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220 results for “Buenos Aires”
Fig. 7. A and B in Reproduction of Brevoortia aurea (Spix & Agassiz, 1829) (Actinopterygii: Clupeidae) in the Mar Chiquita Coastal Lagoon, Buenos Aires, Argentina
Fig. 7. A and B: Batch fecundity as a function of total weight (without ovary) and total length, respectively. C and D: Relative fecundity as a function of total weight (without ovary) and total length respectively.
Fig. 4 in Reproduction of Brevoortia aurea (Spix & Agassiz, 1829) (Actinopterygii: Clupeidae) in the Mar Chiquita Coastal Lagoon, Buenos Aires, Argentina
Fig. 4. Monthly relative frequency of the different gonadal development stages observed in females of Brevoortia aurea on the annual cycle, and the added samples of October and November for the Mar Chiquita coastal lagoon.
Fig. 8 in Reproduction of Brevoortia aurea (Spix & Agassiz, 1829) (Actinopterygii: Clupeidae) in the Mar Chiquita Coastal Lagoon, Buenos Aires, Argentina
Fig. 8. Proportion of mature individuals observed for each length classes of Brevoortia aurea. Females (black circles, dotted line) L 50 = 27.77 cm, N = 588. Males (white circles, solid line) L 50 = 26.59 cm, N = 293.
Fig. 2 in Reproduction of Brevoortia aurea (Spix & Agassiz, 1829) (Actinopterygii: Clupeidae) in the Mar Chiquita Coastal Lagoon, Buenos Aires, Argentina
Fig. 2. Captures per unite effort (CPUE kg/h), temperature (°C) and salinity (psu) obtained for Brevoortia aurea during sampled period in Mar Chiquita Coastal Lagoon.
Fig. 5. A in Reproduction of Brevoortia aurea (Spix & Agassiz, 1829) (Actinopterygii: Clupeidae) in the Mar Chiquita Coastal Lagoon, Buenos Aires, Argentina
Fig. 5. A: oogonias (arrow) and primary growth (p) oocytes; B: cortical alveoli stage oocyte (arrow); C: yolked oocytes; D: hydrated oocytes (arrow); E: details of a yolked oocyte (r: radiata zone; g: granulosa cells; t: teca cells); F: atresic follicle (arrow); G: post-ovulatory follicle "0" (arrow); H: post-ovulatory follicle "1" (arrow). Scale bars: A, E 25 μm; B, C, F, G, H, 100 μm; D, 250 μm.
Fig. 3 in Reproduction of Brevoortia aurea (Spix & Agassiz, 1829) (Actinopterygii: Clupeidae) in the Mar Chiquita Coastal Lagoon, Buenos Aires, Argentina
Fig. 3. Monthly variation of the gonadosomatic index (GSI) (females only), based on an annual cycle.
Fig. 6 in Reproduction of Brevoortia aurea (Spix & Agassiz, 1829) (Actinopterygii: Clupeidae) in the Mar Chiquita Coastal Lagoon, Buenos Aires, Argentina
Fig. 6. Frequency distribution of oocyte diameters (N = 6000 oocytes measured). From black bars to white bars: Primary growth oocyte, cortical alveoli, yolked oocytes and hydrated oocytes.
Linked collectors and determiners for: Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Coleccion BAFC de Hongos.
Natural history specimen data linked to collectors and determiners held within, "Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Coleccion BAFC de Hongos". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/96e30d99-3042-4d07-899f-9f01c3ca3fbf">https://bionomia.net/dataset/96e30d99-3042-4d07-899f-9f01c3ca3fbf</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/96e30d99-3042-4d07-899f-9f01c3ca3fbf">https://gbif.org/dataset/96e30d99-3042-4d07-899f-9f01c3ca3fbf</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Herbario Gaspar Xuarez (BAA) - Facultad de Agronomía - Universidad de Buenos Aires.
Natural history specimen data linked to collectors and determiners held within, "Herbario Gaspar Xuarez (BAA) - Facultad de Agronomía - Universidad de Buenos Aires". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/3cc9ba97-17dc-4a4a-8a12-bb36038021c4">https://bionomia.net/dataset/3cc9ba97-17dc-4a4a-8a12-bb36038021c4</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/3cc9ba97-17dc-4a4a-8a12-bb36038021c4">https://gbif.org/dataset/3cc9ba97-17dc-4a4a-8a12-bb36038021c4</a>. Formatted as a Frictionless Data package.
