Machine Intelligence Towards Tomorrow's Earth Science Data Systems
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The Global Learning and Observations to Benefit the Environment (GLOBE) Program is an international program that provides a way for students and the public to contribute Earth system observations. Currently 122 countries, more than 40,000 schools, and 200,000 citizen scientists are participating in GLOBE. Since 1995, participants have contributed 195 million observations. Modes of data collection and data entry have evolved with technology over the lifetime of the program, including the launch of the GLOBE Observer mobile app in 2016 to broaden access and public participation in data collection. GLOBE must meet the data needs of a diverse range of stakeholders, from elementary school classrooms to scientists across the globe, including NASA scientists. Operational quality assurance measures include participant training, adherence to standardized data collection protocols, range and logic checks, and an approval process for photos submitted with an observation. In this presentation, we will discuss the current state of operational data QA/QC, as well as additional QA/QC processes recently explored and future directions.
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Using Open Source to build innovative programs, enable fully remote work & expose massive data for more effective use.
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A plan for the ground-based validation of MISR aerosol retrieval is outlined. Activities occur in two phases: (1) pre-launch, work is focused on technique development and MISR algorithm validation using conventional ground-base methods and a MISR simulator (AirMISR) operating from the ER-2 aircraft to simulate MISR on-orbit observations. (2) Post-launch, the validation program relies on ground campaigns, underflights wit the MISR simulator and the use of local measurements fo aerosol loading and properties and irradiance measurements derived from the AERONET and ISIS networks.
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