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1.
Sensors (Basel) ; 19(5)2019 Mar 05.
Artigo em Inglês | MEDLINE | ID: mdl-30841629

RESUMO

A module for Very High Resolution (VHR) satellite stereo-pair imagery processing and Digital Elevation Model (DEM) extraction is presented. A large file size of VHR satellite imagery is handled using the parallel processing of cascading image tiles. The Scale-Invariant Feature Transform (SIFT) algorithm detects potentially tentative feature matches, and the resulting feature pairs are filtered using a variable distance threshold RANdom SAmple Consensus (RANSAC) algorithm. Finally, point cloud ground coordinates for DEM generation are extracted from the homologous pairs. The criteria of average point spacing irregularity is introduced to assess the effective resolution of the produced DEMs. The module is tested with a 0.5 m × 0.5 m Geoeye-1 stereo pair over the island of Crete, Greece. Sensitivity analysis determines the optimum module parameterization. The resulting 1.5-m DEM has superior detail over reference DEMs, and results in a Root Mean Square Error (RMSE) of about 1 m compared to ground truth measurements.

2.
Sensors (Basel) ; 17(6)2017 Jun 21.
Artigo em Inglês | MEDLINE | ID: mdl-28635625

RESUMO

A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach using Artificial Neural Networks (ANNs) is tested. The methodology is applied in Western Crete, Greece, where a SMC gauge network was deployed during 2015. The performance of the proposed algorithm is evaluated using leave-one-out cross validation and sensitivity analysis. ANNs prove to be the most efficient in SMC estimation yielding R² values between 0.7 and 0.9. The proposed methodology is used to support a hydrological simulation with the HEC-HMS model, applied at the Keramianos basin which is ungauged for SMC. Results and model sensitivity highlight the contribution of combining Sentinel-1 SAR and Landsat 8 images for improving SMC estimates and supporting hydrological studies.

3.
Int J Biometeorol ; 60(8): 1205-15, 2016 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-26637196

RESUMO

Climate and weather patterns are an essential resource for outdoor tourism activities. The projected changes in climate and weather patterns are expected to affect the future state of tourism. The present study aims to quantify the positive or negative effect of a 2 °C global warming on summertime climate comfort in the sense of exercising activities that involve light body activity. The well-established Climate Index for Tourism (CIT) and three variants of the widely used Tourism Climatic Index (TCI) were analyzed. Additionally, a new index based on TCI and CIT was tested and compared against the precious indices. Past and future climate data of five high-resolution regional climate models (RCMs) from different Representative Concentration Pathways (RCP4.5 and RCP8.5) of the European Coordinated Regional Climate Downscaling Experiment (Euro-CORDEX) for a +2 °C period were used. The results indicate improvement in the climate comfort for the majority of European areas for the May to October period. For the June to August period, central and northern European areas are projected to improve, while marginal improvement is found for Mediterranean countries. Furthermore, in specific cases of adjacent Mediterranean areas such as the southern Iberian Peninsula, the June to August climate favorability is projected to reduce as a result of the increase to daytime temperature. The use of a set of different indices and different RCMs and RCPs samples a large fraction of the uncertainty that is crucial for providing robust regional impact information due to climate change. The analysis revealed the similarities and the differences in the magnitude of change across the different indices. Moreover, discrepancies were found in the results of different concentration pathways to the +2 °C global warming, with the RCP8.5 projecting more significant changes for some of the analyzed indices. The estimation of the TCI using different timescale climate data did not change the results on tourism significantly.


Assuntos
Aquecimento Global , Modelos Teóricos , Viagem , Clima , Europa (Continente) , Humanos , Estações do Ano , Sensação Térmica , Tempo (Meteorologia)
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