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5,023 results for “landing”
Dataset for "Estimating Contribution of Sea Ice and Land Snow to Climate Sensitivity"
<p>The reproducible dataset for "Estimating Contribution of Sea Ice and Land Snow to Climate Sensitivity".</p>
Data and R code associated to the publication: "Effects of land use, cover and protection on stream and riparian ecosystem services and biodiversity"
<p>This R code and dataset accompany Hanna et al's 2019 publication in Conservation Biology titled "Effects of land use, cover and protection on stream and riparian ecosystem services and biodiversity". Read the "Metadata" tab of the data file and code annotations for more information. </p>
Quantifying the spatial heterogeneity of forest conversion costs and how it relates to biodiversity, conservation and land use history
<b>Description: </b><p>Start and end dates of salvage logging activity at the SAFE Project experimental site</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/6"><b>Quantifying the spatial heterogeneity of forest conversion costs and how it relates to biodiversity, conservation and land use history</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Sime Darby (grant)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Council (Research licence na)</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3266827">here</a></p><p><b>Files: </b>This dataset consists of 2 files: template_Symes.xlsx, SAFE_COUPE.zip</p><p><b>template_Symes.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Salvage logging records</b> (described in worksheet Data)</p><p>Description: Dates of earliest and latest known salvage logging activity in logging coupes</p><p>Number of fields: 10</p><p>Number of data rows: 187</p><p>Fields: </p><ul><li><b>CoupeNumber</b>: Coupe number (Field type: Location)</li><li><b>StartDateTrack</b>: Earliest date of logging activity recorded through GPS loggers on bulldozers (Field type: Date)</li><li><b>EndDateTrack</b>: Last date of logging activity recorded through GPS loggers on bulldozers (Field type: Date)</li><li><b>StartDateLocation</b>: Earliest date of logging activity recorded through 'Location' method (Field type: Date)</li><li><b>EndDateLocation</b>: Last date of logging activity recorded through 'Location' method (Field type: Date)</li><li><b>StartDateMeasurement</b>: Earliest date of logging activity recorded through 'Measurement' method (Field type: Date)</li><li><b>EndDateMeasurement</b>: Last date of logging activity recorded through 'Measurement' method (Field type: Date)</li><li><b>Contractor</b>: Name of the contractor responsible for the coupe (Field type: ID)</li><li><b>GlobalStart</b>: Earliest date of any recorded salvage logging activity (Field type: Date)</li><li><b>GlobalEnd</b>: Last date of any recorded salvage logging activity (Field type: Date)</li></ul></li></ol><p><b>SAFE_COUPE.zip</b></p><p>Description: SAFE coupe data</p><p><b>Date range: </b>2013-01-02 to 2015-12-31</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p>
Dataset for—The influence of land finance and public service supply on peri-urbanization: Evidence from the counties in China
<p>The dataset covers 2006 counties in China and ranges from 2009 to 2015.It includes land finance data at county level, efficiency of public service supply, economic bias of public service supply, household registration difference of public service supply, financial decentralization data, agricultural development level data, financial development level data, foreign direct investment data and industrial structure data.</p> <p>The data of land finance is from the Ministry of Land and Resources. It is also supplemented by the websites of the prefecture-level municipal land and resources bureaus, the provincial statistical yearbooks and Wind database. The data of public service variables and control variables mainly come from the Economic Statistical Yearbook of China County and City (2010-2016), Statistical Yearbook of China’s Counties (2010-2016), County-level statistical bulletin (2010-2016), Statistical Yearbook of China's Provinces (2010-2016), Statistical Yearbook of Prefecture-level Cities (2010-2016), Wind database, etc.</p> <p>This data set is mainly suitable for studying the development of land finance in the China's counties, the changing trend of peri-urbanization, and the research on the public services supply in China's counties.</p>
