented landscapes, tropical biomes, and developing countries, meanwhile, are routinely overlooked despite their greater coverage of the Earth’s surface, extreme biodiversity, and critical ecosystem services. Satellite remote sensing can be used to bolster understanding of socio-environmental systems within understudied regions. However, persistent cloud cover, particularly in the tropics, limits the utility of satellite-based landscape monitoring. Moreover, the socio-environmental research community, trained in field-based or qualitative methods, have rarely adopted remote sensing approaches due to data/computational complexity as well as traditional disciplinary isolation.

In the proposed Pursuit, we seek to overcome these long-standing, enviro-climatic and disciplinary limitations by convening a diverse group of interdisciplinary, socio-environmental researchers with ongoing projects in understudied regions. We have developed a cloud-resilient remote sensing algorithm (“NITA”) to distill dense time series of satellite imagery into metrics of protracted (e.g., drought) and acute (e.g., forest clearing) land-cover change. Socio-environmental researchers have voiced interest in implementing NITA but presently it is only available as a Matlab prototype and may not optimally satisfy the needs articulated by this diverse community. Thus, we propose this data-intensive SESYNC Pursuit to: 1) Refine NITA through collaboration with the SES community and SESYNC data scientists; 2) Broaden the reach of the algorithm by transitioning to open-source code; and 3) Implement NITA with invited participants to augment research coverage in difficult-to-access areas.

Project Type
Team Synthesis Project
Principal Investigators
Michael Alonzo, American University
Jamon Van Den Hoek, Oregon State University
Jared Stabach, Smithsonian Conservation Biology Institute
Qiongyu Huang, Smithsonian Institution
Cara Steger, Colorado State University
Fernando Sedano, University of Maryland
Jordan Read, United States Geological Survey
Carl Levan, American University
Hannah Friedrich, Oregon State University
Hannah Julia Meszaros Martin, Goldsmiths, University of London
Kaspar Hurni, Centre for Development and Environment (CDE), University of Bern
Paulo Jose Murillo-Sandoval, Oregon State University
Nabil Ahmed, London Metropolitan University
Benjamin DeVries, University of Maryland
Leyang Feng, American University
John Zinda, Cornell University

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