Forest biomass-based remote sensing image feature selection method and apparatus
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A forest biomass and remote sensing image technology, applied in the field of remote sensing image feature selection of forest biomass, can solve the problems of no solution, poor comprehensive effect, large error in the results of forest biomass optimization model, etc., to achieve the optimization effect, Small error effect
Inactive Publication Date: 2016-09-28
LIANYUNGANG TECHN COLLEGE +1
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However, the methods usually used at present will take a long time to select more features, and the results of the derived forest biomass optimization model have large errors, resulting in poor overall results.
[0004] Aiming at the problem that the remote sensing image features selected in the above method are not effective, no effective solution has been proposed so far.
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Embodiment 1
[0036] see figure 1 A flow chart of a remote sensing image feature selection method for forest biomass as shown, the method includes the following steps:
[0037]Step S102, extracting feature values from forest remote sensing images; wherein, forest remote sensing images are satellite images or aerial images that record the characteristics of forest electromagnetic waves, which can reflect various characteristics and attributes contained in the forest. The eigenvalues can be divided into single-band features, vegetation indices, texture features, terrain factors and other feature types, and each feature type can be subdivided into multiple features. For example, the vegetation index feature types mainly include: difference vegetation index, normalized difference vegetation index, ratio vegetation index, environmental vegetation index, soil vegetation index, vertical vegetation index, brightness index transformed by tasseled cap, greenness index, humidity index, And featur...
Embodiment 2
[0065] Corresponding to the method provided by the above-mentioned embodiment, the embodiment of the present invention also provides a remote sensing image feature selection device for forest biomass, see figure 2 , the device consists of the following modules:
[0066] Feature value extraction module 202, for extracting feature values from forest remote sensing images;
[0067] The feature set generation module 204 is used to preprocess the eigenvalues by the SR algorithm, and remove the eigenvalues corresponding to the multicollinearity from the preprocessed eigenvalues to generate the feature set; wherein, the initial set of the feature set is the eigenvalue full set;
[0068] The feature set update module 206 is used to repeatedly update the feature set according to the following functions: according to the SVM algorithm, determine the weight of each feature value in the initialization feature set; use the SVM-REF algorithm and the weight to construct the feature...
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Abstract
The present invention provides a forest biomass-based remote sensing image feature selection method and a forest biomass-based remote sensing image feature selection apparatus. The method includes the following steps that: feature values are extracted from a forest remote sensing image, the feature values are preprocessed through an SR (stepwise regression) algorithm, and feature values corresponding to multicollinearity are removed from the preprocessed feature values, so that a feature set can be generated, the initial set of the feature set is a full set; the feature set is updated repeatedly according to the following processes: an SVM (support vector machine) algorithm is trained according to the initialization feature set, so that the weights of feature values in the initialization feature set are determined, an SVM-REF (support vector machine-recursive feature elimination) algorithm and the weights are adopted to construct the feature sequencing coefficient of the feature values in the feature set, and the feature values in the feature set are sequenced according to the feature sequencing coefficient, and the feature set is updated according to the sequence of the feature set; and update operation is carried out continuously until the number of feature values in the current feature set is equal to a preset number of feature values, and the current feature set is determined as the optimal feature set used for forest biomass. With the method and apparatus of the invention adopted, the effect of remote sensing image feature selection can be optimized.
Description
technical field [0001] The technical field of remote sensing images of the present invention, in particular, relates to a feature selection method and device for remote sensing images of forest biomass. Background technique [0002] Remote sensing image features are the most essential attributes unique to images and used to distinguish them from other images. There are many kinds of image features, including natural features such as terrain, vegetation, and hydrology, as well as human objects such as houses and roads, and the relationship between these features is also intricate. Therefore, in the analysis of remote sensing images Among them, remote sensing image feature selection technology plays an important role. [0003] Forest biomass accounts for about 90% of the global terrestrial vegetation biomass. It is not only an important indicator of forest carbon sequestration capacity, but also an important parameter for evaluating forest carbon budget. Therefore, the study...
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