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I am working at scientific paper about measuring object's size (it's area) using satellite images. I got some progress in it and need to compare my results with other scientific works. I have found some papers in russian scientific journals but can't find such papers in english.

Have you seen scientific papers about size (area) measurement error using satellite images?

Here is a picture of what happens when trying to measure some object's area using satellite images:

Area measure error using satellite images

  • What software are you using? – Corey Pembleton Dec 8 '15 at 4:55
  • Well I use ArcGIS. But my question is about scientific papers, regardless of any software. So I don't need a step by step guide "How to determine area measurement error". – Mr. Che Dec 8 '15 at 4:57
  • @Mr.Chem Russian publications are wrong? Not so trendy? – FelixIP Dec 8 '15 at 6:44
  • @FelixIP In my opinion, that problem is very common. I am very surprised that i can't find a paper in english about area measurement error, they must exist for sure. Maybe someone has seen similar works in scientific journals. – Mr. Che Dec 8 '15 at 7:01
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There are two components in your case that need to be taken into account.

First, based on your figure, there is a rasterizing error, i.e. representing a polygon with pixels. You can find several papers in English if you look for this issue. See for example this paper. It will be the dominant source of error in your illustrated case.

Second, using a binary classifier on a satellite image for the detection of small objects will not necessarily yield the correct results. For objects smaller than the pixels, you must take into account the Point Spread Function, the contrast between foreground and background, the parallax shift (with 3D objects) and the impact of thematic classification errors.

  • The rasterizing error is due to a process of "quantization". – Paulo Raposo Dec 8 '15 at 8:24
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I am more a cartographer than an image analyst, but I think most scientific references you'll find on this topic will be in text books or reference material, since this problem reduces more or less to counting pixels (along with attendant issues such as how much of a pixel is covered in order to classify the pixel as the object, which is directly related to the point-spread function of the sensor, as @randouxju has mentioned).

See, for example:

http://www.r-s-c-c.org/node/81

Köhl, M., Magnussen, S. S., & Marchetti, M. (2006). Sampling Methods, Remote Sensing and GIS Multiresource Forest Inventory. Springer Science & Business Media. --see pg 22.

Much of this is essentially a sampling problem, so literature on the Nyquist-Shannon Sampling Theorem (aka the Sampling Theorem, Nyquist Sampling Theorem, etc.) will be relevant. One such paper in cartography:

Tobler, W. R. (1988). Resolution, resampling, and all that. In H. Mounsey & R. F. Tomlinson (Eds.), Building Databases for Global Science: the proceedings of the first meeting of the International Geographical Union Global Database Planning Project (pp. 129–137). Hampshire, U.K.: Taylor and Francis.

There is nothing wrong with citing Russian (or any foreign-language) sources in English papers, by the way!

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