Grismadox gen. nov., a new Neotropical genus of ant-resembling spiders (Araneae, Corinnidae, Castianeirinae), including the description of two new species from Bolivia and Paraguay

A new genus and two new species of ant-resembling castianeirine spiders are described from the Neotropics. Grismadox gen. nov. comprises four species: Grismadox baueri sp. nov., and Grismadox mazaxoides (Perger & Duperré, 2021) comb. nov. from Bolivia, and Grismadox karugua sp. nov. (type species) and Grismadox mboitui (Pett, 2021) comb. nov. from Paraguay. All species are diagnosed and the new species are described and illustrated. Available ecological data suggests that all four species are primarily epigeal and inhabit Grassland and savannah type habitats.Fil: Pett, Brogan L.. University of Exeter; Reino Unido. Colección Cientifíca Para La Tierra; Paraguay. Biodiversity Inventory For Conservation; BélgicaFil: Rubio, Gonzalo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Misiones. Estación Experimental Agropecuaria Cerro Azul; ArgentinaFil: Perger, Robert. Colección Boliviana de Fauna; Bolivi

Unveiling the weak radio quasar population at z≥4

We applied image stacking on empty-field Faint Images of the Radio Sky at Twenty-Centimeters (FIRST) survey maps centred on optically identified high-redshift quasars at $z\geq4$ to uncover the hidden $\mu$Jy radio emission in these active galactic nuclei (AGN). The median stacking procedure for the full sample of $2229$ optically identified AGN uncovered an unresolved point source with an integrated flux density of 52$~\mu$Jy, with a signal-to-noise ratio $\sim10$. We co-added the individual image centre pixels to estimate the characteristic monochromatic radio power at $1.4~$GHz considering various values for the radio spectral index, revealing a radio population with $P_\mathrm{1.4GHz}\sim10^{24}~$W Hz$^{-1}$. Assuming that the entire radio emission originates from star-forming (SF) activity in the nuclear region of the host galaxy, we obtained an upper limit on the characteristic star formation rate, $\sim4200~$M$_\odot~$yr$^{-1}$. The angular resolution of FIRST images is insufficient to distinguish between the SF and AGN origin of radio emission at these redshifts. However, a comparison with properties of individual sources from the literature indicates that a mixed nature is likely. Future very long baseline interferometry radio observations and ultra-deep Square Kilometre Array surveys are expected to be sensitive enough to detect and resolve the central $1-10~$kpc region in the host galaxies, and thus discriminate between SF and AGN related emission.Comment: 9 pages, 3 figures, 3 tables, accepted for publication in MNRA

Assessing and Improving the Reliability of Volunteered Land Cover Reference Data

Volunteered geographic data are being used increasingly to support land cover mapping and validation, yet the reliability of the volunteered data still requires further research. This study proposes data-based guidelines to help design the data collection by assessing the reliability of volunteered data collected using the Geo-Wiki tool. We summarized the interpretation difficulties of the volunteers at a global scale, including those areas and land cover types that generate the most confusion. We also examined the factors affecting the reliability of majority opinion and individual classification. The results showed that the highest interpretation inconsistency of the volunteers occurred in the ecoregions of tropical and boreal forests (areas with relatively poor coverage of very high resolution images), the tundra (a unique region that the volunteers are unacquainted with), and savannas (transitional zones). The volunteers are good at identifying forests, snow/ice and croplands, but not grasslands and wetlands. The most confusing pairs of land cover types are also captured in this study and they vary greatly with different biomes. The reliability can be improved by providing more high resolution ancillary data, more interpretation keys in tutorials, and tools that assist in coverage estimation for those areas and land cover types that are most prone to confusion. We found that the reliability of the majority opinion was positively correlated with the percentage of volunteers selecting this choice and negatively related to their self-evaluated uncertainty when very high resolution images were available. Factors influencing the reliability of individual classifications were also compared and the results indicated that the interpretation difficulty of the target sample played a more important role than the knowledge base of the volunteers. The professional background and local knowledge had an influence on the interpretation performance, especially in identifying vegetation land cover types other than croplands. These findings can help in building a better filtering system to improve the reliability of volunteered data used in land cover validation and other applications

LACO-WIKI: an open access online portal for land cover validation

The LACO-Wiki tool represents an open access, online portal that offers standardized land cover validation at local to global scales. LACO-Wiki integrates the LACOVAL prototype for land cover validation and the Geo-Wiki system for visualization, validation and crowdsourcing of land cover. This paper presents a conceptual overview of the LACO-Wiki system and describes the main validation workflow, in which the user uploads the map for validation, creates a validation sample, carries out the sample interpretation and generates a report detailing the accuracy assessment. In addition to a land cover validation tool, LACO-Wiki is also intended to become an open access repository for calibration and validation data that can be used by the land monitoring community to improve future land cover products

Cropland Capture – A Game for Improving Global Cropland Maps

Current satellite-derived global land-cover products, which are crucial for many modelling and monitoring applications, show large disagreements when compared with each another. To help improve global land cover (in particular the cropland class), we developed a game called Cropland Capture. This is a simple cross-platform game for collecting image classifications that will be used to develop and validate global cropland maps in the future. In this paper, we describe the game design of Cropland Capture in detail, including aspects such as simplicity,efficiency in data collection and what mechanisms were implemented to ensure data quality.We also discuss the impact of incentives on attracting and sustaining players in the game

