Good afternoon.
I'm really excited to be introducing Nick for this talk.
I was looking, so we, the geography department started having
Darwin speakers in 2002, and at that point we had Doctor Robert
Gates from Clark who talked about sustainability science.
We're back to Clark University again.
Nick came out of Clark about a year and a half ago now, something like that.
So we're kind of coming back full circle and going back to somebody from Clark.
So Nick graduated from Clark, as I said, in 2023 with a PhD in geography,
doing a dissertation on sort of mitigating urban heat island effect.
He's got his master's in education from Lehman College in New York City,
and then spent five years actually teaching high school in the Bronx there.
So we figured if he could teach in the Bronx,
he could probably teach in the Silver State, but that was too much trouble.
And then he's got 2 bachelor's degrees, one in environmental policy and the other
in French lit.
And I forgot, if anybody has questions about French
Liberty, you can have to pick up that there.
While he was at Clark, he taught full time at Holy Cross as a
visiting lecturer for a couple of years.
So we brought Nick in with a lot of teaching experience,
which has been really, really exciting for us.
He's also been, I think starting last year,
managing something called the Hero program at Clark,
which is part of the Green in the Gateway Cities program.
They've been planting trees in and around Worcester,
and I think we're sort of doing, we've done some of that here on Salem
States campus also.
So it's kind of nice that he's been involved with that.
So Nick is our tree and our drone guy there.
You want to know anything about trees or anything about drones,
We're going to talk to Nick there.
He's been doing tree canopy studies and swamps cut in Marblehead.
He helped out.
We were working with biology that down in the Greenlawn Cemetery that's become an
Arboretum.
He helped out doing some of the work down there.
And then he's been teaching our drone class.
If anybody's sort of interested in drones in the fall, we run a drone class.
We are going to learn a lot about sort of all about drones and how you get a
license and you're going to do projects and those kinds of things.
And people have learned that Nick was doing that real quickly as I think he's
now getting more requests to sort of do drone things around than he has time to
do there.
So without further ado, I'm going to introduce Nick Drone,
who's going to be talking about searching for shade,
adapting to extreme heat in the Northeast United States.
All right.
Thank you.
It's really great to be here.
I have to say the opportunity to speak to this many people to reflect on prior
research and future directions at this time,
which is an important time both politically and environmentally is is
just amazing.
I really want to thank especially Ryan Professor Ryan Fischer for helping out
with the organizing and and coordinating all of this is also Professor John Hayes
for establishing the geography speaking time during 2002, a long time ago,
but so really grateful for both for that work.
My talk is titled searching for shade extreme heat in the Northeast and behind
it is a thermal temperature map that is, and I realized I,
I was going to pay us more, but I'm, I'm going to I am plug this in.
So I'm just going to stay here, but it's during a heat wave in July 2022.
So I am going to touch this make sure this goes.
So I'm broken this up into kind of three sections going to go over extreme heat in
the Northeast, what the predictions look like,
what trends are.
Try to get a little bit into the climate science for my climate change class
that's here.
And then we'll go into my work with street trees,
their impacts on temperature and then potential solution.
The Milwaukee forest, and this is me leading a tree talk in the
Havant Arboretum, which is a patch of forests in Worcester
that is very similar to what the types of green solutions that hopefully we'll be
able to have more of in our cities.
So where is the state of the science it related to extreme heat and global
warming.
So in 2023, the IPCC report released this graphic,
among others, talking about different heat or
temperature thresholds.
It starts to start at the global level.
So you'll notice these are global maps down below.
And they identified these thresholds of 1. 5°C,
which I'm going to refer to quite a bit, as well as 2°C.
And these are relics or not relics, but descended from the Paris climate
agreement.
So those numbers were identified then as important for mitigating 1.5°,
for mitigating any of some of the worst adverse effects of climate change.
And then 2°C was sort of the threshold at which we would begin to see irreversible
change.
So maybe no, you know, ice sheets in the Arctic,
huge loss of species biodiversity, you know, no, no coral reefs,
massive amounts of sea level rise, changes that we cannot make any
modifications to.
So those are important thresholds for us.
I also want to draw your attention to in the maps,
they're looking at the hottest day temperature.
So when we're thinking about climate science and especially when we start to
think about how climate impacts health, we're often thinking about the worst case
scenario.
So these maps show what the hottest day would be like that summer and those
changes that.
So that was in 2023.
In 2024 we actually passed for the first time the global one year average for
temperature was 1.6°C.
