Assessing Diversity of Prairie Plants Using Remote Sensing
Authors: RAN WANG – A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy
Department of Earth and Atmospheric Sciences – University of Alberta
Abstract: Biodiversity loss endangers ecosystem services and is considered as a global change that may generate unacceptable environmental consequences on the Earth system. Global biodiversity observations are needed to provide a deep understanding of the biodiversity – ecosystem services relationship and conserve the Earth’s biodiversity. Traditionally, in situ biodiversity monitoring is limited in time and space and is usually a costly and timeconsuming enterprise. Remote sensing can provide data over a large area in a consistent,objective manner and has been used to detect plant biodiversity in a range of ecosystemsbased on the varying spectral properties of different species or functional groups. Studies estimating biodiversity using remote sensing can be generally categorized into three types: estimating biodiversity indirectly with habitat mapping; mapping distribution of individuals as a basis for assessing community composition and diversity; and assessing species richness directly from patterns of spectral variation to yield α-diversity. However, key questions remain:
1) can the diversity-productivity relationship be assessed using remote sensing?
2) what drives the variation of optical signal among species or functional groups?
3) what is the appropriate spectral and spatial scale for biodiversity detection using remote sensing?
The PSR+ Spectroradiometer was one of the instruments used during this study:
• Fast, full-spectrum UV-VIS-NIR measurements (350 – 2,500 nm)
• High Resolution Field Portable Spectroradiometer with 512 element Si array and two 256 element extended InGaAs arrays
• Various optics ranging from 1° to 25° for reflectance, radiance and irradiance measurements
• The PSR+ spectroradiometer is powered by batteries and connected to a rugged tablet which provides GPS, photo tagging, and voice notes
• Our self-developed software allows in-field mineral identification and classification
• Usage of handheld contact probe allows field measurements on outcrops or mapping open pits even at cloudy conditions
• Best signal-to-noise ratio for improved reflectance values by using full range tungsten lamps
• Detailed analysis of field samples in order to build Arctic spectral libraries from natural covers
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