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2,021 results for “valley”
Benthic macroinvertebrate, water temperature, and stream environmental data for Green Lakes Valley, 2021.
This dataset contains stream benthic macroinvertebrate community structure data from nine sites in the Green Lakes Valley ranging from below treeline near Albion Camp to the outflow of the Arikaree Glacier, all sampled in summer of 2021. The dataset also contains files with stream environmental data related to substrate stability, periphyton chlorophyll a concentrations, and water temperatures.
Arbuscular mycorrhizal fungi and dark septate endophytes root colonization in Upper Green Lakes Valley, 2007-2016
Arbuscular mycorrhizal fungi (AMF) and dark septate endophytes (DSE) are two fungal groups that colonize plant roots and can benefit plant growth, but little is known about their landscape distributions. We performed sequencing and microscopy on a variety of plants across a high-elevation landscape featuring plant density, snowpack, and nutrient gradients. Percent colonization by both AMF and DSE varied significantly among plant species, and DSE colonized forbs and grasses more than sedges. AMF were more abundant in roots at lower elevation areas with lower snowpack and lower phosphorus and nitrogen levels, suggesting increased hyphal recruitment by plants to aid in nutrient uptake. DSE colonization was highest in areas with less snowpack and higher inorganic nitrogen levels, suggesting an important role for these fungi in mineralizing organic nitrogen. Both of these groups of fungi are likely to be important for plant fitness and establishment in areas limited by phosphorus and nitrogen.
Green Lakes Valley land cover classification, Niwot Ridge LTER, Colorado
Land cover data generated by Don Cline (graduate student, CU Boulder Geography), as part of suite of spatial maps made for Green Lakes Valley (see Williams et al. 1999).
10-meter elevation contours, Green Lakes Valley, Niwot Ridge LTER, Colorado
10-meter contours clipped with a box made from extents of the Green Lakes Valley 1999 high-resolution orthorectified imagery dataset (glv.tif). This dataset was made to support hierarchical GIS databases at the Niwot Ridge LTER. Additional information concerning the Niwot Ridge LTER hierarchical GIS can be found in Walker et al. (1993).
Vegetation surveys in the riparian (bosque) corridor of the Middle Rio Grande valley, NM
This dataset contains vegetation cover information from 34 long-term Bosque Ecosystem Monitoring Program (BEMP) sites from 2000 – 2021. Data were collected along ten 30-m transects at each site at the centimeter scale each year in August-early October as funding and site access allowed. At the fullest extent, sites spanned 520 km of the riparian forest along the Rio Grande. The purpose of this dataset is to track plant species at sites along the Rio Grande in New Mexico. From this dataset, changes in plant species abundance, richness, and species diversity can be tracked and analyzed with ecosystem drivers such as flooding, fire, species removal/fuel reduction projects, and climate change. Species are coded using USDA Plant Database codes, allowing species information to be added to each species, including origin (native or nonnative), duration (e.g., annual, biennial, perennial), and plant type (e.g., grass, forb, vine, shrub, tree). This dataset has allowed the tracking of the ascendance of nonnatives in some sites, the recovery of natives in other sites, success or lack of success following restoration projects, and records of new species occurring in various counties and the state of New Mexico.
