A new high-resolution global topographic factor dataset calculated based on SRTM.
Sci Data
; 11(1): 101, 2024 Jan 20.
Article
en En
| MEDLINE
| ID: mdl-38245566
ABSTRACT
Topography is an important factor affecting soil erosion and is measured as a combination of the slope length and slope steepness (LS-factor) in erosion models, like the Chinese Soil Loss Equation. However, global high-resolution LS-factor datasets have rarely been published. Challenges arise when attempting to extract the LS-factor on a global scale. Furthermore, existing LS-factor estimation methods necessitate projecting data from a spherical trapezoidal grid to a planar rectangle, resulting in grid size errors and high time complexity. Here, we present a global 1-arcsec resolution LS-factor dataset (DS-LS-GS1) with an improved method for estimating the LS-factor without projection conversion (LS-WPC), and we integrate it into a software tool (LS-TOOL). Validation of the Himmelblau-Orlandini mathematical surface shows that errors are less than 1%. We assess the LS-WPC method on 20 regions encompassing 5 landform types, and R2 of LS-factor are 0.82, 0.82, 0.83, 0.83, and 0.84. Moreover, the computational efficiency can be enhanced by up to 25.52%. DS-LS-GS1 can be used as high-quality input data for global soil erosion assessment.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Sci Data
Año:
2024
Tipo del documento:
Article
País de afiliación:
China