The effects of progressive land use changes on the distribution, abundance and behavior of vector mosquitoes in Sabah, Malaysia
<b>Description: </b><p>The objectives of this study were:1) To investigate the effects of progressive land use change from pre-development forest, through forest clearing and cultivation to plantation maintenance on occurrence of vector mosquitoes.<br>2) To determine the status of Anopheles donaldi as a vector of malaria in changing land uses.<br>3) To study the seasonality, abundance and behaviour of vector mosquitoes in study areas.<br><br>Methods<br>Study sites:<br>Study areas were located at The SAFE Project field site:<br>1. areas between Maliau Basin Conservation Area (old growth site),<br>2. logged forest sites in the Benta Wawasan area (area undergoing clearing),<br>3. oil palm plantation sites in Benta Wawasan's Silangan Batu Estate (oil palm site)<br><br>Mosquito collection<br>Mosquito samplings (adults and immature stages) were taken at all 3 study areas every alternate month from January 2017 until December 2018. Every sampling month, 2 collectors (n=2) spent 1 night at each study area where all-night human landing collection were carried out at 3 different sampling points for each collector. Collectors performed outdoor landing catches from 18:00 to 06:00. They collected mosquitoes that landed on naked legs with aspirators. Collectors were given prophylaxis prior to the sampling activities. Collected mosquitoes were then placed at hourly intervals inside glass vials. Mosquitoes were morphologically identified using available dichotomous keys the following morning. In every sampling period, meteorological data such as air temperature, relative humidity, atmospheric pressure and wind speed was recorded on hourly basis using a handheld weather station.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/180"><b>The effects of progressive land use changes on the distribution, abundance and behavior of vector mosquitoes in Sabah, Malaysia</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Universiti Malaysia Sabah (Studentship)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (SaBC) (Research licence Local)</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3475408">here</a></p><p><b>Files: </b>This consists of 1 file: Evyen_Mosquito_data.xlsx</p><p><b>Evyen_Mosquito_data.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>Mosquito_count</b> (described in worksheet Mosquito_count)</p><p>Description: The taxonomic identification of mosquitos caught</p><p>Number of fields: 6</p><p>Number of data rows: 40</p><p>Fields: </p><ul><li><b>Month</b>: month the mosquitos (Field type: categorical)</li><li><b>Species</b>: species ID of mosquitos caught (Field type: taxa)</li><li><b>MB</b>: Number of species caught in the Maliau Basin (Field type: numeric)</li><li><b>LFE</b>: Number of species caught in the LFE safe plot (Field type: numeric)</li><li><b>B_862</b>: Number of species caught in the B fragment SAFE (Field type: numeric)</li><li><b>Total</b>: Total caught per month (Field type: numeric)</li></ul></li><li><p><b>Mosquito_weather</b> (described in worksheet Mosquito_weather)</p><p>Description: The weather conditions of the mosquito samplings days</p><p>Number of fields: 9</p><p>Number of data rows: 203</p><p>Fields: </p><ul><li><b>Date</b>: Date of sampling (Field type: date)</li><li><b>Time</b>: Time of sampling (Field type: time)</li><li><b>Location</b>: Location of sampling (Field type: location)</li><li><b>Temperature</b>: Air tempreture (Field type: numeric)</li><li><b>Humidity</b>: Air humidity (Field type: numeric)</li><li><b>Wind Speed</b>: Wind (Field type: numeric)</li><li><b>Pressure</b>: Atomspheric pressure (Field type: numeric)</li><li><b>No.mosquito collected</b>: Number of mosquitos caught (Field type: numeric)</li><li><b>Notes</b>: Species (Field type: comments)</li></ul></li></ol><p><b>Date range: </b>2017-07-16 to 2018-08-21</p><p><b>Latitudinal extent: </b>4.4300 to 5.0700</p><p><b>Longitudinal extent: </b>116.5800 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Arthropoda <br> -  -  -  Insecta <br> -  -  -  -  Diptera <br> -  -  -  -  -  Culicidae <br> -  -  -  -  -  -  <i>Heizmannia</i> <br> -  -  -  -  -  -  <i>Anopheles</i> <br> -  -  -  -  -  -  -  <i>Anopheles balabacensis</i> <br> -  -  -  -  -  -  -  <i>Anopheles latens</i> <br> -  -  -  -  -  -  <i>Culex</i> <br> -  -  -  -  -  -  -  <i>Culex sitiens</i> <br> -  -  -  -  -  -  -  <i>Culex vishnui</i> <br> -  -  -  -  -  -  <i>Aedes</i> <br> -  -  -  -  -  -  -  <i>Aedes albopictus</i> <br> -  -  -  -  -  -  -  <i>Aedes ganapathi</i> <br></div><p></p>