Don't be too alarmed, the 1. 5 threshold is a 10 year average.
So in the climate change class we talked about how 30 years is might be too long
in order to really understand the rapid change in our climate.
So the IPCC or International Panel on Climate Change is using a 10 year average.
So we only have broken this threshold once in this year,
but it already looks like 2025 is going to be warmer than 2024.
In January we as a globe broke temperature records even though it's very
cold here, it's very warm in the Arctic and so
relatively.
So we have this about 10, maybe five year window where our before
and we reach this 1. 5°C because it's an average,
we're don't expect to reach it next year or the year after,
but we're in a short time period where you know 5-10 years before that threshold
will be passed.
This is what I've been talking about is global temperature averages.
But if we think about climate change, it happens and we experience it locally.
So looking at this regional map of the United States.
Temperatures that we're going to experience here,
the changes in temperature are going to be much more extreme than the not the
global averages.
And this is generally true for most places further north.
You know, the further north you go, the more warming that we're seeing or
further South.
And with that temperature change comes heat risks, health risks.
So this is a study from 2011 and it looks at just the average temperature.
And so an increase in 1°F of average temperature for the Northeast and for the
Midwest brings an increase of five to 10% of heat mortality risk.
So how to look at this map?
It's basically the big bubbles, big circles are bad.
That's more risk.
And I've kind of put a square around Philadelphia and New York as cities that
have similar temperatures.
You'll notice that those cities on the X axis don't have the highest temperatures.
But because of the Northeast is not used to the extremely hot temperatures,
that's why we see a higher risk there.
And this is true not just in terms of 1° temperature increase,
but which is that first column there for the Northeast.
But you can also see that our heat waves are going to increase in duration.
So multiple days in a row, instead of a three day heat wave,
we might have a four day or five day heat wave.
And that also has a significant amount of mortality increase.
And then we also see that our heat waves are happening earlier in the year,
so in May instead of June or in even early May or late April instead of the
summer.
So those all accompany significant mortality increases.
And you'll notice that the Northeast is unique here.
It's not.
We don't see the same relationships in the South or the Midwest and with health.
And so with these health risk increases, we see increases in heat mortality.
So this is a study ten years later in 2021 and it looks at heat mortality and
you can see the map of the US looks a little bit like you would expect for heat
mortality.
The Southwest is extremely high amount of heat mortality, extreme heat deaths.
And there are pockets throughout the South where we see amounts of large
amounts of extreme heat on those.
You can think of those as a map of cities almost.
But then there's this corridor from DC to Boston of extreme heat mortality over the
last like 30-40 years.
And a lot of this is because our infrastructure and culture is just not
designed around preparing for extreme heat.
We're we're ready to deal with extreme cold like this week and we have the
infrastructure for that, but we're not prepared in the summer or
in early June or late May for heat waves.
And a lot of that has to do with some cultural things.
Like I'm very proud last summer we didn't turn on the AC in our home.
And you know, I brag to friends about that.
But if we think about it, that's not really what we should be
bragging about.
Like, how can we actually live sustainably with
this?
Now that might not mean turning on the AC, but how do we build buildings or change
our built environment so you don't have to?
And a lot of that has to do with our housing stock.
So these are triple deckers.
You can see one this street in Worcester, but also we see them in Salem.
They're kind of ubiquitous across Massachusetts landscape.
And I was showing this PowerPoint to my my parents and my dad told me I was born
in a triple Decker in, in Chicago.
So they're not just the Northeast, but they are not designed for extreme
heat and they are not well insulated and especially on third floors can be
extremely dangerous, especially for young children.
So there is the health aspect of extreme heat,
but there's also the economic aspect.
And this study looked at peak energy use.
And what's interesting about this is that for colder temperatures, this line,
the slope is a little lower.
So and the temperatures are the energy usage doesn't actually get as high as
during extreme heat where we see that temperature the the relationship is much
steeper.
And so the increase in energy usage goes up faster during for every degree of
temperature increases and it gets to a higher level.
So often again, it's those urban the air areas that are
relying on energy to deal with heat that will bear this burden.
And so when we look and now zooming into just the Northeast,
we're looking at where across the Northeast,
where will the heat be the worst.
You know, I showed you that initial map of the
regions of North America across the US, but if we actually zoom into just the
Northeast, we see that heat is not distributed
evenly across this region.
So this paper looked at trying to understand the patterns of heat.
It uses land surface temperature, which is a product from the Landsat or
it's a satellite product.