Cropland Capture: A gaming approach to improve global land cover

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Accurate and reliable information on global cropland extent is needed for a number of applications, e g. to estimate potential yield losses in the wake of a drought or for assessing future scenarios of climate change on crop production. However, current global land cover and cropland products are not accurate enough for many of these applications. One way forward is to increase the amount of data that are used to create these maps as well as for validation purposes. One method for doing this is to involve citizens in the classification of satellite imagery as undertaken using the Geo-Wiki tool. This paper outlines Cropland Capture, which is simplified game version of Geo-Wiki in which players classify satellite imagery based on whether they can see evidence of cropland or not. On overview of the game is provided along with some initial results from the first 3 months of game play. The paper concludes with a discussion of the future steps in this research

Crowdsourcing EO datasets to improve cloud detection algorithms and land cover change

Involving citizens in science is gaining considerable traction of late. With positive examples (e.g. Geo-Wiki, FotoQuest Austria), a number of projects are exploring the options to engage the public in contributing to scientific research, often by asking participants to collect some data or validate some results. The International Institute for Applied Systems Analysis (IIASA), with extensive experience in crowdsourcing and gamification, has joined Sinergise, Copernicus Masters 2016 winners, to engage the public in an initiative involving ESA’s Sentinel-2 satellite imagery. Sentinel-2 imagery offers high revisit times and sufficient resolution for land change detection applications. Unfortunately, simple (but fast) algorithms often fail due to many false-positives: changes in clouds are perceived as land changes. The ability to discriminate of cloudy pixels is thus crucial for any automatic or semi-automatic solutions that detect land change. A plethora of algorithms to distinguish clouds in Sentinel-2 data are available. However, there is a need for better data on where and when clouds occur to help improve these algorithms. To overcome this current gap in the data, we are engaging the public in this task. Using a number of tools, developed at IIASA, and Sentinel Hub services, which provide fast access to the entire global archive of Sentinel-2 data, the aim is to obtain a large data resource of curated cloud classifications. The resulting dataset will be published as open data and made available through Geopedia platform. The gamified process will start by asking users if there are clouds on a small image (e.g. 8x8 pixels at the highest Sentinel-2 resolution of 10 m/px), which will provide us with a screening process to pinpoint cloudy areas, employing Picture Pile crowdsourcing game from IIASA. The next step will involve a more detailed workflow, as users will get a slightly larger image (e.g. 64x64 pixels) and will then be asked to delineate different types of clouds: opaque clouds (nothing is seen through the clouds), thick clouds (where the surface is still discernible through the clouds), and thin clouds (where the surface is unequivocally covered by a cloud); the rest of the image will be implicitly cloud-free. The resulting data will be made available through the Geopedia portal, both for exploring and downloading. This paper will demonstrate this process and show some results from a crowdsourcing campaign. The approach will also allow us to collect other datasets in a rapid and efficient manner. For example, using a slightly modified configuration, a similar workflow could be used to obtain a manually curated land cover classification data set, which could be used as training data for machine learning algorithms

LACO-Wiki: A land cover validation tool and a new, innovative teaching resource for remote sensing and the geosciences

The validation of land cover products is an important step in the workflow of generating a land cover map from remotely-sensed imagery. Many students of remote sensing will be given exercises on classifying a land cover map followed by the validation process. Many algorithms exist for classification, embedded within proprietary image processing software or increasingly as open source tools. However, there is little standardization for land cover validation, nor a set of open tools available for implementing this process. The LACO-Wiki tool was developed as a way of filling this gap, bringing together standardized land cover validation methods and workflows into a single portal. This includes the storage and management of land cover maps and validation data; step-by-step instructions to guide users through the validation process; sound sampling designs; an easy-to-use environment for validation sample interpretation; and the generation of accuracy reports based on the validation process. The tool was developed for a range of users including producers of land cover maps, researchers, teachers and students. The use of such a tool could be embedded within the curriculum of remote sensing courses at a university level but is simple enough for use by students aged 13-18. A beta version of the tool is available for testing at: http://www.lacowiki.net

First detection of thermal radio jets in a sample of proto-brown dwarf candidates

We observed with the JVLA at 3.6 and 1.3 cm a sample of 11 proto-brown dwarf candidates in Taurus in a search for thermal radio jets driven by the most embedded brown dwarfs. We detected for the first time four thermal radio jets in proto-brown dwarf candidates. We compiled data from UKIDSS, 2MASS, Spitzer, WISE and Herschel to build the Spectral Energy Distribution (SED) of the objects in our sample, which are similar to typical Class~I SEDs of Young Stellar Objects (YSOs). The four proto-brown dwarf candidates driving thermal radio jets also roughly follow the well-known trend of centimeter luminosity against bolometric luminosity determined for YSOs, assuming they belong to Taurus, although they present some excess of radio emission compared to the known relation for YSOs. Nonetheless, we are able to reproduce the flux densities of the radio jets modeling the centimeter emission of the thermal radio jets using the same type of models applied to YSOs, but with corresponding smaller stellar wind velocities and mass-loss rates, and exploring different possible geometries of the wind or outflow from the star. Moreover, we also find that the modeled mass outflow rates for the bolometric luminosities of our objects agree reasonably well with the trends found between the mass outflow rates and bolometric luminosities of YSOs, which indicates that, despite the "excess" centimeter emission, the intrinsic properties of proto-brown dwarfs are consistent with a continuation of those of very low mass stars to a lower mass range. Overall, our study favors the formation of brown dwarfs as a scaled-down version of low-mass stars.Comment: 18 pages, 8 figures, 14 tables, accepted by the Astrophysical Journa