Satellites map Bangladesh's rice fields through cloud cover and rain
Rahman HMH, Mahmud H, Hasan MM, Hussain SG
Crop Improvement
If you've ever wondered how researchers track crops across a country the size of Iowa that's cloudy half the year, this shows radar satellites can see through storms that would blind a regular camera.
Rice farming feeds most of Bangladesh, but figuring out exactly how much land is planted each season is tricky because clouds block regular satellite photos during the rainy growing months. Researchers solved this by using radar satellites, which see through clouds, paired with computer programs that learn to recognize rice fields from their unique radar signature. The method worked really well for one rice season, matching government numbers almost exactly, but undercounted the other season by about 29%, showing there's still room to improve.
Key Findings
The k-Nearest Neighbour model achieved the highest accuracy overall: 94.5% for Aman rice and 99.8% for Aus rice
Random Forest for Aman rice mapping estimated 5.72 million hectares, closely matching official Bangladesh government figures
Aus rice mapping using CART underestimated the crop area by 29% (0.76 Mha versus the official 1.06 Mha)
chevron_right Technical Summary
Scientists used satellite radar images and computer learning to map where rice is grown in Bangladesh during two growing seasons, without needing clear skies. Their method nearly matched official government crop area numbers for one season, showing satellites can help track food crops even through clouds and monsoon weather.
Abstract Preview
Original paper
Estimating aman and aus rice area in Bangladesh using sentinel-1 imagery and machine learning algorithms.
Rice (Oryza sativa L.) is Bangladesh's staple crop, cultivated across three distinct seasons: Rabi (Boro), Kharif-1 (Aus) and Kharif-2 (Aman). This study develops an integrated, cloud-independent f...
open_in_new Read full abstractAbstract copyright held by the original publisher.
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