> CHMv2 is derived from single-date imagery, where the acquisition process selects the best available image within a target period (2017 -2020). This limits the direct use of the released CHMv2 data for attributing
canopy height to a specified year of interest. To support change applications, we provide the image acquisition date associated
with each prediction in the dataset metadata.
So generally a few years out of date, but the dataset is transparent about when each image was taken.
> We additionally release a global GeoTIFF of input image acquisition date, where pixel values encode year minus 2000 (e.g., 18.25 indicates April 2018)
That being said, I am sceptical on how accurate mono-depth models can be on a single tree basis. I would probably trust them to do large scale biomass estimates, but probably not single tree height assessments.
From the paper:
> CHMv2 is derived from single-date imagery, where the acquisition process selects the best available image within a target period (2017 -2020). This limits the direct use of the released CHMv2 data for attributing canopy height to a specified year of interest. To support change applications, we provide the image acquisition date associated with each prediction in the dataset metadata.
So generally a few years out of date, but the dataset is transparent about when each image was taken.
This is an important question.
The tree outside of house is not 9 feet tall per. I have a 2 story house and it easily towers 10 feet higher than my house.
Additionally, there are several Royal Palms that are close to 50ft and they show as being only 15 feet.
You could look it up in the metadata file:
> We additionally release a global GeoTIFF of input image acquisition date, where pixel values encode year minus 2000 (e.g., 18.25 indicates April 2018)
That being said, I am sceptical on how accurate mono-depth models can be on a single tree basis. I would probably trust them to do large scale biomass estimates, but probably not single tree height assessments.