NASA ARSET Post-Fire Imagery and Smoke Monitoring

0:00 Speaker 1: Welcome everyone to our r SET training series. Introduction to

0:03 Speaker 1: Advanced NASA Earth Observations and Tools for active fires, smoke

0:07 Speaker 1: and post fire monitoring. Today's part one of our training series,

0:11 Speaker 1: post Fire Imagery and Smoke Monitoring. My name is Brock Blevins.

0:15 Speaker 1: I'm a training coordinator for the r SET program, and

0:18 Speaker 1: I'll be your host for this training series. But before

0:24 Speaker 1: we begin today's training, a few quick words about the

0:26 Speaker 1: art SET program. NASA Applied Remote Sensing Training or our

0:31 Speaker 1: SET program, provides cost free training on the use of

0:35 Speaker 1: remote sensing observations, analysis methods, and tools. We provide training

0:40 Speaker 1: in several thematic areas agriculture, climate and resilience, disasters, eco conservation, health,

0:48 Speaker 1: inner quality, water resources, and such as the training here today,

0:52 Speaker 1: wildline fires. Our SET provides trainings both online or in person.

0:58 Speaker 1: Our online trainings are delivered in two formats, live instructor

1:02 Speaker 1: lead like today's training, or asynchronous in self paced like

1:06 Speaker 1: NASA's free and accessible data. All of our trainings are

1:10 Speaker 1: offered at no cost. We try to offer trainings in

1:13 Speaker 1: more than one language whenever we can, and we only

1:15 Speaker 1: use no cost in open source software and data. We

1:19 Speaker 1: offer our trainings at a range of levels, so you

1:20 Speaker 1: can find a training series that fits your level of

1:23 Speaker 1: experience and need. Please visit our website to learn more.

1:29 Speaker 1: We'll begin today's session by giving an overview of the

1:31 Speaker 1: training series Advanced NASA Earth Observations and Tools for active fire,

1:35 Speaker 1: smoke and post fire monitoring. The system and routine monitoring

1:41 Speaker 1: of active fires, smoke transport, and post fire burned severity

1:46 Speaker 1: is essential for understanding both the immediate as well as

1:49 Speaker 1: the long term impacts of fire on ecosystems, air quality,

1:53 Speaker 1: and human infrastructure. Satellite observations provide continuous and often global

1:59 Speaker 1: data that allow for early detection of new fire ignitions,

2:03 Speaker 1: the tracking of fire progression, and monitoring of smoke transport.

2:08 Speaker 1: These data can help guide emergency responses, reducing risk to communities.

2:12 Speaker 1: Post fire burned area and burn severity maps can be

2:16 Speaker 1: used for damage assessment, evaluation of vegetation loss, and debris

2:21 Speaker 1: flow risk assessment. This information can help scientists and land

2:25 Speaker 1: managers support recovery efforts. Overall, Satellite monitoring is a key

2:29 Speaker 1: tool for both immediate fire response and long term environmental management,

2:35 Speaker 1: and here are training learning objectives for the series. By

2:39 Speaker 1: the end of the training Participants will be able to

2:42 Speaker 1: access relevant post fire imagery in the firm's burned area

2:45 Speaker 1: mode to assess burned area burn severity and other factors.

2:50 Speaker 1: Identify and track wildfire smoke over time using corrective reflectantce OMPs,

2:55 Speaker 1: aerosol index and PYROCB layers available in the firm's smoke aerosols,

3:00 Speaker 1: and also understand when to use the PYROCB layer. Use

3:06 Speaker 1: relevant data and firms to identify static thermal anomalies associated

3:11 Speaker 1: with industrial and natural sources that are not vegetation fires,

3:15 Speaker 1: and use Jupiter notebooks to assess and visualize firms data

3:19 Speaker 1: for different case studies. A prerequisite for this course, we

3:26 Speaker 1: recommend that you take our Fundamentals or Remote Sensing to

3:29 Speaker 1: familiarize yourself with the terminology and concepts you might hear

3:32 Speaker 1: in today's training or have equal knowledge coming in. This

3:37 Speaker 1: training also builds under previous ARSET training introduction to NASA

3:41 Speaker 1: Earth Observations and tools for wildfire monitoring and management. This

3:45 Speaker 1: training gave an overview of the NASA Fire Information and

3:48 Speaker 1: Resource Management System or firms the modules available in firms.

3:53 Speaker 1: We explored the data as well as the characteristics of

3:56 Speaker 1: available satellite based active fire detection and provide a demonstrations

4:00 Speaker 1: on how to query, access, and visualize the data in

4:04 Speaker 1: GIS and other applications. This training will also discuss burned

4:08 Speaker 1: area and indices for burned severity, so for more information

4:12 Speaker 1: on those, we recommend reviewing our previous training spectral indices

4:16 Speaker 1: for land and aquatic applications. But here's our training outline.

4:21 Speaker 1: In Part one today we'll be covering post fire imagery

4:24 Speaker 1: and smoke monitoring, and then in Part two a week

4:26 Speaker 1: from today, on November nineteenth, we'll be looking at data

4:29 Speaker 1: analysis and visualization. There'll be one homework associated with this

4:33 Speaker 1: training and it will be available on November nineteenth, on

4:37 Speaker 1: the day of our last session, and it will be

4:40 Speaker 1: due two weeks from there, due to November three, and

4:43 Speaker 1: that will be posted on the training web page. A

4:46 Speaker 1: certificate of completion will be awarded to those who attend

4:49 Speaker 1: all live sessions and complete the homework. Assignment be fort

4:52 Speaker 1: December third. So let's start Part one our Part one trainers. Today,

4:59 Speaker 1: we're lucky to have Jenny Houston, she is the Lance

5:02 Speaker 1: manager and Diane Davies, who is the Lance Operations manager,

5:07 Speaker 1: and the objectives for the part today, participants will be

5:12 Speaker 1: able to recognize the strengths and limitations of available post

5:15 Speaker 1: fire indices and imagery products in the burned area mode.

5:19 Speaker 1: Access available indices and imagery products and firms to assess

5:23 Speaker 1: burned area and fire damage severity, burned area recovery status,

5:28 Speaker 1: and other land cover characteristics. Recognize the strengths and limitations

5:32 Speaker 1: of available smoke and aerosol data products and firms, and

5:35 Speaker 1: this will be used for monitoring smoke extent and tracking progression.

5:40 Speaker 1: And then how to access available satellite data products and

5:43 Speaker 1: firms that can be used to track the extent and

5:45 Speaker 1: progression of smoke. This as a reminder of some of

5:50 Speaker 1: the key concepts will be using during today's session. If

5:53 Speaker 1: you're completely unfamiliar with these, you can refer back to

5:56 Speaker 1: our recommended for requisites. One is true color imagery is

6:00 Speaker 1: used to show an image as a human eye would

6:02 Speaker 1: see it. It uses red, green, and blue wavelengths to represent

6:06 Speaker 1: the corresponding colors in the real world. False color imagery

6:10 Speaker 1: is created by assigning wavelengths invisible to the human eye,

6:13 Speaker 1: such as infrared, the colors like red, green, and blue.

6:18 Speaker 1: False color imagery is used to enhance surface features like

6:21 Speaker 1: the presence of vegetation or a burn scar. A spectral

6:26 Speaker 1: index combines different wavelengths of light highlight specific features on

6:30 Speaker 1: the earth surface or atmosphere. Different indices can give information

6:35 Speaker 1: on the health of vegetation, water quality, burn severity, the

6:40 Speaker 1: presence of aerosols, and more. Examples of these referred to

6:44 Speaker 1: in Part one are the normalized burn ratio or NBR,

6:49 Speaker 1: the normalized difference of vegetation index, and DVII, an aerosol index.

