An Implementation of Open Source-Based Software as a Service (SaaS) to Produce TOA and TOC Reflectance of High-Resolution KOMPSAT-3/3A Satellite Image

Abstract

The majority of cloud applications are created or delivered to provide users with access to system resources or prebuilt processing algorithms for efficient data storage, management, and production. The number of cases linking cloud computing to the use of global observation satellite data continues to rise, owing to the benefits of cloud computing. This study aims to develop a cloud software as a service (SaaS) that yields reflectance products in high-resolution Korea Multi-Purpose Satellite (KOMPSAT)-3/3A satellite images. The SaaS model was designed as three subsystems: a Calibration Processing System (CPS), a Request System for CPS supporting RESTful application programming interface (API), and a Web Interface Application System. Open-source components, libraries, and frameworks were used in this study’s SaaS, including an OpenStack for infrastructure as a service. An absolute atmospheric correction scheme based on a Second Simulation of a Satellite Signal in the Solar Spectrum (6S) radiative transfer code with atmospheric variable inputs was used to generate the top-of-atmosphere (TOA) and top-of-canopy (TOC) reflectance products. The SaaS implemented in this study provides users with the absolute atmospheric calibration functionality to apply their KOMPSAT-3/3A satellite image set through a web browser and obtain output directly from this service. According to experiments to check the total performance time for images, bundled with four bands of red, green, blue, and near-infrared, it took approximately 4.88 min on average for the execution time to obtain all reflectance results since satellite images were registered into the SaaS. The SaaS model proposed and implemented in this study can be used as a reference model for the production system to generate reflectance products from other optical sensor images. In the future, SaaS, which offers professional analysis functions based on open source, is expected to grow and expand into new application fields for public users and communities.

Deforestation and Its Effect on Surface Albedo and Weather Patterns

“…Atmospheric correction eliminates or reduces the distortion associated with gases and particles in the atmosphere, which scatter solar radiation captured by satellite sensors. It is accomplished by using spectral characteristics for each band of the sensor expressed in digital levels (DN) [1,27,28]; they are proportional to the original radiance captured by the sensor; they are in 16-bit unencrypted format, so it is necessary to transform them to radiance values of the top of the atmosphere (TOA) starting from the sensor calibration coefficients and the scale factor of 0.1 (Equation ( 3)) [20,27]; and they are normalized to transform into reflectance values expressed in percentage given that the real reflectance of a roof captured by the sensor is conditioned by the behavior of the atmosphere and the angle of observation; for this the conversion method with solar angle (Equation ( 4)) [20,27] was used. This method improves the precision of the reflectance of the surface, in comparison with other methods.…”

Prototyping of Utilization Model for KOMPSAT-3/3A Analysis Ready Data Based on the Open Data Cube Platform in Multi-Cloud Computing Environment: A Case Study

“…Therefore, the multi-cloud model proposed in this study includes processing systems for providing data on the private cloud, as shown in Figure 1, and additional services that internal users can use for various processing in the future. As an example of the model that processes ARD data, including the surface reflectance SaaS designed and constructed in [42], this study added a flow that can be connected to public cloud services. In particular, we propose a model that can efficiently add and analyze multiple satellites in large time-series form, even in the internal cloud environment, by adding the ODC platform, which can manage and visualize diverse data.…”

“…Lee et al tested the performance of remote sensing image processing services based on the PaaS of Cloud Foundry and OpenStack [41]. Kim and Lee implemented OpenStack-based SaaS to produce top-of-atmospheric reflectance (TOAR) and top-of-canopy reflectance (TOCR) for KOMPSAT-3/3A Satellite Image [42].…”