ORCID Profile
0000-0002-5599-7456
Current Organisations
INAF-Osservatorio Astronomico di Capodimonte
,
CSIRO
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Publisher: American Astronomical Society
Date: 12-2022
Abstract: Wide Field Slitless Spectroscopy (WFSS) provides a powerful tool for detecting strong line emission in star-forming galaxies (SFGs) without the need for target preselection. As part of the GLASS-JWST Early Release Science (ERS) program, we leverage the near-infrared wavelength capabilities of NIRISS (1–2.2 μ m) to observe rest-optical emission lines out to z ∼ 3.4, to a depth and with a spatial resolution higher than ever before (H α to z 2.4 [O iii ]+H β to z 3.4). In this Letter we constrain the rest-frame [O III ] λ 5007 equivalent width (EW) distribution for a s le of 76 1 z 3.4 SFGs in the A2744 Hubble Frontier Field and determine an abundance fraction of extreme emission line galaxies with EW 750Å in our s le to be 12%. We determine a strong correlation between the measured H β and [O III ] λ 5007 EWs, supporting that the high [O III ] λ 5007 EW objects require massive stars in young stellar populations to generate the high-energy photons needed to doubly ionize oxygen. We extracted spectra for objects up to 2 mag fainter in the near-infrared than previous WFSS studies with the Hubble Space Telescope. Thus, this work clearly highlights the potential of JWST/NIRISS to provide high-quality WFSS data sets in crowded cluster environments.
Publisher: Elsevier BV
Date: 11-2019
Publisher: MDPI AG
Date: 04-06-2021
DOI: 10.3390/RS13112197
Abstract: Digital agriculture services can greatly assist growers to monitor their fields and optimize their use throughout the growing season. Thus, knowing the exact location of fields and their boundaries is a prerequisite. Unlike property boundaries, which are recorded in local council or title records, field boundaries are not historically recorded. As a result, digital services currently ask their users to manually draw their field, which is time-consuming and creates disincentives. Here, we present a generalized method, hereafter referred to as DECODE (DEtect, COnsolidate, and DElinetate), that automatically extracts accurate field boundary data from satellite imagery using deep learning based on spatial, spectral, and temporal cues. We introduce a new convolutional neural network (FracTAL ResUNet) as well as two uncertainty metrics to characterize the confidence of the field detection and field delineation processes. We finally propose a new methodology to compare and summarize field-based accuracy metrics. To demonstrate the performance and scalability of our method, we extracted fields across the Australian grains zone with a pixel-based accuracy of 0.87 and a field-based accuracy of up to 0.88 depending on the metric. We also trained a model on data from South Africa instead of Australia and found it transferred well to unseen Australian landscapes. We conclude that the accuracy, scalability and transferability of DECODE shows that large-scale field boundary extraction based on deep learning has reached operational maturity. This opens the door to new agricultural services that provide routine, near-real time field-based analytics.
Publisher: Elsevier BV
Date: 2018
Publisher: MDPI AG
Date: 03-08-2020
DOI: 10.3390/RS12152483
Abstract: In remote sensing, the term accuracy typically expresses the degree of correctness of a map. Best practices in accuracy assessment have been widely researched and include guidelines on how to select validation data using probability s ling designs. In practice, however, probability s les may be lacking and, instead, cross-validation using non-probability s les is common. This practice is risky because the resulting accuracy estimates can easily be mistaken for map accuracy. The following question arises: to what extent are accuracy estimates obtained from non-probability s les representative of map accuracy? This letter introduces the T index to answer this question. Certain cross-validation designs (such as the common single-split or hold-out validation) provide representative accuracy estimates when hold-out sets are simple random s les of the map population. The T index essentially measures the probability of a hold-out set of unknown s ling design to be a simple random s le. To that aim, we compare its spread in the feature space against the spread of random unlabelled s les of the same size. Data spread is measured by a variant of Moran’s I autocorrelation index. Consistent interpretation of the T index is proposed through the prism of significance testing, with T values 0.05 indicating unreliable accuracy estimates. Its relevance and interpretation guidelines are also illustrated in a case study on crop-type mapping. Uptake of the T index by the remote-sensing community will help inform about—and sometimes caution against—the representativeness of accuracy estimates obtained by cross-validation, so that users can better decide whether a map is fit for their purpose or how its accuracy impacts their application. Subsequently, the T index will build trust and improve the transparency of accuracy assessment in conditions which deviate from best practices.
Publisher: American Astronomical Society
Date: 04-2023
Abstract: We present the spectroscopic confirmation of a protocluster at z = 7.88 behind the galaxy cluster Abell 2744 (hereafter A2744-z7p9OD). Using JWST NIRSpec, we find seven galaxies within a projected radius of 60 kpc. Although the galaxies reside in an overdensity around ≳20× greater than a random volume, they do not show strong Ly α emission. We place 2 σ upper limits on the rest-frame equivalent width –28 Å. Based on the tight upper limits to the Ly α emission, we constrain the volume-averaged neutral fraction of hydrogen in the intergalactic medium to be x HI 0.45 (68% C i ). Using an empirical M UV – M halo relation for in idual galaxies, we estimate that the total halo mass of the system is ≳4 × 10 11 M ⊙ . Likewise, the line-of-sight velocity dispersion is estimated to be 1100 ± 200 km s −1 . Using an empirical relation, we estimate the present-day halo mass of A2744-z7p9OD to be ∼2 × 10 15 M ⊙ , comparable to the Coma cluster. A2744-z7p9OD is the highest redshift spectroscopically confirmed protocluster to date, demonstrating the power of JWST to investigate the connection between dark-matter halo assembly and galaxy formation at very early times with medium-deep observations at hr total exposure time. Follow-up spectroscopy of the remaining photometric candidates of the overdensity will further refine the features of this system and help characterize the role of such overdensities in cosmic reionization.
