The potential of satellite imagery in soil compaction studies for implementation of precision farming

The objective of this study is to evaluate the potential of satellite imagery and GIS (Geographic Information System) in soil compaction studies by investigating the spectral reflectance in producing soil compaction maps for implementation of precision farming. It analyzes the significant correlati...

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Main Author: Norasmanizan, Abdullah
Format: Thesis
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2014
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Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/31919
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Institution: Universiti Malaysia Perlis
Language: English
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spelling my.unimap-319192014-02-13T14:24:17Z The potential of satellite imagery in soil compaction studies for implementation of precision farming Norasmanizan, Abdullah Precision agriculture Remote sensing Soil compaction Regression Satellite imagery Geographic Information System (GIS) The objective of this study is to evaluate the potential of satellite imagery and GIS (Geographic Information System) in soil compaction studies by investigating the spectral reflectance in producing soil compaction maps for implementation of precision farming. It analyzes the significant correlation between soil penetration resistance data and reflectance data of the Landsat 5 TM image. This study identifies the possible areas of soil compaction by analyzing the spectral indexes of moisture content (NDMI), vegetation indexes (SAVI,MSAVI) and soil index (BSI). The relationship between variables is investigated using coefficient of determination (R²). The results of gravimeter measurement showed had a significant relationship of water content level in soil compaction. Thus, NDMI reflectance data were studied and it was found that it had significant correlation (R²=0.755) with soil penetration data. Linear regression of SWIR channel indicated highest significant correlation (R²=0.84) with (p<0.05) compared to several channels visible band of Band 1, (R²=0.209) Band 2, (R²=0.142), Band 3, (R²=0.382) and Band 7, (R²=0.305). The expression of linear regression was used in predicting the compact area using Band Math function and the compaction status map was created using geostatistical method. The mathematical models of spectral indexes also indicated a correlation with the significant correlation of SAVI is (R²=0.724), MSAVI (R²=0.725) and BSI (R²=0.422). The combined information of the soil compaction map and space technology is valuable for farmers and growers in land treatment, tillage activities and consequently in the implementation of site specific agricultural management. 2014-02-13T14:24:17Z 2014-02-13T14:24:17Z 2013 Thesis http://dspace.unimap.edu.my:80/dspace/handle/123456789/31919 en Universiti Malaysia Perlis (UniMAP) School of Environmental Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Precision agriculture
Remote sensing
Soil compaction
Regression
Satellite imagery
Geographic Information System (GIS)
spellingShingle Precision agriculture
Remote sensing
Soil compaction
Regression
Satellite imagery
Geographic Information System (GIS)
Norasmanizan, Abdullah
The potential of satellite imagery in soil compaction studies for implementation of precision farming
description The objective of this study is to evaluate the potential of satellite imagery and GIS (Geographic Information System) in soil compaction studies by investigating the spectral reflectance in producing soil compaction maps for implementation of precision farming. It analyzes the significant correlation between soil penetration resistance data and reflectance data of the Landsat 5 TM image. This study identifies the possible areas of soil compaction by analyzing the spectral indexes of moisture content (NDMI), vegetation indexes (SAVI,MSAVI) and soil index (BSI). The relationship between variables is investigated using coefficient of determination (R²). The results of gravimeter measurement showed had a significant relationship of water content level in soil compaction. Thus, NDMI reflectance data were studied and it was found that it had significant correlation (R²=0.755) with soil penetration data. Linear regression of SWIR channel indicated highest significant correlation (R²=0.84) with (p<0.05) compared to several channels visible band of Band 1, (R²=0.209) Band 2, (R²=0.142), Band 3, (R²=0.382) and Band 7, (R²=0.305). The expression of linear regression was used in predicting the compact area using Band Math function and the compaction status map was created using geostatistical method. The mathematical models of spectral indexes also indicated a correlation with the significant correlation of SAVI is (R²=0.724), MSAVI (R²=0.725) and BSI (R²=0.422). The combined information of the soil compaction map and space technology is valuable for farmers and growers in land treatment, tillage activities and consequently in the implementation of site specific agricultural management.
format Thesis
author Norasmanizan, Abdullah
author_facet Norasmanizan, Abdullah
author_sort Norasmanizan, Abdullah
title The potential of satellite imagery in soil compaction studies for implementation of precision farming
title_short The potential of satellite imagery in soil compaction studies for implementation of precision farming
title_full The potential of satellite imagery in soil compaction studies for implementation of precision farming
title_fullStr The potential of satellite imagery in soil compaction studies for implementation of precision farming
title_full_unstemmed The potential of satellite imagery in soil compaction studies for implementation of precision farming
title_sort potential of satellite imagery in soil compaction studies for implementation of precision farming
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/31919
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