It's an average of temperature, thermal temperature of the surface of the
Earth from May to September 2013 to 2017.
So it's an entire summer average.
So it just gives you a sense of where it could be hot.
And they found that heat was concentrated again in cities and urban areas without
access to vegetation, without a lot of vegetation.
But in these neighborhoods, there were concentrations of racial and
ethnic populations as well as high concentrations of young children who are
especially a vulnerable population to extreme heat.
And these trends were strongest for black and Hispanic or Latin X communities.
So we're seeing that these, the extreme heat is not an equitable
distribution at any sense and the people who are vulnerable to it are,
are often the most exposed as well.
So I'm going to be showing a lot of land surface temperature data here.
So I want to kind of show you where it's coming from.
This is Landsat 8 or an image of Landsat 8.
It's a satellite that's a joint product of NOAA and or NASA and USGS and they
provide, it's been continuously providing data
since 1984 with different Landsat missions except for Landsat sake.
So, but it provides just surface temperature.
So it's not telling you the surf, the temperature that you feel.
And it only passes over at 10:30 AM every two weeks.
So it's not like a continuous amount of coverage.
And critically, it's not air temperature.
This is a map of Lynn look at using land surface temperature by Nate in my class
in the fall, you can see how parts of Lynn,
like the Lynn Woods are much cooler where we see lots of vegetation,
whereas downtown Lynn we see pockets of extreme heat or very, very,
very hot areas.
What I like about what Nate did here is he overlaid it over just like kind of
like a Google imagery layer.
And you can actually see the white roofs in some large buildings in downtown Lynn
that are providing some cooling, even though it's a pretty dense
neighborhood.
But again, it's not air temperature.
So a lot of my research has been how can we connect this satellite information?
How can we connect that to the lived experiences of people on the ground?
So my dissertation use this network of air temperature sensors.
It's a global network, but we use just the sensors in New
England.
36 of them fell within our study area.
So we have this land site Landsat image during a heat wave that was cloud free.
It's incredibly important when using satellite data for heat that you have
cloud free imagery.
Clouds are extremely cool and so any clouds could potentially modify the
surrounding temperatures.
But this area of Massachusetts is actually 80% of all census block groups
in Massachusetts and it contained also 36 air temperature sensors.
So using that we had three days of cloud free imagery that were used to create
this model July 27th 2021, July 22nd, 2022 and September 24th, 2020.
It is hard.
It is.
I spent a lot of my my time looking trying to find cloud free data.
Now that I have when we get to the drone part of this talk,
that's no longer part of my my my daily routine,
but I do spend it's so frustrating.
Haven't clouds or?
Say EJ.
So we talked about the previous study looked at the distribution or the
inequities of of heat across the Northeast.
But in Massachusetts we actually have an environmental justice definition.
It was passed in 2020 as part of the climate change bill.
And so it classifieds environmental justice based on historical inequities
and or vulnerabilities to environmental harm.
So median household income is 1 character of this.
We also have minority population, which is another factor.
So 40% or more of the population being non white.
And then English language isolation.
And you can see here on the map of Salem where those communities are.
And it's important to note that a block group or community could have multiple
characteristics, right?
Multiple factors.
So it could be low income and minority, or it could just be minority,
or it could just have English language isolation.
They don't always necessarily stack up, but so this is what I mean when I'm
talking about the environmental justice side.
And so we combined the Massachusetts layer of environmental justice with our
extreme heat data.
I'm able to create 4 typologies or typical scenarios of extreme heat in
Massachusetts.
So number A, or I keep saying number A, letter A is Chelsea.
Chelsea is defined as just extremely hot everywhere.
There is nowhere in Chelsea during a heat wave that is not experiencing the heat
wave.
And there's also each block group in Chelsea is characterized as an
environmental justice block group.
So incredible overlap.
It's also important to note that Chelsea is surrounded by other cities that have
the same characteristics, So there's nowhere for someone in Chelsea
to go locally to get out of the extreme heat.
For the second typology is Leominster or or B, which is like Gateway city,
like Leominster, Worcester, Salem I would put under this category as
well.
They have an urban core with environmental justice communities,
but they're surrounded by forests or larger amounts of green space,
so they have access to typical temperatures during a heat wave.
Then we have small towns like Webster, which are.
Have very small environmental justice communities,
but also experience extreme heat, even though they're very, very,
very small towns.
It's like 10,000 people.
And then we have typology D, which is large cities like Newton,
which have no environment or few environmental justice communities,
but also experience extreme heat and so, you know, very dense urban environment.