Comparison of Dielectric Properties and Structure of Lunar Regolith at Chang'e-3 and Chang'e-4 Landing Sites Revealed by Ground Penetrating Radar
<p><strong>Fig 2(d) dataset.</strong> Signal Power profile and after R<sup>2</sup>, R<sup>3</sup>, R<sup>4 </sup>backscatter/spreading correction. The first column is depth in meter, second column is original data, third, forth, fifth column is original data after R<sup>2</sup>, R<sup>3</sup>, R<sup>4</sup> correction,respectively.</p> <p><strong>Fig 3(b) dataset. </strong>The first five days of Lunar penetrating radar (LPR) of CE-4 site with Auto Gain Control (AGC) method. Each column represents a single sample of data.</p> <p><strong>Fig 3(c) dataset. </strong>LPR dataset of CE-4 site using an exponential equation gain function for amplitude compensation. Each column represents a single sample of data.</p>
Code and data to reproduce the results of the paper: "Land Use Patterns and Climate Change---A Modeled Scenario of the Late Bronze Age in Southern Greece"
<p>Code and data to reproduce the results of Knitter et al. (2019): Land Use Patterns and Climate Change---A Modeled Scenario of the Late Bronze Age in Southern Greece. ERL.</p>
РИС. 10. Относительная ваЖность предикторов для моделей распространения Brephulopsis.cylindrica. in Land snails Brephulopsis cylindrica and Xeropicta derbentina (Gastropoda: Stylommatophora): case study of invasive species distribution modelling
РИС. 10. Относительная ваЖность предикторов для моделей распространения Brephulopsis.cylindrica.
РИС. 7. Пригодность местообитаний для Xeropicta derbentina согласно ансамблевой модели. in Land snails Brephulopsis cylindrica and Xeropicta derbentina (Gastropoda: Stylommatophora): case study of invasive species distribution modelling
РИС. 7. Пригодность местообитаний для Xeropicta derbentina согласно ансамблевой модели.
Figure 1 in Record of pestiferous land snail, Macrochlamys indica Godwin-Austen 1883 (Gastropoda: Ariophantidae), on citrus and guava plants in Punjab, India
Figure 1. Snail on Kinnow mandarin nursery plant.
Fig. 4 in Abundance And Diversity Of Land-Snails (Mollusca: Gastropoda) On Limestone Hills In Borneo
Fig. 4. Diversity against abundance for Tabin, with logarithmic trendline fitted.
Fig. 2 in Abundance And Diversity Of Land-Snails (Mollusca: Gastropoda) On Limestone Hills In Borneo
Fig. 2. Relative abundance (number of snails found per plot) against pH.
Fig. 3 in Abundance And Diversity Of Land-Snails (Mollusca: Gastropoda) On Limestone Hills In Borneo
Fig. 3. Relative abundance (number of snails found per plot) against carbonate concentration.
Fig. 5 in Abundance And Diversity Of Land-Snails (Mollusca: Gastropoda) On Limestone Hills In Borneo
Fig. 5. Diversity against abundance for Danum, with logarithmic trendline fitted.
Figure 1 in Distribution and diversity of earthworm (Annelida, Clitellata) populations across four land use types in northern Cameroon
Figure 1. Map of Cameroon showing the study area. Adapted from SOGEFI (2016).
Fig. 1 in Effect of temperature and egg laying depths on giant African land snail (Gastropoda: Achatinidae) viability
Fig. 1. Percent mortality of Lissachatina fulica at different temperature extremes.
Fig. 2 in Effect of temperature and egg laying depths on giant African land snail (Gastropoda: Achatinidae) viability
Fig. 2. Percent hatch and emergence of Lissachatina fulica from different soil depths.
Moreno_et_al_2024_Biodiversity impacts of Paris-compliant land-based mitigation scenarios
<p>Land cover areas in 2020 and 2050, charecterisation factors and PSL impacts in 2050 by land cover type and by ecoregion under the five mitigation scenarios modelled.</p>
Land and Fernald, 1992
Land, M.F., and Fernald, R.D. 1992. The Evolution of Eyes. Annual Review of Neuroscience, Vol. 15:1-29. <p></p>https://doi.org/10.1146/annurev.ne.15.030192.000245<p></p>
Land, 1980
Land, M. F. (1980). Compound eyes: old and new optical mechanisms. Nature, 287(5784), 681–686. <p></p>https://doi.org/10.1038/287681a0<p></p>
ScienceDex guides
Understand access before you commit
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.