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Large river deltas are usually ecologically important wetland habitats, but also fertile agricultural exploitation areas, creating a conflict of long‐running substantial interest between agricultural expansion and wetland conservation. Over the past several years, large‐scale cultivation of water‐consuming rice has been growing rapidly in the semi‐...
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... of the samples were randomly selected for training and classification, and the remaining half was used to validate the resultant annual rice paddy map for the corresponding year. Figure 2 shows the stratified workflow for producing annual rice paddy maps from 2016 to 2021 using timeseries Sentinel-1/2 images. First, we used annual statistical indices (annual NDVImax) to identify vegetated areas and non-vegetated areas, and seasonal statistical indices (NDVImax between Jan. and Apr.) to eliminate doubleseason vegetation and obtain the single-season vegetation layer. ...
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Mineralogical studies are incipient and necessary in the Apodi Plateau, Brazil. This study aimed to evaluate the interrelationship between the mineralogy of the clay fraction and its structural and chemical attributes and to differentiate two important pedo-environments in the semi-arid region of northeastern Brazil (Ferralsol and Cambisols of the...
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... With the launch of Sentinel-1, time series of high spatial resolution SAR data become available globally (Torres et al., 2012). The combination of SAR and optical data is expected to provide advantages of land surface reflectance and surface structure features, which has been demonstrated to improve classification accuracy of built-up area (Huang and Zhang, 2022;Qin et al., 2017), sugarcane (Wang et al., 2020a), mangrove , and paddy rice (Huang and Zhang, 2023). However, the potential of combining SAR and optical images for wetland mapping at large scales remains unexplored fully. ...
Wetlands are rich in biodiversity, provide habitats for many wildlife species, and play a vital role in the transmission of bird-borne infectious diseases (e.g., highly pathogenic avian influenza). However, wetlands worldwide have been degraded or even disappeared due to natural and anthropogenic activities over the past two centuries. At present, major data products of wetlands have large uncertainties, low to moderate accuracies, and lack regular updates. Therefore, accurate and updated wetlands maps are needed for the sustainable management and conservation of wetlands. Here, we consider the remote sensing capability and define wetland types in terms of plant growth form (tree, shrub, grass), life cycle (perennial, annual), leaf seasonality (evergreen, deciduous), and canopy type (open, closed). We identify unique and stable features of individual wetland types and develop knowledge-based algorithms to map them in Northeast China at 10 m spatial resolution by using microwave (PALSAR-2, Sentinel-1), optical (Landsat (ETM+/OLI), Sentinel-2), and thermal (MODIS land surface temperature, LST) imagery in 2020. The resultant wetland map has a high overall accuracy of >95%. There were a total 154,254 km 2 of wetlands in Northeast China in 2020, which included 27,219 km 2 of seasonal open-canopy marsh, 69,158 km 2 of yearlong closed-canopy marsh, and 57,878 km 2 of deciduous forest swamp. Our results demonstrate the potential of knowledge-based algorithms and integrated multi-source image data for wetlands mapping and monitoring, which could provide improved data for the planning of wetland conservation and restoration.