Cartas de Suelos República Argentina - Provincia de Buenos Aires
<p>El Plan Mapa de Suelos de la Región Pampeana en el año 1964 marca la etapa de mayor trascendencia del inventario de los suelos de nuestro país a escala de semidetalle y de reconocimiento (1:50.000 - 1:100.000). Las Cartas de Suelos de la Provincia de Buenos Aires son el resultado de este plan y la continuación de las tareas de relevamiento y cartografía de suelos hasta la actualidad. El Instituto Nacional de Tecnología Agropecuaria (INTA) pone a disposición de la comunidad, para su libre descarga la información vectorial de suelos a escala 1:50.000 de la Provincia de Buenos Aires elaborado a partir de la digitalización del material original de las Cartas de Suelos de la República Argentina. La información de las series de suelos se encuentra basada en lo publicado en http://anterior.inta.gob.ar/suelos/cartas/.</p> <p>También se presenta para la descarga la Carta de suelos del partido de Villarino a escala 1: 250.000. En el siguiente link se puede acceder al informe de dicha carta y la descarga de mapas temáticos: https://inta.gob.ar/documentos/carta-de-suelos-de-la-republica-argentina-partido-de-villarino-provincia-de-buenos-aires.</p> <p>En los siguientes scripts (https://github.com/INTA-Suelos/SuelosBA) se puede trabajar con las unidades cartográficas y series.</p>
Deep Learning with Satellite Images Enables High-Resolution Income Estimation: a Case Study of Buenos Aires
<p>This repository contains the datasets required for replicating the results in Abbate et al (forthcoming). The datasets also include per capita income estimates at a 50x50 meter resolution for the years 2013, 2018, and 2022, using satellite images from the Metropolitan Area of Buenos Aires (Argentina) and 2010 census+survey data. The model, based on the EfficientnetV2 architecture, achieved high accuracy in predicting household incomes (R2=0.878), surpassing existing methods in spatial resolution and performance. </p> <p>Inside the Replication Package folder, the user can replicate the main results from the paper. This includes:</p> <ol> <li> <p><strong>Small Area Estimation (SAE) Replication:</strong></p> <ul> <li> <p><strong>Argentina Household Survey Data (EPH):</strong> Processed microdata for 2010, 2013, 2018, and 2022 (ARG_*_EPHC-S2_*.dta).</p> </li> <li> <p><strong>Argentina Census Microdata:</strong> Raw 2010 census microdata (censo2010_fullraw_p.dta).</p> </li> <li> <p><strong>Census Tract Map:</strong> Shapefile of 2010 census tracts (radios_eph_with_link.shp).</p> </li> <li> <p><strong>SAE Output:</strong> The final small_area_estimates.parquet file containing census tract-level population and estimated income, which serves as labels for the CNN model.</p> </li> </ul> </li> <li> <p><strong>CNN-based Income Prediction Replication (Paper Results):</strong></p> <ul> <li> <p><strong>CNN Model Income Predictions:</strong> Gridded 50x50m income estimates for Buenos Aires for 2013, 2018, and 2022 (income_estimates_*.shp).</p> </li> <li> <p><strong>Normalization Scalars:</strong> A CSV file (scalars_ln_pred_inc_mean_trimTrue.csv) to convert the model's log-scale outputs into real income values (2010 PPP-adjusted Argentinian pesos).</p> </li> <li> <p><strong>World Settlement Footprint (WSF):</strong> Satellite-based data (WSF2015_v2_-60_-36.tif) used to mask predictions in uninhabited areas.</p> </li> </ul> </li> </ol> <p>Key prediction datasets are published in shapefile format, while input data for SAE and other auxiliary files are in formats like .dta, .parquet, .csv, and .tif.</p> <p>Results can be replicated by connecting these datasets with the scripts available at the GitHub repo linked below.</p> <p>For researchers who wish to replicate the full analysis pipeline starting from the original source imagery, the data must be acquired commercially. The proprietary Pleiades and Pleiades NEO satellite imagery is owned by Airbus and can be purchased through their data portal: https://space-solutions.airbus.com/imagery/. To facilitate this process, we provide the unique product identifiers for each scene used in this study. These identifiers can be used to query the Airbus archive and purchase the exact scenes.