Forest remote sensing information change probability model
A technology of information change and probability model, applied in the field of forest remote sensing, which can solve problems such as low saturation value
Pending Publication Date: 2021-07-02
国家林业和草原局林草调查规划院
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The commonly used normalized difference vegetation index (NDVI has a low saturation value for LAI (<3), although it can better reflect vegetation information under sparse vegetation conditions, it is also greatly affected by the soil background
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[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0042] see Figure 1-6 , the forest remote sensing information change probability model, using the GVI difference image histogram to describe the forest remote sensing information change probability model, the establishment of the GVI difference image histogram includes the following steps:
[0043] Step 1. First, carry out precise registration of two phases of TM images;
[0044] Step 2, establishing a mask image of the forest area;
[0045] Step 3, perform...
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The invention discloses a forest remote sensing information change probability model, the forest remote sensing information change probability model is described by using a GVI difference image histogram, and the establishment of the GVI difference image histogram comprises the following steps: firstly, carrying out two-stage TM image accurate registration; establishing a mask image of the forest region; performing mask operation on the GVI image; obtaining forest region images, and then respectively obtaining GVI images; and if the difference between the phenological periods of the two images is large, phenological normalization processing needs to be carried out, otherwise, the forest change probability is directly calculated, and the probability image is segmented according to a preset threshold value. According to the forest remote sensing information change probability model, the change probability of the forest can be described by using normal distribution. Along with the implementation of six major forestry projects in China, the serious degeneration phenomenon of the forest is more and less, and the condition that a changed area only occupies a small part in a whole scene image is met, so that the GVI difference value is ensured to obey a normal distribution rule.
Description
technical field [0001] The invention relates to the technical field of forest remote sensing, in particular to a forest remote sensing information change probability model. Background technique [0002] The northern forest region of my country belongs to the temperate zone, with four distinct seasons and great changes in phenology, especially in deciduous broad-leaved trees. The growing season of deciduous broad-leaved trees is the period of time between the beginning of growth and the end of growth before entering dormancy. Due to the great differences in the growing season in forest areas, the specific growing season in a certain place can be determined based on plant phenology and remote sensing data. Although the annual variation of phenology is not completely consistent due to global warming and some accidental factors, we still assume that the multi-year average phenology period is stable. [0003] Remote sensing data used to extract forest changes must be obtained d...
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IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/188G06F18/2415
Inventor 张煜星黄国胜任怡韩爱惠王雪军
Owner 国家林业和草原局林草调查规划院