And what we've found is that when you layer on multiple factor environmental
justice factors.
So when you add income alongside minority status,
alongside English language isolation, those are the hottest block groups in the
eastern part of the eastern Massachusetts during a heat wave.
And so that's what this black arrow is showing the red line.
So you can see the general increase as you add multiple types of environmental
justice in multiple categories.
You get hotter block groups.
The red line is the threshold for extreme heat.
It's important to know that almost all environmental justice black groups are
experiencing extreme heat.
So 85% of the EJ communities in our study area had extreme heat and that would be
places like Chelsea and Webster, but 15% of them did not.
And that would be the surrounding communities in Leominster, Worcester,
Salem, that in these gateway cities is where we
found environmental justice block groups that were not having the environmental
burden.
And it's important to note that even the non environmental justice communities in
this box plot over here, there are still a lot of places like
Newton that experience extreme heat, even though they're not classified as
environmental justice.
So that is looking at the severity of extreme heat in specific locations.
But I went to a talk in Boston recently by BU in the School of Public Health and
a program called Be Cool where they actually put air temperature sensors
around the city of Boston.
And this is a study that's looking at the heat wave or heat advisory from August
1st to August 3rd from last summer.
And what they saw is that while Logan Airport had a heat advisory for three
days, places like Austin, Brighton, which is where I've lived in the past,
had a heat advisory for over 2 days before that and two days after.
And then during the actual heat advisory, there was actually heat emergency,
which is when the temperature goes above 95°.
And this was consistent in a lot of the downtown or or more urban parts of the
city.
So we're seeing that in Massachusetts.
But in New England broadly, not only is extreme heat much more spread
out and then we might expect, but we're also seeing that these heat
waves are lasting much longer and that all in companies potential risks for heat
mortality.
So basically taking that, trying to draw a tie a little bow around
all of this is we need to start planning for these communities right now for this
climate future.
We have like a 5 to 10 year window before we start to see large scale changes to
our environment, and our communities that live in very
urbanized neighborhoods are experiencing that future climate right now.
So if we can make those modifications, if we can learn how to adapt our cities
to this extreme heat, we'll have a better shot.
Specifically focusing on vulnerable populations,
black groups with lots of young children, places that have been historically
marginalized and think about how we can support those groups individually,
but also collectively, like how can we support a community
during a heat wave?
And so an example.
And for me, so as as Professor Radner said, I'm,
I'm the tree guy.
I, I like trees a lot.
Trees are kind of how I see my role in, in trying to understand this climate
future and our climate adaptation.
So I'm always thinking, how can tree, what role can trees play, if any,
in some of these very dense urban neighborhoods emitting or adapting to
this climate future?
So I'm going to be talking about Worcester, but an example,
and I'm going to come back to this, is this small patch of vegetation in
Swampscott just on the road.
You can see that some of the this is a thermal drone image.
And you can see in this area that it's been planted with very dense or large
amounts of native plants and the temperatures are 20°C cooler than like
the lawns that or other areas that are just in the sunshine,
but right next door that have not been planted.
So we're seeing tremendous difference in the ways that vegetation is responding to
heat.
So I'm looking at, I'm going to be talking about Worcester
as a case study because Worcester has had a tremendous amount of tree planting and
tree turnover in the past 20 years or 10 years.
These are some of my students in the HERO programme measuring some St.
trees that I'm going to be giving you examples of.
But I wanted you to see what the street trees look like.
They're not fully grown yet.
They're still kind of mid sized, but they're they're much larger than they
were before.
I have this longer relationship with trees.
I would say I was a science teacher in the South Bronx and it was during the
Million Trees NYC planting programme where they were trying to plant 1,000,
000 trees over all New York City.
And so there are some of my students mulching a tree in in our neighborhood
and then that the death of a lot of those trees,
there was not a lot of stewardship or understanding led me to want to study the
tree planting program in Massachusetts, the Green and the Gateway cities.
We often studied these trees when they were really young,
so they've just been planted.
So we would use this 10 foot long pole to measure the tree height.
And then if the tree was taller than 10 feet,
you had to like put the pole in your head and hope you kind of like eyeball it.
So now that the trees are really large, we actually use a psychometer.
So we don't we don't use this method anymore.
They've grown too tall, but spent a lot of time thinking about
tree planting.
And I'm hoping that we can begin to understand the impacts of this tree
planting now that it's been going on for 10 plus years.
But it's important to note that this planting is still happening.
