GLOBAL FORUM London, October 24 & 25, 2012

Similar documents
Satellite Observation of Heavily Lit Fishing Boat Activity in the Coral Triangle Region

Change Detection In Satellite Observed Nightime Lights:

Spectral Response for DigitalGlobe Earth Imaging Instruments

Joint Polar Satellite System (JPSS)

STAR Algorithm and Data Products (ADP) Beta Review. Suomi NPP Surface Reflectance IP ARP Product

Universidad Nacional de Rosario Facultad de Ciencias Exactas, Ingeniería y Agrimensura Centro de Sensores Remotos CONICET CONAE NASA

Review for Introduction to Remote Sensing: Science Concepts and Technology

Satellite Snow Monitoring Activities Project CRYOLAND

Cloud detection and clearing for the MOPITT instrument

Estimating Firn Emissivity, from 1994 to1998, at the Ski Hi Automatic Weather Station on the West Antarctic Ice Sheet Using Passive Microwave Data

ADAGUC & PyTROLL. Maarten Plieger Ernst de Vreede. Application of polar orbiter products in weather forecasting Using open source tools and standards

Using Remote Sensing to Monitor Soil Carbon Sequestration

High Resolution Information from Seven Years of ASTER Data

A remote sensing instrument collects information about an object or phenomenon within the

From lowest energy to highest energy, which of the following correctly orders the different categories of electromagnetic radiation?

SPECTRAL SIGNATURES OF NIGHTTIME LIGHTS

USING THE GOES 3.9 µm SHORTWAVE INFRARED CHANNEL TO TRACK LOW-LEVEL CLOUD-DRIFT WINDS ABSTRACT

Evaluation of the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius

Active Fire Monitoring: Product Guide

Daily High-resolution Blended Analyses for Sea Surface Temperature

Clear Sky Radiance (CSR) Product from MTSAT-1R. UESAWA Daisaku* Abstract

Satellite Remote Sensing of Volcanic Ash

Update on EUMETSAT ocean colour services. Ewa J. Kwiatkowska

MODIS IMAGES RESTORATION FOR VNIR BANDS ON FIRE SMOKE AFFECTED AREA

Measurements Of Pollution In The Troposphere (MOPITT) NASA Langley ASDC Data Collection Guide

Clouds and the Energy Cycle

The Benefits and Challenges in Global Meteorological Satellite Data Sharing

WATER BODY EXTRACTION FROM MULTI SPECTRAL IMAGE BY SPECTRAL PATTERN ANALYSIS

Best practices for RGB compositing of multi-spectral imagery

Obtaining and Processing MODIS Data

Marcus A. Watkins Director of the Joint Agency Satellite Division, Science Mission Directorate, NASA HQ, Washington DC

Outline of RGB Composite Imagery

Generating Current Electricity: Complete the following summary table for each way that electrical energy is generated. Pros:

Hyperspectral Satellite Imaging Planning a Mission

How Landsat Images are Made

Generation of Cloud-free Imagery Using Landsat-8

Treasure Hunt. Lecture 2 How does Light Interact with the Environment? EMR Principles and Properties. EMR and Remote Sensing

The NASA NEESPI Data Portal to Support Studies of Climate and Environmental Changes in Non-boreal Europe

Night Microphysics RGB Nephanalysis in night time

ESCI 107/109 The Atmosphere Lesson 2 Solar and Terrestrial Radiation

Measurement of the effect of biomass burning aerosol on inhibition of cloud formation over the Amazon

Systems Thinking and Modeling Climate Change Amy Pallant, Hee-Sun Lee, and Sarah Pryputniewicz

REMOTE SENSING OF CLOUD-AEROSOL RADIATIVE EFFECTS FROM SATELLITE DATA: A CASE STUDY OVER THE SOUTH OF PORTUGAL

Validating MOPITT Cloud Detection Techniques with MAS Images

CIESIN Thematic Guide to Night-time Light Remote Sensing and its Applications

ECMWF Aerosol and Cloud Detection Software. User Guide. version /01/2015. Reima Eresmaa ECMWF