Publisher: Elsevier BV
Date: 04-2020
Publisher: MDPI AG
Date: 18-11-2015
DOI: 10.3390/RS71115494
Publisher: American Astronomical Society
Date: 12-2022
Abstract: We investigate the blue and optical rest-frame sizes ( λ ≃ 2300–4000 Å) of three compact star-forming regions in a galaxy at z = 4 strongly lensed (×30, ×45, and ×100) by the Hubble Frontier Field galaxy cluster A2744 using GLASS-ERS James Webb Space Telescope (JWST)/NIRISS imaging at 1.15 μ m, 1.50 μ m, and 2.0 μ m with a point-spread function ≲0.″1. In particular, the Balmer break is probed in detail for all multiply imaged sources of the system. With ages of a few tens of Myr, stellar masses in the range (0.7–4.0) ×10 6 M ⊙ and optical/ultraviolet effective radii spanning the interval 3 R eff 20 pc, such objects are currently the highest-redshift (spectroscopically confirmed) gravitationally bound young massive star clusters (YMCs), with stellar mass surface densities resembling those of local globular clusters. Optical (4000 Å, JWST-based) and ultraviolet (1600 Å, Hubble Space Telescope–based) sizes are fully compatible. The contribution to the ultraviolet underlying continuum emission (1600 Å) is ∼30%, which decreases by a factor of 2 in the optical for two of the YMCs (∼4000 Å rest-frame), reflecting the young ages ( Myr) inferred from the spectral energy distribution fitting and supported by the presence of high-ionization lines secured with the Very Large Telescope/MUSE. Such bursty forming regions enhance the specific star formation rate of the galaxy, which is ≃10 Gyr −1 . This galaxy would be among the extreme analogs observed in the local universe having a high star formation rate surface density and a high occurrence of massive stellar clusters in formation.
Publisher: IOP Publishing
Date: 11-2020
Abstract: The increasingly chaotic nature of rainfall in semi-arid climates challenges crop growers to balance nitrogen fertiliser inputs for both food security and environmental imperatives. Too little nitrogen restricts yields and runs down soil organic carbon, while too much nitrogen is economically wasteful and environmentally harmful. The degree to which crop-water and crop-nitrogen processes combine to drive yields of rainfed wheat crops is not well understood or quantified. Here we investigate two comprehensive Australia-wide data sets, one from commercial wheat growers’ fields and the other from systematic simulation of 50 sites by 15 years using a comprehensive mechanistic cropping system model. From these data, we derived a simple model combining water use with available nitrogen and their interaction. The model accounted for 73% of the variation in the simulated yield data and 46% of the variation in the growers’ yield data. We demonstrate how the simple model developed here can be deployed as a tool to aid growers’ in-crop nitrogen application decisions.
Publisher: American Astronomical Society
Date: 10-2022
Abstract: We present the first search for z ≥ 7, continuum-confirmed Lyman break sources with NIRISS/WFS spectroscopy over the Abell 2744 Frontier Fields cluster, as part of the GLASS-JWST-ERS survey. With ∼15 hr of preimaging and multiangle grism exposures in the F115W, F150W, and F200W filters, we describe the general data handling (i.e., reduction, cleaning, modeling, and extraction processes) and analysis for the GLASS-JWST survey. We showcase the power of JWST to peer deep into reionization, when most intergalactic hydrogen is neutral, by confirming two galaxies at z = 8.04 ± 0.15 and z = 7.90 ± 0.13 by means of their Lyman breaks. Fainter continuum spectra are observed in both the F150W and F200W bands, indicative of blue (−1.69 and −1.33) UV slopes and moderately bright absolute magnitudes (−20.37 and −19.68 mag). We do not detect strong Ly α in either galaxy, but do observe tentative (∼2.7–3.8 σ ) He ii λ 1640 Å, O iii ] λλ 1661,1666 Å, and N iii ] λλ 1747,1749 Å line emission in one, suggestive of low-metallicity, star-forming systems with possible nonthermal contributions. These novel observations provide a first look at the extraordinary potential of JWST/NIRISS for confirming representative s les of bright z ≥ 7 sources in the absence of strong emission lines, and gain unprecedented insight into their contributions toward cosmic reionization.
