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2,021 results for “valley”
Linked collectors and determiners for: Grand Valley State University.
Natural history specimen data linked to collectors and determiners held within, "Grand Valley State University". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/d3f96902-f86e-463d-9e38-1b35aaed5caf">https://bionomia.net/dataset/d3f96902-f86e-463d-9e38-1b35aaed5caf</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/d3f96902-f86e-463d-9e38-1b35aaed5caf">https://gbif.org/dataset/d3f96902-f86e-463d-9e38-1b35aaed5caf</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: A northern range extension of a Canadian species of Special Concern, Dielis pilipes (Hymenoptera: Scoliidae), in the Okanagan Valley of British Columbia.
Natural history specimen data linked to collectors and determiners held within, "A northern range extension of a Canadian species of Special Concern, Dielis pilipes (Hymenoptera: Scoliidae), in the Okanagan Valley of British Columbia". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/8430fcd6-85f7-4daf-931f-91a035277c17">https://bionomia.net/dataset/8430fcd6-85f7-4daf-931f-91a035277c17</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/8430fcd6-85f7-4daf-931f-91a035277c17">https://gbif.org/dataset/8430fcd6-85f7-4daf-931f-91a035277c17</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Wild Bee Specimens from Blueberry and Raspberry Farms in the Champlain Valley, Vermont, USA.
Natural history specimen data linked to collectors and determiners held within, "Wild Bee Specimens from Blueberry and Raspberry Farms in the Champlain Valley, Vermont, USA". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/26c7440a-f4e4-4564-9901-9aac6e116536">https://bionomia.net/dataset/26c7440a-f4e4-4564-9901-9aac6e116536</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/26c7440a-f4e4-4564-9901-9aac6e116536">https://gbif.org/dataset/26c7440a-f4e4-4564-9901-9aac6e116536</a>. Formatted as a Frictionless Data package.
Belham Valley Lahar Record
<p>This .csv fille contains a record of lahars in the Belham River Valley, Montserrat, Eastern Caribbean, spanning 1995 - 2024. It details: 1) date of lahar event, 2) estimated size (categorised as small, medium, large), and 3) means of observation.</p>
Alpine Beetles from Takehe Valley
<p>Alpine Beetles from Takehe Valley, Fiordland, New Zealand as part of a long-term experiment simulating climate change and responses of insects</p>
Image 159. Hyarotis adrastus praba Image 157. Koruthaialos butleri butleri Image 158 in Butterflies (Lepidoptera) of Dibang Valley, Mishmi Hills, Arunachal Pradesh, India
Image 159. Hyarotis adrastus praba Image 157. Koruthaialos butleri butleri Image 158. Scobura cephaloides
Normalized Difference Water Index for Douro Valley based on MODIS
<p><strong>Normalized Difference Water Index </strong>(NDWI) calculated using MODIS09 imagery provided by USGS/EROS.The original MODIS09 bands were used as data source and then the ndwi was calculated. </p> <p>The Normalized Difference Water Index (NDWI) (Gao, 1996) is a satellite-derived index from the Near-Infrared (NIR) and Short Wave Infrared (SWIR) channels. Its usefulness for drought monitoring and early warning has been demonstrated in different studies (e.g., Gu et al., 2007; Ceccato et al., 2002). It is computed using the near infrared (NIR) and the short wave infrared (SWIR) reflectance, which makes it sensitive to changes in liquid water content and in spongy mesophyll of vegetation canopies (Gao, 1996 ; Ceccato et al., 2001).</p> <p><a href="https://edo.jrc.ec.europa.eu/documents/factsheets/factsheet_ndwi.pdf">https://edo.jrc.ec.europa.eu/documents/factsheets/factsheet_ndwi.pdf</a></p> <p>Each compressed file contains the NDVI by years. Internally each file have an ISO TC 211 metadata with a complete geographical description.</p> <p>spatial resolution: 463.313m<br> format: GeoTiff<br> reference system:SR-ORG 6842</p> <p> </p> <p>To easily manage the data, each file follow name structure:</p> <p>YYYYMMDD_medgold_workpackage_AoI_sensor_index.</p> <p>YYYYMMDD: Imagery acquisition date</p> <p>medgold: Project name</p> <p>sensor: sensor name</p> <p>workpackage: sectorial workpackage name ( WP2 - Olive Oil Sector, WP3 – Wine Grape sector, WP4- Durum wheat pasta sector)</p> <p>Aoi: Andalusia, Douro Valley.</p> <p>Index: NDVI, NMDI, NDWI</p> <p>Example:</p> <p>20000218_medgold_wp3_douro_MOD09A1_ndwi</p> <p> </p>
Normalized Multi-band Drought Index for Douro Valley based on MODIS
<p><strong>Normalized Multi-band Drought Index</strong> (NMDI) calculated using MODIS09 imagery provided by USGS/EROS.The original MODIS09 bands were used as data source and then the nmdi was calculated. </p> <p>NMDI uses the 860 nm channel as the reference; instead of using a single liquid water absorption channel, however, it uses the difference between two liquid water absorption channels centered at 1640 nm and 2130 nm as the soil and vegetation moisture sensitive band. Analysis revealed that by combining information from multiple near infrared, and short wave infrared channels, NMDI has enhanced the sensitivity to drought severity, and is well suited to estimate both soil and vegetation moisture.