THD technique applied on Vp data of Long Valley Caldera
<p>We considered the V<sub>p</sub> tomographic model of Seccia et al. (2011) for Long Valley Caldera on which we applied the Horizontal Gradient technique for retrieving geometrical information about the deep structures characterizing the first 10 km of crust. Specifically, after the regularization through spatial based kriging interpolator, we compute the horizontal derivatives on single z-layers with sampling step of 500 m. The results are presented in Gola G., Barone A., Castaldo R., Chiodini G., D'Auria L., Garcia-Hernandez R., Pepe S., Solaro G. & Tizzani P. "A novel multidisciplinary approach for the thermo-rheological study of volcanic areas: The case study of Long Valley Caldera", which has been submitted for possible publication in Journal of Geophysical Research - Solid Earth.</p> <p>Coordinates: North America NAD27 UTM Zone 11N<br> Easting: 308000 - 353000 m.; Northing: 4155000 - 4185000 m; XY resolution: 500 m.</p>
Experimental data for bulk valley transport and Berry curvature spreading at the edge of flat bands
<p>This dataset was used in our study of bulk valley transport and Berry curvature spreading at the edge of flat bands in twisted double bilayer graphene.</p>
Subglacial valleys preserved in the highlands of south and east Greenland record restricted ice extent during past warmer climates: Datasets
<p>This dataset contains the following files:</p><ul><li><strong>mountain_glacial_valleys_2km.shp (and ancillary files: .dbf, .prj, .shx)</strong>: ESRI shapefile of the subglacial valleys mapped along the southern and eastern highlands of Greenland using MODIS Mosaic of Greenland imagery and radio-echo sounding data.</li><li><strong>mountain_glacial_limit.shp (and ancillary files: .dbf, .prj, .shx)</strong>: ESRI shapefile of the interpreted palaeo-glacial valley limit along the southern and eastern highlands of Greenland based on the distribution and morphology of the mapped subglacial valleys.</li><li><strong>ex_g5km_10ka_hy_east.nc</strong>: NetCDF file of the Parallel Ice Sheet Model output spatially variable fields for the best-fitting simulation for the eastern highlands (run at 5 km horizontal resolution for 10,000 model years).</li><li><strong>ts_g5km_10ka_hy_east.nc</strong>: NetCDF file of the Parallel Ice Sheet Model output scalar time series for the best-fitting simulation for the eastern highlands (run at 5 km horizontal resolution for 10,000 model years).</li><li><strong>ex_g5km_10ka_hy_south.nc</strong>: NetCDF file of the Parallel Ice Sheet Model output spatially variable fields for the best-fitting simulation for the southern highlands (run at 5 km horizontal resolution for 10,000 model years).</li><li><strong>ts_g5km_10ka_hy_south.nc</strong>: NetCDF file of the Parallel Ice Sheet Model output scalar time series for the best-fitting simulation for the southern highlands (run at 5 km horizontal resolution for 10,000 model years).</li></ul>
Neogene–Quaternary uplift and landscape evolution in northern Greenland recorded by subglacial valley morphology: Datasets
<p>This dataset contains a csv file of subglacial valley morphology derived from radio-echo sounding datasets in northern Greenland, and an ESRI shapefile of the interpreted channel network. For further documentation of the data please view the README.txt file.</p> <p>RADAR-DERIVED VALLEY MORPHOLOGY</p> <ul> <li><strong>northern_Greenland_valley_morphology.csv</strong>: location and morphology of subglacial valleys in northern Greenland, as imaged by airborne radio-echo sounding datasets.</li> </ul> <p>SUBGLACIAL VALLEY NETWORK</p> <ul> <li><strong>northern_Greenland_valley_network.shp (and ancillary files: .cpg, .dbf, .prj, .qpj, .shx)</strong>: ESRI shapefile of the interpreted valley network in the northern Greenland subglacial drainage catchment.</li> </ul>
Interpolated Clay Fraction and Resistivity model of the Aare Valley, Switzerland
