Applying remote sensing to fish welfare is a neat idea! I’ve got a few thoughts.
I’m surprised that temperature had no/low correlation with the remote sensing data. My understanding is that using infrared radiation to measure water surface temperature was quite robust. The skin depth of these techniques are quite small, e.g., measuring the temperature in the top 10 μm. Do you have a sense of the temperature profile with respect to depth for these ponds? Perhaps you were measuring the temperature below the surface, and the surface temperature as predicted by the satellite was different. Then again, you might expect some systematic error here giving you some kind of correlation anyway.
The methodology used by Captain Fresh is a black box as you say, but maybe you could ask for more detail. When I was working for an exploration company, specialist contractors who gave us data were usually eager to give us presentations on the minutia of the data and methodology and answer our questions because they wanted our future business.
Do you know what water depth your on-site measurements were taken at? Ensuring that this was consistent seems important, and it’s important to remember the depth of penetration of the remote sensing data. If you could ask Captain Fresh for this, that would be ideal, but it’s typically quite small/shallow. I’m less familiar with best practice for data collection, e.g., how important is it to collect on-site data from as close as possible to the surface, but these might be important considerations. Did Captain Fresh or ProDigital give any guidance for this? (I didn’t see anything from a brief skim of the user manual)
You might also want to consider doing more detailed on-site measurements at a few sites to see how well each water property at depth x correlates to depth y. If the remote sensing data gives you good predictions of the properties at the surface but the properties vary greatly at depth, it’s probably not a very useful prediction, unless they vary in a systematic or predictable way.
This study was able to predict pH levels in lakes using Landsat data with an R2 of 0.81, but the lakes were quite large, on the scale of several km wide. I intuitively but weakly suspect that this method would be less effective for small farmed fish ponds.
I’m surprised to see salinity missing from this list. Predicting water salinity with remote sensing also seems to be quite robust, and it seems to be quite important for monitoringfish welfare. Was this omitted just due to limitations of the Captain Fresh data? Your ProDigtal seems to be capable of measuring water salinity on-site.
Happy to chat about this some more if any of this was helpful. It’s been quite a while since I actually did any remote sensing myself, but I’ve relied on remote sensing data for other work from time to time.
Thanks for taking the time to look at the report and respond with your thoughts. We very much appreciate it!
Specific to temperature, we do not know how our partner extracted data from images to determine temperature (or any parameter). We have already followed up with them to get more specific information about what exactly they did.
Regarding the depth of measurements, our “ground truthed” data were collected at a depth of approximately 0.5-1m. The sensor of the handheld device—which collected data for all parameters except for ammonia—was submerged just below the water surface. For ammonia, a sample of water was collected from the same site at approximately the same depth. This aspect of the study protocol was designed to match the procedures conducted by the ARA.
No problem! I think my main concern is just that you make sure the water properties at 0.5-1m depth match the water properties at the surface, or at least, you can work out how they vary to apply corrections to the satellite data. But overall I’m positive about this venture.
Applying remote sensing to fish welfare is a neat idea! I’ve got a few thoughts.
I’m surprised that temperature had no/low correlation with the remote sensing data. My understanding is that using infrared radiation to measure water surface temperature was quite robust. The skin depth of these techniques are quite small, e.g., measuring the temperature in the top 10 μm. Do you have a sense of the temperature profile with respect to depth for these ponds? Perhaps you were measuring the temperature below the surface, and the surface temperature as predicted by the satellite was different. Then again, you might expect some systematic error here giving you some kind of correlation anyway.
The methodology used by Captain Fresh is a black box as you say, but maybe you could ask for more detail. When I was working for an exploration company, specialist contractors who gave us data were usually eager to give us presentations on the minutia of the data and methodology and answer our questions because they wanted our future business.
Do you know what water depth your on-site measurements were taken at? Ensuring that this was consistent seems important, and it’s important to remember the depth of penetration of the remote sensing data. If you could ask Captain Fresh for this, that would be ideal, but it’s typically quite small/shallow. I’m less familiar with best practice for data collection, e.g., how important is it to collect on-site data from as close as possible to the surface, but these might be important considerations. Did Captain Fresh or ProDigital give any guidance for this? (I didn’t see anything from a brief skim of the user manual)
You might also want to consider doing more detailed on-site measurements at a few sites to see how well each water property at depth x correlates to depth y. If the remote sensing data gives you good predictions of the properties at the surface but the properties vary greatly at depth, it’s probably not a very useful prediction, unless they vary in a systematic or predictable way.
This study was able to predict pH levels in lakes using Landsat data with an R2 of 0.81, but the lakes were quite large, on the scale of several km wide. I intuitively but weakly suspect that this method would be less effective for small farmed fish ponds.
I’m surprised to see salinity missing from this list. Predicting water salinity with remote sensing also seems to be quite robust, and it seems to be quite important for monitoring fish welfare. Was this omitted just due to limitations of the Captain Fresh data? Your ProDigtal seems to be capable of measuring water salinity on-site.
Happy to chat about this some more if any of this was helpful. It’s been quite a while since I actually did any remote sensing myself, but I’ve relied on remote sensing data for other work from time to time.
Thanks for taking the time to look at the report and respond with your thoughts. We very much appreciate it!
Specific to temperature, we do not know how our partner extracted data from images to determine temperature (or any parameter). We have already followed up with them to get more specific information about what exactly they did.
Regarding the depth of measurements, our “ground truthed” data were collected at a depth of approximately 0.5-1m. The sensor of the handheld device—which collected data for all parameters except for ammonia—was submerged just below the water surface. For ammonia, a sample of water was collected from the same site at approximately the same depth. This aspect of the study protocol was designed to match the procedures conducted by the ARA.
No problem! I think my main concern is just that you make sure the water properties at 0.5-1m depth match the water properties at the surface, or at least, you can work out how they vary to apply corrections to the satellite data. But overall I’m positive about this venture.