scholarly journals FY-3D MERSI On-Orbit Radiometric Calibration from the Lunar View

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4690 ◽  
Author(s):  
Ronghua Wu ◽  
Peng Zhang ◽  
Na Xu ◽  
Xiuqing Hu ◽  
Lin Chen ◽  
...  
Keyword(s):  
Large Deviation ◽  
Calibration Method ◽  
Earth Observation ◽  
Observation Data ◽  
Radiometric Calibration ◽  
Medium Resolution ◽  
Laboratory Calibration ◽  
Earth Observation Satellites ◽  
Spectral Imager ◽  
Single Pixel

Limited by the on-orbital calibration capability, scaling the measured radiance in accuracy and stability is challenging for the Earth observation satellites in the reflective solar bands (RSBs). Although the lunar calibration is a well-developed technique in the RSBs, limited work has been done for Chinese Earth observation satellites. To improve the on-orbital calibration performance, the advanced MEdium Resolution Spectral Imager (MERSI II), which is the primary payload of the fourth satellite of the Fengyun 3 Series (FY-3D), expands the space view angle of the imager in order to capture better lunar images. In this study, we propose an absolute radiometric calibration method based on the FY-3D/MERSI lunar observation data. A lunar irradiance model named ROLO/GIRO has been used together with the necessary data procedures, including dark current count estimation, single pixel irradiance calculation, and full disk lunar irradiance calculation. The calibration coefficients obtained by the lunar calibration are compared with the pre-launch laboratory calibration. The results show that the deviations between the two calibration procedures are in a reasonable range in general. However, a relatively high non-linear response was found in the low energy incidence for some detectors, which leads to the large deviation in the corresponding bands. This study explored an ideal and independent method to validate MERSI on-orbit radiometric performance. The lunar calibration practiced for MERSI also gave a valuable example that can be recommended to the other Chinese Earth observation satellites.

scholarly journals Vicarious Radiometric Calibration of Ocean Color Bands for FY-3D/MERSI-II at Lake Qinghai, China

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 139
Author(s):  
Shengli Chen ◽  
Xiaobing Zheng ◽  
Xin Li ◽  
Wei Wei ◽  
Shenda Du ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Large Deviation ◽  
Ocean Color ◽  
Calibration Method ◽  
Surface Measurement ◽  
Radiometric Calibration ◽  
Lake Qinghai ◽  
Vicarious Calibration ◽  
Calibration Methods ◽  
Spectral Imager

To calibrate the low signal response of the ocean color (OC) bands and test the stability of the Fengyun-3D (FY-3D)/Medium Resolution Spectral Imager II (MERSI-II), an absolute radiometric calibration field test of FY-3D/MERSI-II at the Lake Qinghai Radiometric Calibration Site (RCS) was carried out in August 2018. The lake surface and atmospheric parameters were mainly measured by advanced observation instruments, and the MODerate spectral resolution atmospheric TRANsmittance algorithm and computer model (MODTRAN4.0) was used to simulate the multiple scattering radiance value at the altitude of the sensor. The results showed that the relative deviations between bands 9 and 12 are within 5.0%, while the relative deviations of bands 8, and 13 are 17.1%, and 12.0%, respectively. The precision of the calibration method was verified by calibrating the Aqua/Moderate-resolution Imaging Spectroradiometer (MODIS) and National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer (VIIRS), and the deviation of the calibration results was evaluated with the results of the Dunhuang RCS calibration and lunar calibration. The results showed that the relative deviations of NPP/VIIRS were within 7.0%, and the relative deviations of Aqua/MODIS were within 4.1% from 400 nm to 600 nm. The comparisons of three on-orbit calibration methods indicated that band 8 exhibited a large attenuation after launch and the calibration results had good consistency at the other bands except for band 13. The uncertainty value of the whole calibration system was approximately 6.3%, and the uncertainty brought by the field surface measurement reached 5.4%, which might be the main reason for the relatively large deviation of band 13. This study verifies the feasibility of the vicarious calibration method at the Lake Qinghai RCS and provides the basis and reference for the subsequent on-orbit calibration of FY-3D/MERSI-II.

