首页> 外文会议>IFIP WG 5.14 International conference on computer and computing technologies in agriculture >Evaluation and Mapping of Rice Flood Damage Using Domestic Remotely Sensed Data in China
【24h】

Evaluation and Mapping of Rice Flood Damage Using Domestic Remotely Sensed Data in China

机译:利用国内遥感数据评价水稻洪灾危害及其制图。

获取原文

摘要

It has great significance to study quick monitoring of rice flood disaster and applying timely remedial measures in the disaster area. The purpose of this research paper was to evaluate the rice flood damage, which happened on July to August 2009 in Shouxian, Huoqiu, Bengbu and Huainan are mainly rice producing areas in Anhui Province in China, using two images from domestic remotely sensing data from China that named Huan Jing satellite (HJ-CCD images). One was pre-flood disaster and the other was post-flood disaster. According to the change characteristics of NDVI (Normalized Difference Vegetation Index) of forty field-sampling points of post-flood in study area, the flood damage degrees (light, moderate and serious) were been classified also. The verification of the classification accuracy calculated by confusion matrix that based on 40 field-sampling verification points. Accuracy results showed that Kappa coefficient (κ) was 0.6907 and the overall accuracy was 80.0%. At the same time, extract nine vegetation indices calculated from HJ-CCDs data were to build the model to inverted LAI of rice, and analyze the growth of rice after flood disaster stress. Hence, this study descriptive that multi-temporal and multispectral imagery domestic remotely sensing data from China (HJ-1 CCD images) are sufficient to assess rice flood disaster areas, specify relative damage degrees and growth analysis after flood stress.
机译:研究水稻洪水灾害的快速监测,并在灾区采取及时的补救措施,具有重要的意义。本研究报告的目的是使用两个来自中国国内遥感数据的图像,评估2009年7月至8月在寿县,火球,蚌埠和淮南主要是中国安徽省水稻产区的水稻洪水灾害。命名为环景卫星(HJ-CCD图像)。一个是洪水前的灾难,另一个是洪水后的灾难。根据研究区40个洪灾后田间采样点NDVI(归一化植被指数)的变化特征,对洪灾的危害程度(轻度,中度和严重度)进行了分类。通过基于40个现场采样验证点的混淆矩阵计算的分类准确性的验证。准确性结果表明,卡伯系数(κ)为0.6907,总体准确性为80.0%。同时提取HJ-CCDs数据计算得到的9个植被指数,建立水稻倒LAI模型,并分析洪涝灾害后水稻的生长情况。因此,本研究描述了来自中国的多时相和多光谱图像的国内遥感数据(HJ-1 CCD图像)足以评估水稻洪灾灾区,详细说明洪灾后的相对破坏程度和生长分析。

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