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Journal ArticleDOI

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

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TLDR
A fast and easy-to-use system has been realized based on 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.
Abstract
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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Citations
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Journal ArticleDOI

A CNN-Based Fusion Method for Feature Extraction from Sentinel Data

TL;DR: This work proposes to estimate missing optical features through data fusion and deep-learning, and results are very promising, showing a significant gain over baseline methods according to all performance indicators.
Journal ArticleDOI

Quantitative analysis of the dynamic changes of ecological security in the provinces of China through emergy-ecological footprint hybrid indicators

TL;DR: Zhang et al. as mentioned in this paper established a framework on historical evaluation and future projection of ecological security in China and applied it to China's provincial ecological security evaluation during 2006-2015.
Journal ArticleDOI

Fusing optical and SAR time series for LAI gap filling with multioutput Gaussian processes

TL;DR: This work proposes the use of Multi-Output Gaussian Process (MOGP) regression, a machine learning technique that learns automatically the statistical relationships among multisensor time series, to detect vegetated areas over which the synergy between SAR-optical imageries is profitable, and demonstrates the advantage of MOGP especially for long data gaps.
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Swarm coordination of mini-UAVs for target search using imperfect sensors

TL;DR: The design of the novel swarming algorithm is reported on, reviewing different strategies and measuring their performance on a number of synthetic and real-world scenarios.
Journal ArticleDOI

Medium-to-long-term coupled strategies for energy efficiency and greenhouse gas emissions reduction in Beijing (China)

TL;DR: Li et al. as discussed by the authors analyzed the situations of socio-economic development and energy consumption in Beijing and established LEAP-Beijing model for the medium-to-longterm prediction of GHG emissions.
References
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Object based image analysis for remote sensing

TL;DR: This paper gives an overview of the development of object based methods, which aim to delineate readily usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way.
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