scholarly journals Fire Monitoring - The use of medium resolution satellites (AVHRR, MODIS, TET) for long time series processing and the implementation in User Driven Applications and Services

2015 ◽  
Vol XL-7/W3 ◽  
pp. 797-804
Author(s):  
E.-M. Fuchs ◽  
E. Stein ◽  
G. Strunz ◽  
C. Strobl ◽  
C. Frey
Keyword(s):  
Time Series ◽  
Hot Spot ◽  
Earth Observation ◽  
Observation Data ◽  
Fire Monitoring ◽  
Open Platform ◽  
Spot Detection ◽  
Medium Resolution ◽  
Long Time ◽  
Earth Observation Data

This paper introduces fire monitoring works of two different projects, namely TIMELINE (TIMe Series Processing of Medium Resolution Earth Observation Data assessing Long –Term Dynamics In our Natural Environment) and PHAROS (Project on a Multi-Hazard Open Platform for Satellite Based Downstream Services). It describes the evolution from algorithm development from in applied research to the implementation in user driven applications and systems. Concerning TIMELINE, the focus of the work lies on hot spot detection. A detailed description of the choice of a suitable algorithm (round robin approach) will be given. Moreover, strengths and weaknesses of the AVHRR sensor for hot spot detection, a literature review, the study areas and the selected approach will be highlighted. The evaluation showed that the contextual algorithm performed best, and will therefore be used for final implementation. Concerning the PHAROS project, the key aspect is on the use of satellite-based information to provide valuable support to all phases of disaster management. The project focuses on developing a pre-operational sustainable service platform that integrates space-based EO (Earth Observation), terrestrial sensors and communication and navigation assets to enhance the availability of services and products following a multi-hazard approach.

MAAP: The Mission Algorithm and Analysis Platform: A New Virtual and Collaborative Environment for the Scientific Community

2020 ◽  
Author(s):  
Clement Albinet ◽  
Sebastien Nouvellon ◽  
Björn Frommknecht ◽  
Roger Rutakaza ◽  
Sandrine Daniel ◽  
...  
Keyword(s):  
Scientific Community ◽  
Forest Biomass ◽  
Data Access ◽  
Earth Observation ◽  
Observation Data ◽  
Societal Benefit ◽  
Collaborative Environment ◽  
Earth Observation Data ◽  
Earth Observation Satellites ◽  
Analysis Platform

<p>The ESA-NASA multi-Mission Algorithm and Analysis Platform (MAAP) is dedicated to the BIOMASS [1], NISAR [2] and GEDI [3] missions. This analysis platform will be a virtual open and collaborative environment. The main goal is to bring together data centres (Earth Observation and non-Earth Observation data), computing resources and hosted processing in order to better address the needs of scientists and federate the scientific community.</p><p>The MAAP will provide functions to access data and metadata from different sources such as Earth observation satellites data from science missions; visualisation functions to display the results of the system processing (trends, graphs, maps ...) and results of statistic and analysis tools; collaborative functions to share data, algorithms, ideas between the MAAP users; processing functions including development environments and an orchestration system allowing to create and run processing chains from official algorithms.</p><p>Currently, the MAAP is in its pilot phase. The architecture for the MAAP pilot foresees two independent elements, one developed by ESA, one developed by NASA, unified by a common user entry point. Both elements will be deployed on Cloud infrastructures. Interoperability between the elements is envisaged for data discovery, data access and identity and access management.</p><p>The ESA element architecture is based on technical solutions including: Microservices, Docker images, Kubernetes; Cloud-based virtual development environments (such as Jupyter or Eclipse CHE) for the MAAP algorithm developers; a framework to create, run and monitor chains of algorithms containerised as docker images. Interoperability between both ESA and NASA elements will be based on CMR (NASA Common Metadata Repository), services bases on OGC standards (such as WMS/WMTS, WCS and WPS) and secured with the OAUTH2 protocol.</p><p>This presentation focuses on the pilot platform and how interoperability between the NASA and ESA elements will be achieved. It also gives insight into the architecture of the ESA element and the technical implementation of this virtual environment. Finally, it will present the very first achievements and return of experience of the pilot platform.</p><p> </p><p><strong>REFERENCES</strong></p><p>[1] T. Le Toan, S. Quegan, M. Davidson, H. Balzter, P. Paillou, K. Papathanassiou, S. Plummer, F. Rocca, S. Saatchi, H. Shugart and L. Ulander, “The BIOMASS Mission: Mapping global forest biomass to better understand the terrestrial carbon cycle”, Remote Sensing of Environment, Vol. 115, No. 11, pp. 2850-2860, June 2011.</p><p>[2] P.A. Rosen, S. Hensley, S. Shaffer, L. Veilleux, M. Chakraborty, T. Misra, R. Bhan, V. Raju Sagi and R. Satish, "The NASA-ISRO SAR mission - An international space partnership for science and societal benefit", IEEE Radar Conference (RadarCon), pp. 1610-1613, 10-15 May 2015.</p><p>[3] https://science.nasa.gov/missions/gedi</p>

