A Vegetation Phenology Extraction Method Based on High Temporal and Spatial Resolution Remote Sensing Data
A space-time resolution, remote sensing data technology, applied in image data processing, image analysis, image enhancement, etc., can solve the problems of inability to extract vegetation phenology, etc., and achieve the effect of improving extraction accuracy, high extraction efficiency, and fast speed
Active Publication Date: 2021-12-21
CHINESE ACAD OF SURVEYING & MAPPING
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[0005] The purpose of the present invention is to propose a method for extracting vegetation phenology based on high-temporal-spatial resolution remote sensing data, which is used to alleviate the technical problem that the prior art cannot accurately extract the surface vegetation phenology
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[0091] The present invention proposes a schematic diagram of the logical relationship of a vegetation phenology extraction method based on high temporal and spatial resolution remote sensing data, wherein the high temporal and spatial resolution remote sensing data is based on Sentinel-2 NDVI time series, see figure 2 , acquire the sequence remote sensing images of the target area, perform cloud detection preprocessing on the remote sensing images, and generate vegetation NDVI growth curves; design noise removal methods to optimize the NDVI growth curves, and generate stable and smooth vegetation NDVI growth curves; image 3 As shown, based on the maximum change slope method, three characteristic points of the vegetation phenophase are extracted, and finally the false phenology points are removed to generate the optimal phenophase of vegetation.
[0092] As a kind of implementation row, the step of this implementation vegetation phenology extraction method is:
[0093] Step 1...
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A vegetation phenology extraction method based on high-temporal-spatial resolution remote sensing data, which acquires sequenced remote sensing images of the target area, performs cloud detection preprocessing on the remote sensing images, and generates vegetation NDVI growth curves; designs a noise removal method to optimize the NDVI growth curves, and generates Stable and smooth vegetation NDVI growth curve; based on the maximum change slope method to extract three characteristic points of vegetation phenology; design method to filter vegetation pseudo-phenology. Finally, the extraction of surface vegetation phenology in the target area is completed. The present invention uses NDVI curves to extract surface vegetation phenology, synthesizes surface NDVI every 20 days, performs secondary filtering based on noise points of adjacent observations after synthesis, and performs an optimal synthesis after phenology extraction, using automatic extraction of all possible phenological features in NDVI curves Points, with high extraction accuracy, high extraction efficiency and fast speed, can provide technical means and references for accurately extracting the phenological stages of surface vegetation in large areas.
Description
technical field [0001] The present invention relates to a method for extracting phenology, in particular to a method for extracting vegetation phenology based on high-temporal-spatial resolution remote sensing data, which can be based on the time series of NDVI (Normalized Difference Vegetation Index) Technical issues of accurate extraction of vegetation phenology. Background technique [0002] Vegetation phenology refers to the phenomenon that the vegetation itself undergoes regular changes such as germination, branching, leaf spreading, flowering and fruiting, leaf fall, and dormancy as the vegetation changes rhythmically in the interannual climate, precipitation, temperature, and radiation. Vegetation phenology is highly sensitive to climate change. Its changes can not only reveal the growth dynamics of vegetation, but also directly reflect the response and adaptation process of vegetation ecosystems to global environmental changes. It is the most sensitive and obvious in...
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IPC IPC(8): G06K9/00G06K9/40
CPCG06T2207/10032G06T2207/30188
Inventor 车向红孙擎刘纪平王勇徐胜华罗安刘慧慧
Owner CHINESE ACAD OF SURVEYING & MAPPING