We've had over 60 trees planted by this degree in the Gateway Cities program on
Salem State's campus, with more to come.
So it's really exciting to see how, you know,
this work has LED it kind of snowballs to more tree plants, more tree plants.
And I'm hoping that will continue.
So Worcester is the case study because it was where the Longhorn beetle was
discovered in 2008.
About in 2005 there was a street tree sentence of Worcester and 80% of the
trees were all the same species.
They're all Norway maples.
And the host species for the Longhorn beetle is Acer or or genus, host genus.
So Norway maples were a prime tree.
And so you can see what a typical St.
in Worcester would look like where that had lots of St.
trees with normally maples.
And this is an example of the beetle.
Once the that this beetle was found, the USDA set up a quarantine area really
quickly.
They were worried about the beetle spreading into the Northeast forest.
So Vermont, New Hampshire, Massachusetts and Worcester was actually
referred to many times as the gateway to the Northeast forest,
which I don't think anyone ever thought of it like that,
but we liked it as I live in Worcester, South of Worcester resident.
It was great, but 35, 000 trees were removed almost overnight.
So you would go to work and come home and the federal government would be in your
backyard with a crane airlifting trees off your property.
They did not have to require a permit or anything.
It was a national emergency.
So you can imagine the amount of loss and change in identity that residents
experienced.
They also talked about how they noticed their environment change.
So it got hotter and colder, colder in the winters and hotter in the
summers.
Here's another example of some of that change.
This is in 2009, right before these trees were removed.
And this is the next day into that same year.
But they just came through and took almost every tree on the street that was
not an Evergreen tree.
So huge amounts of change.
This is what this tree, the street looks like now or not now,
but 2023 and I'm going to be showing drone imagery of this same street.
So we'll we're seeing it from from the street level,
but we'll look at it as well from above.
And what residents thought they were experiencing with higher temperatures,
more heat bills was what we were able to measure.
So this is a study out of Clark in two 2013 that measured that the temperature
increased in these neighborhoods with tree loss by 4.3°F.
So quite a lot and you can see in this map below what that looks like.
We have a 2007 image with the full canopy trees and then in 2010 you can see the
amount of tree loss.
But on previous slide there has been tree planting.
And so you these little dots on this slide are the public and private trees
that were planted.
And then here you can see the Landsat imagery showing warming.
And this is AZ score of temperature.
So it's just metric.
Basically, if it's above 0, it's warmer, and if it's below 0, it's cooler.
But you can see it's generally warmer where we saw this tree loss.
But you can't really see the trees, right?
Can be in these pixels, these squares.
You can't really see individual trees, right?
And that's always been kind of the struggle with using Landsat.
It flies over at 10:30 AM and also can't see individual tree.
We can't measure the impacts of tree planting yet.
Maybe over long periods of time, but not at the individual scale.
So instead of using satellite imagery, we've been measuring these trees by hand.
So you can see here a pin oak as part of a repeat survey in 2023.
This is the pin oak in 2016 when we first measured it.
This was, that was the year before I started at
Clark.
So I can't claim credit for that tree.
But then you can see the same tree when we measured it in 2023.
And when we did these surveys, we'd measure the diameter at base height.
So the diameter is the well, it's the diameter of the trunk of the
tree.
So we're not looking at the canopy, it's just the trunk.
And then we also look at the crown canopy width as well as the total height of the
tree, either using the pole or a psychometer.
And then we also looked at a bunch of health metrics.
So that's crown vigor condition and also if the tree is alive or not.
And so that survey was in 2023, which is right before I started at Salem
State.
And I thought, ah, wouldn't it be great?
Once we once I started here, we bought a thermal drone and a multi
spectral drone.
What if we could fly over those same trees and understand, you know, the,
the field metrics, the field survey data, combine it with the drone imagery.
And so I asked my classes always to make methods diagrams.
So it's like it has to show a methods diagram.
So I'll try to go through it pretty quickly.
But we have two drone flights in 2024 in the summer and that was Geo referenced
with NAEP imagery and then clipped and also overlay manually,
which I'll get into more with the tree points from those drone flights,
we could create a land surface temperature map as well as NDBI map,
which I'll explain more.
But NDBI is essentially a health metric using the spectral bands.
And so we're able to get health and temperature in order to isolate the
canopy of specific trees, we use segmentation to find similar
pixels.
So pixels added similar characteristics in visible and, and infrared,
as well as in the thermal.
We classified those pixels, those patches of pixels that were similar.
