28,089 research outputs found
Horizontal accuracy assessment of very high resolution Google Earth images in the city of Rome, Italy
Google Earth (GE) has recently become the focus of increasing interest and popularity
among available online virtual globes used in scientific research projects, due to the
free and easily accessed satellite imagery provided with global coverage. Nevertheless,
the uses of this service raises several research questions on the quality and uncertainty
of spatial data (e.g. positional accuracy, precision, consistency), with implications for
potential uses like data collection and validation. This paper aims to analyze the
horizontal accuracy of very high resolution (VHR) GE images in the city of Rome
(Italy) for the years 2007, 2011, and 2013. The evaluation was conducted by using
both Global Positioning System ground truth data and cadastral photogrammetric
vertex as independent check points. The validation process includes the comparison of
histograms, graph plots, tests of normality, azimuthal direction errors, and the
calculation of standard statistical parameters. The results show that GE VHR imageries
of Rome have an overall positional accuracy close to 1 m, sufficient for deriving
ground truth samples, measurements, and large-scale planimetric maps
A Framework for SAR-Optical Stereogrammetry over Urban Areas
Currently, numerous remote sensing satellites provide a huge volume of
diverse earth observation data. As these data show different features regarding
resolution, accuracy, coverage, and spectral imaging ability, fusion techniques
are required to integrate the different properties of each sensor and produce
useful information. For example, synthetic aperture radar (SAR) data can be
fused with optical imagery to produce 3D information using stereogrammetric
methods. The main focus of this study is to investigate the possibility of
applying a stereogrammetry pipeline to very-high-resolution (VHR) SAR-optical
image pairs. For this purpose, the applicability of semi-global matching is
investigated in this unconventional multi-sensor setting. To support the image
matching by reducing the search space and accelerating the identification of
correct, reliable matches, the possibility of establishing an epipolarity
constraint for VHR SAR-optical image pairs is investigated as well. In
addition, it is shown that the absolute geolocation accuracy of VHR optical
imagery with respect to VHR SAR imagery such as provided by TerraSAR-X can be
improved by a multi-sensor block adjustment formulation based on rational
polynomial coefficients. Finally, the feasibility of generating point clouds
with a median accuracy of about 2m is demonstrated and confirms the potential
of 3D reconstruction from SAR-optical image pairs over urban areas.Comment: This is the pre-acceptance version, to read the final version, please
go to ISPRS Journal of Photogrammetry and Remote Sensing on ScienceDirec
Big Data Techniques to Improve Learning Access and Citizen Engagement for Adults in Urban Environments
This presentation explores the emerging concept of âBig Data in Educationâ and introduces
novel technologies and approaches for addressing inequalities in access to participation and
success in lifelong learning, to produce better life outcomes for urban citizens. It introduces
the work of the new Urban Big Data Centre (UBDC) at the University of Glasgow, presenting
a case study of its first data product â the integrated Multimedia City Data (iMCD) project.
Educational engagement and predictive factors are presented for adult learners, and older
adult learners, in a representative survey of 1500 households. This was followed up with
mobility tracking data using GPS data and wearable camera images, as well as one yearâs
worth of contextual data from over one hundred web sources (social media, news, weather).
The chapter introduces the complex dataset that can help stakeholders, academics, citizens
and other external users examine active aging and citizen learning engagement in the
modern urban city, and thus support the development of the learning city. It concludes with a call for a more three-dimensional view of citizen-learnersâ daily activity and mobility, such
as satellite, mobile phone and active travel application data, alongside administrative data
linkage to further explore lifelong learning participation and success. Policy implications are
provided for addressing inequalities, and interventions proposed for how cities might
promote equal and inclusive adult learning engagement in the face of continued austerity
cuts and falling adult learner numbers
Post-failure evolution analysis of a rainfall-triggered landslide by multi-temporal interferometry SAR approaches integrated with geotechnical analysis
Persistent Scatterers Interferometry (PSI) represents one of the most powerful techniques for Earth's surface deformation processes' monitoring, especially for long-term evolution phenomena. In this work, a dataset of 34 TerraSAR-X StripMap images (October 2013âOctober 2014) has been processed by two PSI techniques - Coherent Pixel Technique-Temporal Sublook Coherence (CPT-TSC) and Small Baseline Subset (SBAS) - in order to study the evolution of a slow-moving landslide which occurred on February 23, 2012 in the Papanice hamlet (Crotone municipality, southern Italy) and induced by a significant rainfall event (185 mm in three days). The mass movement caused structural damage (buildings' collapse), and destruction of utility lines (gas, water and electricity) and roads. The results showed analogous displacement rates (30â40 mm/yr along the Line of Sight â LOS-of the satellite) with respect to the pre-failure phase (2008â2010) analyzed in previous works. Both approaches allowed detect the landslide-affected area, however the higher density of targets identified by means of CPT-TSC enabled to analyze in detail the slope behavior in order to design possible mitigation interventions. For this aim, a slope stability analysis has been carried out, considering the comparison between groundwater oscillations and time-series of displacement. Hence, the crucial role of the interaction between rainfall and groundwater level has been inferred for the landslide triggering. In conclusion, we showed that the integration of geotechnical and remote sensing approaches can be seen as the best practice to support stakeholders to design remedial works.Peer ReviewedPostprint (author's final draft
First insights on the potential of Sentinel-1 for landslides detection
