Team Members:
Person Name | Person role on project | Affiliation |
---|---|---|
Volker Radeloff | Principal Investigator | University of Wisconsin-Madison, Madison, US |
He Yin | Postdoc Researcher | Kent State University, Kent, USA |
Patrick Griffiths | Collaborator | Humboldt-Universität zu Berlin, Berlin, DE |
Patrick Hostert | Collaborator | Humboldt University of Berlin, Berlin, Germany |
Sarah Marcotte | Other | The Board of Regents of the University of Wisconsin System, Madison, US |
Abandoned agriculture is widespread, has major environmental consequences, and is an important land use change process. Indeed, the interface of abandoned versus active agriculture is often where rapid land use change takes place. However, monitoring abandoned agriculture with satellite data is difficult, and it is easily confused with fallow fields, and grasslands. Monitoring abandoned agriculture is now possible though thanks to more frequent satellite observations that capture phenology at medium resolution. Our main goal is to monitor abandoned agriculture, fallow fields, and grasslands with combined satellite images from Landsat and Sentinel-2. Our objectives are: 1) Analyze Landsat and Sentinel-2 data from single years to classify active agriculture, hayfields, and both non-woody and woody herbaceous cover; 2) analyze Landsat data from multiple years to classify a) non-woody herbaceous cover into non-woody abandoned agriculture, fallow fields, and grasslands, b) woody herbaceous cover into woody abandoned agriculture and permanent grasslands, and c) active agriculture in permanent agriculture and areas that were re-cultivated; 3) conduct a rigorous accuracy assessment and uncertainty analyses, and evaluate the robustness of the developed algorithms and their potential for operational use in the future, and 4) explore the effects of a) temperature data from TIRS, b) texture information, and c) fire detection on the mapping accuracy of abandoned agriculture. We will analyze Harmonized Landsat Sentinel-2 data after 2013, and Landsat Collection 1 data from 1983-2012. For each year after 2013, we will derive metrics from the full phenology curve, and from a spectral mixture analysis to capture green vegetation, nonphotosynthetically active vegetation, soils, and shade. Prior to 2013, we will analyze 3-5 year bins. We will test our approach globally in ten areas where we have worked before, and that capture a wide range of environmental conditions, ranging from drylands, to temperate regions, to the wet tropics, and all three major causes for abandonment, i.e., economic, political, and environmental degradation. In addition, we will analyze 345 Landsat footprints in a regional analysis across Eastern Europe, where abandonment is widespread. In addition to these research objectives, we will train one graduate student and one postdoc in remote sensing and land use science, publish at least seven journal articles, analyze data from several NASA assets to answer important scientific questions, and strengthen collaborations between scientists in the U.S. and Europe, to foster the integrated analysis of satellite data from American and European satellite missions. Our proposed work to develop algorithms and prototype products, and to analyze combined Landsat and Sentinel-2 data, to monitor abandoned agriculture, fallow fields, and grasslands, is directly relevant to the scope of the solicitation, the goals of the NASA-LCLUC program, and NASA’s mission, and it will make an important contribution to the routine monitoring of land use and land cover change globally.