New PDF release: Advances in Watershed Science and Assessment

By Tamim Younos, Tammy E. Parece

ISBN-10: 3319142119

ISBN-13: 9783319142111

ISBN-10: 3319142127

ISBN-13: 9783319142128

This quantity bargains techniques, tools and case reviews of cutting edge and evolving applied sciences within the quarter of watershed evaluation. themes mentioned comprise: (1) improvement and purposes of geospatial, satellite tv for pc imagery and distant sensing applied sciences for land tracking; (2) improvement and purposes of satellite tv for pc imagery for tracking inland water caliber; (3) improvement and functions of water sensor applied sciences for real-time tracking of water volume and caliber; and (4) Advances in organic tracking and microbial resource monitoring technologies.

This booklet may be of curiosity to graduate scholars and researchers all for watershed technology and environmental reports. both, it's going to function a helpful advisor to specialists in govt organizations who're focused on water-availability and water-quality concerns, and engineers and different execs fascinated by the layout of land- and water-monitoring systems.

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Extra resources for Advances in Watershed Science and Assessment

Sample text

Most specifically, they used a building detection algorithm to identify buildings from Lidar data and then used seven spatial characteristics of these buildings to help classify varying residential land uses. In a watershed study, for the Garonne and Allier River watersheds in France, researchers used airborne Lidar and SPOT images for land cover classification [60]. Nine separate land cover types were classified—five different types of riparian forests, along with gravel, low vegetation, water, and bare earth.

Louisville, 23–28 Mar 2014 55. United States National Aeronautics and Space Administration (2014) About LVIS. http://lvis. gov. Accessed 24 May 2014 56. Lee DS, Shan J (2003) Combining Lidar elevation data and IKONOS multispectral imagery for coastal classification mapping. Mar Geod 26(1/2):117–127 57. Buja´n S, Gonza´lez-Ferreiro E, Reyes-Bueno F, Barreiro-Ferna´ndez L, Crecente R et al (2012) Land use classification from Lidar data and ortho-images in a rural area. Photogramm Rec 27(140):401–422 58.

2 Detecting Groundwater . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Detecting Freshwater Springs and Biomass . . . . . . . . . . . . . . . . . . . . . . . . . 1 Detecting Freshwater Plumes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Determining Biomass Production . . . . . . . . . . . . . . . . . . . . . . . .

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Advances in Watershed Science and Assessment by Tamim Younos, Tammy E. Parece

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