6:56 Speaker 1: How to ask questions. Please put your questions in the

6:59 Speaker 1: question spots and we'll address them at the end of

7:02 Speaker 1: this training. Feel free to answer your questions as we go.

7:06 Speaker 1: We'll try to get to all the questions during the

7:07 Speaker 1: Q and A session After the training, the remainder of

7:11 Speaker 1: the questions will be answered in the Q and A document,

7:13 Speaker 1: which we posted the training's webpage about a week after

7:16 Speaker 1: the training. So now I will hand this off to

7:19 Speaker 1: Jenny Houston, who will start us with burned area mode

7:23 Speaker 1: in firms.

7:25 Speaker 2: Thank you, Jenny, Okay, great, welcome to this demonstration.

7:33 Speaker 3: Using firms to map the monitor burned area and post

7:37 Speaker 3: via dynamics. The demos will provide an overview of the

7:43 Speaker 3: firms burned area interface and global burned area products and

7:48 Speaker 3: an overview of the vegetation in disease and other imagery

7:51 Speaker 3: available to analyze burned area and post via dynamics through

7:55 Speaker 3: a particular area of interest. By the end of the session,

7:59 Speaker 3: you should be able to assess burned area globally using

8:02 Speaker 3: the monthly annual burned area products available for Modus and VIAS,

8:07 Speaker 3: and be able to analyze burned area and post biodynamics

8:12 Speaker 3: for a particular area of interest using vegetation in disease

8:16 Speaker 3: and other imagery from the harmonized lansat Sentinel datester. There

8:27 Speaker 3: are two global burned area products that can be accessed

8:30 Speaker 3: through the burned Airy mode as well as the Advanced mode,

8:33 Speaker 3: which you can access here. There is the NASA Modus

8:39 Speaker 3: Monthly Burned Area product as well as the NASA VIA's

8:43 Speaker 3: Monthly burned Area product. The MODUS burned Area product is

8:48 Speaker 3: generated using Modus.

8:50 Speaker 2: Terror as well as Modus and AQUA.

8:52 Speaker 3: The VIA's product is generated using vias aboard SMPP. The

8:59 Speaker 3: MODE product is available from late two thousand and the

9:05 Speaker 3: VIA's product is available from early twenty twelve. If I

9:13 Speaker 3: change this to twenty twenty five, you will notice that

9:17 Speaker 3: the products are available for the Modus product as well

9:21 Speaker 3: as the VIA's product through August of this year, and

9:29 Speaker 3: that is because the products are based on a burned

9:35 Speaker 3: area algorithm that uses a time series of reflectance imagery

9:39 Speaker 3: to identify abrupt changes in reflectance. The algorithm then checks

9:44 Speaker 3: for the persistence of this abrupt change and then uses

9:48 Speaker 3: a series of active fire detections to double check these

9:52 Speaker 3: changes resulted from wildfires. This process can result in a

9:56 Speaker 3: lack of anywhere from two to four months.

10:02 Speaker 2: Now.

10:02 Speaker 3: As they are both based on the same algorithm, the

10:06 Speaker 3: VIAS uses a modified version of the Modus burnd Airy algorithm.

10:13 Speaker 3: This ensures that the VIA's product will provide continuity to

10:17 Speaker 3: the Modus product once Terra and Aqua, which both carry

10:21 Speaker 3: the most instrument, are decommissioned, and both products also have

10:26 Speaker 3: the same spatial resolution five hundred meters. Other options to

10:32 Speaker 3: note on the interfaces. Again, the interfaces are identical. There

10:38 Speaker 3: is the monthly product that is available and then there

10:42 Speaker 3: is also an annual cumulative product. The monthly product can

10:47 Speaker 3: be viewed for one, two or three years simultaneously. For example,

10:53 Speaker 3: you can change the dates to any year of interest

10:57 Speaker 3: and then that you will pop up at which point

11:02 Speaker 3: you can manipulate which of the layers, which of the

11:06 Speaker 3: months you would like to view based on your area

11:10 Speaker 3: of interest. You can change the colors here, and you

11:13 Speaker 3: can change the opacity of a particular month. Using this tool,

11:19 Speaker 3: you can also decide whether you want the months filled

11:23 Speaker 3: or would like to use an outline instead. And then

11:29 Speaker 3: there is the annual cumulative product. And again you can

11:35 Speaker 3: look at this for one, two or three years simultaneously.

11:43 Speaker 2: Okay, so that's the interface.

11:46 Speaker 3: And now we're actually looking at the pans and Now

11:49 Speaker 3: region in South America. It is the world's largest wetland

11:54 Speaker 3: and it is located in this area of Brazil, Bolivia

11:59 Speaker 3: and Perle. Why so all throughout this area here that

12:06 Speaker 3: pant and I generally experiences a dry season between June

12:10 Speaker 3: and October, and in twenty twenty three and twenty four

12:14 Speaker 3: the region actually saw a significant rout and a.

12:17 Speaker 2: Large amount of area burned.

12:20 Speaker 3: We are actually looking at let me just collapse these

12:24 Speaker 3: down for a moment. We're actually looking at a modus

12:28 Speaker 3: board APPUA false color composite produced using Band seven two

12:33 Speaker 3: and one, and burned area in this composite shows up

12:36 Speaker 3: as a brick red color. You can also see out

12:40 Speaker 3: of wildfires and smoke emanating from the wildfires in these areas.

12:46 Speaker 3: Here we can now explore when the area is burned

12:52 Speaker 3: using the burned area product. Let me collapse a couple

12:59 Speaker 3: of layers and then open up the Modus burned airy product.

13:03 Speaker 3: So I changed this to twenty twenty four, and now

13:08 Speaker 3: I can look at the areas that burned and were

13:11 Speaker 3: mapped by the modest product in May, in June, in July,

13:20 Speaker 3: and in August twenty twenty four. As I mentioned, you

13:25 Speaker 3: can change the color of individual months, and so we're

13:28 Speaker 3: going to change June to more of an orange color

13:32 Speaker 3: because the green does not really stand out of the

13:37 Speaker 3: false color composite.

13:42 Speaker 2: And if we.

13:45 Speaker 3: Turn each of these layers off, you can actually see

13:48 Speaker 3: the burned area that was mapped underneath the burned area

13:54 Speaker 3: product generated by motors.

14:00 Speaker 2: Now, if we fast.

14:01 Speaker 3: Forward to the end of September and pop that on,

14:05 Speaker 3: we can see that even more area has burned again.

14:09 Speaker 3: There is smoke from some of their active fires. And

14:16 Speaker 3: this is all of the area that was burned from

14:20 Speaker 3: the end of August to the end of September. And

14:26 Speaker 3: if you wanted to compare the Modus and Vius burned

14:31 Speaker 3: airy product. You pop down to the VIA's product and

14:37 Speaker 3: select the same yeah, twenty twenty four, and we will

14:41 Speaker 3: compare August. Now we're actually looking at August twenty twenty

14:46 Speaker 3: four of Modus and August twenty twenty four of Vias.

14:50 Speaker 2: And let me change the core of.

14:52 Speaker 3: The VIA's product to the yellow so that we can.

14:59 Speaker 2: Now both products.

