The Impact of Water and Soil Conservation Structures on Remotely Sensed Vegetation Cover During the Dry and Wet Seasons at the Buenos Aires National Wildlife Refuge
KeywordsClassification and Regression Trees
Fraction Vegetational Cover
High spatial resolution imagery
Land Cover Change
AdvisorGuertin, David P.
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PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractThe effect of soil and water conservation structures (SWCS) conditions on vegetation in drylands is important because intact SWCS allow water storage that facilitates the infiltration, increases soil moisture and enhances vegetation cover. In contrast, failed SWCS cause redirection of runoff, channel incision, and lateral head cutting (Nichols et al., 2017).The present study assessed the impact of SWCS on remotely-sensed vegetation cover and landscape fragmentation metrics during the wet and dry seasons for 2017, 2018, and 2019 at the Buenos Aires National Wildlife Refuge. Multispectral PlanetScope and UAV color imagery were used to develop Land Use Land Cover Change maps, the Normalized Difference Vegetation Index (NDVI), and the Fraction Vegetation Cover (FVC). Creating and analyzing a range of different buffers sizes for all three products, I examined which intact and failed SWCS had an impact on vegetation cover and where that happened. Land Cover maps created using a supervised Classification and Regression Trees (CART) algorithm had an overall accuracy higher than 90% for all maps used in the study. Post-classification change between dry and wet seasons detected an increase in the grass/desert vegetation and a decrease for the shrubs/trees class in 2017 and 2018. This decrease can be explained because a) the woody cover presents greater variations particularly in dry years, b) small shrubs without leaves are hard to distinguish in imagery and they can die off quicker in a drought situation, and c) the data and methodology selected for this study could not detect the small shrubs/trees class in 2017 and 2018. The t-test and ANOVA statistics for NDVI and FVC revealed differences between intact and failed SWCS in the floodplain and the upland. The landscape metrics demonstrated that SWCS’s effects on vegetation cover based on fragmentation metrics were more evident during the wet season for 2017 and 2018 than for the dry season. It is necessary to identify the value of the SWCS to wildlife to determine if the structures should be maintained when they begin to deteriorate because the SWCS are related to increasing species richness associated with expanding shrubs/trees vegetation cover.
Degree ProgramGraduate College