Publisher: MDPI AG
Date: 17-06-2015
DOI: 10.3390/RS70607959
Publisher: Elsevier BV
Date: 08-2020
Publisher: Elsevier BV
Date: 12-2015
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-102
Abstract: & & Many of the promises of smart farming centre on assisting farmers to monitor their fields throughout the growing season. Having precise field boundaries has thus become a prerequisite for field-level assessment. When farmers are being signed up by agricultural service providers, they are often asked for precise digital records of their boundaries. Unfortunately, this process remains largely manual, time-consuming and prone to errors which creates disincentives.& There are also increasing applications whereby remote monitoring of crops using earth observation is used for estimating areas of crop planted and yield forecasts. Automating the extraction of field boundaries would facilitate bringing farmers on board, and hence fostering wider adoption of these services, but would also improve products and services to be provided using remote sensing. Several methods to extract field boundaries from satellite imagery have been proposed, but the apparent lack of field boundary data sets seems to indicate low uptake, presumably because of expensive image preprocessing requirements and local, often arbitrary, tuning. Here, we introduce a novel approach with low image preprocessing requirements to extract field boundaries from satellite imagery. It poses the problem as a semantic segmentation problem with three tasks designed to answer the following questions: & ) Does a given pixel belong to a field? 2) Is that pixel part of a field boundary? and 3) What is the distance from that pixel to the closest field boundary? Closed field boundaries and in idual fields can then be extracted by combining the answers to these three questions. The tasks are performed with ResUNet-a, a deep convolutional neural network with a fully connected UNet backbone that features dilated convolutions and conditioned inference. First, we characterise the model& #8217 s performance at local scale. Using a single composite image from Sentinel-2 over South Africa, the model is highly accurate in mapping field extent, field boundaries, and, consequently, in idual fields. Replacing the monthly composite with a single-date image close to the compositing period marginally decreases accuracy. We then show that, without recalibration, ResUNet-a generalises well across resolutions (10 m to 30 m), sensors (Sentinel-2 to Landsat-8), space and time. Averaging model predictions from at least four images well-distributed across the season is the key to coping with the temporal variations of accuracy.& Finally, we apply the lessons learned from the previous experiments to extract field boundaries for the whole of the Australian cropping region. To that aim, we compare three ResUNet-a models which are trained with different data sets: field boundaries from Australia, field boundaries from overseas, and field boundaries from both Australia and overseas (transfer learning). & & By minimising image preprocessing requirements and replacing local arbitrary decisions by data-driven ones, our approach is expected to facilitate the adoption of smart farming services and improve land management at scale.& &
Publisher: American Astronomical Society
Date: 05-2023
Abstract: We report the detection of a high density of redshift z ≈ 10 galaxies behind the foreground cluster A2744, selected from imaging data obtained recently with NIRCam on board JWST by three programs—GLASS-JWST, UNCOVER, and DDT#2756. To ensure robust estimates of the lensing magnification μ , we use an improved version of our model that exploits the first epoch of NIRCam images and newly obtained MUSE spectra and avoids regions with μ 5 where the uncertainty may be higher. We detect seven bright z ≈ 10 galaxies with demagnified rest frame −22 ≲ M UV ≲ −19 mag, over an area of ∼37 arcmin 2 . Taking into account photometric incompleteness and the effects of lensing on luminosity and cosmological volume, we find that the density of z ≈ 10 galaxies in the field is about 10× (3×) larger than the average at M UV ≈ −21 ( −20) mag reported so far. The density is even higher when considering only the GLASS-JWST data, which are the deepest and the least affected by magnification and incompleteness. The GLASS-JWST field contains five out of seven galaxies, distributed along an apparent filamentary structure of 2 Mpc in projected length, and includes a close pair of candidates with M UV −20 mag having a projected separation of only 16 kpc. These findings suggest the presence of a z ≈ 10 overdensity in the field. In addition to providing excellent targets for efficient spectroscopic follow-up observations, our study confirms the high density of bright galaxies observed in early JWST observations but calls for multiple surveys along independent lines of sight to achieve an unbiased estimate of their average density and a first estimate of their clustering.
Publisher: Elsevier BV
Date: 08-2017
Publisher: American Astronomical Society
Date: 04-2023
Abstract: The JWST observations of high-redshift galaxies are used to measure their star formation histories—the buildup of stellar mass in the earliest galaxies. Here we use a novel analysis program, SEDz*, to compare near-IR spectral energy distributions for galaxies with redshifts 5 z 7 to combinations of stellar population templates evolved from z = 12. We exploit NIRCam imaging in seven wide bands covering 1–5 μ m taken in the context of the GLASS-JWST-ERS program and use SEDz* to solve for well-constrained star formation histories for 24 exemplary galaxies. In this first look, we find a variety of histories, from long, continuous star formation over 5 z 12 to short but intense starbursts, sometimes repeating, and, most commonly, contiguous mass buildup lasting ∼0.5 Myr, possibly the seeds of today’s typical M * galaxies.
Publisher: Informa UK Limited
Date: 19-12-2017
Publisher: MDPI AG
Date: 13-11-2022
DOI: 10.3390/RS14225738
Abstract: Crop field boundaries aid in mapping crop types, predicting yields, and delivering field-scale analytics to farmers. Recent years have seen the successful application of deep learning to delineating field boundaries in industrial agricultural systems, but field boundary datasets remain missing in smallholder systems due to (1) small fields that require high resolution satellite imagery to delineate and (2) a lack of ground labels for model training and validation. In this work, we use newly-accessible high-resolution satellite imagery and combine transfer learning with weak supervision to address these challenges in India. Our best model uses 1.5 m resolution Airbus SPOT imagery as input, pre-trains a state-of-the-art neural network on France field boundaries, and fine-tunes on India labels to achieve a median Intersection over Union (mIoU) of 0.85 in India. When we decouple field delineation from cropland classification, a model trained in France and applied as-is to India Airbus SPOT imagery delineates fields with a mIoU of 0.74. If using 4.8 m resolution PlanetScope imagery instead, high average performance (mIoU 0.8) is only achievable for fields larger than 1 hectare. Experiments also show that pre-training in France reduces the number of India field labels needed to achieve a given performance level by as much as 10× when datasets are small. These findings suggest our method is a scalable approach for delineating crop fields in regions of the world that currently lack field boundary datasets. We publicly release 10,000 Indian field boundary labels and our delineation model to facilitate the creation of field boundary maps and new methods by the community.
Publisher: F1000 Research Ltd
Date: 29-11-2017
DOI: 10.12688/F1000RESEARCH.12037.3
Abstract: Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.
