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Agrihub INSPIRE Hackathon 2021: Challenge #1 Crop detection
The document outlines the tasks and results related to Challenge #1 on crop detection, led by Herman Snevajs and Iva Bartlova. Various approaches were tested, including the use of different datasets, unsupervised classification for data preprocessing, and smoothing methods for radar images, but accuracy improvements were limited. Current efforts involve negotiations with the state agriculture intervention fund to apply the results more effectively.
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Agrihub INSPIRE Hackathon 2021: Challenge #1 Crop detection
- 1. Challenge #1 CROP DETECTION HermanSNEVAJS, Iva BARTLOVA
- 2. TASKS OF THECHALLENGE 1. different input dataset 2. pre-process data using unsupervised classification 3. improve accuracy of Sentinel-1 classification 4. application of crop classification
- 3. TASK1: DIFFERENT DATASETS SOLUTION:NORMALIZED DIFFERENCE MOISTURE INDEX RESULT: THE SAME ACCURACY
- 4. TASK2: PREPROCESSING OFINPUT LAYERS SOLUTION: UNSUPERVISED CLASSIFICATION RESULT: LOWER ACCURACY
- 5. TASK3: IMPROVE ACCURACYOF SENTINEL-1 CLASSIFICATION SOLUTION: SMOOTHING OF RADAR IMAGES RESULT: THE SAME ACCURACY
- 6. TASK4: APPLICATION OFTHE RESULTS SOLUTION: NEGOTIATING WITH STATE AGRICULTURE INTERVENTION FUND AGRICULTURE COMMODITY TRADE FOOD INDUSTRY FOOD SECURITY RESULT: IN PROGRESS
- 7.