Mapping annual center-pivot irrigated cropland in Brazil during the 1985-2021 period with cloud platforms and deep learning

ISPRS Journal of Photogrammetry and Remote Sensing(2023)

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摘要
As an important agricultural facility that supports efficient crop production and precise water management, center-pivot irrigated cropland (CPIC) plays a critical role in increasing crop yield and ensuring food security globally. Since the 1980s, CPIC has expanded significantly and has become one of the most valuable irrigated croplands in Brazil. However, national-scale and long-term CPIC products are currently unavailable, making spatiotemporal analysis for related ecological and economic factors challenging. In this study, we proposed a novel framework combining cloud platforms and deep learning algorithms to produce annual CPIC maps (ACMs) with 30 m spatial resolution in Brazil from 1985 to 2021. Leveraging all available Landsat-5, 7, and 8 images in Brazil, we generated three-band annual composite images to obtain stable image features for CPIC and alleviate the heterogeneity of CPIC. Then we constructed a large-scale training dataset covering different climatic zones of Brazil and spanning multiple years. Based on this dataset a CNN model was trained and applied to the whole of Brazil and generalized to other years. We deployed the CNN model to the cloud platform and combined it with Google Earth Engine to produce Brazil's annual CPIC Maps (ACMs). Moreover, we analyzed the spatiotemporal dynamics of CPIC and explored the impact of CPIC expansion on forests. The accuracy assessment demonstrated that our ACMs reached an average mIoU of 0.947 +/- 0.021 for all study years, and the estimated CPIC area was highly consistent with official statistics. Our results indicated that Brazilian CPICs reached 1.8 x 106 ha in 2021, which was 45 times more than that in 1985. CPIC expansion occurred mainly in the states of Minas Gerais, Goi ' as, and Bahia over the past few decades, with an average annual increase in area of over 8,000 ha. We also found that CPIC expansion had encroached on 42,000 ha of shrubs and 25,000 ha of forests since 1985, and the impact was continuing and intensifying. To the best of our knowledge, the produced ACMs are the longest and most spatially detailed CPIC products in Brazil that reflect the CPIC spatiotemporal changes in the last four decades and can provide essential information services for Brazil's water resource management and agricultural decision-making.
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关键词
Irrigation,Landsat,Google Earth Engine,Deep learning,U-Net,Brazil
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