...
首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >A NOVEL METHOD FOR WATER AND WATER CANAL EXTRACTION FROM LANDSAT-8 OLI IMAGERY
【24h】

A NOVEL METHOD FOR WATER AND WATER CANAL EXTRACTION FROM LANDSAT-8 OLI IMAGERY

机译:LANDSAT-8 OLI IMAGERY提取水和水渠的新方法

获取原文
           

摘要

Constituents of hydrologic network, River and water canals play a key role in Agriculture for cultivation, Industrial activities and urban planning. Remote sensing images can be effectively used for water canal extraction, which significantly improves the accuracy and reduces the cost involved in mapping using conventional means. Using remote sensing data, the water Index (WI), Normalized Difference Water Index (NDWI) and Modified NDWI (MNDWI) are used in extracting the water bodies. These techniques are aimed at water body detection and need to be complemented with additional information for the extraction of complete water canal networks. The proposed index MNDWI-2 is able to find the water bodies and water canals as well from the Landsat-8 OLI imagery and is based on the SWIR2 band. In this paper, we use Level-1 precision terrain corrected OLI imagery at 30 meter spatial resolution. The proposed MNDWI-2 index is derived using SWIR2 (B7) band and Green (B3) band. The usage of SWIR2 band over SWIR1 results in very low reflectance values for water features, detection of shallow water and delineation of water features with rest of the features in the image. The computed MNDWI-2 index values are threshold by making the values greater than zero as 1 and less than zero as zero. The binarised values of 1 represent the water bodies and 0 represent the non-water body. This normalized index detects the water bodies and canals as well as vegetation which appears in the form of noise. The vegetation from the MNDWI-2 image is removed by using the NDVI index, which is calculated using the Top of Atmosphere (TOA) corrected images. The paper presents the results of water canal extraction in comparison with the major available indexes. The proposed index can be used for water and water canal extraction from L8 OLI imagery, and can be extended for other high resolution sensors.
机译:水文网络,河道和水渠的组成部分在农业种植,工业活动和城市规划中起着关键作用。遥感图像可以有效地用于水渠提取,这大大提高了准确性,并减少了使用常规方法进行地图绘制所涉及的成本。利用遥感数据,水指数(WI),归一化差水指数(NDWI)和修正NDWI(MNDWI)用于提取水体。这些技术旨在检测水体,并且需要补充其他信息来提取完整​​的水渠网络。提议的索引MNDWI-2能够从Landsat-8 OLI影像中找到水体和水渠,并且基于SWIR2波段。在本文中,我们使用30米空间分辨率的Level-1精确地形校正OLI图像。拟议的MNDWI-2索引是使用SWIR2(B7)频段和Green(B3)频段得出的。在SWIR1上使用SWIR2波段会导致水特征的反射率值非常低,浅水检测以及水特征与图像中其余特征的轮廓描绘。通过将大于零的值设为1并将小于零的值设为零,将计算出的MNDWI-2索引值设为阈值。二值化的值1表示水体,0表示非水体。该归一化指标检测水体和运河以及以噪声形式出现的植被。使用NDVI指数从MNDWI-2图像中去除植被,该指数是使用“大气层顶部”(TOA)校正图像计算得出的。与主要可用指标相比,本文介绍了水渠提取的结果。所提出的指标可用于从L8 OLI图像中提取水和水道,并可扩展到其他高分辨率传感器。

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