</p> <ul> <li><strong>Pléiades</strong>: for 2013 imagery the IDs are DS_PHR1A_201302051411520_FR1_PX_W059S35_0807_03124, DS_PHR1A_201302071357305_FR1_PX_W059S35_0410_06105 and DS_PHR1A_201302071357509_FR1_PX_W059S35_0609_05426, and for 2018, DS_PHR1A_201803251356358_FR1_PX_W059S35_0909_03875, DS_PHR1A_201808021356574_FR1_PX_W059S35_0509_06938 and DS_PHR1A_201808021357186_FR1_PX_W059S35_0706_06104.</li> <li><strong>Pleiades NEO</strong>: for 2022 imagery the IDs used are 000047717_1_22_STD_A, 000047717_1_24_STD_A, 000047717_1_25_STD_A, 000047717_1_26_STD_A, 000058605_1_3_STD_A, 000058605_1_4_STD_A, 000058605_1_7_STD_A, and 000058608_1_2_STD_A.</li> </ul> <p><strong>Important Usage Note:</strong> Since the predictions for each 50x50m cell individually present some random variation, we recommend that the results are used by averaging out the estimations for each area of interest (e.g., municipalities, neighborhoods, sections, or census tracts) and not at an individual cell level. As detailed throughout the paper, the aggregated results, even in small areas such as census tracts, predict household incomes with precision.</p> <p>Furthermore, inside this repository, it is possible to access and use the model’s trained parameters to make predictions about different satellite images.</p> <p>Data can be visualized by accessing: <a href="https://ingresoamba.netlify.app">https://ingresoamba.netlify.app</a></p> <p> </p> <p> </p>
Figure 1 in Helvetia cf. cancrimana (Araneae: Salticidae: Chrysillini) from Buenos Aires
Figure 1. Female Helvetia cf. cancrimana on a tree in the Reserva Ecológica Costanera Sur in the city of Buenos Aires, 20 March 2018.. Body length of this spider was 3.13 mm. 2, Note the glabrous, rugose anterolateral carapace below the lateral eyes, part of a stridulatory apparatus that opposes setal sockets inside of the ipsilateral femur (Ruiz & Brescovit 2008).
Figure 2 in Helvetia cf. cancrimana (Araneae: Salticidae: Chrysillini) from Buenos Aires
Figure 2. Distribution of Helvetia species, all endemic to South America. Localities shown here are listed
Drainage network for a region in central Buenos Aires province, 30m resolution raster, EPSG:5347
<p>This drainage network was obtained using the Copernicus-30 Global Digital-Surface-Model, tiles (S37-38, W60) with QGIS and PCraster plugin: local direction drainage and flow accumulation algorithms. It helps to clarify the surrounding drainage pattern at cities like Azul, Cacharí and Tandil, for flood alleviation schemes.</p>
Fig. 2 in Reproductive studies of Anchoa marinii Hildebrand, 1943 (Actinopterygii: Engraulidae) in the nearby-coastal area of Mar Chiquita coastal lagoon, Buenos Aires, Argentina
Fig. 2. Monthly relative frequency (%) of gonad phases for females of Anchoa marinii.
Fig. 5 in Reproductive studies of Anchoa marinii Hildebrand, 1943 (Actinopterygii: Engraulidae) in the nearby-coastal area of Mar Chiquita coastal lagoon, Buenos Aires, Argentina
Fig. 5. Oocyte diameter distribution in spawning capable phase of Anchoa marinii. N= 183.
Fig. 1 in Temporal variations of larval digenean assemblages parasitizing Heleobia parchappii (Mollusca: Cochliopidae) in two shallow lakes from the Buenos Aires province, Argentina
Fig. 1. Sampling sites in the Buenos Aires province, Argentina.
Fig. 1 in Reproduction of Brevoortia aurea (Spix & Agassiz, 1829) (Actinopterygii: Clupeidae) in the Mar Chiquita Coastal Lagoon, Buenos Aires, Argentina
Fig. 1. Study area showing the sample station.
Figure 4 in Stranded humpback whale (Megaptera novaeangliae) (Cetacea: Balaenopteridae) in Paraná River Delta, Buenos Aires Province, Argentina. Comments on the occurrence of marine
Figure 4. Median-joining network based on the cytochrome c oxidase subunit I mtDNA haplotypes of Megaptera novaeangliae. Haplotypes are represented with discs and colors that indicate geographical locations. Mutational steps are indicated with stripes.
Figure 1 in Stranded humpback whale (Megaptera novaeangliae) (Cetacea: Balaenopteridae) in Paraná River Delta, Buenos Aires Province, Argentina. Comments on the occurrence of marine
Figure 1. Paraná River delta map were Megaptera novaeangliae (CFA-MA-13084) was found dead (exact location is indicated with a black dot).
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.