CN-122019815-A - Domestic land exploration data automatic framing method based on space geometric overlapping relation

CN122019815ACN 122019815 ACN122019815 ACN 122019815ACN-122019815-A

Abstract

The application discloses an automatic framing method of domestic land probe data based on a space geometric overlapping relation, which comprises the steps of obtaining SAR image data, wherein the SAR image data comprise standard image data sets and image data sets to be framed, framing each scene single-view standard image in the labeling image data sets to obtain a plurality of single standard image, searching each single standard image in the image data sets to be framed, screening according to the space geometric overlapping relation, selecting images with the space overlapping relation as primary screening results, searching the single standard image in the image data sets to be framed according to the geometric overlapping relation, searching the image data sets to be framed according to the angular point longitude and latitude relation, and finally searching according to imaging time, the geometric overlapping relation and the overlapping area proportion.

Inventors

HUANG YONGFANG
LIU QINGYAO
HUANG HONGLI
BIAN HAORAN
HU JUN
Lei Yongqiao
Lin Miaoping
WU QIQIAN
LIU CAIWEI
GAO MENGFEI

Assignees

广东省国土资源测绘院
中南大学

Dates

Publication Date: 20260512
Application Date: 20251222

Claims (10)

1.A domestic land detection data automatic framing method based on a space geometric overlapping relation is characterized by comprising the following steps: Acquiring SAR image data, wherein the SAR image data comprises a standard image data set and a to-be-divided image data set; framing each single-scene standard drawing in the labeling drawing dataset to obtain a plurality of single standard drawings; Each single standard picture is searched in the picture data set to be divided, screening is carried out according to the geometric overlapping relation in space, and images with overlapping relation in space are selected as primary screening results, wherein the primary screening results comprise track data on the left side and the right side of the standard picture; setting a corner longitude threshold value for the preliminary screening result to remove the image data on other tracks except the left side and the right side to obtain a first image data set; setting a corner latitude threshold value for the first image data set to remove redundant covered image data sets in the upper and lower standard images to obtain a second image data set; and screening the second image data set by utilizing a time and space geometrical overlapping relation and overlapping area proportion to obtain an image data set after framing.
2. The method for automatically framing homemade terrestrial magnetism data based on spatial geometrical overlap relation according to claim 1, wherein the filtering the second graphic data set by using the spatial geometrical overlap relation comprises: Sorting the second image data set according to a time sequence to find out two images with the same year, month and day; Judging whether two images with the same year, month and day have an overlapping area, and when the two images have the overlapping area, forming a time sequence SAR image; and judging whether the overlapping proportion of the time sequence SAR image and the standard picture is larger than a set threshold value, and reserving if the overlapping proportion is larger than the set threshold value.
3. The method for automatically framing homemade land detection data based on spatial geometrical overlapping relationship as set forth in claim 1, wherein said screening said second image dataset with overlapping area ratio comprises: and carrying out space overlapping area proportion analysis on each single-view image in the second image data set and the standard image, deleting the data with the space geometric overlapping area not reaching the set area proportion, and reserving the data overlapped with the standard image in a large range.
4. The method for automatically framing domestic land detection data based on spatial geometrical overlapping relation as set forth in claim 1, wherein said SAR image data is derived from L-band satellite land detection satellite No. 1.
5. The method for automatically framing domestic land probe data based on spatial geometrical overlapping relationship as set forth in claim 1, wherein the labeled graphic data set refers to the graphic position of the coverage study area.
6. The method for automatically framing homemade terrestrial magnetism data based on spatial geometrical overlapping relation as set forth in claim 1 or 5, wherein the image dataset to be framed contains image data of all coverage study areas within an imaging time range.
7. The method for automatically framing domestic land detection data based on spatial geometrical overlapping relation as set forth in claim 4, wherein the SAR image data is obtained by: firstly, selecting coverage of an interested region in a land observation satellite service center according to requirements, wherein the coverage comprises file input, administrative area selection and custom polygon selection; selecting a satellite-imaging mode, wherein parameter settings comprise mode selection, terrestrial observation satellite sensor settings, orbit types, and setting a time range for acquiring images; and downloading the selected corresponding product number and the original data information in the terrestrial observation satellite service center.
8. The method for automatically framing domestic land detection data based on spatial geometrical overlapping relationship as set forth in claim 1, wherein the method further comprises: And cutting and splicing the framing data sets to obtain time sequence SAR image data on the standard frame.
9. The method for automatically framing domestic land detection data based on spatial geometrical overlapping relation as recited in claim 8, wherein the method further comprises importing the obtained time-series SAR image map data set and standard map data into a land observation satellite service center website for inspection.
10. The method for automatically framing domestic land detection data based on spatial geometrical overlapping relation as set forth in claim 2, wherein the threshold is 90%.

