Weights Based Decision Level Data Fusion of Landsat-8 and Sentinel-L for Soil Moisture Content Estimation

Yahia, Oualid; Guida, Raffaella; Iervolino, Pasquale

doi:10.1109/igarss.2018.8518027

Cited by 7 publications

(2 citation statements)

References 9 publications

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“…This level of data fusion resulted in the direct production of Refs. [78,79], which was the ultimate conclusion. By using this approach, it is possible to successfully prevent the ambiguity and unreliability that can occur from making a final judgment based solely on the perceptual results of one sensor.…”

Section: Fusion Strategy Based On Multi-source Decision (Fsbmd)mentioning

confidence: 81%

Analyzing Factors Influencing Situation Awareness in Autonomous Vehicles—A Survey

Ignatious

El-Sayed

Khan

et al. 2023

Sensors

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Autonomous driving of higher automation levels asks for optimal execution of critical maneuvers in all environments. A crucial prerequisite for such optimal decision-making instances is accurate situation awareness of automated and connected vehicles. For this, vehicles rely on the sensory data captured from onboard sensors and information collected through V2X communication. The classical onboard sensors exhibit different capabilities and hence a heterogeneous set of sensors is required to create better situation awareness. Fusion of the sensory data from such a set of heterogeneous sensors poses critical challenges when it comes to creating an accurate environment context for effective decision-making in AVs. Hence this exclusive survey analyses the influence of mandatory factors like data pre-processing preferably data fusion along with situation awareness toward effective decision-making in the AVs. A wide range of recent and related articles are analyzed from various perceptive, to pick the major hiccups, which can be further addressed to focus on the goals of higher automation levels. A section of the solution sketch is provided that directs the readers to the potential research directions for achieving accurate contextual awareness. To the best of our knowledge, this survey is uniquely positioned for its scope, taxonomy, and future directions.

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Section: Fusion Strategy Based On Multi-source Decision (Fsbmd)mentioning

confidence: 81%

Analyzing Factors Influencing Situation Awareness in Autonomous Vehicles—A Survey

Ignatious

El-Sayed

Khan

et al. 2023

Sensors

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“…Sentinel-1 is a mission of twin satellites Sentinal-1A and Sentinel-1B, both equipped with a C-SAR on board (5.405 GHz frequency) [ 51 ].…”

Section: Study Areamentioning

confidence: 99%

Novel Weight-Based Approach for Soil Moisture Content Estimation via Synthetic Aperture Radar, Multispectral and Thermal Infrared Data Fusion

Yahia

Guida

Iervolino

2021

Sensors

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Though current remote sensing technologies, especially synthetic aperture radars (SARs), exhibit huge potential for soil moisture content (SMC) retrievals, such technologies also present several performance disadvantages. This study explored the merits of proposing a novel data fusion methodology (partly decision level and partly feature level) for SMC estimation. Initially, individual estimations were derived from three distinct methods: the inversion of an Empirically Adapted Integral Equation Model (EA-IEM) applied to SAR data, the Perpendicular Drought Index (PDI), and the Temperature Vegetation Dryness Index (TVDI) determined from Landsat-8 data. Subsequently, three feature level fusions were performed to produce three different novel salient feature combinations where said features were extracted from each of the previously mentioned methods to be the input of an artificial neural network (ANN). The latter underwent a modification of its performance function, more specifically from absolute error to root mean square error (RMSE). Eventually, all SMC estimations, including the feature level fusion estimation, were fused at the decision level through a novel weight-based estimation. The performance of the proposed system was analysed and validated by measurements collected from three study areas, an agricultural field in Blackwell farms, Guildford, United Kingdom, and two different agricultural fields in Sidi Rached, Tipasa, Algeria. Those measurements contained SMC levels and surface roughness profiles. The proposed SMC estimation system yielded stronger correlations and lower RMSE values than any of the considered SMC estimation methods in the order of 0.38%, 1.4%, and 1.09% for the Blackwell farms, Sidi Rached 1, and Sidi Rached 2 datasets, respectively.

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Exploiting Knowledge Graph for Multi-faceted Conceptual Modelling using GCN

Wan

Chen

et al. 2022

Procedia Computer Science

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Weights Based Decision Level Data Fusion of Landsat-8 and Sentinel-L for Soil Moisture Content Estimation

Cited by 7 publications

References 9 publications

Analyzing Factors Influencing Situation Awareness in Autonomous Vehicles—A Survey

Analyzing Factors Influencing Situation Awareness in Autonomous Vehicles—A Survey

Novel Weight-Based Approach for Soil Moisture Content Estimation via Synthetic Aperture Radar, Multispectral and Thermal Infrared Data Fusion

Exploiting Knowledge Graph for Multi-faceted Conceptual Modelling using GCN

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