( <a href="https://agupubs.onlinelibrary.wiley.com/action/doSearch?ContribAuthorStored=Wang%2C+Lingli">Lingli Wang</a>, 2007)</p> <p><a href="https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007GL031021">https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007GL031021</a></p> <p> </p> <p>Each compressed file contains the NDVI by years. Internally each file have an ISO TC 211 metadata with a complete geographical description.</p> <p>spatial resolution: 463.313m<br> format: GeoTiff<br> reference system:SR-ORG 6842</p> <p> </p> <p>To easily manage the data, each file follow name structure:</p> <p>YYYYMMDD_medgold_workpackage_AoI_sensor_index.</p> <p>YYYYMMDD: Imagery acquisition date</p> <p>medgold: Project name</p> <p>sensor: sensor name</p> <p>workpackage: sectorial workpackage name ( WP2 - Olive Oil Sector, WP3 – Wine Grape sector, WP4- Durum wheat pasta sector)</p> <p>Aoi: Andalusia, Douro Valley.</p> <p>Index: NDVI, NMDI, NDWI</p> <p>Example:</p> <p>20000218_medgold_wp3_douro_MOD09A1_nmdi</p>
Normalized Difference Vegetation Index for Douro Valley based on MODIS
<p><strong>Normalized Difference Vegetation Index</strong> (NDVI) calculated using MODIS09 imagery provided by USGS/EROS.The original MODIS09 bands were used as data source and then the ndvi was calculated. </p> <p>NDVI quantifies vegetation by measuring the difference between near-infrared and red light (which vegetation absorbs). NDVI is a standardized way to measure healthy vegetation. High NDVI values indicates healthy vegetation.</p> <p>Each compressed file contains the NDVI by years. Internally each file have an ISO TC 211 metadata with a complete geographical description.</p> <p>spatial resolution: 463.313m<br> format: GeoTiff<br> reference system:SR-ORG 6842</p> <p> </p> <p>To easily manage the data, each file follow name structure:</p> <p>YYYYMMDD_medgold_workpackage_AoI_sensor_index.</p> <p>YYYYMMDD: Imagery acquisition date</p> <p>medgold: Project name</p> <p>sensor: sensor name</p> <p>workpackage: sectorial workpackage name ( WP2 - Olive Oil Sector, WP3 – Wine Grape sector, WP4- Durum wheat pasta sector)</p> <p>Aoi: Andalusia, Douro Valley.</p> <p>Index: NDVI, NMDI, NDWI</p> <p>Example:</p> <p>20000218_medgold_wpe_douro_MOD09A1_ndvi</p> <p> </p>
Figure 2 in Comparisons of the alpine bird communities across habitats and between autumn and winter in the mid- Yalong Zangbo River valley, Tibet
Figure 2. Dominance–diversity curves of bird assemblages in different alpine habitats in a valley near Lhasa, Tibet.
Figure 1 in Comparisons of the alpine bird communities across habitats and between autumn and winter in the mid- Yalong Zangbo River valley, Tibet
Figure 1. The map shows the vegetation patterns of the study site, and its location and landscape type at a larger geographical scale.
Figure 3 in Comparisons of the alpine bird communities across habitats and between autumn and winter in the mid- Yalong Zangbo River valley, Tibet
Figure 3. Seasonal change of relative abundances of several selected species in alpine habitats (pooled data) in a valley near Lhasa, Tibet.
Figs. 29–30 in Lixus davidiani, a new weevil species from Aras Valley (Coleoptera: Curculionidae: Lixinae)
Figs. 29–30. Habitat and host plants of Lixus davidiani sp. nov. 29 – habitat (Aras Valley, 15 km E of Karakurt); 30 – Lythrum salicaria L., host plant of the new species.
Figs. 25–28 in Lixus davidiani, a new weevil species from Aras Valley (Coleoptera: Curculionidae: Lixinae)
Figs. 25–28. Dorsal view of aedeagus of the Lixus spp. 25 – L. iridis Olivier, 1807; 26 – L. divaricatus Motschulsky, 1861; 27 – L. recurvus Olivier, 1807; 28 – L. davidiani sp. nov.
Figs. 13–20 in Lixus davidiani, a new weevil species from Aras Valley (Coleoptera: Curculionidae: Lixinae)
Figs. 13–20. Lixus davidiani sp. nov. (paratypus, female). 13 – habitus, dorsal view; 14 – rostrum; 15 – protibia; 16 – protarsus; 17 – tergite VIII; 18 – sternite VIII; 19 – coxite; 20 – spermatheca.
Figs. 1–12 in Lixus davidiani, a new weevil species from Aras Valley (Coleoptera: Curculionidae: Lixinae)
Figs. 1–12. Lixus davidiani sp. nov. (holotype, male). 1 – habitus, dorsal view; 2 – rostrum; 3 – protibia; 4 – protarsus; 5 – apex of elytra, ventral view; 6 – tergite VIII; 7 – sternite VIII; 8–9 – aedeagus, dorsal view; 10 – aedeagus, lateral view; 11 – spiculum gastrale; 12 – tegmen.
Figs. 21–24 in Lixus davidiani, a new weevil species from Aras Valley (Coleoptera: Curculionidae: Lixinae)
Figs. 21–24. Dorsal view of elytral apex of the Lixus spp. 21 – L. iridis Olivier, 1807; 22 – L. divaricatus Motschulsky, 1861; 23 – L. recurvus Olivier, 1807; 24 – L. davidiani sp. nov.
Fig. 6 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 6. Average daily travel distance and average sleeping time of the JACUZZI male for May–June (dry season) and December (wet season) from 2011 to 2013. Travel distance was counted for 13 days in August and for 13 days in December. Sleeping time was counted for 14 days in August and for 15 days in December. Solid line: travel distance. Dotted line: sleeping time.
Fig. 3 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 3. Activity budget of the SAPA male in both wet season (December) and dry season (August) from 2005 to 2008.
Fig. 2 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 2. Location of the BRL, the territory of the SAPA group and the territory of the JACUZZI group. The grey area represents the territory.
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.