Remote Sensing-Based Crop Identification and Acreage Estimation of Rabi Wheat in Anand, Gujarat
K. K. Chauhan, M. M. Lunagaria
International Journal of Environment and Climate Change · pp. 1–11 · Published 1 Jan 2025
10.9734/ijecc/2025/v15i14668Abstract
The Study evaluates the performance of supervised and unsupervised classification techniques for crop identification using Sentinel-2 imagery. Four supervised classifiers—Random Forest (RF), Minimum Distance (MD), Support Vector Machine (SVM), and Smile Cart (sCART)—were assessed, with RF achieving the highest overall average accuracy (91%) and kappa value (87%) across two cropping seasons. The unsupervised classification method, utilizing the Isoclustering algorithm, recorded an average accuracy and kappa value of 84% in the first season and 80% in the second season. Acreage estimation revealed RF to be the most reliable, estimating 69,000 hectares (2019-20) and 64,000 hectares (2020-21), closely aligning with district statistical yield data. In contrast, sCART and SVM classifiers demonstrated lower accuracies of 46% and 36%, respectively. The study underscores RF's superiority in crop identification and acreage estimation, offering valuable insights for agricultural planning and management.
Cited by 2
2 citations reported by external sources — individual citing-article records aren't available to list yet.
Related research
- Efficacy of Fungicides against Spot Blotch Disease of Wheat Caused by Bipolaris sorokiniana (Sacc.) Shoemaker — shares topic coverage
- Nutritive Appraisal of Various Wheat Varieties/Lines for Developing Biofortified Wheat (Triticum aestivum L.) — shares topic coverage
- Investigate the Effects of Increased Yeast Addition and Proofing Time on the Quality Characteristic of Bread from Wheat and Cassava Flour — shares topic coverage
- Effect of Carrot Powder Addition on the Quality Attributes of Cookies Produced from Wheat and Soy Flour Blends — shares topic coverage
- Quality Assessment of Bread from Wheat, Water Yam and Soybean Flours — shares topic coverage
Article metrics
Real usage data collected on this platform.
7
Page views
0
PDF downloads
0
Outbound clicks
2
Citations
Views over time
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
Traffic sources
Referring site, by host.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.