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Sensors 2017, 17(6), 1241; doi:10.3390/s17061241

Using Color, Texture and Object-Based Image Analysis of Multi-Temporal Camera Data to Monitor Soil Aggregate Breakdown

Department of Earth Systems Analysis, Faculty of Geo-Information Science and Earth Observation, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
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Academic Editor: Lammert Kooistra
Received: 23 March 2017 / Revised: 18 May 2017 / Accepted: 25 May 2017 / Published: 30 May 2017
(This article belongs to the Special Issue Precision Agriculture and Remote Sensing Data Fusion)
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Abstract

Remote sensing has shown its potential to assess soil properties and is a fast and non-destructive method for monitoring soil surface changes. In this paper, we monitor soil aggregate breakdown under natural conditions. From November 2014 to February 2015, images and weather data were collected on a daily basis from five soils susceptible to detachment (Silty Loam with various organic matter content, Loam and Sandy Loam). Three techniques that vary in image processing complexity and user interaction were tested for the ability of monitoring aggregate breakdown. Considering that the soil surface roughness causes shadow cast, the blue/red band ratio is utilized to observe the soil aggregate changes. Dealing with images with high spatial resolution, image texture entropy, which reflects the process of soil aggregate breakdown, is used. In addition, the Huang thresholding technique, which allows estimation of the image area occupied by soil aggregate, is performed. Our results show that all three techniques indicate soil aggregate breakdown over time. The shadow ratio shows a gradual change over time with no details related to weather conditions. Both the entropy and the Huang thresholding technique show variations of soil aggregate breakdown responding to weather conditions. Using data obtained with a regular camera, we found that freezing–thawing cycles are the cause of soil aggregate breakdown. View Full-Text
Keywords: soil aggregate; Huang technique; entropy; multi-temporal; proximal sensing; freezing–thawing; rainfall soil aggregate; Huang technique; entropy; multi-temporal; proximal sensing; freezing–thawing; rainfall
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Ymeti, I.; van der Werff, H.; Shrestha, D.P.; Jetten, V.G.; Lievens, C.; van der Meer, F. Using Color, Texture and Object-Based Image Analysis of Multi-Temporal Camera Data to Monitor Soil Aggregate Breakdown. Sensors 2017, 17, 1241.

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