Coder Social home page Coder Social logo

Comments (4)

jreiberkyle avatar jreiberkyle commented on June 4, 2024

To compare apples to apples, I suggest comparing TOA to TOA. For that, you can look at the 'analytic' asset_type. Do the resulting NDVI's match up?

from notebooks.

craigdsouza avatar craigdsouza commented on June 4, 2024

so i looked at TOA(reflectance & radiance) instead , the discrepancy is still there, but in this case NDVI is being underestimated vis-a-vis Sentinel. I'm attaching histograms and thumbnail images for reference.

While I understand the histograms for the two images won't match exactly, what I don't get is why NDVI over built up land and even river water is being overestimated to such a large degree upto values of 0.1-0.2 which is definitely unexpected.
However note, the raw radiance image does show expected values over built up areas but here the histogram is skewed far left of the Sentinel histogram. Besides S2 is a reflectance image, not radiance so the two aren't comparable.

1. TOA Planet Scope Reflectance Image 2nd Oct 2018

toa_reflectance-ndvi-histogram
toa-reflectance-ndvi

2. TOA Planet Scope Radiance Image 2nd Oct 2018

toa-radiance-ndvi-histogram
toa-radiance-ndvi-fig

3. TOA Sentinel 2 Image 29 Sep 2018

s2-ndvi-hist
s2-ndvi-fig

3. SR Planet Scope Image 2nd Oct 2018

sr-ndvi-histogram
sr-ndvi-fig

from notebooks.

craigdsouza avatar craigdsouza commented on June 4, 2024

Hey,
any thoughts here?

Best
Craig

from notebooks.

jreiberkyle avatar jreiberkyle commented on June 4, 2024

Hey Craig,

Sorry for the delay over the holidays. So first of all, what comes into mind is the fact that NDVI indices are really best used for comparison within a sensor type. This is primarily because the spectral bands differ between sensors (e.g. the 'red' band is actually measuring different wavelengths). This is true for Landsat, Sentinel, and most sensors. Within a sensor 'family', such as Landsat, the design is such that those differences are minimized as much as possible. Planetscope sensors have a different spectral response than Sentinel, so I would expect NDVI to be different regardless of the target (water, vegetation, built-up areas). It is possible to minimize these differences by 'calibrating' the NDVI values using known targets, but that requires care to avoid introducing errors.

A good starting point is the description of the spectral response of the PlanetScope sensors, given here (click the link to Download Full Specs).

from notebooks.

Related Issues (20)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.