3.4 Cryosphere-related Algorithms

Data processing (3) Cloud and Aerosol Imager (CAI)

Passive Remote Sensing of Clouds from Airborne Platforms

Saharan Dust Aerosols Detection Over the Region of Puerto Rico

SATELLITE IMAGES IN ENVIRONMENTAL DATA PROCESSING

NOAA National Data Center. + CLASS Overview

Electromagnetic Radiation (EMR) and Remote Sensing

NCDC s SATELLITE DATA, PRODUCTS, and SERVICES

Volcanic Ash Monitoring: Product Guide

Studying cloud properties from space using sounder data: A preparatory study for INSAT-3D

Moderate- and high-resolution Earth Observation data based forest and agriculture monitoring in Russia using VEGA Web-Service

Cloud Masking and Cloud Products

CHAPTER 2 Energy and Earth

Denis Botambekov 1, Andrew Heidinger 2, Andi Walther 1, and Nick Bearson 1

History of satellites, and implications for hurricanes monitoring and forecasting

GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document For Low Cloud and Fog

RESULTS FROM A SIMPLE INFRARED CLOUD DETECTOR

12.5: Generating Current Electricity pg. 518

Remote Sensing Satellite Information Sheets Geophysical Institute University of Alaska Fairbanks

Data Processing Flow Chart

Using Photometric Data to Derive an HR Diagram for a Star Cluster

Huai-Min Zhang & NOAAGlobalTemp Team

COMPUTING CLOUD MOTION USING A CORRELATION RELAXATION ALGORITHM Improving Estimation by Exploiting Problem Knowledge Q. X. WU

Principle of Thermal Imaging

McIDAS-V Tutorial Displaying Polar Satellite Imagery updated September 2015 (software version 1.5)

How to Use the NOAA Enterprise Cloud Mask (ECM) Andrew Heidinger, Tom Kopp, Denis Botambekov and William Straka JPSS Cloud Team August 29, 2015

A SURVEY OF CLOUD COVER OVER MĂGURELE, ROMANIA, USING CEILOMETER AND SATELLITE DATA

Integrating the Solar Spectrum

Establishing a Geospatial Intelligence Pipeline through Earth SySTEM Education

Land Use/Land Cover Map of the Central Facility of ARM in the Southern Great Plains Site Using DOE s Multi-Spectral Thermal Imager Satellite Images

Landsat Monitoring our Earth s Condition for over 40 years

Overview of the IR channels and their applications

Synoptic assessment of AMV errors

STAAR Science Tutorial 30 TEK 8.8C: Electromagnetic Waves

ATM S 111, Global Warming: Understanding the Forecast

Evaluation of Wildfire Duration Time Over Asia using MTSAT and MODIS

Blackbody radiation. Main Laws. Brightness temperature. 1. Concepts of a blackbody and thermodynamical equilibrium.

Sky Monitoring Techniques using Thermal Infrared Sensors. sabino piazzolla Optical Communications Group JPL

Supervised Classification workflow in ENVI 4.8 using WorldView-2 imagery

VIIRS-CrIS mapping. NWP SAF AAPP VIIRS-CrIS Mapping

Online Solar Databases at NGDC RSTN Solar Radio Databases

Solar Irradiance Variability

Transcription:

GLOBAL FORUM London, October 24 & 25, 2012-1 -

Global Observations of Gas Flares Improving Global Observations of Gas Flares With Data From the Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Christopher D. Elvidge, Ph.D. Earth Observation Group NOAA National Geophysical Data Center Boulder, Colorado 80305 USA chris.elvidge@noaa.gov Kimberly Baugh, Feng-Chi Hsu, Mikhail Zhizhin, Tilottama Ghosh Cooperative Institute for Research in Environmental Sciences University of Colorado October 25, 2012-2 -

Heritage from DMSP Cloud-free annual composites F162004 = Red F141998 = Green F101992 = Blue Vectors drawn on gas flares. In 2005, NGDC developed a method for estimating flared gas volumes using nighttime lights data collected by the U.S. Air Force Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS). - 3 -

