{ "cells": [ { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "# Monitoring fires with next-generation satellites from MTG and Metop-SG" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "In the near future, new satellites such as [Meteosat Third Generation (MTG)](https://www.eumetsat.int/meteosat-third-generation) and [Metop - Second Generation (Metop-SG)](https://www.eumetsat.int/metop-sg) will provide advanced capabilities and valuable data for monitoring fires and their impacts. This two-part case study will introduce upcoming data products from MTG and Metop-SG in the context of the 2020 August Complex fire which occurred in California, USA. In this part, we will be focusing on fire monitoring on 11 September 2020 using data products from MTG. In [Part 2](./ca_part2_application_case.ipynb), we will introduce you to new capabilities in monitoring smoke transport using data products from Metop-SG.\n", "\n", "## The Case Event\n", "The [2020 August Complex fire](https://www.fire.ca.gov/incidents/2020/8/16/august-complex-includes-doe-fire/) was the largest wildfire in California’s history, spreading over 1,000,000 acres (over 4,000 sq km). The fires were caused by a series of lightning strikes on 17 August, resulting in 37 separate fires that merged into a complex. The fires burned for 86 days before being fully contained. On 10 September 2020, CNN reported that the west coast of the US had [“the worst air quality in the world”](https://edition.cnn.com/us/live-news/west-coast-wildfires-09-10-2020/h_e2555d569133a17107a9a99891668c25#:~:text=The%20US%20West%20Coast%20has%20the%20worst%20air%20quality%20in%20the%20world%20right%20now) that day, with multiple locations reporting hazardous PM2.5 pollution levels. " ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "## Meteosat Third Generation (MTG)\n", "\n", "MTG will see the launch of six new geostationary satellites from 2022 onwards. The satellite series will be based on 3-axis platforms and comprise: four imaging satellites (MTG-I) and two sounding satellites (MTG-S). The full operational configuration will consist of two MTG-I satellites operating in tandem, one scanning Europe and Africa every 10 minutes, and the other scanning only Europe every 2.5 minutes, and one MTG-S satellite. \n", "\n", "## EUMETSAT Polar System - Second Generation (EPS-SG)\n", "\n", "The EPS-SG is a partnership programme, which involves the European Space Agency, the German Aerospace Agency and the National Center for Space Studies. The mission is composed of two series of spacecraft, Metop-SG A and B, flying on the same mid-morning orbit, like the current Metop satellites. The orbit height is in the range 823-848 km (dependent on latitudes). There will be three satellites each of Metop-SG A and Metop-SG B. The first two satellites Metop-SG A1 and Metop-SG B1 are planned to be launched in Q2 and Q4 2024 respectively. See [here](https://www.eumetsat.int/our-satellites/metop-series?sjid=future) an overview of the planned launch dates. \n", "\n", "Consisting of low earth orbiting satellites, Metop-SG will provide high spatial resolution imagery and data. However, they will only cover a smaller observation region and have a longer revisit period compared to geostationary satellites like MTG. \n", "\n", "In this case study, we will be focusing on data from several instruments, namely MTG’s [Flexible Combined Imager](https://www.eumetsat.int/mtg-flexible-combined-imager) and Metop-SG’s [METimage](https://www.eumetsat.int/eps-sg-metimage) radiometer. We will also be using data from the Sentinel-2 [MultiSpectral Instrument](https://sentinel.esa.int/web/sentinel/missions/sentinel-2/instrument-payload) to assess burn severity. While data from MTG and Metop-SG is not yet available, we will be using proxy data from existing instruments to demonstrate the new capabilities that will arise from these satellites. \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```{admonition} What is proxy data?\n", "\n", "Proxy data refers to “data with valid scientific content, to be used in early training on instrument capabilities and application areas, for example in test beds. These are real datasets from relevant existing precursor instruments.” (Source: [EUMETSAT](https://www.eumetsat.int/media/43504)) \n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Monitoring the fire life cycle consists of three stages: (1) pre-fire, (2) active fire and (3) post-fire. First, we can assess pre-fire risk based on meteorological and vegetation conditions. During the fire, we can detect and monitor the location of active fires as well as smoke being produced by the fires. Finally, after the fires have been extinguished, the burned area and burn severity can be assessed." ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### MTG Flexible Combined Imager\n", "\n", "(ca_part1_fig1)=\n", "#### Fire risk mapping\n", "\n", "Early information for fire risk is crucial for emergency response. Data from [Flexible Combined Imager (FCI)](https://www.eumetsat.int/mtg-flexible-combined-imager) aboard the MTG satellites will be incorporated into fire risk mapping that will enable operational users to plan ahead and allocate resources to mitigate potential fire damage. The FCI provides 16 channels in the visible and infrared spectrum with a spatial sampling distance in the range of 1 to 2 km and four channels with a spatial sampling distance in the range of 0.5 to 1 km. \n", "\n", "`Figure 1` shows a fire risk map for California on 17 August 2020, when the August Complex Fires were ignited by a lightning storm. The proxy data source is the [Wildland Fire Potential Index (WFPI)](https://www.usgs.gov/fire-danger-forecast/wildland-fire-potential-index-wfpi#:~:text=WFPI%20(Figure%201)%20is%20developed,and%20relates%20to%20vegetation%20flammability.), which integrates meteorological information such as wind speed, dry bulb temperature and rainfall, with satellite-based vegetation condition information to estimate the moisture levels of both live and dead vegetation. The WFPI is a unitless number that ranges from 0 to 150, with higher values indicating higher vegetation flammability. This WFPI is produced by the United States Geological Service (USGS) and is available as a [daily forecast](https://firedanger.cr.usgs.gov/viewer/index.html) for 7 days into the future. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```{image} ./img/ca_part1_figure_1.png\n", ":alt: Figure 1. Fire risk map of California on 17th August 2020 from USGS\n", ":width: 600px\n", ":align: center\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Figure 1. Fire risk map of California on 17th August 2020 from USGS" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "(ca_part1_fig2)=\n", "#### True colour composite imagery" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "As the FCI will be capturing data every 10 minutes, it will be possible to have near-real time true colour monitoring of smoke transport and spread of active fires. As an example, Figure 3 shows an animation of the August Complex fires in California recorded on 20 August 2020. The proxy data source is Level 1B surface reflectance data from the [GOES-17 ABI](https://www.goes-r.gov/spacesegment/abi.html) instrument.\n" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide_input" ] }, "source": [ "