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Measurement of Erosion in Agricultural Fields Using Monoscopic Photogrammetry (2963)

Shlomo Abergel, Sagi Filin and Naftali Goldshleger (Israel)
Dr. Sagi Filin
Senior Lecturer
Technion - Israel Institute of Technology
Rabin Bldg., Technion City
Haifa
32000
Israel
 
Corresponding author Dr. Sagi Filin (email: filin[at]technion.ac.il, tel.: +972 4 829-5855)
 

[ abstract ] [ paper ] [ handouts ]

Published on the web 2008-03-21
Received 2008-01-31 / Accepted 2008-03-14
This paper is one of selection of papers published for the FIG Working Week 2008 in Stockholm, Sweden and has undergone the FIG Peer Review Process.

FIG Working Week 2008
ISBN 978-87-90907-67-9 ISSN 2307-4086
http://www.fig.net/resources/proceedings/fig_proceedings/fig2008/index.htm

Abstract

Erosion in agricultural fields damages cultivated land that consequently causes agricultural and economic damage. Therefore, monitoring changes in the amount of soil erosion is important for agricultural planning as well as for planning the use of different soil conservation systems. This paper describes a terrestrial photogrammetry model for measuring erosion amounts and estimating the change in volume of raised beds, resulting from irrigation or rainstorms in cultivated fields. The example is taken from ridged and furrowed fields on sandy to loam soils (Typic Rhodoxeralfs) in the coastal plain of Israel. The paper presents a method for estimating the amount of erosion. Unlike existing methods that are labor intensive and error prone, the approach described here enables a high-level of automation and accuracy while making use of low-cost consumer cameras. Emphasis is placed on parameters for robustness of the model and on linear methods that do not require approximate parameters for the photogrammetric solution, thus enabling using consumer cameras. Experiments show that accurate results can be achieved in estimating volume and erosion.
 
Keywords: Geoinformation/GI; Remote sensing; Photogrammetry; Soil erosion, Photogrammetry, Homography, Agriculture, Gabor filters

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