# A Blockchain Solution for Remote Sensing Data Management Model
## 2 Problem Description  
### Characteristics of Remote Sensing Data  
Remote sensing data refer to the remote sensing images obtained via various remote sensing techniques, which are multi-level, multi-angle, multi-spectral, multi-temporal, and multi-dimensional data with temporal, spatial, and spectral dimensions. Based on the above definition, the remote sensing data are abstracted into the following types, \(T_{i}=\{Key_{i},Time_{i},Space_{i},imageinfo_{i},sinffo_{i}\}\). The \(Key_{i}\) is the hash value generated by the hashing operation of \(T_{i}\), \(Space_{i}\) is the spatial attribute, and \(Time_{i}\) is the temporal attribute, \(mageinfo_{i}\) represents the metadata of this image itself, such as the image type, size, scale, etc. And \(rsinffo_{i}\) means remote sensing information, includes satellite and sensor information [19]. At the same time, remote sensing data also have the characteristics of big data, with massive remote sensing datasets as the main dataset, and comprehensive other auxiliary data from multiple sources, and using big data thinking and means to focus on the theory, method, technology, and activities of obtaining valuable information from massive remote sensing datasets of multiple sources, multiple media, multiple frequency bands, and multiple resolutions. At present, the main challenges facing the management and production of remote sensing big data are as follows. 1. Data credibility problem  
From satellite data acquisition to product visualization for public services, the production process of remote sensing data faces various challenges that cause data unreliability. (a) The source of the auxiliary data, such as proximity sensors, is unreliable. (b) Starting from the satellite data reception, the remote sensing data will go through multiple pre-processing steps, such as geometric correction, radiometric correction, atmospheric correction, etc., and then various value-added products will be obtained through various algorithms. Throughout the life cycle, the complex process leads to the possibility of errors [20]. It is difficult to assess the accuracy of the remote sensing data processing steps in the process, which leads to unreliable final decision knowledge. (c) There is a risk of falsification in processing and circulation, and the data are recorded in a centralized platform, meaning that there is a possibility of data being attacked and tampered with, both of which can cause unreliable data to be in circulation. The result of these factors is that the quality of the data that users eventually obtain cannot be guaranteed. This is one of the main challenges in remote sensing data production and management. 2. The issue of data traceability and confirmation of rights  
The traceability of remote sensing data to confirm rights refers to determining the ownership attribution and using the rights attribution of remote sensing product data. This issue and the credibility issue are complementary to each other. If we can successfully trace the source of, and clarify, the data attribution issue, then these problem data can also find the source of, and provide the basis for, the credibility of the data. The current production process of remote sensing products cannot be authentically traced because of the lack of reliable accounting books for data processing, although the process of data processing can be recorded throughout the data-information-knowledgelife cycle. The ownership of product data is often unclear. The traditional means of validation uses the model of submitting proof of ownership and expert review, which lacks technical credibility and has uncontrollable factors, such as potential tampering. Improving the transparency of the process of realizing the value of remote sensing data, and providing users with authentic and reliable datasets are other major issues in remote sensing big data management. In the current context of the big data era, using multiple remote sensing data sources for information extraction has become a major trend.