Forest tree species remote sensing fine classification method based on cloud platform

A technology for fine classification and tree species classification, applied in the fields of instrumentation, climate sustainability, computing, etc., can solve the problem that remote sensing technology cannot quickly achieve fine classification of forest tree species, etc., to improve accuracy and reliability, repeatability and reliability. The effect of robustness

Inactive Publication Date: 2022-04-01
CHINA FORESTRY STAR BEIJING TECH INFORMATION CO LTD
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Problems solved by technology

[0005] In order to solve the problem that the existing remote sensing technology cannot quickly realize the fine classification of forest tree species in

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  • Forest tree species remote sensing fine classification method based on cloud platform
  • Forest tree species remote sensing fine classification method based on cloud platform
  • Forest tree species remote sensing fine classification method based on cloud platform

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specific Embodiment approach 1

[0050] A remote sensing fine classification method for forest tree species based on a cloud platform of the present invention is applied to the fine classification of forest tree species in the Lushui River area of ​​Fusong County, Baishan City, Jilin Province, and specifically includes the following steps:

[0051] (1) Obtain the field measured sample point data through the method of field survey. Based on the field measured sample point data, use the object-oriented classification technology in eCognition to conduct multi-scale segmentation experiments on Google's high-resolution remote sensing images near the sample point data. Segment images at the best segmentation scale, and superimpose survey quadrats at the same time. Based on the best segmentation scale results, select homogeneous patches containing survey quadrats as extended sample data, and use this data as reference data for forest tree species classification.

[0052] Using object-oriented classification technolog...

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Abstract

The invention discloses a forest tree species remote sensing fine classification method based on a cloud platform, and relates to the field of forest tree species classification methods. Screening high-quality Sentinel-2 MSI images to form an image set; calculating NDVI, EVI, NDII and NBR of each image in the image set to obtain images of four indexes in space; using a median synthesis function to generate monthly, seasonal and annual synthesis images; calculating topographic factors and adding the topographic factors into the synthetic image; using a random forest to calculate variables with top feature importance ranking; optimizing hyper-parameters of the random forest to obtain an optimal parameter combination, and realizing tree species classification by utilizing the optimized classifiers under different data sets; and verifying and comparing the classifier precision under different data sets to realize forest tree species fine classification and spatial distribution mapping. According to the method, forest tree species fine classification in a large-area mountainous area can be accurately and quickly realized.

Description

technical field [0001] The invention relates to the technical field of forest tree species classification methods, in particular to a remote sensing fine classification method for forest tree species based on a cloud platform. Background technique [0002] Forests are called the "lungs of the earth" and play a vital role in regulating the climate, preventing wind and sand, conserving water sources, and purifying pollution. Tree species composition and spatial distribution information is of great significance to forest resource survey and monitoring, stock volume or biomass estimation, forest disturbance identification, and biodiversity monitoring. Due to global warming and human disturbance, forest fires, pests and diseases, and deforestation occur frequently, resulting in major changes in the composition and spatial distribution of forest tree species, resulting in a decline in forest ecological functions. Therefore, timely and accurate mapping of the spatial distribution ...

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Application Information

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IPC IPC(8): G06V10/26G06K9/62G06V10/764G06V20/10
CPCG06F18/241Y02A90/10
Inventor 张蓉曹禹贾明明王宗明王生杰
Owner CHINA FORESTRY STAR BEIJING TECH INFORMATION CO LTD
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