Comments on: Image Classification Techniques in Remote Sensing [Infographic]

By: Ahmed Ghodieh

Ahmed Ghodieh — Mon, 22 Jul 2024 09:48:55 +0000

Very useful material. Many thanks

By: Consolatha S Nicholaus

Consolatha S Nicholaus — Tue, 05 Mar 2024 12:55:06 +0000

Thank you. So wonderful.

By: Bartholomew Etuk

Bartholomew Etuk — Tue, 19 Apr 2022 06:43:36 +0000

Well written. Thanks a lot.

By: Ashiq

Ashiq — Sun, 10 Apr 2022 20:43:34 +0000

Very useful materials. I am currently working on Object-Based Classification through recognition software.

By: Namuli Bena

Namuli Bena — Wed, 06 Apr 2022 14:00:03 +0000

Very useful indeed. Thanks a lot

By: Irshad S shaikh

Irshad S shaikh — Mon, 27 Sep 2021 21:50:06 +0000

Thanks a lot very informative details are given

By: Zintle Langa

Zintle Langa — Wed, 17 Feb 2021 08:40:09 +0000

Thank you for this articles, it is very helpful.

By: Bapitha

Bapitha — Thu, 21 May 2020 19:05:28 +0000

Keep up your great work. Well articulated and extremely useful and understandable. Thank you

By: Pablo Arcadio Flores

Pablo Arcadio Flores — Mon, 03 Dec 2018 18:41:16 +0000

Thanks for this article. It is quite helpful. I have one question:
Don’t you think there only two classification ways? Supervised and non-supervised (and ok maybe semi-supervised…) And then both of them can work pixel-based or segment-based? And inside the segment-case we could find at the highest level the object-based? I say this because I have been working for example in a non supervised approach object-based. And this doesn’t fix much in the classification as it is presented in this article. Thanks. Pablo

By: GISGeography

GISGeography — Sat, 02 Dec 2017 15:50:55 +0000

In reply to Ernestina.

Here’s a visual on the reflectance for NIR and red – but not a reflectance curve. https://gisgeography.com/ndvi-normalized-difference-vegetation-index/