15:02 Speaker 3: Vias is in yellow, and we can actually see how

15:04 Speaker 3: well the products generally correspond to each other, even though

15:08 Speaker 3: the products are from two different sensors Modus and Vias,

15:12 Speaker 3: and these have different sensor characteristics. And if I zoom

15:17 Speaker 3: in and now pick up the capacity tool and slide

15:27 Speaker 3: back and forth, we can see how well the products

15:33 Speaker 3: overlap and any small differences that there may be.

15:37 Speaker 2: If that's an.

15:38 Speaker 3: Average, the annual global difference between the two products is

15:42 Speaker 3: two to six percent. And this is all explained and

15:45 Speaker 3: documented in a recent paper by jiglio Out that is

15:49 Speaker 3: in the references section. In this section, we're exploring other

15:56 Speaker 3: data layers that can be helpful in assessing burned area,

16:00 Speaker 3: post fire dynamics, etc. We're using the firm's US Canada,

16:05 Speaker 3: and we're going to explore the harmonized lance that sentinel

16:09 Speaker 3: to imagery drop down right here using the Mosquito Fire

16:15 Speaker 3: in California. This was the largest fir in California in

16:20 Speaker 3: twenty twenty two. It started in September the sixth. It

16:25 Speaker 3: burned in two counties, Place and Eldorado. And just to

16:30 Speaker 3: orientate a little bit to the east is Lake Tahoe

16:34 Speaker 3: on the border of California and Nevada. This is an

16:39 Speaker 3: older burn. This is the Calder Fire burn from twenty

16:43 Speaker 3: twenty one, and then over to the west are.

16:48 Speaker 2: Irrigated areas. We're actually looking at a fast color.

16:55 Speaker 3: Composite from two days into the fire on September the eighth.

17:02 Speaker 3: This particular image was generated mainly using oli aboard lands

17:11 Speaker 3: at eight and nine, and you can see which source

17:16 Speaker 3: of data is providing.

17:18 Speaker 2: The image by clicking these on and off.

17:23 Speaker 3: And if we zoom in a little bit, you can

17:26 Speaker 3: see this is the area that has already burned in

17:29 Speaker 3: brick red and there are active firefronts on multiple sides

17:33 Speaker 3: of the fire and lots of smoke emanating out. We

17:38 Speaker 3: can also make use of the active fire detections to

17:42 Speaker 3: look at the progression of the fire. So if we

17:46 Speaker 3: hop forward to September the twelfth, and look at a

17:50 Speaker 3: week's worth of active fire detections. And for this we'll

17:55 Speaker 3: use their active fire detections from Veers on Noah twenty

18:01 Speaker 3: and we'll just give it a moment to load. Okay,

18:08 Speaker 3: Now we're looking at all the active fire detections over

18:11 Speaker 3: the first seven days, so the sick through the twelve.

18:15 Speaker 3: I have this set the display set to time based,

18:20 Speaker 3: and so we're actually looking at these based on when

18:24 Speaker 3: they were detected. So orange and red are the most recent.

18:29 Speaker 3: And again this is days since detection, all right, So

18:33 Speaker 3: we have made use of the PHOS color imagery as

18:39 Speaker 3: well as the active fire detections to look at the

18:41 Speaker 3: onset and progression of the fire over the first week

18:45 Speaker 3: and to help users assess areas that have been burned.

18:49 Speaker 3: We've recently incorporated a number of vegetation industries from the

18:53 Speaker 3: HLS data set that are available under the HLS Imagery

18:59 Speaker 3: drop down, which I'm showing over on the right. So

19:04 Speaker 3: let's fast forward to further into the fire. So on

19:07 Speaker 3: the twenty fifth of September, we're now looking at a

19:13 Speaker 3: false color composite from the twenty fifth of September, and

19:18 Speaker 3: if I change this to one day and give it

19:20 Speaker 3: a moment to load. Let me zoom in to the area.

19:27 Speaker 3: And so this is the area that has burned that

19:31 Speaker 3: appears in brick red in this false color composite. And

19:35 Speaker 3: now we're going to make use of the normalized burn

19:38 Speaker 3: ratio or NBR. So let me pop that on. And

19:46 Speaker 3: the NBR from last OLI is calculated using infrared and

19:52 Speaker 3: shortwave infrared bands. That's BANS five and then BANS seven

19:58 Speaker 3: of the short wave infrared, and the NBR can be

20:01 Speaker 3: useful firstly in mapping the extent of the burnt area.

20:07 Speaker 3: In this purple shows vegetated areas and shades of orange

20:12 Speaker 3: show burned areas. Secondly, the NBER can help in assessing

20:17 Speaker 3: burned severity. Darker orange areas generally indicate while severe burning,

20:23 Speaker 3: somewhat damage to vegetation, increased bare or exposed ground, presence.

20:29 Speaker 2: Of ash, etc.

20:31 Speaker 3: But it's important to note that the NBR can be

20:35 Speaker 3: impacted by terrain effects, so things such as steep terrain, shadow,

20:40 Speaker 3: et cetera, of which there was a lot in this area.

20:45 Speaker 3: And then, as I mentioned, increasing shades of purple generally

20:48 Speaker 3: indicate healthy vegetation or only lightly burnt areas.

20:53 Speaker 2: The third way that.

20:54 Speaker 3: The NBR can be helpful is in planning vegetation recovery

20:58 Speaker 3: and post fire response activities.

21:02 Speaker 2: All right, so keeping this.

21:04 Speaker 3: Image in mind, let me now change the date to

21:11 Speaker 3: three years later on. So three years post fire, and

21:17 Speaker 3: there was actually a good image available on the twenty

21:23 Speaker 3: fourth of September. Okay, So now we can see more

21:35 Speaker 3: shades of purple, indicative of recovering vegetation and undamaged or

21:41 Speaker 3: healthy vegetation, and lessening shades of orange.

21:44 Speaker 2: Member there was a lot of orange in this.

21:47 Speaker 3: Area, and that orange is indicative of damage to vegetation,

21:55 Speaker 3: burned severity, et cetera. And if we pop on the

22:00 Speaker 3: false color composite, we've seen more shades of green, which

22:12 Speaker 3: is indicative of the vegetation recovery. And I have loaded

22:17 Speaker 3: up the image that was collected after the first several

22:24 Speaker 3: days of the fire, and all of this is burned

22:28 Speaker 3: area throughout here. And then this for comparison three years

22:33 Speaker 3: later on, so we can look at two snapshots now

22:36 Speaker 3: the freshly burned and then three years after and with

22:40 Speaker 3: this we can start to assess the magnitude of change

22:45 Speaker 3: that has occurred in the recovery.

22:47 Speaker 2: Of vegetation at the time.

22:49 Speaker 3: In addition to the normalized burn ratio, we also have

22:54 Speaker 3: available the normalized difference Vegetation index or NDBI, the normalized

22:59 Speaker 3: difference Oisteri index, and then the normalized burn ratio two

23:03 Speaker 3: and each of these can be explored after the webinar

23:06 Speaker 3: using the information tool at the bottom of the interface.

23:14 Speaker 3: I wanted to highlight that all of the bands for

23:19 Speaker 3: both Sentinel as well as landsacked, so the ten lancet

23:24 Speaker 3: bands and the twelve cent bands are available so that

23:29 Speaker 3: you can generate your own customized bound combination using.

23:35 Speaker 2: The bands that are available.

23:41 Speaker 3: You can also download the Modus and Beers Burned Area

23:44 Speaker 3: products for using a GIS. For example, you can navigate

23:48 Speaker 3: to the page using the downloads option here, or you

23:53 Speaker 3: can access it over on the left via the download

23:57 Speaker 3: Archived Data.

23:59 Speaker 2: From this drop down.

