98%
921
2 minutes
20
Since the launch of the Chinese High-resolution Earth Observation System (CHEOS) program, China has strengthened its research and development in the field of satellite remote sensing. A large number of sensors has been or will be launched, providing very large data streams which all require processing of the engineering data, as provided by the instruments, to physical data which will be used for further processing and interpretation. To handle such large data streams we developed a one-click batch pre-processing toolkit for CHEOS remote sensing data as described in this paper. In this toolkit, IDL language and environment are used as the primary program combined with other programming languages developed in this research. In this paper, we first describe the Gaofen (GF) series data used in this research and then introduce the function design and realization of this one-click batch pre-processing toolkit. Some examples will be presented to illustrate the application of the toolkit to data from several CHEOS satellites.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11560028 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0313584 | PLOS |
Sensors (Basel)
July 2025
Geological Survey Institute of Hunan Province, Changsha 410114, China.
This study investigates the influence of root cohesion spatial heterogeneity on rainfall-induced landslide distribution across the Loess Plateau, addressing limitations in existing methods that oversimplify root reinforcement. Leveraging Landsat and GaoFen satellite images, we developed a regional root cohesion inversion model that quantifies spatial heterogeneity using tree height (derived from time series Landsat imagery) and above-ground biomass (from 30 m resolution satellite products). This approach, integrated with land use-specific hydrological parameters and an infinite slope stability model, significantly improves landslide susceptibility predictions compared to models ignoring root cohesion or using uniform assignments.
View Article and Find Full Text PDFPLoS One
November 2024
College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, China.
Since the launch of the Chinese High-resolution Earth Observation System (CHEOS) program, China has strengthened its research and development in the field of satellite remote sensing. A large number of sensors has been or will be launched, providing very large data streams which all require processing of the engineering data, as provided by the instruments, to physical data which will be used for further processing and interpretation. To handle such large data streams we developed a one-click batch pre-processing toolkit for CHEOS remote sensing data as described in this paper.
View Article and Find Full Text PDFSensors (Basel)
September 2024
Beijing Key Laboratory of Sensor, Beijing Information Science & Technology University, Beijing 100101, China.
Sensors (Basel)
August 2022
Badong National Observation and Research Station of Geohazards, China University of Geosciences, Wuhan 430074, China.
Landslides have been frequently occurring in the high mountainous areas in China and poses serious threats to peoples' lives and property, economic development, and national security. Detecting and monitoring quiescent or active landslides is important for predicting risks and mitigating losses. However, traditional ground survey methods, such as field investigation, GNSS, and total stations, are only suitable for field investigation at a specific site rather than identifying landslides over a large area, as they are expensive, time-consuming, and laborious.
View Article and Find Full Text PDFThe directional polarimetric camera (DPC) is a remote-sensing instrument for the characterization of atmospheric aerosols and clouds by simultaneously conducting spectral, angular, and polarimetric measurements. Polarization measurement accuracy is an important index to evaluate the performance of the DPC and mainly related to the calibration accuracy of instrumental parameters. In this paper, firstly, the relationship between the polarization measurement accuracy of DPC and the parameter calibration errors caused by the nonideality of the components of DPC are analyzed, and the maximum polarization measurement error of DPC in the central field of view and edge field of view after initial calibration is evaluated respectively.
View Article and Find Full Text PDF