Publisher: F1000 Research Ltd
Date: 11-2017
DOI: 10.12688/F1000RESEARCH.12037.2
Abstract: Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.
Publisher: Informa UK Limited
Date: 06-08-2017
Publisher: MDPI AG
Date: 03-12-2015
DOI: 10.3390/RS71215818
Publisher: American Astronomical Society
Date: 2023
Abstract: We present the serendipitous discovery of a late T-type brown dwarf candidate in JWST NIRCam observations of the Early Release Science Abell 2744 parallel field. The discovery was enabled by the sensitivity of JWST at 4 μ m wavelengths and the panchromatic 0.9–4.5 μ m coverage of the spectral energy distribution. The unresolved point source has magnitudes F115W = 27.95 ± 0.15 and F444W = 25.84 ± 0.01 (AB), and its F115W−F444W and F356W−F444W colors match those expected for other known T dwarfs. We can exclude it as a reddened background star, high redshift quasar, or a very high redshift galaxy. Comparison with stellar atmospheric models indicates a temperature of T eff ≈ 650 K and surface gravity log g ≈ 5.25 , implying a mass of 0.03 M ⊙ and age of 5 Gyr. We estimate the distance of this candidate to be 570–720 pc in a direction perpendicular to the Galactic plane, making it a likely thick disk or halo brown dwarf. These observations underscore the power of JWST to probe the very low-mass end of the substellar mass function in the Galactic thick disk and halo.
Publisher: MDPI AG
Date: 06-10-2015
DOI: 10.3390/RS71013208
Publisher: Center for Open Science
Date: 03-09-2020
Abstract: Many private and public actors are incentivized by big data technologies: digital tools underpinned by capabilities such as artificial intelligence and machine learning. While many shared value propositions exist about what these technologies afford, public facing concerns related to in idual privacy, algorithm fairness, and access to insights require attention if the widespread use and subsequent value of these technologies are to be fully realized. Drawing from perspectives of data science, social science and technology acceptance, we present an interdisciplinary analysis that reveals the connections between these concerns and traditional research and development (R& D) activities of data collection, technology development and implementation. Given the behaviors associated with digital transformation opportunities, we suggest a reframing of the public-facing R& D ‘brand’ that responds to legitimate concerns related to in idual privacy, fairness, and social equity. We offer as a case study Australian agriculture, which is currently undergoing such digitalisation and where concerns have been raised by landholders and the research community. With seemingly limitless possibilities, an updated account of responsible R& D in an increasing digitalized world may accelerate how we might realize benefits of big data and mitigate harmful social and environmental costs.
Publisher: MDPI AG
Date: 09-06-2016
DOI: 10.3390/RS8060488
Publisher: Springer Science and Business Media LLC
Date: 31-10-2019
DOI: 10.1038/S41598-019-51715-7
Abstract: Empirical yield estimation from satellite data has long lacked suitable combinations of spatial and temporal resolutions. Consequently, the selection of metrics, i . e ., temporal descriptors that predict grain yield, has likely been driven by practicality and data availability rather than by systematic targetting of critically sensitive periods as suggested by knowledge of crop physiology. The current trend towards hyper-temporal data raises two questions: How does temporality affect the accuracy of empirical models? Which metrics achieve optimal performance? We followed an in silico approach based on crop modelling which can generate any observation frequency, explore a range of growing conditions and reduce the cost of measuring yields in situ . We simulated wheat crops across Australia and regressed six types of metrics derived from the resulting time series of Leaf Area Index (LAI) against wheat yields. Empirical models using advanced LAI metrics achieved national relevance and, contrary to simple metrics, did not benefit from the addition of weather information. This suggests that they already integrate most climatic effects on yield. Simple metrics remained the best choice when LAI data are sparse. As we progress into a data-rich era, our results support a shift towards metrics that truly harness the temporal dimension of LAI data.
Publisher: American Astronomical Society
Date: 05-2023
Abstract: We combine JWST/NIRCam imaging and MUSE data to characterize the properties of galaxies in different environmental conditions in the cluster Abell2744 ( z = 0.3064) and in its immediate surroundings. We investigate how galaxy colors, morphology, and star-forming fractions depend on wavelength and on different parameterizations of environment. Our most striking result is the discovery of a “red excess” population in F200W−F444W colors in both the cluster regions and the field. These galaxies have normal F115W−F150W colors but are up to 0.8 mag redder than red sequence galaxies in F200W−F444W. They also have rather blue rest-frame B − V colors. Galaxies in the field and at the cluster virial radius are overall characterized by redder colors, but galaxies with the largest color deviations are found in the field and in the cluster core. Several results suggest that mechanisms taking place in these regions might be more effective in producing these colors. Looking at their morphology, many cluster galaxies show signatures consistent with ram pressure stripping, while field galaxies have features resembling interactions and mergers. Our hypothesis is that these galaxies are characterized by dust-enshrouded star formation: a JWST/NIRSpec spectrum for one of the galaxies is dominated by a strong PAH at 3.3 μ m, suggestive of dust-obscured star formation. Larger spectroscopic s les are needed to understand whether the color excess is due exclusively to dust-obscured star formation, as well as the role of environment in triggering it.
