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Willem van Leeuwen

Publications and source records attributed to Willem van Leeuwen.

3 recordsLinked to original sources

Historical analysis of riparian vegetation change in response to shifting management objectives on the Middle Rio Grande

Riparian ecosystems are valuable to the ecological and human communities that depend on them. Over the past century, they have been subject to shifting management practices to maximize human use and ecosystem services, creating a complex relationship between water policy, management, and the natural ecosystem. This has necessitated research on the spatial and temporal dynamics of riparian vegetation change. The San Acacia Reach of the Middle Rio Grande has experienced multiple management and river flow fluctuations, resulting in threats to its riparian and aquatic ecosystems. This research uses remote sensing data, GIS, a review of management decisions, and an assessment of climate to both quantify how riparian vegetation has been altered over time and provide interpretations of the relationships between riparian change and shifting climate and management objectives. This research focused on four management phases from 1935 to 2014, each highlighting different management practices and climate-driven river patterns, providing unique opportunities to observe a direct relationship between river management, climate, and riparian response. Overall, we believe that management practices coupled with reduced surface river-flows with limited overbank flooding influenced the compositional and spatial patterns of vegetation, including possibly increasing non-native vegetation coverage. However, recent restoration efforts have begun to reduce non-native vegetation coverage.

New Mexico

Hyperspectral remote sensing tools for quantifying plant litter and invasive species in arid ecosystems

Green vegetation can be monitored and distinguished using visible and infrared multiband and hyperspectral remote sensing methods. The problem has been in identifying and distinguishing the nonphotosynthetically active radiation (PAR) landscape components, such as litters and soils, from green vegetation [35-38]. Additionally, distinguishing different species of green vegetation is challenging using the relatively few bands available on most satellite sensors. This chapter focuses both on previously published work by Nagler et al. [35-38] that identified hyperspectral remote sensing characteristics that distinguish between green vegetation, soil, and litter (or senescent vegetation), and on new research conducted to aid in distinguishing invasive species from the mixed landcover surface.

Book chapter

Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data

This study introduces a new geographic framework, phenological classification, for the conterminous United States based on Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time-series data and a digital elevation model. The resulting pheno-class map is comprised of 40 pheno-classes, each having unique phenological and topographic characteristics. Cross-comparison of the pheno-classes with the 2001 National Land Cover Database indicates that the new map contains additional phenological and climate information. The pheno-class framework may be a suitable basis for the development of an Advanced Very High Resolution Radiometer (AVHRR)-MODIS NDVI translation algorithm and for various biogeographic studies.

Remote Sensing