24:01 Speaker 3: The files are available in HGF, GOTIV or SHAPEFE format,

24:08 Speaker 3: and download instructions of detailed in the user guide. So

24:12 Speaker 3: the Modus user guide is here. In the vis user

24:15 Speaker 3: guide is listed here. There's also additional downloading guidance noted

24:21 Speaker 3: at the bottom of the page here.

24:27 Speaker 1: Thank you so much, Jenny for your demonstration on the

24:29 Speaker 1: burned area monitoring and post fire dynamics. And now I'll

24:33 Speaker 1: send this off to Diane Davies who will talk about

24:36 Speaker 1: the Smoke and Airsols mode infirms. After a little bit

24:39 Speaker 1: of background information, Diane will demonstrate an overview of the

24:44 Speaker 1: smoke Aerosols mode infirms as well as tracking smoke and

24:48 Speaker 1: aerosols using the OPS aerosol indices and corrective reflectance imagery.

24:54 Speaker 1: Thank you, Diane.

24:58 Speaker 4: Great Well, welcome to this demonstration on using NASA firms

25:01 Speaker 4: to monitor smoke and aerosols. By the end of this session,

25:06 Speaker 4: you should know how to use ferms to track smoke

25:08 Speaker 4: from routine fire events all the way up to extreme

25:12 Speaker 4: pyrocumulo nimbus or fire induced events that can inject smoke

25:16 Speaker 4: into the atmosphere. So let's get started first. I wanted

25:22 Speaker 4: to just establish our foundation that when we talk about aerosols,

25:26 Speaker 4: we're referring to tiny particles suspended in the atmosphere and

25:30 Speaker 4: these come in many forms. We have natural aerosols like

25:34 Speaker 4: sea salt from motion, spray, dust from deserts, pollen from plants,

25:39 Speaker 4: and volcanic ash. We have human generated aerosols from vehicle

25:43 Speaker 4: emissions and industrial pollution, and then we have fire generated

25:48 Speaker 4: aerosols and this is where smoke fits in. So a

25:51 Speaker 4: key concept from this is that smoke is simply a

25:55 Speaker 4: type of aerosol. It's made up of tiny particles from

25:58 Speaker 4: burning vegetation. Because it's suspended in the atmosphere, we can

26:02 Speaker 4: track it using satellite instruments and that's what makes firms

26:06 Speaker 4: so useful for smoke monitoring. Why does this matter? It

26:10 Speaker 4: matters because smoke doesn't just stay local. These particles can

26:15 Speaker 4: travel hundreds or even thousands of kilometers from their source,

26:18 Speaker 4: affecting air quality far from the original fires. So understanding

26:23 Speaker 4: smoke as an aerosol helps us use the right tools

26:26 Speaker 4: to track its movement. So what tools does firms give

26:31 Speaker 4: us for tracking aerosols. Well, we're going to be looking

26:34 Speaker 4: at the smoke and aerosols mode, and I think there

26:38 Speaker 4: are three main data sets that are extremely useful. First,

26:42 Speaker 4: we have visual detection through corrected reflectance imagery, So firms

26:47 Speaker 4: through NASA Gibbs provides true color imagery from multiple satellites.

26:52 Speaker 4: So we've got the Modus instruments on board Terinaqua and

26:55 Speaker 4: the vea's instruments on SUMI MPP Noah twenty and No.

26:59 Speaker 4: Twenty one, and this imagery shows us what the Earth

27:03 Speaker 4: looks like from space as our eyes would see it,

27:06 Speaker 4: making smoke plumes look clearly visible against the landscape. I

27:11 Speaker 4: should just note that in the advanced tab of firms,

27:14 Speaker 4: which I'll come too later. We also have the harmonized

27:18 Speaker 4: Lancet Sentinel imagery, which has a thirty meter resolution, but

27:22 Speaker 4: it's only available two to four days after satellite overpass,

27:25 Speaker 4: and I know that's been covered in some of the

27:27 Speaker 4: other training sessions. So in addition to the visual detection,

27:31 Speaker 4: we need quantitative measurements, and that's where the OMPs Aerosol

27:36 Speaker 4: Index products come. In OMPs or the Ozone Mapping and

27:40 Speaker 4: Profile A suite was originally designed to measure ozone, but

27:44 Speaker 4: it excels in detecting aerosols In firms.

27:48 Speaker 5: We have two OMPs Aerosol.

27:50 Speaker 4: Index layers, and we'll discuss those in a moment. But

27:54 Speaker 4: I just want to mention active fires because, as I

27:58 Speaker 4: mentioned earlier, smoke is just one type of aerosol, and

28:01 Speaker 4: so adding in the active fires helps us distinguish what

28:04 Speaker 4: sort of aerosol we're looking at and make us more

28:06 Speaker 4: confident that we're looking at smoke as opposed to dust,

28:10 Speaker 4: for example, and in my example we'll look at both

28:14 Speaker 4: smoke and dust. So I mentioned that firms actually provides

28:20 Speaker 4: two related OMPs aerosol index products. It's actually the same

28:23 Speaker 4: index and the value is related to both the thickness

28:27 Speaker 4: and the height of the atmospheric aerosol layer, but they

28:30 Speaker 4: have different values, so understanding when to use each one

28:34 Speaker 4: is key to successful smoke monitoring. The standard OMPs aerosol

28:39 Speaker 4: index has ranged from zero to five, and this works

28:42 Speaker 4: perfectly for most smoke and dust events. Values above five

28:46 Speaker 4: are actually filtered out of this product because they're considered

28:49 Speaker 4: too extreme for routine monitoring. But what happens when we

28:53 Speaker 4: have extreme fire events, Well, that's where the pyrocumulin nimbus

28:56 Speaker 4: or PYROCB layer comes in. And this has arranged from

28:59 Speaker 4: five to fifty and removes all that high value screening

29:03 Speaker 4: and is useful for identifying fires with dense smoke blooms.

29:07 Speaker 4: And it has effectively been used to track these pyrocumulum

29:11 Speaker 4: nimbus clouds or thunderstorms generated by wildfires, and so it's

29:17 Speaker 4: useful to know when to switch between these two layers.

29:20 Speaker 4: We generally start with the standard product for routine monitoring

29:23 Speaker 4: and switch to the PYROCB layer when you're dealing with

29:26 Speaker 4: extreme fire events or when you see gaps in the

29:29 Speaker 4: standard product. So let's just spend a moment looking at

29:33 Speaker 4: what these numbers mean and the resolution of the data. Okay,

29:40 Speaker 4: so this is very approximate, but generally for the standard

29:42 Speaker 4: once cerosol index values from zero to one indicate clear

29:46 Speaker 4: or minimal aerosol conditions. Values from one to three show

29:50 Speaker 4: light smoke or dust. Three to five indicate moderate smoke

29:54 Speaker 4: levels and is an important threshold that when you see

29:58 Speaker 4: aerosol index values of five, that indicates heavy aerosol conditions

30:03 Speaker 4: that can reduce visibility and impact human health. For the

30:08 Speaker 4: PYROCB layer, values above five indicate dense smoke that's probably

30:12 Speaker 4: reached higher in the troposphere. I should point out that

30:16 Speaker 4: there's a bit of variation between the OMPs aerosol index

30:19 Speaker 4: B products between SUMIMPP and NORAH twenty. This should be

30:24 Speaker 4: rectified in the future, but for now, values above seven

30:27 Speaker 4: from SUMIMPP and values above ten from No. Twenty suggest

30:32 Speaker 4: a likely PYROCB event. Under Values from twenty to fifty

30:38 Speaker 4: indicate extreme PIROCB events where smoke has likely been injected

30:42 Speaker 4: into the stratosphere, so temporarily we get daily coverage with

30:47 Speaker 4: near real time observation within about three hours of satellite overpass.