<p>The dataset is an underground model of the Upper Aare Valley in Switzerland. It has been made in the framework of the Phenix project at the University of Neuchâtel. It has been produced by applying the CF prediction method (doi : 10.5194/hess-18-4349-2014) to an EM dataset (doi : 10.5194/essd-13-2743-2021).</p> <p>The Model was then interpolated using Multiple Point statistics, with robust uncertainty quantification (doi : In review).</p> <p>The two files contain the same data, as pointset or gridVTK files. The data contained are :</p> <ul> <li>Log10(Resistivity)</li> <li>Log10(Resistivity) Uncertainty (STD)</li> <li>ClayFraction</li> <li>ClayFraction Uncertainty (STD)</li> </ul> <p>The X,Y,Z positions are provided in UTM32N (epsg : 32632).</p>
Dataset for 'Valley Networks and the Record of Glaciation on Ancient Mars'
<p>Supplementary information (in pdf format, ~800 kb) containing the model, setup, and parameter analysis supporting the manuscript 'Valley Networks and the Record of Glaciation on Ancient Mars'. </p> <p>Includes a detailed table of parameters with references. </p>
Soil carbon and nitrogen stock data for dominant geomorphological terrain units in Qarlikturvik Valley, Bylot Island, Arctic Canada
<p>Dataset for the manuscript 'The distribution of soil carbon and nitrogen stocks among dominant geomorphological terrain units in Qarlikturvik Valley, Bylot Island, Arctic Canada.' to appear in the 'Journal of Geophysical Research: <em>Biogeosciences'.</em></p>
ALS-based DEMs (100 cm): the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași)
<p>This dataset is part of a larger project on the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași), supervised by the ArchaeoSciences Division of the Research Institute of the University of Bucharest (ICUB) and Kiel University (Germany), in partnership with HOGENT, University of Applied Sciences and Arts (Belgium), Museum of Bucharest, Museum of the Lower Danube Călărași, Museum of Gumelnița Civilization Oltenița, and "Vasile Pârvan" Institute of Archaeology (Romania), under the "Sultana School of Archaeology" initiative.</p> <p>Spatial data play a crucial role in archaeological research, and orthophotos, digital elevation models, and 3D models are frequently used for the mapping, documentation, and monitoring of archaeological sites. Thanks to the availability of compact and low-cost uncrewed airborne vehicles, the use of UAV-based photogrammetry is well matured in this field over the last two decades. More recently, compact airborne systems are also available that allow the recording of thermal data, multispectral data, and airborne laser scanning. For this project, various platforms and sensors are applied at the Chalcolithic archaeological sites in the Mostiștea Basin and Danube Valley (Southern Romania). By analyzing the performance of the systems and the resulting data, insight is given into the selection of the appropriate system for the right application. This analysis requires thorough knowledge of data acquisition and data processing as well. As both laser scanning and photogrammetry typically result in very large amounts of data, a special focus is also required on the storage and publication of the data. Hence, the objective of this project is to provide a full overview of various aspects of 3D data acquisition for UAV-based mapping. Based on the conclusions drawn in our related publications, it is stated that photogrammetry and laser scanning can result in data with similar geometrical properties when acquisition parameters are appropriately set. On the one hand, however, the used ALS-based system outperforms the photogrammetric platforms in terms of operational time and the area covered. On the other hand, conventional photogrammetry provides flexibility that might be required for very low-altitude flights, or emergency mapping. Furthermore, as the used ALS sensor only provides a geometrical representation of the topography, photogrammetric sensors are still required to obtain true color- or false color composites of the surface. Lastly, the variety of data, like pre- and post-rendered raster data, 3D models, and point clouds, requires the implementation of multiple methods for the online publication of data. Various client-side and server-side solutions are presented to make the data available for other researchers.</p>
MS-based orthophotos (50 cm): the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași)
