首页> 外文会议>International Conference on Agro-geoinformatics >Crop Mapping Improvement by Combination of Optical and SAR datasets
【24h】

Crop Mapping Improvement by Combination of Optical and SAR datasets

机译:通过光学和SAR数据集的组合进行裁剪改进

获取原文

摘要

Investigation of radar and optical data indices that contain a lot more information on landscapes and vegetation dynamics can be useful to identify opportunities and challenges in agricultural activities. In addition, the potential of synchronous implications of radar and optical data will be an effective method for agro-environmental monitoring and management to promote economic and environmental sustainability as monitoring programs. Crop discrimination as an agricultural monitoring system is a critical step regarding to estimate the area allocated to each crop type, computing statistics for crop control of area-based subsidies or crop production forecasting, environmental impact analysis and some other applications. Integrating both optical (reflectance) and Synthetic Aperture Radar (backscatter) multi-temporal features provides some advantages in terms of a more reliable crop map. We utilize multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) imagery and Sentinel-2 optical datasets in order to investigate the performance of the sensors backscatter and reflectance for temporal crop type mapping and the sustainable management of agricultural activities. Multi-temporal Sentinel-1, C-band VV and VH polarized SAR data and Sentinel2 optical data were acquired simultaneously by in-situ measurements for the study area. As preliminary results, it is concluded that the classification accuracies were improved results (5%) with using combinations of sensors. Classification accuracies of 93% were achieved in this study with integration use of SAR and optical data.
机译:雷达和光学数据指数调查包含更多关于景观和植被动态的更多信息,可用于识别农业活动中的机会和挑战。此外,雷达和光学数据同步影响的可能性将是农业环境监测和管理的有效方法,以促进经济和环境可持续性作为监测计划。作为农业监测系统的作物歧视是关于估计分配给每种作物类型的区域,计算基于区域的补贴或作物生产预测,环境影响分析和其他一些应用的作物控制统计数据的重要步骤。集成光学(反射率)和合成孔径雷达(反向散射)多时间特征在更可靠的作物地图方面提供了一些优点。我们利用多时相的Sentinel-1合成孔径雷达(SAR)图像和Sentinel-2的光学数据集,以调查传感器的性能后向散射和反射的时间作物类型映射和农业活动的可持续管理。通过对研究区域的原位测量同时获取多时间哨声-1,C波段VV和VH偏振SAR数据和Sentinel2光学数据。作为初步结果,得出结论是,使用传感器的组合,分类准确性得到改善的结果(5%)。本研究中实现了93%的分类精度,通过SAR和光学数据的集成使用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号