30:52 Speaker 4: This global daily coverage is what makes OMPs so valuable

30:56 Speaker 4: for tracking smoke transport over long distances. In terms of

31:00 Speaker 4: the resolution, the spatial resolution OMPs Aerosol Index from SUMIMPP

31:05 Speaker 4: has a spatial resolution of fifty by fifty kilometers. The

31:09 Speaker 4: newer NOAH twenty and no twenty one satellites actually provide

31:14 Speaker 4: higher spatial resolution for the OMPs aerosol index and ultimately

31:19 Speaker 4: this will give us more detail in smoke plumes. But

31:22 Speaker 4: currently firms displays both the aerosol indices from SUMI MPP

31:27 Speaker 4: and NOAH twenty at a resolution of fifty by fifty kilometers.

31:32 Speaker 4: In the near future, we plan to enhance the resolution

31:34 Speaker 4: of the NOA twenty AMPS data to twelve x seventeen

31:39 Speaker 4: kilometers and add in the OMPs aerosol index data from

31:43 Speaker 4: NOAH twenty one, which will have a ten x ten

31:46 Speaker 4: kilometer resolution. And this is what that will look like.

31:55 Speaker 4: So I'm just going to switch out here. So now

32:02 Speaker 4: let's see this in action with the real world example,

32:05 Speaker 4: I'm going to walk you through the Canadian wildfire events

32:09 Speaker 4: that occurred in May twenty twenty five. So when you

32:12 Speaker 4: first go into firms, you'll be in the basic mode.

32:16 Speaker 4: You can click on these horizontal lines at the top

32:20 Speaker 4: to go into the smoke and aerosols mode. And here

32:22 Speaker 4: I'm going to put on the corrected reflectance imagery from

32:27 Speaker 4: Noah twenty one, and I'm going to zoom into I've

32:32 Speaker 4: already set the date here to May twenty fourth, twenty

32:35 Speaker 4: twenty five, and now I'm going to put on the

32:39 Speaker 4: active fires. I'm going to put on the fires for

32:42 Speaker 4: Veer's Noah twenty one, so they're coincident with the imagery.

32:46 Speaker 4: And you can start to see here that we can

32:48 Speaker 4: see some smoke plumes, so these are milky white against

32:54 Speaker 4: the landscape, and that's exactly how it would look to

32:57 Speaker 4: your eyes if you're viewing it from space, and you

33:01 Speaker 4: can see some cloud cover here to the left, and

33:04 Speaker 4: if I zoom out a little bit, you can also

33:07 Speaker 4: see there's snow to the north, and there's ice in

33:11 Speaker 4: the Hudson Bay. So sometimes it can be a bit

33:15 Speaker 4: challenging to distinguish between clouds and smoke, and so that's

33:19 Speaker 4: why the fire active fire detections are very useful to

33:22 Speaker 4: help us to be sure that it is smoke. And

33:27 Speaker 4: now we're going to add in the OMPs aerosol index layer,

33:32 Speaker 4: and here you can start to see that we've got

33:37 Speaker 4: values in the probably in the two to four range.

33:40 Speaker 4: If you want to look at the actual values, you

33:42 Speaker 4: can click on this opacity button here and you can

33:46 Speaker 4: change the value. So if you just wanted to look

33:48 Speaker 4: at values from two, you can change it here almost their.

33:54 Speaker 5: And there you are.

33:56 Speaker 4: You can also if you want to be able to

33:58 Speaker 4: see through the cloud as well, you can change the

34:00 Speaker 4: opacity so sorry, if you want to see through the

34:03 Speaker 4: aerosol index, you can change.

34:05 Speaker 5: The opacity here. So that's quite a useful tip.

34:09 Speaker 4: So this shows us where the smoke is, and the

34:11 Speaker 4: aerosol index starts to give us an idea of how

34:14 Speaker 4: dense the smoke is, and in this case, it's not

34:16 Speaker 4: very dense.

34:17 Speaker 5: But as we progress through the.

34:19 Speaker 4: Dates, you can see that the aerosol index values are

34:24 Speaker 4: getting higher and the smoke plume is getting larger and denser.

34:30 Speaker 4: So I'm going to scroll through a little bit more.

34:34 Speaker 4: All right, Now, WA's what happens if I put on

34:38 Speaker 4: the pyrocumulo nimbus layer. You can see that we now

34:43 Speaker 4: have So I change this to blue to make it

34:46 Speaker 4: really stand out. But again there's a functionality here. This

34:50 Speaker 4: is the default. You can switch at to whatever color

34:53 Speaker 4: you like for your preference. But you can start to

34:57 Speaker 4: see that the smoke is being lofted high in to

35:00 Speaker 4: the troubosphere and it's starting to transport well beyond the

35:06 Speaker 4: boundaries of Canada. So what I want to do now

35:11 Speaker 4: is I just want to switch across and show you

35:14 Speaker 4: an animation of this smoke plume.

35:17 Speaker 5: You can see.

35:19 Speaker 4: I'm going to put it onto repeat actually, so that

35:21 Speaker 4: you can see it a couple of times.

35:25 Speaker 2: So here we are.

35:25 Speaker 4: We've got if you can see my cursor, we've got

35:27 Speaker 4: the smoke plumes coming from Canada. They go right across

35:30 Speaker 4: the Atlantic to Europe and onto Asia. And at the

35:35 Speaker 4: same time as heading out into the Atlantic, there's also

35:38 Speaker 4: a plume that goes up to the Arctic, and you

35:40 Speaker 4: can also you might also notice that there are some

35:43 Speaker 4: fires occurring in eastern Russia, and you can see again

35:48 Speaker 4: that the smoke plumes are quite large there. Now you

35:51 Speaker 4: might notice that there's quite a lot of activity going

35:54 Speaker 4: on on the west coast of Africa, north and west

35:57 Speaker 4: coast of Africa here, and so we're just going to

36:00 Speaker 4: take a look at that, because in this case it's

36:05 Speaker 4: still aerosols, but it's not actually from fires. So we're

36:09 Speaker 4: going to follow the same procedure. We're going to have

36:11 Speaker 4: a look at the corrected reflect and symmetry, and I'm just.

36:16 Speaker 5: Going to scroll through to third I think it is.

36:22 Speaker 4: Yeah, so what we what we What we saw here

36:26 Speaker 4: was that we were seeing fairly high aerosol in disease

36:30 Speaker 4: in the Sahara. And we can tell whether or not

36:36 Speaker 4: it's smoke or fire by looking to see if there's

36:38 Speaker 4: any fires close by and if we can see any

36:40 Speaker 4: smoke plumes, and in this case there isn't. And also

36:44 Speaker 4: if you turn this off, you can see that we

36:47 Speaker 4: have a huge dust plume coming off the west coast

36:51 Speaker 4: of Mauritanium. And again if I just zoom out, you

36:56 Speaker 4: can start to see.

37:00 Speaker 1: It.

37:00 Speaker 5: Catch up, there we are.

37:01 Speaker 4: You can see the smoke plume coming out into the ocean,

37:05 Speaker 4: and there you can see the OMPs aerosol index. And

37:09 Speaker 4: I probably should have put this back down to the

37:11 Speaker 4: original value before I started, so again it's approximately got okay,

37:17 Speaker 4: So there's an example of dust rather than just than smoke.

