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Willem van Leeuwen
Area of Expertise:Land Surface Phenology; Biogeography; Remote Sensing Science and Applications of Coupled Natural and Human Systems; Geospatial & Temporal Decision Support Systems and Tools for Land and Water management; Assessing Impact of Fire and Drought on Vegetation Response and Drylands around the World.
Wim is an Associate Professor with joint appointments in the School of Natural Resources and the Environment - Office of Arid Lands Studies & the School of Geography and Development at the University of Arizona, Tucson, where he is teaching:
- Geographical Field Study of Environmental Geography (GEOG 303 - Spring),
- Biogeography (GEOG/ECOL/GEOS 438/538 Fall)
- Remote Sensing for the Study of Planet Earth (REM/OPT/GEOG/RNR/HWR/GEOS 490/590 - Spring).
- Physical geography seminar e.g. Coupled human and natural systems, Phenology (GEOG696C)
After a decade of research on operational remote sensing products and their validation, I am now applying my soil science background and expertise to the development and application of new remote sensing data products that focus on biogeographical and applied landscape ecological research. My overall research goals focus on the employment of remote sensing and geospatial tools for solving natural and cultural resource issues with an emphasis on the arid and semi-arid landscapes of the world. This encompasses the integration of field and remote sensing data, multi-source data analysis, modeling of coupled human and natural systems, and the development and use of decision support tools.
Wim is currently working on the development of tools and methods for characterizing and monitoring post wildfire vegetation recovery, species habitat, land degradation, invasive species mapping, land cover classification and land surface phenology in response to climate variability and human impacts, employing remote sensing and geospatial tools. He also works on cyber and web-based decision support tools and applications for agriculture and natural resource management in the US and Africa.
More specifically, Wim’s current research goals and objectives are to:
1) Develop methodologies to monitor spatio-temporal vegetation dynamics and phenology of coupled natural and human systems (e.g. land cover and land use), that are based on the synergistic use of remotely sensed and ground based biogeographic data and tools,
2) Improve our understanding of ecosystem dynamics and the role of disturbance processes by creating soil and vegetation response models that are driven by climate and other applicable biotic and abiotic variables, and
3) Integrate and translate research results and products into decision support tools for ecological forecasting and natural resource management.
Monitoring spatio-temporal vegetation dynamics and phenology of coupled natural and human systems –Wim is actively involved in interdisciplinary soil-plant-hydrologic-atmospheric research projects that are focused on attaining an improved understanding of landscape ecology and climate response, as well as our ability to map and monitor biophysical surface properties for environmental and global change studies. His initial research activities involved the collection and analysis of biophysical and radiometric in-situ data, analyzing satellite-based observations, and utilizing canopy models to explore the relationships between semi-arid vegetation cover and radiometric response. These projects involved large teams of scientists and provided an excellent training ground for successful interdisciplinary research initiatives. As an adjunct member of NASA’s MODIS land science team, he still collaborates with MODIS science team members. Another research focus is the development of a new remote sensing based methodology to monitor vegetation community life cycle trajectories (phenology) in response to climate change and variability and anthropogenic forcings. Most of this research revolves around characterizing vegetation and phenological clines of biologically diverse sky islands in Arizona. The ultimate goal and application of this research is aimed at assessing vegetation cover and land use/cover change due to climatic and anthropogenic effects.
Ecosystem dynamics and the role of disturbance processes - In the southwestern United States, drought, wildfire and monsoon rainfall events can have a devastating impact on the sustainable use of natural resources. As such, understanding the responses of ecosystems to wildfire, water erosion and management activities are foci of my current research program. In addition to applying remote sensing and GIS techniques to problems of sustainable land use and land degradation, a long-term goal is to develop new drought and ecosystem monitoring algorithms and tools based on the integration of climate data and remotely sensed land surface temperature and biophysical data (e.g. leaf area index, spectral vegetation indices). The validation of research results and new products often require a multi-scale and multi-disciplinary data collection and analysis effort dependent on collecting and utilizing in-situ radiometric and biophysical data to validate coincident airborne observations and model results. In studying these phenomena he utilizes a broad range of tools and field methods including airborne and satellite data as well as ground-based hyperspectral radiometers, Photosynthetically Active Radiation (PAR) sensors, and instruments to measure biophysical parameters. Wim is working on a multi-country research project that examines post-wildfire vegetation recovery and soil erosion dynamics using these remotely sensed time series and ground data.
Decision support tools for natural resource monitoring and management - Another keen interest of mine is developing web-based geospatial decision support tools and systems (DSS) for ecological monitoring and forecasting. A DSS is a way to integrate spatial and temporal climate data, remotely sensed land surface products, soils and reference data with ecological land surface models. He is involved with two DSS projects: 1) Rangeview: a web-based geospatial decision support tool for monitoring natural resources using geospatial technology, and 2) a NASA project, in which he is helping to establish benchmarking methods that will evaluate the performance of Decision Support Systems (DSS) with the incorporation of new NASA data and models. He also has been largely responsible for a detailed characterization of the Decision Support System of the Foreign Agricultural Service (FAS).