So they were either trees, grass or impervious surface.
So buildings, roads, anything that wasn't vegetation.
And then that was manually edited.
They, they came out great.
I, I love my little patches of pixels, but they still weren't perfect.
So a lot of these had to be drawn on and and edited manually.
And so using those polygons, those or pixel patches,
we were able to calculate descriptive statistics.
So you know, the mean, the median, the minimum,
the maximum land surface temperature for all these trees and then analyse that
with the species information, with the growth information to understand
what are the important factors for temperature for street trees.
So here's more information about the drone flights as well as this is me with
the thermal drone, my advisor at Clark John,
Professor John Rogan and another former doctoral student who is now a professor
at Auburn and has his own drone program.
So he's been incredibly helpful in kind of advising me.
We have the DJI Maverick 3T and DJI Maverick 3 M and I always said that that
that's a Chinese drone company.
And I always said I wasn't worried about that drone company as long as TikTok
wasn't banned, which is kind of gone up and down
recently, but I think it's still not banned.
So I'm still not worried about our DJI drones.
And we were looking at a small area where we had done the field survey of the
streets.
Excellent.
We had a high precision GPS unit, but just with the amount of trees and
buildings in the area, a lot of the points still ended up in the
middle of the road or slightly near the tree,
so those points had to be adjusted manually.
On top of the drone imagery, we also noticed the shadow.
So I think this is actually tree shadow that's appearing as if it is tree in the
multi spectral image.
But overall, despite in remote sensing we always have
the I try to just be transparent about issues with the data before I show you
any of the results.
But we 64 trees were in the study area with 12 different species.
And so we were able to calculate NDVINDVI is a health metric.
As I said before, it relies on the near infrared band,
so just beyond the visible spectrum and plants and specifically chlorophyll and
leaves reflects really highly, 50% in the near infrared,
whereas a healthy tree will actually absorb all the red wavelength.
So that's why trees don't usually look red, they look green.
So there's not, they're not reflecting red light.
And so this ratio, if it's really large, is a sign of a healthy tree.
So NDVI is a value from 1 to -1 whereas if the tree turns brown or gets those
pretty red leaves in the fall, starts reflecting more red light,
and we see that that value of NDVI drops a lot.
So it's a good sign or a metric for tree stress.
And this is a map of where our trees are as well as with NDVI.
And this is just a zoom in.
So here you can see the tree canopies that we measured are the ones in with
yellow boundaries.
And you can see what the NDVI kind of looks like compared to the road or
compared to grass.
It does seem to be a little bit of a darker green.
And then this is our land surface temperature data.
So this is imagery that was taken at noon, so no shade or, you know, mostly at nadir.
So the the sun is almost directly overhead.
You can see what the tree canopy polygons or my my patches,
my pixel patches look like.
And then also the thermal.
What really jumps out here is you know how hot the roofs are.
It's I, we didn't have too many solar panels on
roofs, but there is one down here.
They actually cool the roof quite a lot.
So that, that'd be another interesting study of
just like the cooling properties of, of having solar on your house.
But more noticeably for me at least, is the cool,
the cool patches where we have trees.
So those are some of the coolest areas in the site.
And this is land surface temperature, not air temperature.
So it was not 75°C that day.
Important to know.
So our research questions where well are these larger shade trees?
Are they actually cooling more than small ornamental trees?
And so here are all the different species we have and or genus.
If we didn't have high confidence and identifying the species,
we would just stick with the genus.
And so you can see that the majority of the species St.
trees are shade trees.
They're all quite large.
This is their average heat height and feet.
And then you can see what the small trees height is, cherry being the largest,
but they're pretty different in terms of the growth.
So are these shade trees?
Are they cooler than the the smaller trees, ornamental trees?
And then also what variables, what metrics are important for predicting
temperature?
So we wanted to choose a temperature variable.
We had minimum temperature, median temperature, median temperature,
could have used Max temperature, but I wanted to use just see what these
look like typically.
And what we see here is that the minimum temperature,
it does look like the pin oak, which is the largest tree is slightly
cooler than you know, for example, the Dogwood or the apple or the Japanese
lilac cherries are interesting in that they are, they do seem to be a lot cooler,
but we just saw much more variation with the media and LST.
So going forward, I'm just going to be sticking with
minimum land surface temperature within that patch of pixels just to kind of
drive home show some other metrics related to species kind of biology
audience we have looking at NDVI for different species was really interesting.
Specifically the Max NDVI seems to be much higher for the shade trees.