DMSP Observations of Gas Flares Pros Nightly global coverage Strong signal from flares Global monitoring built on existing algorithms and processing system Archive extends from mid-1990 s to present Cons Usable observations reduced by solar and lunar contamination Inability to detect flares in urban areas Ambiguous features is it a flare or a light With detection in a single spectral band it is not possible to estimate temperature Spectral band misses peak radiant emissions of flares - 4 -

MODIS Observations of Gas Flares Pros Daily global coverage Two satellites provide up to four observations per day No solar or lunar constraints Open access to archive Archive extends from 2000 to present Cons Operational fire product skips over ocean / water areas Weak signal from flares Operational cloudproduct identifies flares as clouds Archive would need to be reprocessed for flares - 5 -

Suomi NPP VIIRS NASA / NOAA launched the Suomi NPP satellite October 28, 2011 The VIIRS instrument offers substantial improvements over both DMSP and MODIS NGDC is funded by NOAA to develop a system for estimating flared gas volumes and CO 2 emissions from VIIRS The VIIRS operational fire and cloud products have same issues as MODIS - 6 -

VIIRS Data Flow Svalbard Ground Station Archive National Geophysical Data Center Processing for Combustion Sources Web Access to KMZ and CSV NSOF (NOAA Satellite Operations Facility) Interface Data Processing Segment (IDPS), Suitland, Maryland - 7 -

What makes VIIRS data so great? DNB M7,8,10 M12 M13 fire band M14 M15 M16 The M7,8,10 spectral bands are well placed to record the peak radiant emissions from flares. During daylight hours the signal is overwhelmed by sunlight. At night combustion sources stand out clearly against the noise background. - 8 -

What makes VIIRS data so great? At night the VIIRS collects data in three daytime imaging bands: M7, M8, and M10. The nighttime M10 data have an remarkable ability to detect combustion sources! M13 The Fire Band M10 Detection of Combustion Sources Basra, Iraq Region at Night - 9 -

Why we do our own product generation? The VIIRS operational fire product: Is based on M13, which detects fewer gas flares than M10 at night. Part of the reason for this is that gas flares generally burn hotter than biomass. The peak radiant emission is shifted to shorter wavelengths. Only produced for land areas. Misses offshore flaring. The VIIRS operational cloud product: Detects gas flares as clouds. Spectral confusion! Overdetects clouds for our purpose of making global cloud-free composites. - 10 -

NGDC s Nightfire Service - 11 - p://www.ngdc.noaa.gov/dmsp/data/viirs_fire/viirs_html/download_viirs_fire.htm

NGDC s Nightfire Service - 12 - p://www.ngdc.noaa.gov/dmsp/data/viirs_fire/viirs_html/download_viirs_fire.htm

Nightfire KMZ Placemarks The placemarks are color coded by temperature: white T<400 or T>3000 purple 400<T<1000 blue 1000<T<1200 green 1200<T<1400 yellow 1400<T<1600 red 1600<T<3000 The placemark size depends on logarithm of total radiance LOG10(totalradiance)>1 large LOG10(totalradiance) 0 to 1 medium otherwise small - 13 -

NGDC s Nightfire Service - 14 - p://www.ngdc.noaa.gov/dmsp/data/viirs_fire/viirs_html/download_viirs_fire.htm

NGDC s Nightfire Service - 15 - p://www.ngdc.noaa.gov/dmsp/data/viirs_fire/viirs_html/download_viirs_fire.htm

NGDC s Nightfire Service Provides Data on Combustion Sources Detected at Night - 16 - p://www.ngdc.noaa.gov/dmsp/data/viirs_fire/viirs_html/download_viirs_fire.htm

Plan Forward Nightly combustion source detections will be pair with cloud detection to generate monthly and cumulative annual cloud free composites of combustion sources. Combustion sources will be labeled by type: biomass burning, gas flares, industrial sources. Calibrations will be developed for estimating flared gas and CO 2 emission volumes. Visualization tool will be developed to see temporal trends at individual flaring sites. Ranking of flares based on total radiant output. - 17 -

GLOBAL FORUM London, October 24 & 25, 2012-18 -