Aerospace Information Research Institute, Chinese Academy of Sciences (20240265697). OPTICAL SATELLITE REMOTE SENSING TRANSFER CALIBRATION METHOD BASED ON NEAR SPACE AEROSTAT simplified abstract

OPTICAL SATELLITE REMOTE SENSING TRANSFER CALIBRATION METHOD BASED ON NEAR SPACE AEROSTAT

Organization Name

Aerospace Information Research Institute, Chinese Academy of Sciences

Inventor(s)

Lingling Ma of Beijing (CN)

Ning Wang of Beijing (CN)

Geer Teng of Beijing (CN)

Qiang Liu of Beijing (CN)

Yongguang Zhao of Beijing (CN)

Jingmei Li of Beijing (CN)

Taihua Zhang of Beijing (CN)

Yanchu Yang of Beijing (CN)

Yaokai Liu of Beijing (CN)

Caixia Gao of Beijing (CN)

Wan Li of Beijing (CN)

Lu Ren of Beijing (CN)

Guangzhou Ouyang of Beijing (CN)

Yifang Niu of Beijing (CN)

OPTICAL SATELLITE REMOTE SENSING TRANSFER CALIBRATION METHOD BASED ON NEAR SPACE AEROSTAT - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240265697 titled 'OPTICAL SATELLITE REMOTE SENSING TRANSFER CALIBRATION METHOD BASED ON NEAR SPACE AEROSTAT

Simplified Explanation:

This patent application describes a method for calibrating optical satellite remote sensing using near-space aerostats. The method involves matching image data from a benchmark radiometric payload with data from a satellite-borne payload to obtain calibration coefficients.

• Performing temporal-spatial matching between image data collected by benchmark and satellite payloads
• Obtaining average radiance of benchmark payload
• Obtaining average digital number (dn) captured by satellite payload
• Calculating matching radiance for observation bands
• Determining calibration coefficient for satellite payload

Key Features and Innovation:

• Utilizes near-space aerostats for calibration of satellite remote sensing
• Matches image data from different payloads for accurate calibration
• Calculates calibration coefficients based on radiance and digital number values

Potential Applications:

• Improving the accuracy of satellite remote sensing data
• Enhancing the reliability of environmental monitoring
• Facilitating better analysis of Earth's surface features

Problems Solved:

• Inaccuracies in satellite remote sensing data calibration
• Lack of reliable methods for matching data from different payloads
• Difficulty in obtaining consistent radiometric measurements

Benefits:

• Increased precision in satellite remote sensing applications
• Enhanced data quality for scientific research and environmental monitoring
• Improved understanding of Earth's surface dynamics

Commercial Applications:

• Geospatial analysis companies
• Environmental monitoring agencies
• Agricultural monitoring services

Questions about Optical Satellite Remote Sensing Transfer Calibration Method based on Near-Space Aerostat: 1. How does this method improve the accuracy of satellite remote sensing data calibration? 2. What are the potential implications of using near-space aerostats for calibration in the field of remote sensing?

Frequently Updated Research: Ongoing research in the field of satellite remote sensing calibration methods and advancements in near-space aerostat technology may further enhance the accuracy and efficiency of this calibration method.

Original Abstract Submitted

an optical satellite remote sensing transfer calibration method based on near-space aerostat, including: performing a temporal-spatial matching between first observation image data of a target region collected by a benchmark radiometric payload and second observation image data of the target region collected by a satellite-borne payload, to obtain a plurality of matchups of observation image data (s); obtaining an average radiance of the benchmark radiometric payload from a plurality of first observation image data (s); obtaining an average dn captured by the satellite payload in the target region from a plurality of second observation image data (s); obtaining a matching radiance for an observation band of the benchmark radiometric payload corresponding to the satellite payload based on the average radiance of the benchmark radiometric payload (s); and obtaining a calibration coefficient of the satellite payload based on the matching radiance and the average dn (s).