Our goal is to establish the earth observation data in the business world Unser Ziel ist es, die Erdbeobachtungsdaten in der Geschäftswelt zu etablieren

GIS Business ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 12-14
Author(s):  
Eicher, A
Keyword(s):  
Earth Observation ◽  
Observation Data ◽  
Business World ◽  
The Earth ◽  
Earth Observation Data

Our goal is to establish the earth observation data in the business world Unser Ziel ist es, die Erdbeobachtungsdaten in der Geschäftswelt zu etablieren

Mapping slums and model population density using earth observation data and open source solutions

2019 ◽  
Author(s):  
Tais Grippa ◽  
Stefanos Georganos ◽  
Sabine Vanhuysse ◽  
Moritz Lennert ◽  
Nicholus Mboga ◽  
...  
Keyword(s):  
Population Density ◽  
Open Source ◽  
Earth Observation ◽  
Observation Data ◽  
Model Population ◽  
Earth Observation Data

scholarly journals Examining the Economic and Environmental Impacts of COVID-19 Using Earth Observation Data

2020 ◽  
Vol 13 (1) ◽  
pp. 5
Author(s):  
William Straka ◽  
Shobha Kondragunta ◽  
Zigang Wei ◽  
Hai Zhang ◽  
Steven D. Miller ◽  
...  
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
Environmental Impacts ◽  
Demographic Data ◽  
The United States ◽  
Earth Observation ◽  
Observation Data ◽  
Washington Dc ◽  
Mobility Data ◽  
Earth Observation Data

The COVID-19 pandemic has infected almost 73 million people and is responsible for over 1.63 million fatalities worldwide since early December 2019, when it was first reported in Wuhan, China. In the early stages of the pandemic, social distancing measures, such as lockdown restrictions, were applied in a non-uniform way across the world to reduce the spread of the virus. While such restrictions contributed to flattening the curve in places like Italy, Germany, and South Korea, it plunged the economy in the United States to a level of recession not seen since WWII, while also improving air quality due to the reduced mobility. Using daily Earth observation data (Day/Night Band (DNB) from the National Oceanic and Atmospheric Administration Suomi-NPP and NO2 measurements from the TROPOspheric Monitoring Instrument TROPOMI) along with monthly averaged cell phone derived mobility data, we examined the economic and environmental impacts of lockdowns in Los Angeles, California; Chicago, Illinois; Washington DC from February to April 2020—encompassing the most profound shutdown measures taken in the U.S. The preliminary analysis revealed that the reduction in mobility involved two major observable impacts: (i) improved air quality (a reduction in NO2 and PM2.5 concentration), but (ii) reduced economic activity (a decrease in energy consumption as measured by the radiance from the DNB data) that impacted on gross domestic product, poverty levels, and the unemployment rate. With the continuing rise of COVID-19 cases and declining economic conditions, such knowledge can be combined with unemployment and demographic data to develop policies and strategies for the safe reopening of the economy while preserving our environment and protecting vulnerable populations susceptible to COVID-19 infection.

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