Publisher: MDPI AG
Date: 08-06-2015
DOI: 10.3390/RS70607545
Publisher: Elsevier BV
Date: 04-2020
Publisher: MDPI AG
Date: 11-03-2016
DOI: 10.3390/RS8030232
Publisher: MDPI AG
Date: 23-01-2018
DOI: 10.3390/RS10020159
Publisher: Springer Science and Business Media LLC
Date: 31-08-2016
Publisher: CSIRO Publishing
Date: 21-03-2022
DOI: 10.1071/CP21386
Abstract: The Australian dryland grain-cropping landscape occupies 60 Mha. The broader agricultural sector (farmers and agronomic advisors, grain handlers, commodity forecasters, input suppliers, insurance providers) required information at many spatial and temporal scales. Temporal scales included hindcasts, nowcasts and forecasts, at spatial scales ranging from sub-field to the continent. International crop-monitoring systems could not service the need of local industry for digital information on crop production estimates. Therefore, we combined a broad suite of satellite-based crop-mapping, crop-modelling and data-delivery techniques to create an integrated analytics system (Graincast™) that covers the Australian cropping landscape. In parallel with technical developments, a set of user requirements was identified through a human-centred design process, resulting in an end-product that delivered a viable crop-monitoring service to industry. This integrated analytics solution can now produce crop information at scale and on demand and can deliver the output via an application programming interface. The technology was designed to underpin digital agriculture developments for Australia. End-users are now using crop-monitoring data for operational purposes, and we argue that a vertically integrated data supply chain is required to develop crop-monitoring technology further.
Publisher: MDPI AG
Date: 23-04-2020
DOI: 10.3390/RS12081337
Abstract: Fallows are widespread in dryland cropping systems. However, timely information about their spatial extent and location remains scarce. To overcome this lack of information, we propose to classify fractional cover data from Sentinel-2 with biased support vector machines. Fractional cover images describe the land surface in intuitive, biophysical terms, which reduces the spectral variability within the fallow class. Biased support vector machines are a type of one-class classifiers that require labelled data for the class of interest and unlabelled data for the other classes. They allow us to extrapolate in-situ observations collected during flowering to the rest of the growing season to generate large training data sets, thereby reducing the data collection requirements. We tested this approach to monitor fallows in the northern grains region of Australia and showed that the seasonal fallow extent can be mapped with % accuracy both during the summer and winter seasons. The summer fallow extent can be accurately mapped as early as mid-December (1–4 months before harvest). The winter fallow extent can be accurately mapped from mid-August (2–4 months before harvest). Our method also detected emergence dates successfully, indicating the near real-time accuracy of our method. We estimated that the extent of fallow fields across the northern grains region of Australia ranged between 50% in winter 2017 and 85% in winter 2019. Our method is scalable, sensor independent and economical to run. As such, it lays the foundations for reconstructing and monitoring the cropping dynamics in Australia.
Publisher: Elsevier BV
Date: 02-2019
Publisher: American Astronomical Society
Date: 10-2022
Abstract: We present the results of a first search for galaxy candidates at z ∼ 9–15 on deep seven-band NIRCam imaging acquired as part of the GLASS-James Webb Space Telescope (JWST) Early Release Science Program on a flanking field of the Frontier Fields cluster A2744. Candidates are selected via two different renditions of the Lyman-break technique, isolating objects at z ∼ 9–11, and z ∼ 9–15, respectively, supplemented by photometric redshifts obtained with two independent codes. We find five color-selected candidates at z 9, plus one additional candidate with photometric redshift z phot ≥ 9. In particular, we identify two bright candidates at M UV ≃ −21 that are unambiguously placed at z ≃ 10.6 and z ≃ 12.2, respectively. The total number of galaxies discovered at z 9 is in line with the predictions of a nonevolving luminosity function. The two bright ones at z 10 are unexpected given the survey volume, although cosmic variance and small number statistics limits general conclusions. This first search demonstrates the unique power of JWST to discover galaxies at the high-redshift frontier. The candidates are ideal targets for spectroscopic follow-up in Cycle-2.
Publisher: Elsevier BV
Date: 09-2020
Publisher: F1000 Research Ltd
Date: 20-07-2017
DOI: 10.12688/F1000RESEARCH.12037.1
Abstract: Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of Web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform current models while avoiding as many of the biases of existing systems as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that, at least partially, resolves many of the technical and social issues associated with peer review, and can potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.
Publisher: MDPI AG
Date: 13-08-2015
DOI: 10.3390/RS70810400
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 12-2018
Publisher: EDP Sciences
Date: 21-11-2019
DOI: 10.1051/0004-6361/201936550
Abstract: Context. The upcoming new generation of optical spectrographs on four-meter-class telescopes, with their huge multiplexing capabilities, excellent spectral resolution, and unprecedented wavelength coverage, will provide invaluable information for reconstructing the history of star formation in in idual galaxies up to redshifts of about 0.7. Aims. We aim at defining simple but robust and meaningful physical parameters that can be used to trace the coexistence of widely erse stellar components: younger stellar populations superimposed on the bulk of older ones. Methods. We produced spectra of galaxies closely mimicking data from the forthcoming Stellar Populations at intermediate redshifts Survey (StePS), a survey that uses the WEAVE spectrograph on the William Herschel Telescope. First, we assessed our ability to reliably measure both ultraviolet and optical spectral indices in galaxies of different spectral types for typically expected signal-to-noise ratios. We then analyzed such mock spectra with a Bayesian approach, deriving the probability density function of r - and u -band light-weighted ages as well as of their difference. Results. We find that the ultraviolet indices significantly narrow the uncertainties in estimating the r - and u -band light-weighted ages and their difference in in idual galaxies. These diagnostics, robustly retrievable for large galaxy s les even when observed at moderate signal-to-noise ratios, allow us to identify secondary episodes of star formation up to an age of ∼0.1 Gyr for stellar populations older than ∼1.5 Gyr, pushing up to an age of ∼1 Gyr for stellar populations older than ∼5 Gyr. Conclusions. The difference between r -band and u -band light-weighted ages is shown to be a powerful diagnostic to characterize and constrain extended star-formation histories and the presence of young stellar populations on top of older ones. This parameter can be used to explore the interplay between different galaxy star-formation histories and physical parameters such as galaxy mass, size, morphology, and environment.
