Probability of cloud-free observation conditions across Great Britain estimated using MODIS cloud mask

Armitage, RP; Alberto Ramirez, F; Mark Danson, F; Ogunbadewa, EY

Abstract

Image objects obtained by segmentation usually provide a much more reliable
representation of real world objects than individual pixels. However, in regions
with high quality spatial information, image analysis should focus on objects of
interest rather than artificial image objects. A simple method for applying this
object-oriented approach consists of converting existing vector geographic infor-
mation system (GIS) data into raster objects. A problem with this method is that it
may produce image objects with saw-toothed edges which barely match measured
objects boundaries. In order to address such a problem, a method for adjusting
boundaries of image objects is proposed. The new method uses a vector square
grid for pixel representation. Vector-based image objects exhibit boundaries which
better reproduce the shape and appearance of GIS objects. The proposed approach
was applied to extract geometric and biophysical properties of agricultural plots
from remotely sensed imagery. Results suggest that vector-based image objects
provide much more accurate values than raster-based image objects.

Citation

Armitage, R., Alberto Ramirez, F., Mark Danson, F., & Ogunbadewa, E. (2013). Probability of cloud-free observation conditions across Great Britain estimated using MODIS cloud mask. Remote Sensing Letters, 4(5), 427-435. https://doi.org/10.1080/2150704X.2012.744486

• Journal Article Type: Article
• Publication Date: Jan 1, 2013
• Deposit Date: Sep 11, 2014
• Journal: Remote Sensing Letters
• Print ISSN: 2150-704X
• Publisher: Taylor and Francis
• Volume: 4
• Issue: 5
• Pages: 427-435
• DOI: https://doi.org/10.1080/2150704X.2012.744486
• Publisher URL: http://dx.doi.org/10.1080/2150704X.2012.744486