Hooray for GIS! It's truly amazing that in this day and age, this quality of data, and the computing power to crunch it, is available to the average user sitting on their couch with a laptop.
Some things I'd like to see:
1. I've generally seen heat islands referring to not so much getting hotter on a hot day, but staying warmer on a cold day, or at night -- this is one reason why cities get rain when the suburbs get snow, especially in the mid-Atlantic. Would like to test whether trees impact that.
2. I'm concerned from a statistical perspective that trees vs. no trees could be strongly correlated with other variables that might be more causative, like building type and density. Would like to see a paired comparison of areas in the city that are otherwise very similar, with the only difference being more vs. less trees.
Not complaining at all; the author is laying out the tools. Time for me or someone else to pick them up and investigate further ...
> I'm concerned from a statistical perspective that trees vs. no trees could be strongly correlated with other variables that might be more causative, like building type and density.
Wasn't that why he mentioned using the tree request program, to provide controls?
I'm a little confused. The image that's captioned "Land surface temperature, Philadelphia" (top label: "Landsat 8 derived land temperature") is that estimated or measured? Because it sounds like the hot spots were detected by taking a satellite image and looking for places that "looked" hot, but then it's presented like those places really were hotter?
A little later, he says the black warehouses were located under the really hot spots. But weren't the really hot spots determined by finding all the black spots in the image?
> Our calibration team has found that with current processing these surface brightness temperatures are accurate to within ~±1 K for many 15 – 35° C targets, e.g., growing season vegetated targets.
Wow, I would have never expected that!
Dump European question: ±1 K is the same as ±1° C, right?
> Dump European question: ±1 K is the same as ±1° C, right?
Yes the intervals are identical, the only difference is the scale's starting point. In fact although that's discouraged papers often use Celsius absolutes and Kelvin intervals, as is the case here.
The temperature was almost certainly determined by fitting the spectral data to the black body radiator equation, the reason that red-hot metal glows red. Basically, objects emit light when they are warm, and the hotter they are, the higher the energy of their emissions (more blue). At normal Earth temperatures, these emissions will be in the infrared, not visible. Remember, the Landsat data includes not just visible data, but also registered images at a bunch of other wavelengths (near and far IR, at least). The actual color of the object is not really relevant.
According to this data, I don't want to live in such cities. I get that for some people those pools of houses and people in a small area are nice, but for me, in the information age, it doesn't make much sense anymore to live in a crowded area with all the amplified problems people have when stacked on top of each other.
But at the same time, rural and suburban living have their own problems. You lose economies of scale when it comes to rolling out new technology (fiber, cable, etc). Residents have to drive more. Transportation of goods/services costs more. Some jobs (services) require you to be on-site - straight up software development is one of a few that doesn't require any live face-time (but even that goes away as soon as you move into executive management or sales).
The real answer seems to be somewhere in the middle. Well-planned urban areas should be able to mitigate much of the heat island effect. And if the suburbs are reigned in (and replaced with a more natural environment, with more plant-life, etc), we should see some benefits in the overall environment.
Forests create their own microclimate that stabilises temperatures during the day and night - meaning it doesn't cool down as quickly as an open field. So I would expect trees to also make a city more pleasant during nighttime.
Some things I'd like to see: 1. I've generally seen heat islands referring to not so much getting hotter on a hot day, but staying warmer on a cold day, or at night -- this is one reason why cities get rain when the suburbs get snow, especially in the mid-Atlantic. Would like to test whether trees impact that.
2. I'm concerned from a statistical perspective that trees vs. no trees could be strongly correlated with other variables that might be more causative, like building type and density. Would like to see a paired comparison of areas in the city that are otherwise very similar, with the only difference being more vs. less trees.
Not complaining at all; the author is laying out the tools. Time for me or someone else to pick them up and investigate further ...