Multi-year mapping of cropping systems in regions with smallholder farms from Sentinel-2 images in Google Earth engine
| Autor: | Hongwei Qi, Ximin Qian, Songhao Shang, Heyang Wan |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | GIScience & Remote Sensing, Vol 61, Iss 1 (2024) |
| Druh dokumentu: | article |
| ISSN: | 15481603 1943-7226 1548-1603 |
| DOI: | 10.1080/15481603.2024.2309843 |
| Popis: | Accurate acquisition of spatial and temporal distribution information for cropping systems is important for agricultural production and food security. The challenges of extracting information about cropping systems in regions with smallholder farms are considerable, given the varied crops, complex cropping patterns, and the fragmentation of cropland with frequent reclamation and abandonment. This study presents a specialized workflow to solve this problem for regions with smallholder farms, which utilizes field samples and Sentinel-2 data to extract cropping system information over multiple years. The workflow involves four steps: 1) processing Sentinel-2 data to simulate crop growth curves with the Savitzky‒Golay filter and computing feature variables for classification, including phenology indices, spectral bands, and time series of vegetation indices; 2) mapping annual croplands with one-class support vector machine; 3) mapping various cropping patterns, including single cropping, intercropping, double cropping, multiple harvest, and fallow by decision tree and K-means clustering; and 4) mapping crops with random forest where Jeffries-Matusita distance was used to select appropriate vegetation indices. The workflow was applied in the Hetao irrigation district in Inner Mongolia Autonomous Region, China from 2018 to 2021. The overall accuracies were 0.98, 0.96, and 0.97 for cropland, cropping patterns, and crop type mapping, respectively. The mapping results indicated that the study area has low cropping continuity and is dominated by single cropping patterns. Furthermore, the area of wheat cultivation has decreased, and vegetable cultivation has expanded. Overall, the proposed workflow facilitated the accurate acquisition of cropping system information in regions with smallholder farms and demonstrated the effectiveness of available Sentinel-2 imagery in classifying complex cropping patterns. The workflow is available on Google Earth Engine. |
| Databáze: | Directory of Open Access Journals |
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