Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017) 2017
DOI: 10.1117/12.2277506
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Tracing dynamics of relative volumetric soil moisture content using SAR data

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Cited by 6 publications
(5 citation statements)
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“…Only where there is a strong change in the territories, values up to 1 unit or the places colored in red can be seen. From the images thus made the strongest dynamics are observed in the region of Plovdiv and Pernik, where NDGI has the most values around +1 (one) 30,31 . The index can be used to analyze urbanized and non-urbanized areas.…”
Section: Resultsmentioning
confidence: 96%
“…Only where there is a strong change in the territories, values up to 1 unit or the places colored in red can be seen. From the images thus made the strongest dynamics are observed in the region of Plovdiv and Pernik, where NDGI has the most values around +1 (one) 30,31 . The index can be used to analyze urbanized and non-urbanized areas.…”
Section: Resultsmentioning
confidence: 96%
“…The same profiles are transferred to the Merge image (figure 9). Transforming the SAR image into dB has already proven its effectiveness (figure 10), since dB is a logarithmic quantity with particularly high accuracy and clear values for surfaces 36 , but after removing speckle.…”
Section: Resultsmentioning
confidence: 99%
“…,where σ is the microwave reflectance coefficient for time instant t1 (satellite image of earlier date ) and for time instant (satellite image of later date ), i, j are the row and column numbers of pixels in a given SAR image, and r is the relative soil moisture content reported for the corresponding period between two images of one polarization. This mathematical approach was used between four images over a period of about a month, showing promising results in identifying areas of moderate and high change in vegetation, wet snow, ice, and water 13 . The values above 2 register serious changes in the reflectance of a given object in selected areas, and low values below 1.0 indicate little or no change in an object's reflectance.…”
Section: Modifiedmentioning
confidence: 99%
“…The availability of ground-based data in addition allows effective and cost-effective monitoring of climate change in remote areas using SAR data. The SAR C-band enables the effective study of various objects [5][6][7][8][9][10][11][12][13][14][15] and especially wet snow and ice 3,4,[16][17][18][19] . Using SAR data, we studied the type of changes in the digital value of the reflected signal (Q) from various objects, including water in different phase states.…”
Section: Introductionmentioning
confidence: 99%