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首页> 外文期刊>The Madras Agricultural Journal >Mapping mango area using multi-temporal feature extraction from Sentinel 1A SAR data in Dharmapuri, Krishnagiri and Salem districts of Tamil Nadu
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Mapping mango area using multi-temporal feature extraction from Sentinel 1A SAR data in Dharmapuri, Krishnagiri and Salem districts of Tamil Nadu

机译:使用来自Dharmapuri,Krishnagiri和泰米尔纳德塞勒姆地区的Sentinel 1A SAR数据的多时间特征提取映射芒果区域

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摘要

Judicious and reliable information on crop area and production for tactical and strategic decision making is the need of the hour by all stakeholders in agriculture, such as producers, processors, resource managers, marketing, finance, and the government. The lacunae in conventional methods of crop delineation and area estimation can be overcome by the scientific method of estimation using remote sensing and GIS techniques. Sentinel 1A SAR data pertaining to the 2018 year acquired at 12 days intervals were downloaded and processed for intensity in Mapscape software. Sentinel 1A is anactive SAR microwave data, which can capture crop characteristics irrespective of weather and illumination condition. Ground truth observations collected during a surveyfor mango/ non-mango was used to derive mango signature from the processed satellite images. The dB values extracted as signature were then subjected to the Multi-Temporal feature extraction method to delineate the mango growing areas. Around 8015 ha and 31118 ha was mapped as mango growing areas in Dharmapuri and Krishnagiri districts, respectively. Accuracy assessment using the confusion matrix techniquewas done with the 40 per cent of the ground truth datedataand a kappa coefficient value of 0.71 was obtained which showed a good accuracy of estimation.
机译:关于作物地区的明智和可靠的信息和战术和战略决策的生产信息是农业所有利益攸关方的需要,例如生产者,处理器,资源经理,营销,金融和政府。可以通过使用遥感和GIS技术的科学方法来克服传统的作物描绘和面积估计方法中的LELUNAE。 Sentinel 1A关于在12天内收购的2018年的SAR数据是下载并在MAPSCUPY软件中的强度下载和处理。 Sentinel 1a是Anactive SAR微波数据,可以捕获不管天气和照明条件如何捕获裁剪特征。用于芒果/非芒果的调查期间收集的地面真理观察用于从加工卫星图像中衍生芒果签名。然后将提取为签名的DB值进行多时间特征提取方法以描绘芒果生长区域。在8015公顷和31118公顷分别被映射为Dharmapuri和Krishnagiri区的芒果生长区。使用混淆矩阵技术的准确性评估与地面真理DateAdAd的40%进行了kappa系数值0.71,显示出良好的估计准确性。

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