Mixed grasslands in south Canada serve a variety of economic, environmental and ecological purposes. Numerical modeling has become a major method used to identify potential grassland ecosystem responses to environment changes and human activities. In recent years, the focus has been on process models because of their high accuracy and ability to describe the interactions among different environmental components and the ecological processes. At present, two commonly-used process models (CENTURY and BIOME-BGC) have significantly improved our understanding of the possible consequences and responses of terrestrial ecosystems under different environmental conditions. However, problems with these models include only using site-based parameters and adopting different assumptions on interactions between plant, environmental conditions and human activities in simulating such complex phenomenon. In light of this shortfall, the overall objective of this research is to integrate remote sensing products into ecosystem process model in order to simulate productivity for the mixed grassland ecosystem in the landscape level. Data used includes 4-years of field measurements and diverse satellite data (System Pour lObservation de la Terre (SPOT) 4 and 5, Landsat TM and ETM, Advanced Very High Resolution Radiometer (AVHRR) imagery). <p>Using wavelet analyses, the study first detects that the dominant spatial scale is controlled by topography and thus determines that 20-30 m is the optimum resolution to capture the vegetation spatial variation for the study area. Second, the performance of the RDVI (Renormalized Difference Vegetation Index), ATSAVI (Adjusted Transformed Soil-Adjusted Vegetation Index), and MCARI2 (Modified Chlorophyll Absorption Ratio Index 2) are slightly better than the other VIs in the groups of ratio-based, soil-line-related, and chlorophyll-corrected VIs, respectively. By incorporating CAI (Cellulose Absorption Index) as a litter factor in ATSAVI, a new VI is developed (L-ATSAVI) and it improves LAI estimation capability by about 10%. Third, vegetation maps are derived from a SPOT 4 image based on the significant relationship between LAI and ATSAVI to aid spatial modeling. Fourth, object-oriented classifier is determined as the best approach, providing ecosystem models with an accurate land cover map. Fifth, the phenology parameters are identified for the study area using 22-year AVHRR data, providing the input variables for spatial modeling. Finally, the performance of popular ecosystem models in simulating grassland vegetation productivity is evaluated using site-based field data, AVHRR NDVI data, and climate data. A new model frame, which integrates remote sensing data with site-based BIOME-BGC model, is developed for the mixed grassland prairie. The developed remote sensing-based process model is able to simulate ecosystem processes at the landscape level and can simulate productivity distribution with 71% accuracy for 2005.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:SSU.etd-03272008-112659 |
| Date | 16 April 2008 |
| Creators | He, Yuhong |
| Contributors | Piwowar, Joe, Noble, Bram F., Guo, Xulin, Franklin, Steven E., DeBoer, Dirk, Si, Bing C. |
| Publisher | University of Saskatchewan |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://library.usask.ca/theses/available/etd-03272008-112659/ |
| Rights | restricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Saskatchewan or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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