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...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
Universiti Malaysia Perlis (UniMAP)
2014
|
| Subjects: | |
| Online Access: | http://dspace.unimap.edu.my:80/dspace/handle/123456789/31919 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Malaysia Perlis |
| Language: | English |
| Summary: | 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. |
|---|