By Shunlin (Ed.) Liang, Shunlin Liang

ISBN-10: 1402064497

ISBN-13: 9781402064494

This booklet collects the overview papers from either technical classes and 3 dialogue panels of the ninth overseas Symposium on actual Measurements and Signatures in distant Sensing (ISPMSRS). It systematically summarizes the earlier achievements and identifies the frontier matters because the learn schedule for the close to destiny. It covers all elements of land distant sensing, from sensor platforms, actual modeling, inversion algorithms, to numerous functions. The papers on distant sensing process review the functions of alternative sensor platforms for estimating key land floor variables and the way they could most sensible be more advantageous and built-in successfully sooner or later. Papers on modeling and inversion overview the cutting-edge methodologies on actual modeling and the inversion algorithms for estimating a sequence of land floor variables. The papers on distant sensing program investigate the present prestige of assorted functions and speak about how greater to bridge the advance of remote-sensing technological know-how and expertise and sensible functions. Representing the group attempt and contributed by means of a workforce of foreign top specialists, this quintessential reference booklet for graduate scholars and practitioners of distant sensing additionally aids these engaged in educational examine, govt and industry.

Included is a CD-ROM containing the entire color photos that are published in Black and White within the book.

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Additional info for Advances in Land Remote Sensing: System, Modeling, Inversion and Application

Example text

There is some justification for this; however, it is also compounded by lags in time between changes in soil moisture and changes in canopy visible-near infrared characteristics. Using thermal infrared for disaggregation has also been proposed. It too has limitations. J. Jackson temperature changes will be shorter than with physiographic features observed with visible-near infrared. Disaggregation was explored by Chauhan et al. (2003) as a solution for NPOESS. It was proposed that a combination of microwave, visible-near infrared, and thermal infrared could be used.

1995). However, there is a large dielectric contrast between the solid and liquid phases of water at microwave frequencies. As snow starts melting, even a small amount of liquid water reduces the penetration depth of the radar signal, and thereby changes the dominant scattering source from the snow–ground interface to the snow volume and the air–snow interface. The backscattering coefficients decrease substantially at C-band and X-band (Stiles and Ulaby, 1980; Nagler and Rott, 2000; Shi and Dozier, 1995).

In the classification of the TM scene, there are only four target categories: lake, snow, forest, and range land that includes both bare ground and short vegetation. 1 shows the SAR classification map (right) and the Fig. 1 Comparison of SAR (right) and TM (left) derived classification maps. Black – Forest and lake, gray – bare surface and short vegetation, white – snow 30 J. Shi TM classification map (left). The comparison estimation of this two results indicated that at 86% accuracy can be obtained for snow cover area under consideration of the TM classification map as the ground truth.

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Advances in Land Remote Sensing: System, Modeling, Inversion and Application by Shunlin (Ed.) Liang, Shunlin Liang

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