<p>This dataset is part of a larger project on the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași), supervised by the ArchaeoSciences Division of the Research Institute of the University of Bucharest (ICUB) and Kiel University (Germany), in partnership with HOGENT, University of Applied Sciences and Arts (Belgium), Museum of Bucharest, Museum of the Lower Danube Călărași, Museum of Gumelnița Civilization Oltenița, and "Vasile Pârvan" Institute of Archaeology (Romania), under the "Sultana School of Archaeology" initiative.</p> <p>Spatial data play a crucial role in archaeological research, and orthophotos, digital elevation models, and 3D models are frequently used for the mapping, documentation, and monitoring of archaeological sites. Thanks to the availability of compact and low-cost uncrewed airborne vehicles, the use of UAV-based photogrammetry is well matured in this field over the last two decades. More recently, compact airborne systems are also available that allow the recording of thermal data, multispectral data, and airborne laser scanning. For this project, various platforms and sensors are applied at the Chalcolithic archaeological sites in the Mostiștea Basin and Danube Valley (Southern Romania). By analyzing the performance of the systems and the resulting data, insight is given into the selection of the appropriate system for the right application. This analysis requires thorough knowledge of data acquisition and data processing as well. As both laser scanning and photogrammetry typically result in very large amounts of data, a special focus is also required on the storage and publication of the data. Hence, the objective of this project is to provide a full overview of various aspects of 3D data acquisition for UAV-based mapping. Based on the conclusions drawn in our related publications, it is stated that photogrammetry and laser scanning can result in data with similar geometrical properties when acquisition parameters are appropriately set. On the one hand, however, the used ALS-based system outperforms the photogrammetric platforms in terms of operational time and the area covered. On the other hand, conventional photogrammetry provides flexibility that might be required for very low-altitude flights, or emergency mapping. Furthermore, as the used ALS sensor only provides a geometrical representation of the topography, photogrammetric sensors are still required to obtain true color- or false color composites of the surface. Lastly, the variety of data, like pre- and post-rendered raster data, 3D models, and point clouds, requires the implementation of multiple methods for the online publication of data. Various client-side and server-side solutions are presented to make the data available for other researchers.</p>
On-site Jomo Propitiation in Chug valley: photographs
<p>Both participants in this ritual are <em>bon-po</em>, practitioners of the traditional religious system in the Chug valley. Jomo Gamdong is the place on the west bank of the Chug river which is considered the <em>pho-bra</em><em>ṅ</em> ‘palace’ of <em>jo-mo u-si</em><em>ṅ bu-khrid</em>, one of the nine daughters of the female deity <em>jo-mo a-ni u-</em><em>ñi</em><em>ṅ</em>, located on the Bhutan-Arunachal border in Jomotsangkha block of Samdrup Jongkhar district in Bhutan. The peak of <em>jo-mo u-si</em><em>ṅ bu-khrid</em> is the westernmost peak in the north of the Chug valley (see figure1). Propitiation of the Jomo takes place on monthly basis at home. Only on rare occasions does the <em>bon-po</em> go to the Jomo Gamdong for the propitiation, typically once in a few years.</p> <p>The <em>phobrang</em> is located in a grove of oak trees starting from the large trees in figure5. The area is a collection of large rocks (see photographs). Each rock has a significance, of which little could be recorded (exceptions are the white female <em>naga</em> in figure2 and the servant of the Jomo in figure3). As the marking on the tree in figure4 shows, at the time of the visit many trees were about to be felled. Although the land is owned by individual households from Jagarbasti village in the Chug valley, the trees were felled by people from the neighbouring village of Lish Gonpatse (whether this is a case of illegal felling and encroachment as a result of the on-going land dispute between the two communities, or whether the owners from Jagarbasti sold the standing trees (with the land?) to the Lish Gonpatse people is not clear. This degradation of the site, in combination with the 2016 death of <em>bon-po</em> Kesang, means that propitiation of the Jomo here has ceased completely.