37:23 Speaker 5: Okay.

37:25 Speaker 4: So the other thing that I wanted to look at

37:31 Speaker 4: was an example from India. So in northern India, there

37:39 Speaker 4: tends to be recurring seasonal haze and pollution that becomes

37:43 Speaker 4: trapped near the ground by seasonal weather patterns, and this

37:47 Speaker 4: can create unhealthy air quality.

37:49 Speaker 2: So here we are, we've.

37:51 Speaker 4: Jumped to India for November first, and you can see

37:55 Speaker 4: here that we have these seasonal agricultural fires. This is

38:00 Speaker 4: they burn the remaining stubble after the rice harvest. So

38:04 Speaker 4: this stubble burning often creates haze and smoke. And again

38:09 Speaker 4: if you use the timeslider, you can see how this progresses.

38:14 Speaker 4: And this is this has been a source of contention

38:18 Speaker 4: often in the news in Delhi and northern India due

38:22 Speaker 4: to the poor equality. So I just wanted to show

38:29 Speaker 4: you what a pyrocumulinnimbus event looks like in firms. So

38:34 Speaker 4: I've jumped over to the advanced mode here and we

38:38 Speaker 4: are looking at the Vias Noah twenty one imagery and

38:45 Speaker 4: you can see that we've got very thick smoke here

38:47 Speaker 4: we've got the winds going from kind of west to east,

38:52 Speaker 4: and if we put on the aerosol index, you can

38:56 Speaker 4: see that we've got quite high values. And if we

39:00 Speaker 4: put on the pyrocumula numbers event, you can see procumulan

39:04 Speaker 4: nimbus layer. You can see that where you've got these

39:06 Speaker 4: gaps in the standard layer, it's filled in with the

39:12 Speaker 4: OMPs pyrocb layer. So I'm just going to turn those

39:16 Speaker 4: off for a moment and just zoom in, so what

39:19 Speaker 4: we're actually seeing the pyrocumulin umbus event. You can actually

39:23 Speaker 4: see them pretty well here. But what's happening is the

39:26 Speaker 4: higher values in terms of the aerosol index only show

39:31 Speaker 4: when the smoke has been lifted into the air and

39:34 Speaker 4: is being transported. But yeah, just to show you quickly

39:37 Speaker 4: what it looks like, I'm going to just put on

39:40 Speaker 4: the year's twenty one active fires and again just to

39:45 Speaker 4: show you here if you want to kind of just

39:48 Speaker 4: match the daytime fires with the imagery so it's coincident,

39:52 Speaker 4: you can even again change the size of the pixel

39:55 Speaker 4: so you can really get a good view of the smoke.

39:58 Speaker 4: And in this case, what I just wanted to also

40:00 Speaker 4: show you is that in the advance mode, we have

40:03 Speaker 4: the HLS layers and I think we've seen these in

40:07 Speaker 4: previous art set trainings, but here you can put on

40:11 Speaker 4: the I think it's a lands of that data. Yeah,

40:15 Speaker 4: and if you zoom right in again, you can see

40:18 Speaker 4: that thick smoke that's funneling up, the funneling up into

40:25 Speaker 4: the shopsphere and then being lofted across. And I think

40:30 Speaker 4: it's so these pyrocum numbus events, we've seen quite a

40:33 Speaker 4: few of them this year and in previous years. I

40:36 Speaker 4: think twenty twenty three had a record number of PYROCB

40:40 Speaker 4: events in Canada. And these are very much a smoke

40:44 Speaker 4: fire induced thunderstorms that can impact the weather and loft

40:49 Speaker 4: these smoke aerosols far into transported very many kilometers. I

40:59 Speaker 4: just wanted to cap on when to use each product.

41:02 Speaker 4: So the standard OMPs aerosol index should be used for

41:05 Speaker 4: most situations for routine monitoring for smoke and aerosols, and

41:10 Speaker 4: the PYROCB aerosol Index layers should be used when there

41:15 Speaker 4: are extreme events, when you think there might be fire,

41:18 Speaker 4: th fire created thunderstorms or gaps in the aerosol index product.

41:24 Speaker 4: And then just by way of recap. I think FIRMS

41:27 Speaker 4: is particularly useful for monitoring and tracking smoke by starting

41:32 Speaker 4: with the true color imagery to give you a visual

41:35 Speaker 4: overview of smoke potential, smoke and aerosols, and then you

41:40 Speaker 4: can add in the OMPs aerosol index, and then I

41:45 Speaker 4: recommend that you add in the active first better distinguished

41:47 Speaker 4: between smoke and other forms of aerosols, and then switch

41:50 Speaker 4: to the PYROCB aerosol index if values exceed five, and

41:55 Speaker 4: then use the temporal progression to track the fires over

41:59 Speaker 4: a number of days. And you can also use the

42:03 Speaker 4: orbit tracks and subdaily timeline for adding additional time context.

42:12 Speaker 1: Okay, thank you so much Diane and Jenny, and thank

42:16 Speaker 1: you very much for demonstrating those for us today. Just

42:20 Speaker 1: as a summary, today we look at an overview of

42:22 Speaker 1: available burned area data sets and post fire imagery and indices.

42:27 Speaker 1: We had a demonstration of FIRMS burned area mode, an

42:30 Speaker 1: overview of available aerosol indsease, and then a demonstration FIRM

42:35 Speaker 1: smoke and aerosols mode. Looking ahead to part two, we'll

42:40 Speaker 1: be visualizing active fire information on static graph and interactive maps.

42:46 Speaker 1: Analyze active fire information using a fire count instagram overview

42:52 Speaker 1: of static thermal anomaly data available in firms and how

42:56 Speaker 1: to use that static thermal anomaly data information to identify

43:00 Speaker 1: through mo anomalies that are likely not vegetation fires. And

43:05 Speaker 1: just as a reminder, after part two, we'll have your

43:08 Speaker 1: homework available and we'll be DOUE on the third of December.

43:12 Speaker 1: Anybody who attends both live webinars and complete the homework

43:15 Speaker 1: by the third or receive a certificate via email approximately

43:18 Speaker 1: two months after the completion data of this training. Here's

43:23 Speaker 1: the contact information for Jenny Houston, Diane Davies, and myself

43:27 Speaker 1: Rock Blevins, as well as a link to the our

43:31 Speaker 1: Set website and our Set YouTube channel. Thank you very much,

43:36 Speaker 1: and now we'll start the question and answer session. Okay, great, well,

43:46 Speaker 1: let's just jump right into it here. Your questions have

43:48 Speaker 1: been coming in throughout the presentation and we've been diligently

43:53 Speaker 1: getting to these as well as we can before this session,

43:57 Speaker 1: so we can jump right into it. We have Jenny

44:02 Speaker 1: and Diane on here, so we'll start up with question one.

44:07 Speaker 1: Most of the satellite analysis is mainly for focusing on

44:10 Speaker 1: examining the incident that happened already in stead update intervals

44:15 Speaker 1: extend the damage further, Is there any possibility to predict

44:19 Speaker 1: or foresee the incident beforehand?