Publisher: Oxford University Press (OUP)
Date: 12-06-2023
Abstract: We present a search and characterization of ultra-diffuse galaxies (UDGs) in the Frontier Fields cluster Abell 2744 at $z$ = 0.308. We use JWST/NIRISS F200W observations, acquired as part of the GLASS-JWST Early Release Science programme, aiming to characterize morphologies of cluster UDGs and their diffuse stellar components. A total number of 22 UDGs are identified by our selection criteria using morphological parameters, down to stellar mass of ∼107 M⊙. The selected UDGs are systematically larger in effective radius in F200W than in Hubble Space Telescope (HST)/ACS F814W images, which implies that some of them would not have been identified as UDGs when selected at rest-frame optical wavelengths. In fact, we find that about one-third of the UDGs were not previously identified based on the F814W data. We observe a flat distribution of the UDGs in the stellar mass–size plane, similar to what is found for cluster quiescent galaxies at comparable mass. Our pilot study using the new JWST F200W filter showcases the efficiency of searching UDGs at cosmological distances, with 1/30 of the exposure time of the previous deep observing c aign with HST. Further studies with JWST focusing on spatially resolved properties of in idual sources will provide insight into their origin.
Publisher: F1000 Research Ltd
Date: 09-06-2016
DOI: 10.12688/F1000RESEARCH.8460.2
Abstract: Ongoing debates surrounding Open Access to the scholarly literature are multifaceted and complicated by disparate and often polarised viewpoints from engaged stakeholders. At the current stage, Open Access has become such a global issue that it is critical for all involved in scholarly publishing, including policymakers, publishers, research funders, governments, learned societies, librarians, and academic communities, to be well-informed on the history, benefits, and pitfalls of Open Access. In spite of this, there is a general lack of consensus regarding the potential pros and cons of Open Access at multiple levels. This review aims to be a resource for current knowledge on the impacts of Open Access by synthesizing important research in three major areas: academic, economic and societal. While there is clearly much scope for additional research, several key trends are identified, including a broad citation advantage for researchers who publish openly, as well as additional benefits to the non-academic dissemination of their work. The economic impact of Open Access is less well-understood, although it is clear that access to the research literature is key for innovative enterprises, and a range of governmental and non-governmental services. Furthermore, Open Access has the potential to save both publishers and research funders considerable amounts of financial resources, and can provide some economic benefits to traditionally subscription-based journals. The societal impact of Open Access is strong, in particular for advancing citizen science initiatives, and leveling the playing field for researchers in developing countries. Open Access supersedes all potential alternative modes of access to the scholarly literature through enabling unrestricted re-use, and long-term stability independent of financial constraints of traditional publishers that impede knowledge sharing. However, Open Access has the potential to become unsustainable for research communities if high-cost options are allowed to continue to prevail in a widely unregulated scholarly publishing market. Open Access remains only one of the multiple challenges that the scholarly publishing system is currently facing. Yet, it provides one foundation for increasing engagement with researchers regarding ethical standards of publishing and the broader implications of 'Open Research'.
Publisher: Informa UK Limited
Date: 28-06-2016
Publisher: F1000 Research Ltd
Date: 11-04-2016
DOI: 10.12688/F1000RESEARCH.8460.1
Abstract: Ongoing debates surrounding Open Access to the scholarly literature are multifaceted and complicated by disparate and often polarised viewpoints from engaged stakeholders. At the current stage, Open Access has become such a global issue that it is critical for all involved in scholarly publishing, including policymakers, publishers, research funders, governments, learned societies, librarians, and academic communities, to be well-informed on the history, benefits, and pitfalls of Open Access. In spite of this, there is a general lack of consensus regarding the advantages or disadvantages of Open Access at multiple levels. This review aims to to be a resource for current knowledge on the impacts of Open Access by synthesizing important research in three major areas of impact: academic, economic and societal. While there is clearly much scope for additional research, several key trends are identified, including a broad citation advantage for researchers who publish openly, as well as additional benefits to the non-academic dissemination of their work. The economic case for Open Access is less well-understood, although it is clear that access to the research literature is key for innovative enterprises, and a range of governmental and non-governmental services. Furthermore, Open Access has the potential to save publishers and research funders considerable amounts of financial resources. The social case for Open Access is strong, in particular for advancing citizen science initiatives, and leveling the playing field for researchers in developing countries. Open Access supersedes all potential alternative modes of access to the scholarly literature through enabling unrestricted re-use, and long-term stability independent of financial constraints of traditional publishers that impede knowledge sharing. Open Access remains only one of the multiple challenges that the scholarly publishing system is currently facing. Yet, it provides one foundation for increasing engagement with researchers regarding ethical standards of publishing. We recommend that Open Access supporters focus their efforts on working to establish viable new models and systems of scholarly communication, rather than trying to undermine the existing ones as part of the natural evolution of the scholarly ecosystem. Based on this, future research should investigate the wider impacts of an ecosystem-wide transformation to a system of Open Research.
