Quantitative analysis and spatial distribution of slope spectrum: a case study in the Loess Plateau in north Shaanxi province

Fayuan Li; Guoan Tang; Chun Wang; Ting Zhang

doi:10.1117/12.761894

25 July 2007 Quantitative analysis and spatial distribution of slope spectrum: a case study in the Loess Plateau in north Shaanxi province

Fayuan Li, Guoan Tang, Chun Wang, Ting Zhang

Author Affiliations +

Proceedings Volume 6753, Geoinformatics 2007: Geospatial Information Science; 67531R (2007) https://doi.org/10.1117/12.761894
Event: Geoinformatics 2007, 2007, Nanjing, China

Abstract

Slope spectrum is defined as a statistic model of slope distribution in a certain area. Previous researches mainly focus on morphology depiction of the slope spectrum; its spatial distribution is unknown yet, especially in the Loess Plateau. Theory and methodology of information entropy and statistics are applied for the objective of quantitatively analyzing the slope spectrum and its spatial distribution in the Loess Plateau in North Shaanxi province. Experiment results show that slope spectrum's information entropy (H), skewness of slope spectrum (S) and terrain driving force factor (T_d) can appropriately depict the slope spectrum and its spatial distribution from different points of view. Spatial distribution of the slope spectrum represents spatial distribution of loess landform types, and it is correlatable with spatial distribution of soil erosion intensity in the Loess Plateau. H, T_d and gully density, surface incision depth show positive correlation: gully density and surface incision increase as H, T_d increase. On the contrary, the S and gully density, surface incision depth show negative correlation. Lastly, spatial relationship between slope spectrum and loess landform types are qualitatively analyzed, and loess landform evolution as well.

Citation Download Citation

Fayuan Li, Guoan Tang, Chun Wang, and Ting Zhang "Quantitative analysis and spatial distribution of slope spectrum: a case study in the Loess Plateau in north Shaanxi province", Proc. SPIE 6753, Geoinformatics 2007: Geospatial Information Science, 67531R (25 July 2007); https://doi.org/10.1117/12.761894

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available