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Mapping Double and Single Crop Paddy Rice With Sentinel-1A at Varying Spatial Scales and Polarizations in Hanoi Vietnam

机译:在越南河内使用空间尺度和极化程度不同的Sentinel-1A绘制双季和单季水稻。

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摘要

Paddy Rice is the prevalent land cover in the mosaicked landscape of the Hanoi Capital Region, Vietnam. In this study, we map double and single crop rice in Hanoi using a random forest algorithm and a time-series of Sentinel-1 SAR imagery at 10 and 20 m resolution using VV-only, VH-only, and both polarizations. We compare spatial and areal variation and quantify input band importance, estimate crop growth stages, estimate rice field/collective metrics using Fragstats with image segmentation, and highlight the importance of the results for land use and land cover. Results suggest double crop rice ranged from 208 000 to 220 000 ha with 20-m resolution imagery accounting for the most area in all polarizations. Based on accuracy assessment, we found 10 m data for VV/VH to have highest overall accuracy (93.5%, ±1.33%), while VV at 10 and 20 m had lowest overall accuracies (90.9%, ±1.57; 91.0%, ±2.75). Mean decrease in accuracy suggests for all but VV at 10 m, data from harvest and flooding stages are most critical for classification. Results suggest 20 m data for both VV and VH overestimates rice land cover, however 20 m data may be indicative of rice land use. Analysis of growing season suggests average estimated length of 93–104 days for each season. Commune-level results suggest up to 20% coefficient of variation between VV10m and VH10m with significant spatial variation in rice area. Landscape metrics show rice fields are typically plantedin groups of 3–4 fields with over 796 000 collectives and 2.69 millionfields estimated in the study area.
机译:水稻是越南河内首都地区镶嵌景观中普遍的土地覆盖。在这项研究中,我们使用随机森林算法和Sentinel-1 SAR图像的时间序列在10和20 m分辨率下使用仅VV,仅VH和两个极化对河内的双季和单季稻作图。我们比较空间和区域变化,量化输入波段的重要性,估计作物生长阶段,使用Fragstats和图像分割来估计稻田/集体指标,并强调结果对土地利用和土地覆盖的重要性。结果表明,双季稻的面积为208 000至220 000公顷,分辨率为20 m的图像占所有极化的面积最大。根据准确性评估,我们发现VV / VH的10 m数据具有最高的总体准确性(93.5%,±1.33%),而10和20 m处的VV的总体准确性最低(90.9%,±1.57; 91.0%,± 2.75)。准确度的平均下降表明,除VV以外的所有区域均在10 m处,收获和洪水阶段的数据对于分类最为关键。结果表明,VV和VH的20 m数据都高估了稻米的土地覆盖率,但是20 m的数据可能表示稻米的土地利用。对生长季节的分析表明,每个季节的平均估计长度为93-104天。公社水平的结果表明,VV10m和VH10m之间的变异系数高达20%,水稻面积存在明显的空间变异。景观指标显示,稻田通常以3至4个田地为一组种植,研究区估计有超过796 000个集体和269万个田地。

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