</p> <p>The relevant stanza from the Jomo propitiation ritual (see file), in which the very first offerings are always made to the Jomo, are as follows:</p> <p><strong>Phonetic:</strong> [ʨʰɔtɔː {ŋa} ʨʰɔtɔː, ʨʰɔtɔː {ŋa} ʨʰɔtɔː, kʰamzaŋ {ŋa} ama ʥɔmɔː, jap {la} gawɔː ʑɔkpɔː, makpøn {na} meme ʨʰøjɕi, lúmɔː karmɔː {ŋa}, lúmɔː jáŋzɔm {ma}, lúmɔː manɖɛn {na} ʦʰeriŋ zaŋmɔː, ʦʰɛnla sɛrgi ʥɔːmɔː {ŋa} sagaŋ, ɬabraŋ {ŋa} laʨʰɛn, lúbraŋ {ŋa} lúʨʰuŋ, pʰygɔː {ŋa} gile.</p> <p>ʦʰekjɛt náŋla, jáŋkjɛt náŋla, ʨʰamneː kakɲeː, rimneː kakɲeː, natʥa kakɲeː, rimʥa kakɲeː, siwɔː neːdak, kɔrda ɬa lú ʦɛn sum kakɲeː, ʦʰɛnla sɛrgi ʥɔːmɔː, sɛrkjɛm karpɔː, pʰyjgɔː gile.</p> <p>jaski kɔːra, yønla gonʨʰa, náŋna gile. lemʨʰaŋ karpɔː, pʰyjgo gile. ʨʰɔːto {ŋa} ʨʰɔːtɔː.]</p> <p><strong>Tibetan:</strong> <em>ḥbyo ldog ḥbyo ldog, ḥbyo ldog ḥbyo ldog! kham-zaṅ a-ma jo-mo, yab dgaḥ-bo źog-po (<TM ʑokpo), dmag-dpon mes-mes chos-śi (?), klu-mo dkar-mo, klu-mo dbyaṅ-ḥdzoms, klu-mo sman-dran (?) tshe-riṅ bzaṅ-mo, mtshan ser-gi jo-mo sa-gaṅ (?), lha-braṅ lha-chen, klu-braṅ klu-chuṅ, phul-dgos gi-le (< TSD gi-la-aj)!</em></p> <p><em>tshe-skyed gnaṅ-la, g.yaṅ-skyed gnaṅ-la, cham-nad bkag-ñe (<TSD ɲi), rims-nad bkag-ñe, nat-brgya bkag-ñe, rims-brgya bkag-ñe, sre-ḥu (?) gnas-bdag, skor-da lha klu btsan gsum bkag-ñe, mtshan-la ser-gi jo-mo, ser-skyem dkar-po, phul-dgos gi-le!</em></p> <p><em>g.yas-kyi skor-ra (?), g.yon-la bgon-chas (?), gnaṅ-na gi-le! lem-chaṅ (?) dkar-po, phul-dgos gi-le! ḥbyo-ldog ḥbyo-ldog!</em></p> <p><strong>English:</strong> Hark (and) dispel, hark (and) dispel, hark (and) dispel, hark (and) dispel! The healthy (?) mother Jomo, the father Gawo Zhokpo, the general Meme Choshi, the white female <em>naga</em> (see figure2), the female <em>naga</em> Yangzom, the female <em>naga</em>Mandren Tshering Zangmo, the name is the pit (?) (of) the golden Jomo, the deity residence for the important deities, the <em>naga</em> residence for the less important <em>naga</em>, it has to be offered ok!</p> <p>Provide (with) longevity, provide (with) prosperity, preventing the flu diseases, preventing the infectious diseases, preventing the hundred diseases, preventing the hundred infectious diseases, the host of the smallpox (?), prevent the roaming of the three, the deities, the <em>naga</em> and the <em>tsen</em>, the name (is) the golden Jomo, the white libation offering, it has to be offered ok!</p> <p>Surrounding on the right side (?), the clothing apparel on the left (?), it is provided ok! The white <em>lemchang</em>, it has to be offered ok! Hark (and) dispel, hark (and) dispel!</p> <p>This material is made freely available to everyone for informative or scientific purposes as long as the source (this DOI) / the collectors are properly credited. Please note that use of the material for commercial purposes <em><strong>of any kind</strong>, which includes conversion into commercial audio-visual media (documentaries etc.), storage and dissemination through sites that require registration & payment for access, or sites that rely on advertisement (including YouTube) </em>is <strong>not</strong> permitted without <strong>specific written consent</strong> from the speakers and their community, obtained through the collectors of the material. By downloading our material, you agree to these restrictions.</p> <p>This data set falls under the Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license. This license lets you remix, tweak, and build upon this work non-commercially, as long as you credit us and license your new creations under the identical terms. License Deed on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">https://creativecommons.org/licenses/by-nc-sa/4.0/</a>. Legal Code on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode">https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode</a>.</p> <p>Tim Bodt: bodttim (at) gmail (dot) com</p>
At-home Jomo Propitiation in Chug valley: photo files
