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

Li, Fayuan; Tang, Guoan; Chun, Wu; Zhang, Ting

doi:10.1117/12.761894

Cited by 10 publications

(15 citation statements)

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“…The MAB distribution information, which was collated by Fang & Gao [ 48 ] and Li [ 49 ], was investigated and verified in a field survey of Taibai Mountain in June 2018. We can obtain the distribution ranges of vegetation formations and their spatial adjacency from the MAB distribution information.…”

Section: Methodsmentioning

confidence: 99%

Automatic classification of fine-scale mountain vegetation based on mountain altitudinal belt

2020

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Vegetation mapping is of considerable significance to both geoscience and mountain ecology, and the improved resolution of remote sensing images makes it possible to map vegetation at a finer scale. While the automatic classification of vegetation has gradually become a research hotspot, real-time and rapid collection of samples has become a bottleneck. How to achieve fine-scale classification and automatic sample selection at the same time needs further study. Stratified sampling based on appropriate prior knowledge is an effective sampling method for geospatial objects. Therefore, based on the idea of stratified sampling, this paper used the following three steps to realize the automatic selection of representative samples and classification of fine-scale mountain vegetation: 1) using Mountain Altitudinal Belt (MAB) distribution information to stratify the study area into multiple vegetation belts; 2) selecting and correcting samples through iterative clustering at each belt automatically; 3) using RF (Random Forest) classifier with strong robustness to achieve automatic classification. The average sample accuracy of nine vegetation formations was 0.933, and the total accuracy of the classification result was 92.2%, with the kappa coefficient of 0.910. The results showed that this method could automatically select high-quality samples and obtain a high-accuracy vegetation map. Compared with the traditional vegetation mapping method, this method greatly improved the efficiency, which is of great significance for the fine-scale mountain vegetation mapping in large-scale areas.

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Section: Methodsmentioning

confidence: 99%

Automatic classification of fine-scale mountain vegetation based on mountain altitudinal belt

2020

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“…For example, in area with low roughness, such as Chunhua test area, slope distribute mainly between 0°-9°, frequency difference of each slope class is big, and so the Slope spectrum's information entropy is small, H Chunhua = 2.149 nat. In area with high roughness, such as Yanchuan test area, frequency difference of each slope class is less than Chunhua, so the Slope spectrum's information entropy is increased, H Yanchuan = 2.809 nat [2,8].…”

Section: Slope Spectrum Of P-n Terrainmentioning

confidence: 98%

“…Slope spectrum, which shows strong relationship with loess landform, has been proved to be an effective method to deal with loess terrain [1][2][3]. Previous studies mainly focus on its characteristic, representation, extracting method from DEMs and spatial distribution on the loess plateau.…”

Section: Introductionmentioning

confidence: 99%

Slope spectrum of positive and negative terrains on northern Shaanxi loess plateau

Tang

2010

2010 International Conference on Audio, Language and Image Processing

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In loess plateau, the shoulder-line makes a distinct separation between positive terrains and negative terrains. Using 6 typical landform units along northsouth trend of the Loess Plateau as test areas and 5 mresolution DEMs as original test data, positive terrain and negative terrain are extracted with the method of neighborhood analysis and slope threshold estimation. Then a series of carefully design experiments have been done to test the slope spectrum of P-N terrain. The results show that there exists significant difference between the slope spectrums of P-N terrains in aspect of the slope spectrum curve, skewness, slope spectrum information entropy and terrain driving force.

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“…The spectrum method, which has not been used in the study of Mars, is an effective method to reflect the spatial and temporal distribution of phenomena according to the law of gradual varies or distribution of certain indexes. It has been developed to successfully reveal the spatial structure of the slope, i.e., the slope spectrum [76][77][78][79][80]. Moreover, it was first successfully employed in SASR and PSD on Earth to reveal the spatial structure of SASR and PSD based on slope spectrum [11,12].…”

Section: Introductionmentioning

confidence: 99%

“…The spectrum method, as an effective method, can depict the spatial structure more accurately and comprehensively than other methods [11,12,[77][78][79]. Moreover, the determination of critical areas in deriving spectra is an indispensable task [78,79].…”

Section: Introductionmentioning

confidence: 99%

DEM Based Study on Shielded Astronomical Solar Radiation and Possible Sunshine Duration under Terrain Influences on Mars by Using Spectral Methods

Lin

Chen

2021

IJGI

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Solar radiation may be shielded by the terrain relief before reaching the Martian surface, especially over some rugged terrains. Yet, to date, no comprehensive studies on the spatial structure of shielded astronomical solar radiation (SASR) and the possible sunshine duration (PSD) on Mars have been conducted by previous researchers. Previous studies generally ignored the influences of the terrain on the SASR and PSD, which resulted in a corresponding unexplored field on SASR. The purpose of this paper is to study the Martian spatial-temporal structure of SASR and the PSD under terrain influences. In this paper, the theory of Earth’s SASR, the previous Martian SASR model and the theory of planetary science were combined to propose the SASR model that can be applied to Mars. Then, with the spectrum method theory of geography, we defined two new concepts of spectrums to explore the spatial-temporal distribution of SASR and PSD in different Martian landforms. We found SASR and PSD on Mars were significantly influenced by terrain relief and latitude and showed sufficient regularity, which can be concluded as a gradual attenuation with terrain relief and a regularity of latitude anisotropy. The latitude anisotropy feature is a manifestation of the terrain shielding effect. With the latitude varying, SASR and PSD at different temporal scale generally showed different features with those of Earth, which may be attributed to the imbalanced seasons caused by Martian moving orbits and velocity. Compared to PSD, SASR showed more regular variation under terrain relief and was more influenced by the terrain relief which revealed that SASR is more sensitive to terrain relief than PSD. Additionally, the critical area is a quantitative index to reflect the stable spatial structure of SASR and PSD in different landforms and may be viewed as the minimum test region of sample areas. The corresponding result of the experiments herein indicated that either spectrum can effectively depict the spatial-temporal distribution of SASR and PSD on Mars under terrain relief and deepen the understanding of the variation of SASR and PSD influences by terrain. The critical area of either spectrum can be employed to explore and determine the stable spatial structure of SASR and PSD in different landforms. The proposed Martian SASR model and the new spectral method theory shed new light on revealing the spatial-temporal structure of SASR and PSD under terrain influences on Mars.

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

Cited by 10 publications

References 0 publications

Automatic classification of fine-scale mountain vegetation based on mountain altitudinal belt

Automatic classification of fine-scale mountain vegetation based on mountain altitudinal belt

Slope spectrum of positive and negative terrains on northern Shaanxi loess plateau

DEM Based Study on Shielded Astronomical Solar Radiation and Possible Sunshine Duration under Terrain Influences on Mars by Using Spectral Methods

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