So the shade trees do seem to be healthier than the OR less stressed than
the small ornamental trees, which is fascinating,
except for the calorie pair.
I don't know how many of you are familiar with calorie pears, but they're the worst.
When I was practicing this with my parents, my my mother was like,
is that the grocery?
And then my wife was like, is that the one that smells like fish?
So yes.
And yes.
These trees are notorious in urban forestry for being kind of like a
Frankenstein tree.
They were designed to not be able to breed,
but then additional cultivars were introduced and now we have them kind of
spreading like wildfire throughout in the US.
So they're incredibly invasive and illegal to plant in many states now.
And I was surprised, but I was interested, but not surprised to see that they also
the lowest NDVI of all these trade trees.
So the calorie pair is just the worst tree.
No other way but but so that was the first question we're thinking about like
what is the size?
How does the size impact?
It didn't seem like there was a big trend there but wanted to understand what are
the important variables for minimum temperature predicting minimum
temperature.
So we use machine learning model called random forest and this basically
organises variables from most important to least important if based on like the
amount of error or the change in a prediction error if you remove one of the
variables from the model.
So you can see that NDBI Max is and height growth and DBH growth are all
clearly more important than the other variables here.
So taking that information made a multi linear model, multivariate model,
linear model and you'll notice immediately that the R-squared is is
extremely low.
So we only had . 22 or it only explains about 22% of the
variation.
So that aside, Max NDVI did seem to be the most
important.
It was significant and they all were negative relationships,
but so basically an increase in NDVI of of .
1 will actually decrease the land surface temperature by 1°C.
You can see what the scatter plots look like with the individual R squares in
blue, but none of these were very strong
relationships.
I did think it was really interesting that DBH growth,
so the diameter of the trunk is more important than the height of the tree for
temperature, which is a little unexpected.
I would be interested to talk to some more biology minded people about what
role the trunk might play in, in the tree functions.
And potentially that along with seeing NDVI being so important might mean that
like healthier trees have more trunk growth.
I, I, I don't know so, but I'm interested to ask to have those
discussions.
So some issues with this analysis, we just need more samples.
It was kind of exploratory to see what this relationship would look like.
This is the mean DBH growth by species.
And you can see that cherries are actually have some of the largest DBH,
which was quite DBH growth, which was quite interesting because you
remember cherries were also very cool in the minimum temperature.
So cherries are an interesting genus there,
but pin oak largest tree height as well as DBH growth.
So in interest in terms of like which species we might want to plant on street
trees, I'm excited to look at this again, but with more diurnal variation.
So what does this relationship stack up if we fly the drone at 3:00 PM at 7:00 PM
in the morning, this was a drone flight at noon.
But are there potentially different times of the day that we'll see a stronger
relationship and then also look at get more temperature variations?
So the temperature of this day was 82°, but what if it was an extreme heat day,
like 95°?
Would we actually see a much clearer signal?
Would certain trees do better or worse species in those conditions?
And so there's interesting recommendations that can come out of this.
Shouts to our staff from the JS class for modelling how to measure ADBH of a tree
in the JS class.
We always do some tree surveying in that class,
but you can see it's incredibly straightforward for volunteers to measure
DBH.
It's, it's very accessible.
Anyone can get up close to a tree like that.
And so the fact that DBH growth is really important is great for urban forestry.
I think it it's much easier to do that than height.
Our takeaways were that species are not uniform in their impact,
so it does matter what species we plant in cities in terms of their land surface
temperature impact and that NDVI is an interest,
like a metric that could be predictive for cooling.
I think another take away was that two of the most important factor or variables
were growth metrics.
So it speaks to the importance of having repeat studies or repeat surveys.
So if we just surveyed once, we wouldn't have been able to capture the
amount of growth in height and DBH.
So now I'm going to pivot to applying these lessons to Milwaukee Forest.
And I'm running a little low on time, so I'll try to speed up a bit.
But this is a Swampscott Milwaukee Forest you saw earlier.
This is a true color composite or photo of it.
It's that little patch of green right there.
And basically the idea here is that individual trees just don't aren't large
enough or not dense enough.
They can't have the same amount of impact as a patch of trees.
So what could the potential impact of a patch of vegetation be?
And then also what does vegetation quality do?
So if it's just invasive species or kind of a random mix of, of composition of,
of plants versus chosen native capstone community.
So could those potentially lead to cooler surfaces?
So this is a Milwaukee forest in Danahy Park in Cambridge.
