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Accueil du site → Doctorat → États-Unis → 2021 → Evaluation of Rangeland Degradation in Response to Climate Change Using Remote Sensing to Support New Mexico’s Food-Energy-Water Systems

New Mexico State University (2021)

Evaluation of Rangeland Degradation in Response to Climate Change Using Remote Sensing to Support New Mexico’s Food-Energy-Water Systems

Gedefaw, Melakeneh Gelet

Titre : Evaluation of Rangeland Degradation in Response to Climate Change Using Remote Sensing to Support New Mexico’s Food-Energy-Water Systems

Auteur : Gedefaw, Melakeneh Gelet

Université de soutenance : New Mexico State University

Grade : Doctor of Philosophy (PhD) 2021

Description partielle
The prevalence of climate variability, land use/land cover (LULC) change, and prolonged and severe droughts have been affecting water availability and the productivity of rangelands and agriculture systems in arid and semi-arid regions of the Southwestern United States of America (USA), including New Mexico (NM). Rangeland livestock production systems contribute significantly to NM’s economy and society. The use of remote sensing in studying the impacts of interannual precipitation variability and drought on rangeland productivity can provide significant information that can be used in evaluating NM’s Food-Energy-Water systems (FEWS) behavior and for resource monitoring. The main goal of this study was to evaluate land use/land cover change and detect rangeland degradation. This goal was achieved following three objectives. The first objective was to assess the accuracy of land use/land cover thematic maps of the National Land Cover Database (NLCD), evaluate their corresponding area estimates, and related uncertainties at county level. The second objective was to investigate the structural changes of NM’s rangelands due to interannual variability of precipitation. The third objective was to compare identified rangeland changes based on two independent methods of detection and evaluate the impacts of drought on rangeland degradation. To achieve the first objective, the NLCD legacy maps of year 1992, 2002,2006,2011 and 2016, and standardized protocols of accuracy assessment and area estimation based on the System for Earth Observation Data Access, Processing, and Analysis for Land Monitoring (SEPAL) were used. To achieve the second objective, the Normalized Difference Vegetation Index (NDVI) of the Global Inventory Modeling and Mapping Studies (GIMMSv3.1g), monthly precipitation from Parameter elevation Regressions on Independent Slopes Model (PRISM), and The Time Series Segmented Residual Trend Analysis (TSS-RESTREND) method were employed to detect structural and productivity changes during 1982 to 2015. To achieve the third objective, the Self-Calibrated Palmer Severity Drought Index (sc-PDSI), the Standardized Precipitation Evapotranspiration (SPEI) combined with the TSS-RESTREND, simple linear regression, and the Continuous Change Detection and Classification (CCDC) algorithms were used. The results showed that user’s and producer’s accuracy of most LULC classes of all study counties were about or above 80%. The obtained Overall Accuracy (OA) at county level were lower than the OA of the NLCD maps that were reported at the regional or national scale

Présentation (NMSU )

ProQuest

Page publiée le 13 décembre 2022