<p>Kesang was one of the last <em>bon-po</em>, practitioners of the traditional religious system in the Chug valley. This religious system has no ‘name’, but comes under what is often called ‘Bon’. The locus of propitiation is on the opposition between the high, in winter snow-clad mountain peaks <em>phu</em> (Tib. phu) that represent purity, cleanliness, goodness and beneficial powers versus the low-lying marshy, swampy areas <em>da</em> (tib. mdaḥ) that represent pollution, disease, evil and malevolent forces. In between these two there is a plethora of other local deities, many of which are local representations of the <em>lha-srin bde-brgyad</em> ‘eight classes of deities and demons’ also found in Tibetan Buddhism, but many of whom also represent deified human beings who have taken on some negative or positive force. It is the role of the <em>bon-po</em> to maintain the balance between the <em>phu</em>, the ‘good’ and the <em>da</em>, the ‘evil’ and hence prevent damage to humans and their livelihoods in the form of diseases, natural disasters, death etc. The <em>phu-da</em> religious system is not limited to the Chug valley, but, in various forms, can also be found among the related Khispi, Sartang and Sherdukpen people, as well as among the Tshangla speakers of West Kameng and eastern Bhutan.</p> <p>The main ritual conducted by the bon-po is called <em>zhiwa</em> (Tib. źi-ba ‘peace’) or <em>jomo soykha</em> (Tib. jo-mo gsol-kha ‘propitiation of the Jomo). It is conducted once before the 20th day of every Tibetan month. Jomo is the main female deity in the area (see also the files concerning the on-site Jomo propitiation). During this ritual, the <em>bon-po</em> first invites the Jomo and all other deities and spirits to attend the offering. He then offers <em>nyingba</em> (Tib. sñiṅ-ba ‘old’), also called <em>lemchang</em>, a mixture of rice, maize, finger millet (traditionally also wheat, barley, broomcorn millet, foxtail millet, buckwheat and amaranth) that has been kept fermenting for a long time. After that, he offers <em>tochang</em>, freshly cooked rice (Tib. lto-chaṅ ‘food-liquor’), and after that <em>darcok</em> (Tib. dar-lcog ‘prayer flags’), small twigs with triangular-shaped flags made of traditional paper. He then conducts a prediction for the coming month, by making three heaps of a mixture of grains, and interprets the way in which these grains pattern. He then sends off the assembled deities.</p> <p><em>Bon-po</em> Kesang died in early 2016. His son Tow Tsering has taken over his role, but does not seem to know the ritual as well as his father. He may well be the last of the <em>bon-po</em> in Chug valley, given that no one has come forward to learn from him.</p> <p>This material is made freely available to everyone for informative or scientific purposes as long as the source (this DOI) / the collectors are properly credited. Please note that use of the material for commercial purposes <em><strong>of any kind</strong>, which includes conversion into commercial audio-visual media (documentaries etc.), storage and dissemination through sites that require registration & payment for access, or sites that rely on advertisement (including YouTube) </em>is <strong>not</strong> permitted without <strong>specific written consent</strong> from the speakers and their community, obtained through the collectors of the material. By downloading our material, you agree to these restrictions.</p> <p>This data set falls under the Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license. This license lets you remix, tweak, and build upon this work non-commercially, as long as you credit us and license your new creations under the identical terms. License Deed on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">https://creativecommons.org/licenses/by-nc-sa/4.0/</a>. Legal Code on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode">https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode</a>.</p> <p>Tim Bodt: bodttim (at) gmail (dot) com</p>
Menchukha valley - picture files
<p>These pages and the accompanying files contain some initial information regarding the history, ethnography, ethnobotany and language of the Menchukha valley in West Siang district of Arunachal Pradesh, India.</p> <p>This information was collected between November 7<sup>th</sup> and 10<sup>th</sup> 2017.</p>
A comprehensive floristic knowledge of the largest Atlantic Forest fragment of the Fluminense Paraíba do Sul River Valley, Rio de Janeiro, Brazil