These Milwaukee forests are micro forests.
They're composed of native capstone communities of species,
very densely planted.
So there's over 1400 plants within this small circle.
They encourage rapid growth.
So the trees here have grown over 20 feet in four years,
and they provide a lot of ecological benefits to biodiversity benefits.
So what's the cooling potential of these patches?
We flew 3 flights here, thermal imagery in the morning at 3:00 PM
and at 7:00 PM.
And we looked at the micro forest and the surrounding vegetation.
And the two students who worked on this project in the fall in the drone
application class are pictured there with their drone selfies.
And I have their permission to share their final report.
There's a 2 minute video but it'll explain their work and more information
and footage of the Milwaukee forest.
The Danity Park Microphones is planted in autumn of 2021 through a collaboration
with the City of Cambridge and the non profit organization Biodiversity For the
full time forest covers 4310 square feet in those 1400 trees and shrouds from 32
main species.
2 years following the initial finding the survival rate was 95%.
Three largest trees average out at 5. 3 meters tall.
Milwaukee forests and similar ones like David are carefully designed.
After the traditional forest.
Priority, especially in communities where they have
been historically marginalized and are vulnerable to extreme heat.
You know, right now we're kind of removing a lot of
the scientific supports, the data that a lot of the data that I've
shown you is being taken off of websites or no longer publicly available.
But I do think that, you know, just because we don't have the maps to
show it or we might not be recording future measurements,
it doesn't mean that it's not hot in these neighborhoods, right?
That the underlying reality is not the same.
And whether we want to plan for it or whether we want to take action on it does
still rely.
It's something that we can still choose to do regardless of if, you know,
NOAA produces it or not.
But I also think this is a moment that as scientists,
we can kind of think about our data sources.
Obviously, I've shown these maps of where it's hot,
where it's not.
But if you go to the communities, people who live in these neighborhoods,
they'll tell you it's really hot in the summer, right?
So increasing the types of knowledge that we use, the lived experiences,
I think will allow us to tell a better narrative around extreme heat and climate
adaptations.
This is a Milwaukee forest that's being planted in Worcester that I'm extremely
hopeful about.
It's planted where a parking lot used to be.
So the changes in temperature will be even more extreme.
And this is one of three forests that are planted in environmental justice
communities.
So this is downtown Worcester.
There's another one in the Housing Authority,
and then there's another one in Cambridge right next to the Housing Authority.
So these are potential solutions because they're so small,
they can go almost anywhere.
So with that, thank you.
Big thanks to the students that helped, you know, the drone class,
the jazz class and a lot of the master students and 942 had to look at a lot of
joint imageries.
Thank you a lot.
Yeah.
So the the question was why do the Milwaukee forest or the micro forest grow
so much faster than typical forest?
So it has to do with the ecological composition of the the species they plant.
But essentially they're planting capstone communities.
So in a typical forest, it might take 3 or 400 years for the most
dominant tree species to establish themselves.
So like large oaks or the the tallest trees as well.
But what the micro force does, it tries to turbocharge that process,
planting the capstone community right away.
And then they almost like compete with each other in such a way that it spurs
growth.
So really it's ecological knowledge that's being applied to create tree
growth.
And I will say I've looked at St.
Trees 10 years apart, and they haven't grown at all.
They were like, the same size of the planting.
So it does seem to be like the composition of the vegetation around a
tree can impact how well it does.
Anecdotally.
Yeah, we can.
Oh, yeah.
I don't know who's doing.
Oh, yeah, we got OK.
Yeah.
Awesome St.
trees.
They are the pin oak and the red oak.
So I think they they do really well.
They provide a lot of ecosystem services and they're I've heard them described as
like the northeast version of coral reefs, which makes them sound a lot cooler,
right, because they're they're host to a lot of
the ecosystem or the the base level.
So I would recommend oak trees.
My personal preference is the white oak.
I like the rounded leaves, but that's more of an aesthetic thing,
you know, question number.
I worked for a new base and this is for our New Bedford and I guess my question
was just like a lot of.
Big.
It wasn't supposed to be this big.
So there's a certain amount of like understanding of like what the tree will
look like in the future as well.
But yeah, Bob, sorry about the channels of that QR code,
but still waiting.
Take a QR code.
Take a photo.
Doctor Gerard, you have something to give you an apology.
Thank you.
Should I?
No, it's fine.
And if there's no further questions, I'll pass it back to Doctor Randy about
it.
But we're all around pizza.
I can.