A new generation of remote sensing software technology system for rapid application of data (Ⅱ)

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Remote Sensing Interpretation and Analysis

Remote sensing interpretation and analysis technology integrates advanced computer vision algorithms. It realizes a variety of remote sensing interpretation functions, and provides complete process tools to support users to manage image samples, train, reason and evaluate models. In addition, SuperMap provides remote sensing intelligent interpretation pre-training models for a variety of scenarios.

• Intelligent interpretation function

This function supports multiple remote sensing interpretation functions such as binary classification, ground object classification, change detection, target detection, object extraction, scene classification, etc.

• Pre-trained model for intelligent interpretation

The use of deep learning has greatly improved the efficiency of remote sensing image interpretation. However, the data, time and computing power required for deep learning model training are also issues that cannot be ignored in practical applications.

To lower users'usage cost, and improve the usability of remote sensing interpretation products, SuperMap provide pre-trained models for various application scenarios:

1. Ready-to-use pre-trained models are provided for typical scenarios such as forest land, cultivated land, urban water bodies, and urban buildings, with an average accuracy of 85%.

2. A large pre-trained model for remote sensing interpretation is provided for high-precision object classification

The remote sensing interpretation pre-trained large model LIM (Large Imagery Model) is constructed from two parts, upstream and downstream, including the upstream self-supervised learning network and the downstream classification task network.

It can more effectively learn the features of objects contained in remote sensing images and achieve higher-precision and fine-grained classification and recognition of objects. The experimental results show that the classification accuracy of 7 types of objects exceeds 80%, and the classification accuracy of 5 types of objects exceeds 90%.

3. New G-SAM, which introduces semantic information through spatial cues to achieve fine-grained image segmentation

The Segment Anything Model (SAM), a general-purpose computer vision model, is trained with over 1 billion labels and can effectively segment images based on prompt information. SAM is training-free and highly generalizable, and can be applied to the field of remote sensing interpretation. However, the segmentation results obtained by the model on the image do not have spatial information and geographic attributes.

G-SAM (Geospatial SAM) is an extension of SAM in the field of geospatial. By introducing rectangular box prompts or polygon prompts obtained based on remote sensing images, the segmentation results have clear spatial information and geographic attributes, which enhances the practical value of SAM in the field of remote sensing interpretation. Geospatial prompt information can also be automatically obtained through the remote sensing intelligent interpretation model, ensuring the efficiency and ease of use of G-SAM. In addition, it also supports users to segment objects through simple interactive operations, which can improve the efficiency of remote sensing image sample annotation.

Remote sensing data visualization

Remote sensing data visualization refers to the display of processed remote sensing data in the form of images, which can intuitively display the characteristics and changes of the earth surface. It has great application value in the fields of environmental monitoring, resource management, disaster warning, etc. SuperMap supports a variety of remote sensing data visualization display technologies, mainly including:

1. Visualization based on mosaic datasets. In order to improve the query and browsing performance of image data, image pyramids and overviews need to be created before querying and browsing. Image pyramid technology uses image resampling methods to establish a series of image layers with different resolutions and establish a corresponding spatial index mechanism, thereby reducing the amount of transmitted data and optimizing display performance when zooming and browsing images. In order to efficiently display images at small scales, it is necessary to build overviews.

2. Visualization based on image cache. In order to improve the user browsing experience, pre-slicing (i.e. image cache) is generally used to improve the browsing efficiency of image data. Image cache tiles are organized according to a pyramid structure, and each tile can be uniquely marked by level, row and column number. When panning and zooming images, the browser calculates the required tiles according to the pyramid rules, obtains them from the tile server and splices them for display.

3. Visualization based on image services. Image service visualization technology is equipped with the ability to publish image map services without slicing. Images can be dynamically mosaicked and displayed, and support the configuration of display styles, which takes effect in real-time. The " slice-free" technology mainly relies on raster pyramids, distributed rendering, automatic caching and other technologies to achieve the ability to directly store data without slicing and dynamically render spatial data. In addition, the visualization of original image data, image uniformity preview results and image enhancement results are all based on mosaic datasets.

Summary

With the advancement of remote sensing technology and the rapid development of new technologies represented by artificial intelligence and cloud native, it is time to build a new generation of remote sensing software technology. Based on the Geospatial AI Technology Foundation (AIF), covering the full process capabilities from remote sensing data management to remote sensing data visualization, focusing on breakthroughs in core technologies related to remote sensing data processing and remote sensing interpretation and analysis, SuperMap has built a new generation of remote sensing software technology system and developed a series of remote sensing products.

At the remote sensing product level, SuperMap has also released SuperMap iDesktopX 2024, a remote sensing and GIS integrated desktop platform, SuperMap ImageX Pro 2024, a remote sensing image processing desktop software, and SuperMap iServer 2024, a remote sensing and GIS integrated server platform, providing powerful remote sensing and GIS integration capabilities. Welcome to visit SuperMap's official website to download and have a trial.

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