首页> 外文期刊>Journal of Applied Remote Sensing >Monitoring aquatic weeds in a river system using SPOT 5 satellite imagery
【24h】

Monitoring aquatic weeds in a river system using SPOT 5 satellite imagery

机译:使用SPOT 5卫星图像监测河流系统中的水草

获取原文
获取原文并翻译 | 示例
           

摘要

Aquatic weeds have caused significant problems in many lakes and river systems worldwide. Weed outbreaks of water hyacinth (Eichhornia crassipes) and para-grass (Urochloa mutica) are common in Australia and their ecological and recreational impacts mostly negative and costly. Remote sensing offers the ability to map and monitor the distribution of aquatic weeds and their early detection. The objective of this project was to develop an efficient method, using remote sensing techniques, to map and monitor the change of dense water weeds in a river system and to identify a suitable spatial scale for this process. Two SPOT (Satellite Pour l'Observation de la Terre) 5 images from May 2006 and May 2007 were used in combination with two mapping approaches on a) multispectral image data with 10 m spatial resolution and b) pan-sharpened multispectral image data with 2.5 m spatial resolution. A scale dependent validation resulted in case b) an overall producer's classification accuracy of 81percent. Small outbreaks (approx2 m~(2)) alone were 71percent accurate with increasing accuracies of >95percent for outbreaks larger than 6.25m~(2) (2.5m X 2.5m pixel). Case a) generally had lower accuracies, with accuracies of >95percent for outbreaks in the order of 100m~(2) (10m X 10m pixel) and larger. The results suggest that the river infestation by aquatic weeds in a test area of the mid-Brisbane River has increased by a factor of 2 to 3 during the 12-month period. The infested area is estimated to be between 13.6percent and 15.9 percent of the waterbody in 2007, while 6.2percent to 6.8percent in 2006. The method applied in this study included geometric and radiometric corrections, along with linear spectral unmixing and spectral angle mapper techniques. This method is applicable to other waterways worldwide and offers the potential for the early detection of infestations of aquatic surface weeds.
机译:水生杂草已在全球许多湖泊和河流系统中引起严重问题。在澳大利亚,常见的是水葫芦(Eichhornia crassipes)和草丛(Urochloa mutica)的杂草暴发,其生态和娱乐影响主要是负面的,代价高昂的。遥感技术能够绘制和监测水草的分布及其早期发现。该项目的目的是开发一种使用遥感技术的有效方法,以绘制和监视河流系统中稠密水草的变化,并确定适合该过程的空间尺度。将2006年5月和2007年5月的两幅SPOT(卫星观测卫星)5幅图像与两种映射方法结合使用:a)空间分辨率为10 m的多光谱图像数据,b)2.5的全锐化多光谱图像数据m空间分辨率。规模依赖的验证导致案例b)总体生产者的分类准确度为81%。对于大于6.25m〜(2)(2.5m X 2.5m像素)的爆发,仅小规模暴发(大约2 m〜(2))的准确度就达到71%,准确率增加> 95%。情况a)通常具有较低的准确度,对于爆发的准确度> 95%,顺序为100m〜(2)(10m X 10m像素)或更大。结果表明,在12个月的时间里,布里斯班中游试验区水生杂草对河流的侵扰增加了2到3倍。据估计,2007年出没面积为水体的13.6%至15.9%,2006年为6.2%至6.8%。本研究中采用的方法包括几何校正和辐射校正,以及线性光谱分解和光谱角度映射技术。该方法适用于世界范围内的其他水道,并为早期检测水生表面杂草的侵染提供了潜力。

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