44:25 Speaker 4: I'll take bachelor Jenny, Okay, So no, there aren't any

44:28 Speaker 4: specific layers in firms global that enable users to predict

44:32 Speaker 4: fires unfortunately, and we have struggled with the idea of

44:37 Speaker 4: putting in some kind of fire danger rating globally so

44:42 Speaker 4: that that's just not available as local conditions vary. However,

44:46 Speaker 4: Firms has recently added vegetation indices from HLS which Jenny showed,

44:52 Speaker 4: and these can be found in the advanced mode and

44:54 Speaker 4: include the normalized difference vegetation index and normalized difference moisture

44:59 Speaker 4: index and these could be used locally to help monitor

45:03 Speaker 4: fuel conditions For firms. US Canada, there are a couple

45:07 Speaker 4: of layers which may be of interest. There's a US

45:09 Speaker 4: Flag warning and a US fire weather watch. So these

45:13 Speaker 4: are watches and warnings issued by the National Weather Service

45:16 Speaker 4: and their criteria varies for each and National Weather Service

45:21 Speaker 4: forecast area. Fireweather watch is issued when there's a combination

45:25 Speaker 4: of dry fuels and feather condition weather conditions that support

45:29 Speaker 4: extreme fire danger, and the red flag warnings are issued

45:32 Speaker 4: when these extreme conditions are anticipated in the next twenty

45:35 Speaker 4: four hours.

45:38 Speaker 1: Thanks Brad, great, thank you very much. Second question, the

45:43 Speaker 1: HLS products only available over US and Canada or with

45:47 Speaker 1: Firm Global. Can we access the data set? Well?

45:53 Speaker 2: Thanks Brok.

45:54 Speaker 3: So the data are actually available in Firms Global. One

46:00 Speaker 3: thing to note that there is a delay in the

46:05 Speaker 3: data set, that there is a lag of anywhere between

46:08 Speaker 3: two to four days. So again, the imagery is available

46:12 Speaker 3: in firms US, Canada as well as Global. Sometimes it

46:17 Speaker 3: can be helpful to zoom out and just be a

46:21 Speaker 3: little patient so you can see the imagery actually.

46:27 Speaker 2: Load on the screen.

46:29 Speaker 3: And just to know, this is different than the Lancet

46:34 Speaker 3: Active Fire data and they are only available for the

46:39 Speaker 3: US and Canada. So again the HLS imagery are available globally.

46:45 Speaker 2: With this with this light lagtime.

46:50 Speaker 1: Question three, given that the firm's platform will not be

46:53 Speaker 1: updated temporarily as indicated by the I notification, what alternative

46:57 Speaker 1: solutions can you offer us?

47:01 Speaker 3: Yeah, thanks for the question. So there are no enhancements.

47:07 Speaker 3: Are are updates being made to the website currently due

47:12 Speaker 3: to the lapse in funding, but the Active five detections

47:16 Speaker 3: and image products continue to be ingested automatically into firms Additionally,

47:22 Speaker 3: any antages or data nomenblis that occur have been addressed

47:28 Speaker 3: as as as as they've occurred.

47:35 Speaker 1: Great, thank you. We'll see what we can do to

47:38 Speaker 1: swing back around and address question number four. In the meantime,

47:43 Speaker 1: we'll move on to number five. I'm working with the

47:46 Speaker 1: Generator working on generating monthly time series data sets of

47:49 Speaker 1: burned severity metrics over large Baxel scales using modus. My

47:54 Speaker 1: main challenge is identifying appropriate free fire and post fire

47:57 Speaker 1: time windows for calculating the NBR for each month. To

48:02 Speaker 1: suggest this effective approach, So.

48:10 Speaker 2: I'm actually going to invite my colleagues to address this.

48:16 Speaker 3: But I actually think this question will take a little

48:20 Speaker 3: bit of time to just think about and develop the best.

48:25 Speaker 2: Answer for Diana.

48:26 Speaker 3: I don't know if you have an idea off the

48:31 Speaker 3: top of your head.

48:33 Speaker 5: It's such a great question.

48:35 Speaker 4: I think it would be better off getting a proper

48:39 Speaker 4: answer from some of our science team to help answer

48:41 Speaker 4: this question.

48:44 Speaker 2: And we do.

48:46 Speaker 3: As you know, we do answer all of the questions

48:51 Speaker 3: as soon as we as soon as the webinar finishes

48:54 Speaker 3: and we have additional information available.

48:58 Speaker 1: Yeah, that's great. We figure we might as well give

49:02 Speaker 1: a little bit more of a thorough answer to this,

49:04 Speaker 1: So please give a little bit of time to make

49:07 Speaker 1: sure that we can answer this answer this as accurately

49:09 Speaker 1: as we can. Question number six, does the aersow invex

49:13 Speaker 1: correlate with the concentration of smoke stums?

49:22 Speaker 4: That is my understanding that it's to do with density

49:27 Speaker 4: and height of smoke plumes. But again, I feel like

49:34 Speaker 4: this is a very technical question and I will confirm

49:38 Speaker 4: once we circle back with the final answers, unless anybody

49:44 Speaker 4: else on my team would like to chime in.

49:51 Speaker 2: I am in agreement, Diane.

49:52 Speaker 3: I think addressing this when we have additional information that

49:57 Speaker 3: will be ideal.

50:00 Speaker 1: Great. Once again, in the sake of accuracy, please give

50:02 Speaker 1: us some moments on that one. Question number seven, is

50:05 Speaker 1: there some way to use amps in a geostationary satellite?

50:09 Speaker 3: So OPS is on board SMPP NOAH twenty No twenty one.

50:14 Speaker 3: These are all polar orbiting satellites versus the geostationary satellites

50:20 Speaker 3: such as GO as the East and West.

50:26 Speaker 1: Eight. I mean use this data to predict when first

50:29 Speaker 1: nation communities to look at evacuation. So it just looks

50:36 Speaker 1: like emergency response, and.

50:40 Speaker 4: Sure we would question against that the data are provided

50:46 Speaker 4: as it is, and we take no kind of responsibility

50:49 Speaker 4: for it being used in evacuation circumstances. We would rather

50:54 Speaker 4: advise that you use local knowledge on the ground. Obviously,

50:59 Speaker 4: sometimes people find the data is helpful, but please remember

51:01 Speaker 4: that you know the data is near real time, so

51:04 Speaker 4: approximately three hours after satellite overpass, and these are polar

51:07 Speaker 4: orbiting satellites, so they're not constantly updated.

51:12 Speaker 5: Throughout the day.

51:13 Speaker 4: We have the geostationary satellites which do have you know,

51:18 Speaker 4: they are updated throughout the day and night. However, the

51:21 Speaker 4: spatial resolution of those pixels is not really good enough

51:26 Speaker 4: for that kind of decision making.

51:29 Speaker 1: I would say, great, so the deal stationary data have

51:35 Speaker 1: a higher temporal but maybe the straight off being spatial.

51:41 Speaker 5: Yes, thanks for that clarification.

51:43 Speaker 1: Yeah, Question nine, are temperatures of the fire? Of the

51:48 Speaker 1: temperatures of the fire is available.

51:51 Speaker 3: I was trying to find your new button there. So

51:54 Speaker 3: the radiative power FRP, which is the energy of the fire,

51:59 Speaker 3: is available in attribute information and the actifier detections. And

52:04 Speaker 3: this can be identified by by actually clicking on the

52:09 Speaker 3: active fire detection, which will bring up the attribute information

52:14 Speaker 3: for each of the detections.

52:19 Speaker 1: Thanks on the work well provided. Are there are structured

52:23 Speaker 1: guidelines on how to properly reference the data acquired?

52:30 Speaker 5: We do have that information.

52:31 Speaker 4: We have a something you can use on your using

52:35 Speaker 4: our data and we will.

52:37 Speaker 5: Pop that in the chat as soon as I can

52:39 Speaker 5: find it.

52:39 Speaker 4: It's and the data use and data use guidance and disclaimers.

