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Weed mapping in cotton using ground-based sensors and GIS
Antonis V Papadopoulos1, Vaya Kati2, Demosthenis Chachalis2
1Department of Phytopathology, Laboratory of Non-Parasitic Diseases, Benaki Phytopathological Institute, 8 St. Delta Str., Kifissia, 145 61, Athens, Greece. a.papadopoulos@bpi.gr.
Environmental Monitoring and Assessment
|October 1, 2018
Summary
Accurate weed mapping in cotton fields is achievable using multispectral sensors and digital cameras. These technologies enable precise weed monitoring and can help optimize herbicide application for better crop management.
Area of Science:
- Agricultural Science
- Remote Sensing
- Precision Agriculture
Background:
- Site-specific weed management requires accurate mapping of weed infestations.
- Geographical Information Systems (GIS) and sensor technologies aid in sub-field level decision-making for weed control.
Purpose of the Study:
- To digitally map weed patches in cotton fields using two different spectral sensing systems.
- To evaluate the effectiveness of multispectral sensors and digital cameras for weed mapping.
- To assess the correlation between red-edge normalized difference vegetation index (NDVI) and weed cover percentage.
Main Methods:
- Two spectral sensing systems, Crop Circle multispectral sensors (ACS-430) and a Nikon D300S digital camera, were used.
- Data collection involved scanning and photographing spaces between cotton rows in four fields.
- Data analysis was performed in a GIS environment to create spatially interpolated maps of red-edge NDVI and weed cover.
Main Results:
- Both mapping approaches showed a satisfactory relationship with actual weed distribution.
- The digital camera method tended to underestimate weed populations compared to multispectral sensors.
- A high and statistically significant correlation (r > 0.83) was found between red-edge NDVI and weed cover.
- A first-degree linear equation (R² > 0.7) adequately modeled the relationship between the two variables.
Conclusions:
- The studied methodologies are valid for spatially monitoring weed patches in cotton cultivation.
- These technologies can be applied for yearly mapping of weed flora.
- The findings support the rationalization of herbicide application in terms of dosage and spatio-temporal decision-making.
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