Publisher: MDPI AG
Date: 30-10-2015
DOI: 10.3390/IJGI4042379
Publisher: California Digital Library (CDL)
Date: 05-2019
Publisher: F1000 Research Ltd
Date: 21-09-2016
DOI: 10.12688/F1000RESEARCH.8460.3
Abstract: Ongoing debates surrounding Open Access to the scholarly literature are multifaceted and complicated by disparate and often polarised viewpoints from engaged stakeholders. At the current stage, Open Access has become such a global issue that it is critical for all involved in scholarly publishing, including policymakers, publishers, research funders, governments, learned societies, librarians, and academic communities, to be well-informed on the history, benefits, and pitfalls of Open Access. In spite of this, there is a general lack of consensus regarding the potential pros and cons of Open Access at multiple levels. This review aims to be a resource for current knowledge on the impacts of Open Access by synthesizing important research in three major areas: academic, economic and societal. While there is clearly much scope for additional research, several key trends are identified, including a broad citation advantage for researchers who publish openly, as well as additional benefits to the non-academic dissemination of their work. The economic impact of Open Access is less well-understood, although it is clear that access to the research literature is key for innovative enterprises, and a range of governmental and non-governmental services. Furthermore, Open Access has the potential to save both publishers and research funders considerable amounts of financial resources, and can provide some economic benefits to traditionally subscription-based journals. The societal impact of Open Access is strong, in particular for advancing citizen science initiatives, and leveling the playing field for researchers in developing countries. Open Access supersedes all potential alternative modes of access to the scholarly literature through enabling unrestricted re-use, and long-term stability independent of financial constraints of traditional publishers that impede knowledge sharing. However, Open Access has the potential to become unsustainable for research communities if high-cost options are allowed to continue to prevail in a widely unregulated scholarly publishing market. Open Access remains only one of the multiple challenges that the scholarly publishing system is currently facing. Yet, it provides one foundation for increasing engagement with researchers regarding ethical standards of publishing and the broader implications of 'Open Research'.
Publisher: Elsevier BV
Date: 02-2020
Publisher: Springer International Publishing
Date: 2020
Publisher: American Astronomical Society
Date: 12-01-2018
Publisher: IOP Publishing
Date: 10-03-2021
Publisher: Springer Science and Business Media LLC
Date: 25-01-2019
Publisher: American Astronomical Society
Date: 10-2022
Abstract: We present the reduced images and multiwavelength catalog of the first JWST NIRCam extragalactic observations from the GLASS Early Release Science Program, obtained as coordinated parallels of the NIRISS observations of the Abell 2744 cluster. Images in seven bands (F090W, F115W, F150W, F200W, F277W, F356W, and F444W) have been reduced using an augmented version of the official JWST pipeline we discuss the procedures adopted to remove or mitigate defects in the raw images. We obtain a multiband catalog by means of forced aperture photometry on point-spread function (PSF)-matched images at the position of F444W-detected sources. The catalog is intended to enable early scientific investigations, and it is optimized for faint galaxies it contains 6368 sources, with limiting magnitude 29.7 at 5 σ in F444W. We release both images and catalog in order to allow the community to become familiar with the JWST NIRCam data and evaluate their merit and limitations given the current level of knowledge of the instrument.
Publisher: American Astronomical Society
Date: 2023
Abstract: How passive galaxies form, and the physical mechanisms which prevent star formation over long timescales, are some of the most outstanding questions in understanding galaxy evolution. The properties of quiescent galaxies over cosmic time provide crucial information to identify the quenching mechanisms. Passive galaxies have been confirmed and studied out to z ∼ 4, but all of these studies have been limited to massive systems (mostly with log ( M star / M ⊙ ) 10.8 ). Using JWST-NIRISS grism slitless spectroscopic data from the GLASS-JWST Early Release Science program, we present spectroscopic confirmation of two quiescent galaxies at z spec = 2.650 − 0.006 + 0.004 and z spec = 2.433 − 0.016 + 0.032 (3 σ errors) with stellar masses of log ( M star / M ⊙ ) = 10.59 − 0.05 + 0.11 and log ( M star / M ⊙ ) = 10.07 − 0.03 + 0.06 (corrected for magnification factors of μ = 2.0 and μ = 2.1, respectively). The latter represents the first spectroscopic confirmation of the existence of low-mass quiescent galaxies at cosmic noon, showcasing the power of JWST to identify and characterize this enigmatic population.
Publisher: MDPI AG
Date: 16-09-2021
DOI: 10.3390/RS13183707
Abstract: Change detection, i.e., the identification per pixel of changes for some classes of interest from a set of bi-temporal co-registered images, is a fundamental task in the field of remote sensing. It remains challenging due to unrelated forms of change that appear at different times in input images. Here, we propose a deep learning framework for the task of semantic change detection in very high-resolution aerial images. Our framework consists of a new loss function, a new attention module, new feature extraction building blocks, and a new backbone architecture that is tailored for the task of semantic change detection. Specifically, we define a new form of set similarity that is based on an iterative evaluation of a variant of the Dice coefficient. We use this similarity metric to define a new loss function as well as a new, memory efficient, spatial and channel convolution Attention layer: the FracTAL. We introduce two new efficient self-contained feature extraction convolution units: the CEECNet and FracTALResNet units. Further, we propose a new encoder/decoder scheme, a network macro-topology, that is tailored for the task of change detection. The key insight in our approach is to facilitate the use of relative attention between two convolution layers in order to fuse them. We validate our approach by showing excellent performance and achieving state-of-the-art scores (F1 and Intersection over Union-hereafter IoU) on two building change detection datasets, namely, the LEVIRCD (F1: 0.918, IoU: 0.848) and the WHU (F1: 0.938, IoU: 0.882) datasets.
