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Landform Identification in the Chihuahuan Desert for Dust Source Characterization Applications: Developing a Landform Reference Data Set.
| 题名： | Landform Identification in the Chihuahuan Desert for Dust Source Characterization Applications: Developing a Landform Reference Data Set. |
| 作者： | Cook, S. N; Bigl, M. F; LeGrand, S. L; Webb, N; Tyree, G; Treminio, R. |
| 摘要： | ERDC-Geo is a surface erodibility parameterization developed to improvedust predictions in weather forecasting models. Geomorphic landformmaps used in ERDC-Geo link surface dust emission potential to landformtype. Using a previously generated southwest United States landform mapas training data, a classification model based on machine learning (ML)was established to generate ERDC-Geo input data. To evaluate the abilityof the ML model to accurately classify landforms, an independent refer-ence landform data set was created for areas in the Chihuahuan Desert.The reference landform data set was generated using two separate map-ping methodologies: one based on in situ observations, and another basedon the interpretation of satellite imagery. Existing geospatial data layersand recommendations from local rangeland experts guided site selectionsfor both in situ and remote landform identification. A total of 18 landformtypes were mapped across 128 sites in New Mexico, Texas, and Mexico us-ing the in situ (31 sites) and remote (97 sites) techniques. The final data setis critical for evaluating the ML-classification model and, ultimately, forimproving dust forecasting models. |
| 总页数： | 80 pages |
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