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A remote sensing inversion method of vegetation coverage and management measure factors based on LAI and multi-angle data

A technology of vegetation coverage and management measures, applied in the field of remote sensing inversion, can solve the problems of low parameter accuracy, increase prior knowledge of model inversion, etc., and achieve the effect of improving inversion accuracy

Active Publication Date: 2019-06-14
NANJING FORESTRY UNIV
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Problems solved by technology

Therefore, multi-angle remote sensing data can use spectral information and multi-angle three-dimensional structure information to increase prior knowledge in the model inversion process and improve the low accuracy of traditional single-angle data inversion of vegetation structure parameters.

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  • A remote sensing inversion method of vegetation coverage and management measure factors based on LAI and multi-angle data
  • A remote sensing inversion method of vegetation coverage and management measure factors based on LAI and multi-angle data

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Embodiment Construction

[0018] The content of the present invention will be described below in conjunction with specific embodiments.

[0019] A practical remote sensing inversion method of vegetation coverage and management measure factors based on leaf area index and multi-angle data described in this embodiment includes the following specific steps:

[0020] Step 1. In the RUSLE model, the C factor is calculated from the five subfactors of previous land use mode, canopy cover, surface cover, surface roughness, and soil moisture;

[0021] The specific formula is:

[0022] C=PLU×CC×SC×SR×SM

[0023] Among them, C is the vegetation coverage and management measures factor, PLU is the prior land use factor (Prior-land-use), CC is the canopy cover factor (Canpoy-cover), SC is the surface cover factor (Surface-cover), SR is the surface Roughness (Surface-roughness), SM is soil moisture (Soil-moisture);

[0024] CC=1-Fc×exp[-0.1×H]

[0025] Among them, Fc is the ratio of forest canopy cover to land ar...

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Abstract

The invention discloses a vegetation coverage and management measure factor remote sensing inversion method based on a leaf area index and multi-angle data. The method comprises the steps of 1, correcting a subfactor method in a soil loss equation; 2, preprocessing the multi-angle remote sensing image to obtain surface reflectance; 3, screening an optimal waveband by using a principal component analysis method; 4, inputting biochemical component parameters of a field measured sample into the radiation transmission model to obtain simulated reflectivity of the sample; 5, establishing a regression relation model between the actually measured LAI value and the actually measured C value, and determining an optimal C factor inversion model; 6, selecting a vegetation index capable of reflectingthe change of the LAI value of the forest land, and determining an optimal vegetation index; 7, inputting the vegetation index and the wave band into a random forest model, and outputting a multi-angle LAI image obtained through inversion; and 8, obtaining an inversion result of the C factor by using the C factor inversion regression equation established in the step 5. LAI and multi-angle remote sensing image information is fully utilized, and the practicability is high.

Description

technical field [0001] The invention relates to a remote sensing inversion method of vegetation coverage and management measure factor (C) based on leaf area index (LAI) and multi-angle data. Background technique [0002] Cover-Management Factor (C-factor) represents the impact of vegetation coverage and management measures on soil erosion. It is an important factor with the largest variation range in the USLE and RUSLE models, and is most sensitive to soil erosion. Overall effectiveness had the most significant effect. Reasonable estimation of C factor is of great significance for regional soil erosion quantitative evaluation and soil and water conservation planning. The C factor is defined as the ratio of the soil loss on land with specific vegetation coverage and management measures to the soil loss on land with timely plowing and continuous fallow under the same conditions of soil, slope and rainfall. It is a measure of An important indicator of vegetation resistance t...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 林杰潘颖代桥张金池许彦崟
Owner NANJING FORESTRY UNIV
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