Description

Domestic land exploration data automatic framing method based on space geometric overlapping relation Technical Field The invention relates to the technical field of wide area InSAR and domestic land detection data framing, in particular to an automatic domestic land detection data framing method based on a space geometrical overlapping relation. Background The satellite remote sensing technology is used as an advanced information acquisition means, plays an increasingly important role in the production and life of modern human beings, relates to a plurality of fields, brings remarkable social and economic benefits, and provides information support for the production and life of the human beings and the construction of ecological space. Under the background of the time of national 'aerospace information construction', the demands of urban building safety risk assessment, digital earth, large-scale wide-area time sequence deformation monitoring and the like are rapidly induced by utilizing a satellite remote sensing technology, and trillion-level market demands are brought to the country. However, because the monitoring area is wide in range, the types of the regional ground features are complex and various, a large-scale risk investigation work is difficult to develop by manpower. With the continuous maturation and development of satellite remote sensing technology, the combined satellite remote sensing technology becomes a new choice for digital earth construction in a large range. Synthetic aperture radar interferometry (Interferometric Synthetic Aperture Radar, inSAR) technology has the advantages of large range, high precision and high resolution, and gradually becomes an effective tool for large-range 'air-to-ground' observation. In addition, the InSAR technology can monitor the ground surface tiny deformation with high precision, such as natural phenomena of earthquake, sedimentation, landslide and the like. This capability provides important data support for early warning and risk assessment of geological disasters, helping to reduce potential losses. In the aspect of city and infrastructure management, inSAR data obtained regularly can monitor deformation conditions of buildings and infrastructures in real time, discover potential safety hazards in time and support maintenance and reinforcement work. In the SAR image processing process, the time-series SAR image refers to continuous image data acquired by a Synthetic Aperture Radar (SAR) sensor at different times for the same region. And the processing of the long-time-sequence SAR image data can reflect the earth surface characteristics and dynamic information of the target area changing along with time. However, not all of the temporal SAR images are suitable for temporal processing. Along with the extension of satellite monitoring time, the data volume is continuously increased, so that the extraction of SAR image data suitable for InSAR processing from mass data is important. In past research scientists have generally focused on the retrieval of SAR image content, namely identifying and classifying SAR images containing specific targets. These studies include the use of a flight algorithm to generate hash codes for objects in the images to be retrieved, thereby retrieving the terrain classification images in the public dataset OpenSAR and MSTAR. In addition, researchers have also searched based on the coherence of deep-learning Convolutional Neural Networks (CNNs) and SAR images. However, these studies are mainly focused on content classification of SAR images, and there are rarely related problems focused on the time-series InSAR processing. The latest search algorithm focused on the time sequence InSAR data processing flow aims at the foreign sentry image data, and based on the traditional greedy algorithm, the optimal coverage of the region of interest (ROI) is searched, so that the data redundancy problem in the data processing process is reduced. For the land detection data, due to the factors of track control (framing according to time) and SAR sensor position offset, the time sequence SAR images of the same area are discontinuously distributed in the space distribution. For these discontinuous SAR image data, the existing method cannot automatically perform the search and classification, and currently, the classification and search process is performed manually. When facing a wide-area InSAR processing task, the manual searching and classifying method is time-consuming and labor-consuming and has extremely low timeliness. In order to automatically and rapidly perform land detection data wide area InSAR processing, various satellite image imaging positions need to be analyzed, and required SAR image data is retrieved based on a proper geometrical overlapping relation. And then, performing image splicing and cutting by using the retrieved images, so as to furthest utilize SAR data and realize wide area InSAR data processing. Disclosure of I