James001
Joined 10 years ago
Joined 10 years ago
My claim that increased CO2 leads to more biodiversity is more tenuous but is more likely than a decrease in biodiversity, all other factors being controlled for.
You're going to extrapolate from lower nitrogen levels in plants in higher CO2 conditions (without a citation, might i add) to higher CO2 levels causing overall lower nutrition? and more aggressive soil depletion? Keep in mind that obviously more plant growth means more plant decay which cycles back int othe ecosystem.
Are you trying to suggest that we should be decreasing agricultural yields so as to prevent soil depletion? There are better ways.
For example, in Canada those fires were huge because of too-efficient fire suppression methods. Not enough controlled fires were done in that area and Fort Mcmurray expanded beyond its Fire Protection zone.
Not every weather-related catastrophe is caused by global warming, that just harms the credibiltiy of that argument
I was wondering when image recognition was going to play a stronger role in the use of drones for agriculture. When I was doing it, it was simply using combinations of spectral bands and not really delving into pattern recognition. Sounds like that's the right way to be headed. Obviously just at the beginnings of it and I appreciate that you know the current limitations of the technology. But still, that's impressive.
Also curious if you are using satellite imagery in any contextual way or to train your image recognition in any way? Or if you are using the lIDAR already available at all? I imagine you are collecting higher-resolution LIDAR when you fly over?
Anyway, good luck with this, sounds like you guys are doing it right.
I'm curious what the custom-built sensors for specific diseases are? Are you using hyperspectral cameras? I know there was a lot of research into spectral fingerprints of specific diseases.
Also, in regards to the data from the end of season, where you monitor the quality of the crops coming out of the ground. How do you think that assists agricutlrual decision-making? E.g. are you able to predict the quality of the grain and that, in some way, makes it easier to manage?
Again, thanks for answering my questions
Back then, we were just beginning to see the possibilities. Of course we'd do drainage mapping, NDVI maps (as a yield-correlate), we found success mapping field trials and monitoring field trials.
There were alot of possiblities we could've gotten into, but we found it hard to totally commercialize. For example, trying to map chlorophyll content, or water content. Water content was an easier sell, but I got the feeling that drone-assisted precision agriculture was very much still in its infancy at that point, more hype than substance. I am wondering what you think now? What are you actually using your drones for, commercially, but with specific regards to the actual agriculture decision-making.
Thanks eh.
While it is important to consult and listen to doctors, I do think people trust their doctors too much. People should always field second opinions, especially before major interventions. Also, people shouldn't discount their own understandings of their condition.
But seriously, up in Canada I feel like we have a 3rd world medical system for dealing with chronic health conditions. For acute medical conditions, we're amongst the best in the world. But if it's chronic? Or if we cannot diagnose it? Good f'n luck, my friend.
I just really don't agree with your interpretation, but to each their own. Great show all around.