52:44 Speaker 5: So let me put that in the chat for you.

52:48 Speaker 1: Great, thank you very much, and I'll also include that

52:53 Speaker 1: link in the document for future reference to. Then question eleven,

53:02 Speaker 1: are these layers only applicable in Google Earth Engine or

53:05 Speaker 1: they can? Can they also be used in rgis pro

53:11 Speaker 1: as that is the main software used at my institution.

53:16 Speaker 3: Yeah, so I'm rapidly putting the answer in here so

53:20 Speaker 3: that the burned Area products are available in HGF geotif

53:24 Speaker 3: and shapefel format and certainly the geotif and shapefel can

53:28 Speaker 3: be used in r GI s pro, and there is

53:32 Speaker 3: information on the on the firm's website if you look

53:41 Speaker 3: under download archived Data, so those can be downloaded and

53:46 Speaker 3: used in r gis pro. Additionally, the active fier detections

53:50 Speaker 3: are available in multiple formats including CSV and and shapes

53:57 Speaker 3: and so they can also be used in our jais.

54:02 Speaker 1: Okay, So I don't see any other questions adding to

54:07 Speaker 1: the question answer box. If you're not able to find that,

54:12 Speaker 1: please look for the three little dots on the left

54:17 Speaker 1: lower corner of either your application or your web browser,

54:22 Speaker 1: and you can see a Q and A section We

54:25 Speaker 1: can answer your question or ask the questions, and we'll

54:27 Speaker 1: move those over to this document. What we'll end up

54:31 Speaker 1: doing is cleaning this up for accuracy and then posting

54:36 Speaker 1: this ideally within a week, So hopefully before part two

54:42 Speaker 1: next week, we can have this available on the website

54:45 Speaker 1: for your reference. Which sensor characteristics are essential for accurate

54:52 Speaker 1: detection and retrieval atmospheric aerosols sate observations. So I guess

54:59 Speaker 1: it's just to come and some of the characteristics of

55:03 Speaker 1: the sensory.

55:10 Speaker 4: Oh, everybody's really challenging us today. I don't I couldn't

55:16 Speaker 4: give you a good answer to that either. I'm really sorry.

55:19 Speaker 4: I think we'll have to circle.

55:21 Speaker 5: Back to you.

55:25 Speaker 1: Okay, So we'll bring this question to the science team

55:29 Speaker 1: and so look for this answer once we post to

55:33 Speaker 1: our train web page.

55:35 Speaker 4: Yeah, I should just say that, you know, we work

55:37 Speaker 4: very closely with our science teams that they provide us

55:40 Speaker 4: with all this type of information and we aim to

55:44 Speaker 4: make it easily accessible through firms. So apologies for not

55:47 Speaker 4: being able to answer those questions.

55:51 Speaker 1: Well, to see a couple more pop in here. This

55:54 Speaker 1: one seems to be a little bit more of a

55:55 Speaker 1: use case or hypothetical or maybe there's some case studies

55:59 Speaker 1: doing this. But how can satellite managoring help in estate management?

56:02 Speaker 1: So I'm guessing this of mitigation and preparedness, I.

56:10 Speaker 5: Can take a stab at that, I guess.

56:13 Speaker 4: You know, you can look at things like which areas

56:17 Speaker 4: have burnt over time that might be useful for understanding

56:21 Speaker 4: fire regimes in your particular state or area of interest.

56:25 Speaker 4: You can also look to see which areas have burnt

56:29 Speaker 4: and so you might get a better understanding of which

56:31 Speaker 4: areas are more likely to burn in subsequent years of

56:34 Speaker 4: fire seasons. Again, you know, I mentioned earlier on that

56:39 Speaker 4: we have vegetation indices from the HLS data.

56:43 Speaker 5: Again that might.

56:44 Speaker 4: Help you understand what your vegetation conditions are like and

56:49 Speaker 4: give you a sense of whether or not it's more

56:52 Speaker 4: likely to burn. And the same thing for the active

56:56 Speaker 4: fire data. You know, again, you can look at fire

56:59 Speaker 4: patterns over time. We also have an email alert service

57:05 Speaker 4: which is freely available, so if you wanted to put

57:07 Speaker 4: your coordinates in, we could send you an alert when

57:11 Speaker 4: there's a fire in or close to your particular area

57:14 Speaker 4: of interest.

57:18 Speaker 1: Question number fourteen, you mentioned a two to six percent

57:21 Speaker 1: difference and fire detection between motives and fears, one time

57:26 Speaker 1: bias higher than the other, and it looks like we

57:31 Speaker 1: have yeah.

57:33 Speaker 2: Thanks to that question. Sorry brough up to interrupt.

57:38 Speaker 3: In fact, all of the information on the inter comparison

57:42 Speaker 3: between the modus and viewers burned area products is available

57:47 Speaker 3: in the jiglio at our paper, and I have pasted

57:51 Speaker 3: the link for that paper.

57:54 Speaker 2: In the question.

57:58 Speaker 1: We'll just tackle these last two here. Real quick confirms

58:01 Speaker 1: contect some greenhouse gases.

58:04 Speaker 2: So the active Frier detections and the Burndery products that.

58:08 Speaker 3: They don't directly detect any any greenhouse gases, but they

58:13 Speaker 3: can be used in the in the calculation of different

58:17 Speaker 3: greenhouse gases. And Diane, I don't know if you want

58:22 Speaker 3: to add any additional information.

58:25 Speaker 1: To that question sixteen. What are the strengths and limitation

58:29 Speaker 1: of Arizon products for detecting low altitude smoke versus strata

58:34 Speaker 1: spirits here.

58:39 Speaker 3: Yeah, another excellent question, and we can certainly consult the

58:44 Speaker 3: science team members to get some more information on this.

58:50 Speaker 4: And I would just just from having spoken to the

58:53 Speaker 4: science team recently.

58:57 Speaker 5: In preparation for this again say that generally it would

59:02 Speaker 5: be you know, you can use.

59:04 Speaker 4: Sort of the lower A result index values indicate that

59:09 Speaker 4: you've got low altitude smoke, and you can look at

59:15 Speaker 4: the corrected reflectance imagery to try and verify this, and

59:19 Speaker 4: we will circle back on.

59:21 Speaker 5: This answer to make sure we have it correct.

59:23 Speaker 4: And when you have much higher AI value, so you

59:28 Speaker 4: would be looking at the pyro CB layer here, so

59:31 Speaker 4: values above five, that's when you're more likely to have

59:34 Speaker 4: these dense smoke, dense smoke that's gone higher into stratospheric.

59:41 Speaker 5: Into stratospheric layer. And I'd say that you know, the

59:45 Speaker 5: higher the.

59:45 Speaker 4: Value, the more likely the smoke has gone higher up.

59:52 Speaker 1: We are at time here today, I want to respect

59:54 Speaker 1: everybody's day. Thank you very much for joining us for

59:57 Speaker 1: part one of this series. Hopefully you had a chance

59:59 Speaker 1: to pick this training for the intro one back in April.

1:00:03 Speaker 1: If not, all the recordings, videos, homeworks are available so

1:00:08 Speaker 1: you can self pace through it, but we wanted to

1:00:11 Speaker 1: offer this one to highlight some of the additional features

1:00:14 Speaker 1: that have been corporated in the firms. So thank you

1:00:18 Speaker 1: very much Jenny and Diane for showing us those and

1:00:21 Speaker 1: please join us for part two next week, And thank

1:00:26 Speaker 1: you very much for joining us, and we'll see you

1:00:28 Speaker 1: next week