Free eBook Development of models for monitoring the urban environment using radar remote sensing (UNISURV report) download
by Catherine Ticehurst
Author: Catherine Ticehurst
Publisher: School of Geomatic Engineering, University of New South Wales (1998)
Category: Engineering & Transportation
Size MP3: 1171 mb
Size FLAC: 1330 mb
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By Catherine Ticehurst.
By Catherine Ticehurst. Development of models for monitoring the urban environment using radar.
A method for the decomposition of radar polarization signatures is developed
A method for the decomposition of radar polarization signatures is developed. The polarization backscattering model is assumed to consist of odd, double, Bragg, and cross backscattering components, and the Mueller matrix is the sum of the Mueller matrices of these four scattering mechanisms. The application of wavelet transform for speckle suppression in radar imagery.
With developments in. remote-sensing technologies, the monitoring and . obtain urban forest information. to RADAR data, LiDAR data on urban forest have. been widely used and adopted (Forzieri et al. remote-sensing technologies, the monitoring and detection of urban forests can be achieved without performing any eld measurements. In this study, dierent remote-sensing imageries and various methods are evaluated to obtain urban forest information. e use of the combination of LiDAR data with VHR imagery increases the accuracy of information, particularly about tree crown delineation. Traditional pixel-based classication methods are not eectively applicable to obtain urban. 2009
Radar Remote Sensing of Urban Areas pp 1-47 Cite a. Dong Y, Forster B, Ticehurst C (1997) Radar backscatter analysis for urban environments. Int J Remote Sens 18(6):1351–1364CrossRefGoogle Scholar.
Authors and affiliations. Adam N, Kampes B, Eineder M (2004) Development of a scientific permanent scatterer system: modifications for mixed ERS/ENVISAT time series. Ehlers M, Tomowski D (2008) On segment based image fusion. In: Blaschke T, LANG S, Hay G (eds) Object-based image analysis spatial concepts for knowledge-driven remote sensing applications.
The advantages of fusion for land use analysis were assessed in 32 studies, and a large majority (28 studies) concluded that fusion improved results compared to using single data sources.
Remote sensing techniques have proven to be powerful tools for the . Methods for monitoring coastal environments. As the intersection of land and sea, coastal zones are complex and variable.
Remote sensing techniques have proven to be powerful tools for the monitoring of the Earth’s surface and atmosphere on a global, regional, and even local scale, by providing important coverage, mapping and classification of land cover features such as vegetation, soil, water and forests. The coastal zone has been of importance for economic development and ecological restoration due to their rich natural resources and vulnerable ecosystems.
Remote Sensing Image The environment virtually encompasses everything in the .
Remote Sensing Image The environment virtually encompasses everything in the world around us. This includes natural, physical, biotic and abiotic as well as human socio-economic features. For monitoring large areas using remotely sensed data, the water balance approach provides an operational advantage in terms of data availability. While the energy balance models are mainly driven by the thermal data, the water balance models are driven by rainfall.
Radar technology is increasingly being used to monitor the environment. The first four chapters cover the basics of mathematical, statistical modelling as well as physical modelling based on radiowave scattering theory. The subsequent eight chapters summarize applications of polarimetric radar monitoring for various types of earth environments, including vegetation and oceans. The last two chapters provide a summary of Western as well as former Soviet Union knowledge and the outlook.
Furthermore remote sensing can provide multiple cities with periodically updated land use/land cover data useful for revision and refinement of meteorological models for local climate prediction and air pollution models such as the NCAR MM5 code (Grossman-Clarke et a. i. . in press). Concerning the air pollution problem, remotely sensed data are useful for improvement of land use/land cover information to models, rather than actual monitoring of air quality