Exploration of Multitemporal COSMO-SkyMed Data via Interactive Tree-Structured MRF Segmentation

Gaetano, Raffaele; Amitrano, Donato; Masi, Giuseppe; Poggi, Gianfranco; Ruello, Giuseppe; Verdoliva, Luisa; Scarpa, Giuseppe

doi:10.1109/jstars.2014.2316595

Cited by 25 publications

(17 citation statements)

References 38 publications

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“…Figure 2 shows one of the available SAR images, geocoded and resampled on a map grid of 0.5 m/pixel (for comparison to the pan-sharpened optical image) after the application of the multitemporal De Grandi filter (De Grandi et al 1997), followed by a spatial non-local filter (Parrilli et al 2012). Multitemporal filtering, by exploiting time diversity, helps in reducing speckle and hence improves the performance of the successive segmentation step (Gaetano et al 2014). In particular, the De Grandi filter is relatively simple and has proved very effective in the context of several different applications (Ali et al 2013;Fontanelli et al 2014;Amitrano et al 2014).…”

Section: Sar Imagesmentioning

confidence: 99%

Detection of environmental hazards through the feature-based fusion of optical and SAR data: a case study in southern Italy

Errico

Angelino

Cicala

et al. 2015

International Journal of Remote Sensing

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The use of remote-sensing images is becoming common practice in the fight against environmental crimes. However, the challenge of exploiting the complementary information provided by radar and optical data, and by more conventional sources encoded in geographic information systems, is still open. In this work, we propose a new workflow for the detection of potentially hazardous cattle-breeding facilities, exploiting both synthetic aperture radar and optical multitemporal data together with geospatial analyses in the geographic information system environment. The data fusion is performed at a feature-based level. Experiments on data available for the area of Caserta, in southern Italy, show that the proposed technique provides very high detection capability, up to 95%, with a very low false alarm rate. A fast and easy-to-use system has been realized based on this approach, which is a useful tool in the hand of agencies engaged in the protection of territory

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Section: Sar Imagesmentioning

confidence: 99%

Detection of environmental hazards through the feature-based fusion of optical and SAR data: a case study in southern Italy

Errico

Angelino

Cicala

et al. 2015

International Journal of Remote Sensing

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“…The comprehension of the geometric distortions introduced by the side-looking acquisition mode [17] and of the non-linear electromagnetic scattering phenomena that contribute to the SAR signal formation requires the quantitative knowledge of the interactions between the transmitted electromagnetic field and the physical surfaces of the imaged scene. Therefore, several works in the past literature expressed the necessity of remote sensing processing chains devoted to produce results that could be easily interpreted by the potential end-users [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Sentinel-1 for Monitoring Reservoirs: A Performance Analysis

Amitrano¹,

Martino²,

Iodice³

et al. 2014

Remote Sensing

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Abstract:In this paper we explore the performances and the opportunities provided by the European satellite Sentinel-1 for water resource management applications in low-income countries. The analysis is supported by a synthetic aperture radar (SAR) simulator, which allowed the quantification of the expected characteristics of Sentinel-1 products in three applications: interferometric digital elevation models (DEMs) generation, land cover mapping and estimation of water volumes retained by small reservoirs. The obtained results quantitatively show that Sentinel-1 data characteristics are fully suitable for most of the application already explored in the recent SAR literature.

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“…However, this characteristic of SAR sensors can find other applications such as image enhancement [4], classification [5] and urban areas extraction [6]. The interferometric coherence is computed by relation:…”

Section: The Role Of the Mean Window In The Calculation Of The Interfmentioning

confidence: 99%

Urban Areas Extraction from Multitemporal SAR RGB Images Using Interferometric Coherence and Textural Information

Amitrano

Cecinati

Martino

et al. 2015

Proceedings of Fringe 2015: Advances in the Science and Applications of SAR Interferometry and Sentinel-1 InSAR Workshop

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In this paper, we introduce an innovative methodology for urban areas extraction based on a new class of multitemporal colour composite products. As first, we propose a method for enhancing the coherence characteristic of the image adapting the dimension of the main window to the scene target. Thus, we show how to link this property with a colour attribute, which is combined with textural information to form the final fuzzy urban areas map.

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Exploration of Multitemporal COSMO-SkyMed Data via Interactive Tree-Structured MRF Segmentation

Cited by 25 publications

References 38 publications

Detection of environmental hazards through the feature-based fusion of optical and SAR data: a case study in southern Italy

Detection of environmental hazards through the feature-based fusion of optical and SAR data: a case study in southern Italy

Sentinel-1 for Monitoring Reservoirs: A Performance Analysis

Urban Areas Extraction from Multitemporal SAR RGB Images Using Interferometric Coherence and Textural Information

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