Abstract
The diversity of sensors in remote sensing allows for faster and easier detection of changes and issues across different scales, in contrast to conventional ground-based systems. One of the most important distinguishing features among these sensors is their varying resolutions, contributing to the versatility of remote sensing technologies across diverse environmental applications. In this study, the effectiveness of PlanetScope and Sentinel-2 satellite images with different image resolutions in detecting damage caused by a harmful insect (beet webworm moth - Loxostege sticticalis) in sunflower fields in Lüleburgaz district of Kırklareli in the Trace region was evaluated. Damage rates in sunflower fields were analyzed using various spectral indices (Enhanced Vegetation Index and Chlorophyll Index Green) and spectral transformation (Tasseled Cap Greenness) in conjunction with in situ data. Based on the spectral analysis, the satellite image dated 26 July, which showed the most severe damage, was used in the damage assessment analysis. The damaged areas were compared by classifying both satellite images with the Random Forest algorithm. According to the results of the classification accuracy assessment, PlanetScope satellite imagery showed the highest accuracy, with 90% overall accuracy and 84% Kappa statistics, making it a more suitable sensor choice for agricultural applications.
Original language | English |
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Pages (from-to) | 133-139 |
Number of pages | 7 |
Journal | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
Volume | 48 |
Issue number | 4/W9-2024 |
DOIs | |
Publication status | Published - 8 Mar 2024 |
Externally published | Yes |
Event | 8th International Conference on GeoInformation Advances, GeoAdvances 2024 - Istanbul, Turkey Duration: 11 Jan 2024 → 12 Jan 2024 |
Bibliographical note
Publisher Copyright:© Author(s) 2024.
Keywords
- Beet webworm moth
- Random Forest classification
- Sentinel-2A and PlanetScope
- Spectral indexes
- Sunflower fields