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Frontiers of Earth Science

ISSN 2095-0195

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Front. Earth Sci.    2021, Vol. 15 Issue (1) : 94-105    https://doi.org/10.1007/s11707-020-0830-4
RESEARCH ARTICLE
Extraction of lacunarity variation index for revealing the slope pattern in the Loess Plateau of China
Ziyang DAI1,2,3, Fayuan LI1,2,3(), Mingwei ZHAO4, Lanhua LUO1,2,3, Haoyang JIAO1,2,3
1. School of Geography, Nanjing Normal University, Nanjing 210023, China
2. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
3. Key Laboratory of Virtual Geographic Environment (Ministry of Education), Nanjing Normal University, Nanjing 210023, China
4. Department of Land Information Engineering, Chuzhou University, Chuzhou 239000, China
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Abstract

Lacunarity analysis is frequently used in multiscale and spatial pattern studies. However, the explanation for the lacunarity analysis results is limited mainly at a qualitative description level. In other words, this approach can be used to judge whether the spatial pattern of the objective is regular, random or aggregated in space. The lacunarity analysis, however, cannot afford many quantitative information. Therefore, this study proposed the lacunarity variation index (LVI) to reflect the rates of variation of lacunarity with the resolution. In comparison with lacunarity analysis, the simulated experiments show that the LVI analysis can distinguish the basic spatial pattern of the geography objects more clearly and detect the scale of aggregated data. The experiment showed that different slope types in the Loess Plateau display aggregated patterns, and the characteristic scales of these patterns were detected using the slope pattern in the Loess Plateau as the research data. This study can improve the spatial pattern analysis and scale detecting methods, as well as provide a new method for landscape and vegetation community pattern analyses. Lacunarity analysis is frequently used in multiscale and spatial pattern studies. However, the explanation for the lacunarity analysis results is limited mainly at a qualitative description level. In other words, this approach can be used to judge whether the spatial pattern of the objective is regular, random or aggregated in space. The lacunarity analysis, however, cannot afford many quantitative information. Therefore, this study proposed the lacunarity variation index (LVI) to reflect the rates of variation of lacunarity with the resolution. In comparison with lacunarity analysis, the simulated experiments show that the LVI analysis can distinguish the basic spatial pattern of the geography objects more clearly and detect the scale of aggregated data. The experiment showed that different slope types in the Loess Plateau display aggregated patterns, and the characteristic scales of these patterns were detected using the slope pattern in the Loess Plateau as the research data. This study can improve the spatial pattern analysis and scale detecting methods, as well as provide a new method for landscape and vegetation community pattern analyses.
Keywords lacunarity variation index (LVI)      slope pattern      characteristic scale      the Loess Plateau      digital elevation model (DEM)     
Corresponding Author(s): Fayuan LI   
Online First Date: 24 March 2021    Issue Date: 19 April 2021
 Cite this article:   
Ziyang DAI,Fayuan LI,Mingwei ZHAO, et al. Extraction of lacunarity variation index for revealing the slope pattern in the Loess Plateau of China[J]. Front. Earth Sci., 2021, 15(1): 94-105.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-020-0830-4
https://academic.hep.com.cn/fesci/EN/Y2021/V15/I1/94
Fig.1  Spatial distribution of the sample areas
Sample area Geographical coordinates Landform type Basic information
Suide 110°15′00″—110°22′30″E; 37°32′30″—37°37′30″N Loess hill Suide is a key watershed of soil and water conservation. The highest and lowest elevations in this area are 1115 m and 892 m, the average annual precipitation and temperature is 486 mm and 9.7°C, respectively.
Ganquan 109°30′00″—109°37′30″E;
36°10′00″—36°15′00″N		 Loess ridge The highest and lowest elevations in this area are 1459 m and 1147 m, the average annual precipitation is 670 mm, and the average temperature ranges within 10.4°C–13.6°C.
Yijun 109°18′45″—109°26′15″E;
35°25′00″—35°30′00″N		 Loess tableland The highest elevation above sea is 1158 m, whereas the lowest one is 768 m, the average annual precipitation is 709 mm, and the average temperature is 8.9°C.
Tab.1  Basic overview of the sample area
Data set Spatial pattern type Density Map size Aggregated unit size
(a) regular 0.2 250 × 250 \
(b) random 0.5 250 × 250 \
(c) aggregated 0.5 250 × 250 9
(d) aggregated 0.5 250 × 250 25
(e) aggregated 0.5 150 × 150 25
(f) aggregated 0.2 250 × 250 25
Tab.2  Information of the simulated data sets for the simulation experiment
Fig.2  Simulated data sets.
Fig.3  Types of spatial pattern.
Slope type Slope form Schematic diagram Geometric feature
Plan
curvature		 Profile curvature
Straight slope LL slope ±0 ±0
Convex slope VV slope >0 >0
VL slope ±0 >0
Concave slope CC slope <0 <0
CL slope ±0 <0
Tab.3  Geometric feature of the five slope types (ND means no definition)
Fig.4  Analysis results of the lacunarity value and LVI.
Fig.5  Lacunarity and LVI analysis.
Fig.6  CL (a) and LL slopes (b) of Yijun
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