This paper illustrates the potential of Sentinel-1 for landslide detection, Accepted 23 March 2016 mapping and characterization with the aim of updating inventory maps and monitoring landslide activity. The study area is located in Molise, one of the smallest regions of Italy, where landslide processes are frequent. The results achieved by integrating Differential Synthetic Aperture Radar Interferometry (DInSAR) deformation maps and time series, and Geographical Information System (GIS) multilayer analysis (optical, geological, geomorphological, etc.) are shown. The adopted methodology is described followed by an analysis of future perspectives. Sixty-two landslides have been detected, thus allowing the updating of pre-existing landslide inventory maps. The results of our ongoing research show that Sentinel-1 might represent a signiïŹcant improvement in terms of exploitation of SAR data for landslide mapping and monitoring due to both the shorter revisit time (up to 6 days in the close future) and the wavelength used, which determine an higher coherence compared to other SAR sensors
Minimizing the residual topography effect on interferograms to improve DInSAR results: estimating land subsidence in Port-Said City, Egypt
The accurate detection of land subsidence rates in urban areas is important to identify damage-prone areas and provide decision-makers with useful information. Meanwhile, no precise measurements of land subsidence have been undertaken within the coastal Port-Said City in Egypt to evaluate its hazard in relationship to sea-level rise. In order to address this shortcoming, this work introduces and evaluates a methodology that substantially improves small subsidence rate estimations in an urban setting. Eight ALOS/PALSAR-1 scenes were used to estimate the land subsidence rates in Port-Said City, using the Small BAse line Subset (SBAS) DInSAR technique. A stereo pair of ALOS/PRISM was used to generate an accurate DEM to minimize the residual topography effect on the generated interferograms. A total of 347 well distributed ground control points (GCP) were collected in Port-Said City using the leveling instrument to calibrate the generated DEM. Moreover, the eight PALSAR scenes were co-registered using 50 well-distributed GCPs and used to generate 22 interferogram pairs. These PALSAR interferograms were subsequently filtered and used together with the coherence data to calculate the phase unwrapping. The phase-unwrapped interferogram-pairs were then evaluated to discard four interferograms that were affected by phase jumps and phase ramps. Results confirmed that using an accurate DEM (ALOS/PRISM) was essential for accurately detecting small deformations. The vertical displacement rate during the investigated period (2007â2010) was estimated to be â28 mm. The results further indicate that the northern area of Port-Said City has been subjected to higher land subsidence rates compared to the southern area. Such land subsidence rates might induce significant environmental changes with respect to sea-level rise
Vegetation Earth System Data Record (VESDR)
https://eosweb.larc.nasa.gov/project/dscovr/DSCOVR_VESDR_SDRG.pdfFirst author draftFirst author draf
Hyperspectral monitoring of green roof vegetation health state in sub-mediterranean climate: preliminary results
In urban and industrial environments, the constant increase of impermeable surfaces has
produced drastic changes in the natural hydrological cycle. Decreasing green areas not only produce
negative effects from a hydrological-hydraulic perspective, but also from an energy point of view,
modifying the urban microclimate and generating, as shown in the literature, heat islands in our cities.
In this context, green infrastructures may represent an environmental compensation action that can be
used to re-equilibrate the hydrological and energy balance and reduce the impact of pollutant load on
receiving water bodies. To ensure that a green infrastructure will work properly, vegetated areas have
to be continuously monitored to verify their health state. This paper presents a ground spectroscopy
monitoring survey of a green roof installed at the University of Calabria fulfilled via the acquisition
and analysis of hyperspectral data. This study is part of a larger research project financed by European
Structural funds aimed at understanding the influence of green roofs on rainwater management and
energy consumption for air conditioning in the Mediterranean area. Reflectance values were acquired
with a field-portable spectroradiometer that operates in the range of wavelengths 350â2500 nm.
The survey was carried out during the time period November 2014âJune 2015 and data were acquired
weekly. Climatic, thermo-physical, hydrological and hydraulic quantities were acquired as well and
related to spectral data. Broadband and narrowband spectral indices, related to chlorophyll content
and to chlorophyllâcarotenoid ratio, were computed. The two narrowband indices NDVI705 and SIPI
turned out to be the most representative indices to detect the plant health status
The agricultural impact of the 2015â2016 floods in Ireland as mapped through Sentinel 1 satellite imagery
peer-reviewedIrish Journal of Agricultural and Food Research | Volume 58: Issue 1
The agricultural impact of the 2015â2016 floods in Ireland as mapped through Sentinel 1 satellite imagery
R. OâHaraemail
, S. Green
and T. McCarthy
DOI: https://doi.org/10.2478/ijafr-2019-0006 | Published online: 11 Oct 2019
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Abstract
The capability of Sentinel 1 C-band (5 cm wavelength) synthetic aperture radio detection and ranging (RADAR) (abbreviated as SAR) for flood mapping is demonstrated, and this approach is used to map the extent of the extensive floods that occurred throughout the Republic of Ireland in the winter of 2015â2016. Thirty-three Sentinel 1 images were used to map the area and duration of floods over a 6-mo period from November 2015 to April 2016. Flood maps for 11 separate dates charted the development and persistence of floods nationally. The maximum flood extent during this period was estimated to be ~24,356 ha. The depth of rainfall influenced the magnitude of flood in the preceding 5 d and over more extended periods to a lesser degree. Reduced photosynthetic activity on farms affected by flooding was observed in Landsat 8 vegetation index difference images compared to the previous spring. The accuracy of the flood map was assessed against reports of flooding from affected farms, as well as other satellite-derived maps from Copernicus Emergency Management Service and Sentinel 2. Monte Carlo simulated elevation data (20 m resolution, 2.5 m root mean square error [RMSE]) were used to estimate the floodâs depth and volume. Although the modelled flood height showed a strong correlation with the measured river heights, differences of several metres were observed. Future mapping strategies are discussed, which include highâtemporal-resolution soil moisture data, as part of an integrated multisensor approach to flood response over a range of spatial scales
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