<p>The “<em>Serra da Concórdia</em>” is part of the Atlantic Forest phytogeographical domain in the Brazilian state of Rio de Janeiro and it has a predominant phytophysiognomy of Semideciduous Seasonal Forest. This region underwent intense habitat loss and fragmentation during the 19<sup>th</sup> century, due to coffee plantations and later pastures. With the decline of these activities, the areas were abandoned, triggering secondary succession. In 2002, the “<em>Parque Estadual da Serra da Concórdia</em>” was established in this region to preserve the remaining forest fragments. The updated list of vascular plants recorded in this protected area, published in the “<em>Catálogo de Plantas das Unidades de Conservação do Brasil</em>”, is presented here, along with information on richness, endemism, and conservation status.</p>
3D models (NXS): Towards a spatial data repository for archaeological research in the Romanian Mostiștea Basin and Danube Valley
<p><span>Spatial data are crucial in archaeological research, where orthophotos, digital elevation models, and 3D models are widely used for mapping, documenting, and monitoring archaeological sites. The introduction of affordable and compact unmanned aerial vehicles (UAVs) has significantly advanced the use of UAV-based photogrammetry in the past 20 years. Recently, compact airborne systems have also enabled the capture of thermal, multispectral, and aerial laser scanning data. This study presents the data acquired with different platforms and sensors at Chalcolithic archaeological sites in Romania's Mostiștea Basin and Danube Valley. Since laser scanning and photogrammetry generate large data volumes, data storage and dissemination must also be carefully considered. Based on a thorough study of system performance, data acquisition and processing methods, and data outputs, a workflow for the systematic mapping and documentation of sites has been proposed. Given the experience obtained in the last 5 summer campaigns (2018-2023), 19 sites have been accurately mapped, of which 5 sites are mapped using airborne laser scanning. 18 sites are documented using multispectral photogrammetry, and for 17 sites, interactive image-based 3D models are acquired using true-color photogrammetry. All data are stored on a publicly accessible website for visualization, as well as on an open-data platform for data exchange. For the multispectral data, a raster tile service has been implemented, allowing the use of the data in a GIS environment.</span></p>
3D models (true color, TIF): Towards a spatial data repository for archaeological research in the Romanian Mostiștea Basin and Danube Valley
<p>Spatial data are crucial in archaeological research, where orthophotos, digital elevation models, and 3D models are widely used for mapping, documenting, and monitoring archaeological sites. The introduction of affordable and compact unmanned aerial vehicles (UAVs) has significantly advanced the use of UAV-based photogrammetry in the past 20 years. Recently, compact airborne systems have also enabled the capture of thermal, multispectral, and aerial laser scanning data. This study presents the data acquired with different platforms and sensors at Chalcolithic archaeological sites in Romania's Mostiștea Basin and Danube Valley. Since laser scanning and photogrammetry generate large data volumes, data storage and dissemination must also be carefully considered. Based on a thorough study of system performance, data acquisition and processing methods, and data outputs, a workflow for the systematic mapping and documentation of sites has been proposed. Given the experience obtained in the last 5 summer campaigns (2018-2023), 19 sites have been accurately mapped, of which 5 sites are mapped using airborne laser scanning. 18 sites are documented using multispectral photogrammetry, and for 17 sites, interactive image-based 3D models are acquired using true-color photogrammetry. All data are stored on a publicly accessible website for visualization, as well as on an open-data platform for data exchange. For the multispectral data, a raster tile service has been implemented, allowing the use of the data in a GIS environment.</p>
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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.