Publisher: MDPI AG
Date: 11-01-2020
DOI: 10.3390/RS12020257
Abstract: Reference data collected to validate land-cover maps are generally considered free of errors. In practice, however, they contain errors despite best efforts to minimize them. These errors propagate during accuracy assessment and tweak the validation results. For photo-interpreted reference data, the two most widely studied sources of error are systematic incorrect labeling and vigilance drops. How estimation errors, i.e., errors intrinsic to the response design, affect the accuracy of reference data is far less understood. In this paper, we analyzed the impact of estimation errors for two types of classification systems (binary and multiclass) as well as for two common response designs (point-based and partition-based) with a range of sub-s le sizes. Our quantitative results indicate that labeling errors due to proportion estimations should not be neglected. They further confirm that the accuracy of response designs depends on the class proportions within the s ling units, with complex landscapes being more prone to errors. As a result, response designs where the number of sub-s les is predefined and fixed are inefficient. To guarantee high accuracy standards of validation data with minimum data collection effort, we propose a new method to adapt the number of sub-s les for each s le during the validation process. In practice, sub-s les are incrementally selected and labeled until the estimated class proportions reach the desired level of confidence. As a result, less effort is spent on labeling univocal cases and the spared effort can be allocated to more ambiguous cases. This increases the reliability of reference data and of subsequent accuracy assessment. Across our study site, we demonstrated that such an approach could reduce the labeling effort by 50% to 75%, with greater gains in homogeneous landscapes. We contend that adopting this optimization approach will not only increase the efficiency of reference data collection, but will also help deliver more reliable accuracy estimates to the user community.
Publisher: MDPI AG
Date: 21-05-2020
DOI: 10.3390/RS12101653
Abstract: The onus for monitoring crop growth from space is its ability to be applied anytime and anywhere, to produce crop yield estimates that are consistent at both the subfield scale for farming management strategies and the country level for national crop yield assessment. Historically, the requirements for satellites to successfully monitor crop growth and yield differed depending on the extent of the area being monitored. Diverging imaging capabilities can be reconciled by blending images from high-temporal-frequency (HTF) and high-spatial-resolution (HSR) sensors to produce images that possess both HTF and HSR characteristics across large areas. We evaluated the relative performance of Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat, and blended imagery for crop yield estimates (2009–2015) using a carbon-turnover yield model deployed across the Australian cropping area. Based on the fraction of missing Landsat observations, we further developed a parsimonious framework to inform when and where blending is beneficial for nationwide crop yield prediction at a finer scale (i.e., the 25-m pixel resolution). Landsat provided the best yield predictions when no observations were missing, which occurred in 17% of the cropping area of Australia. Blending was preferred when % of Landsat observations were missing, which occurred in 33% of the cropping area of Australia. MODIS produced a lower prediction error when ≥42% of the Landsat images were missing (~50% of the cropping area). By identifying when and where blending outperforms predictions from either Landsat or MODIS, the proposed framework enables more accurate monitoring of biophysical processes and yields, while keeping computational costs low.
Publisher: Elsevier BV
Date: 12-2016
DOI: 10.1016/J.JENVMAN.2016.09.001
Abstract: The Asian Migratory locust (Locusta migratoria migratoria L.) is a pest that continuously threatens crops in the Amudarya River delta near the Aral Sea in Uzbekistan, Central Asia. Its development coincides with the growing period of its main food plant, a tall reed grass (Phragmites australis), which represents the predominant vegetation in the delta and which cover vast areas of the former Aral Sea, which is desiccating since the 1960s. Current locust survey methods and control practices would tremendously benefit from accurate and timely spatially explicit information on the potential locust habitat distribution. To that aim, satellite observation from the MODIS Terra/Aqua satellites and in-situ observations were combined to monitor potential locust habitats according to their corresponding risk of infestations along the growing season. A Random Forest (RF) algorithm was applied for classifying time series of MODIS enhanced vegetation index (EVI) from 2003 to 2014 at an 8-day interval. Based on an independent ground truth data set, classification accuracies of reeds posing a medium or high risk of locust infestation exceeded 89% on average. For the 12-year period covered in this study, an average of 7504 km
Publisher: Springer Science and Business Media LLC
Date: 17-05-2023
Publisher: Elsevier BV
Date: 08-2019
Publisher: Public Library of Science (PLoS)
Date: 17-08-2017
Publisher: MDPI AG
Date: 19-03-2016
DOI: 10.3390/DATA1010003
Publisher: Springer Science and Business Media LLC
Date: 26-09-2017
Abstract: A global reference data set on cropland was collected through a crowdsourcing c aign using the Geo-Wiki crowdsourcing tool. The c aign lasted three weeks, with over 80 participants from around the world reviewing almost 36,000 s le units, focussing on cropland identification. For quality assessment purposes, two additional data sets are provided. The first is a control set of 1,793 s le locations validated by students trained in satellite image interpretation. This data set was used to assess the quality of the crowd as the c aign progressed. The second data set contains 60 expert validations for additional evaluation of the quality of the contributions. All data sets are split into two parts: the first part shows all areas classified as cropland and the second part shows cropland average per location and user. After further processing, the data presented here might be suitable to validate and compare medium and high resolution cropland maps generated using remote sensing. These could also be used to train classification algorithms for developing new maps of land cover and cropland extent.
Location: Australia
No related grants have been discovered for Francois Waldner.