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Method for adaptively designing space sampling scheme of geographic elements with aggregated distribution characteristic

A geographical element and spatial sampling technology, applied in special data processing applications, calculations, calculation models, etc., can solve the problems of general application effect and large influence in complex geographical areas, and achieve the purpose of maintaining agglomeration characteristics, improving representativeness, and intelligentization high degree of effect

Active Publication Date: 2012-07-11
WUHAN UNIV
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Problems solved by technology

However, the sampling efficiency of adaptive sampling is greatly affected by subjective factors such as the size of the sample space unit, the size of the initial sample, and the method of selecting surrounding samples, and the requirements for the distribution characteristics of samples in actual sampling are relatively strict, and the selection rules of sample points are too simplified. In actual sampling, the application effect is general in complex geographical areas where the distribution characteristics of samples change greatly

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  • Method for adaptively designing space sampling scheme of geographic elements with aggregated distribution characteristic
  • Method for adaptively designing space sampling scheme of geographic elements with aggregated distribution characteristic
  • Method for adaptively designing space sampling scheme of geographic elements with aggregated distribution characteristic

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Embodiment

[0059] Theoretical basis of the present invention is as follows:

[0060] In order to accurately reveal the spatial variation of agglomerated geographic elements, it is necessary to describe them from two levels: global and local. From the perspective of the whole domain, the clustering area in the description sampling space can be abstracted as a point (usually refers to the centroid of the clustering area), then according to the design-based method (Design based inference), the set of centroid points formed at this time can be regarded as obeying randomly distributed. That is to say, the sampling area D is divided into K subcategories C k , each C k by K i consists of sampling units, c k ∈ C k for C k The center of mass or center, according to the deduction idea based on the design, it can be known that the center of mass c k The value of Z(c k ) is a random variable. During the sampling process, c k The value of will remain unchanged, and whether it is selected as...

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Abstract

The invention relates to a method for adaptively designing a space sampling scheme of geographic elements with an aggregated distribution characteristic. The method comprises the following steps of: 1, selecting a geographic element as a sampling indicator, selecting pre-sampling point data of the sampling indicator, and determining a sampling unit and a sampling frame; 2, analyzing the pre-sampling point data in the step 1, and judging whether the sampling indicator has a space aggregated distribution characteristic or not; 3, inputting the parameters and the number of categories of a particle swarm clustering algorithm, and performing clustering analysis on the pre-sampling point data by using the particle swarm clustering algorithm to obtain a clustering center serving as an initial sampling point of the sampling indicator; and 4, inputting the parameters of a binary particle swarm optimization (BPSO) algorithm, and encrypting the initial sampling point generated in the step 3 by using the BPSO algorithm to obtain the sampling scheme of the aggregated geographic elements. The method is easy to operate, high in intelligent degree and suitable for the space sampling of geographic element indicators with the aggregated distribution characteristic, the aggregation characteristic of sampling points can be effectively kept, and the representativeness and sampling accuracy of the sampling points are improved.

Description

technical field [0001] The invention relates to a method for designing an adaptive spatial sampling scheme, in particular to a method for designing an adaptive spatial sampling scheme for agglomeration and distribution geographic elements. Background technique [0002] Geographical elements include natural geographic elements and human geographic elements, and they mainly present regular, random, and cluster distribution in space. There are relatively many geographical elements with regular and random distributions, such as soil properties, topography, and hydrology. Their spatial variation characteristics and distribution laws can be fitted by existing model-based and design-based methods, so related research and applications are relatively extensive. . For some geographical elements whose spatial distribution is clustered, the sample points reflecting their spatial variation structure usually tend to cluster distribution, and have obvious distribution centers or distribut...

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Application Information

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IPC IPC(8): G06F17/30G06N3/00
Inventor 刘耀林刘殿锋何建华焦利民
Owner WUHAN UNIV
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