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36 results for “water cover”
Landsat bands (cloud free), tree cover (2000, 2010), bare-ground and surface water occurrence at 250 m based on GlobalForestWatch and USGS
<p>Landsat bands (cloud free) and tree cover (2000) based on Hansen et al. (2013), global surface water occurrence based on Pekel at al. (2016), and tree cover and bare-ground cover (2010) based the USGS land cover mapping projects (University of Maryland, Department of Geographical Sciences and USGS). All layers resampled to spatial resolution 1/480 d.d. (about 250 m) using gdalwarp with "average" resampling. Antarctica is not included. Original layers are available at 30 m resolution.</p> <p>If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels:</p> <ul> <li>Technical issues and questions about the code: <a href="https://gitlab.com/openlandmap/global-layers/issues">https://gitlab.com/openlandmap/global-layers/issues</a> </li> <li>General questions and comments: <a href="https://disqus.com/home/forums/landgis/">https://disqus.com/home/forums/landgis/</a></li> </ul> <p>All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention:</p> <ul> <li>lcv = theme: land cover,</li> <li>bareground = variable: occurrence of bareground,</li> <li>landsat.usgs = determination method: Landsat landcover at 30 m resolution project (https://landcover.usgs.gov/glc/),</li> <li>p = probability or fraction,</li> <li>250m = spatial resolution / block support: 250 m,</li> <li>s0..0cm = vertical reference: land surface,</li> <li>2010..2010 = time reference: year 2010,</li> <li>v1.0 = version number: 1.0,</li> </ul>
Water chemistry, bedrock geology, and land cover data for Pennsylvania headwater streams: 2007-2022.
This data package contains all data necessary to run random forest and regression analyses featured in the article: 'Influence of bedrock geology on headwater stream pH' by G. Moyer, K. Frantz, and M. Shank. The data include water chemistry, land cover, and geologic formations for 271 headwater streams in Pennsylvania. Data from two previously published papers are also included: Ponce et al. (1979) and Lynch and Dise (1985), which were used as validation datasets.
University of Kansas Field Station: Water level and ice cover at Frank B. Cross Reservoir (Kansas, USA) 1993 - 2016
This database is from regular monitoring of water level and surface ice cover at Frank B. Cross Reservoir, a small freshwater impoundment in northeastern Kansas (USA). Cross Reservoir, located at the University of Kansas Field Station near Lawrence (KS), has a 3-ha surface area and a maximum depth of 12 m. Measurements of water elevation and estimates of ice cover were made at semi-monthly intervals (i.e., roughly every two weeks). The first data were taken in December 1993, shortly after the reservoir was constructed and first filled to capacity. Water levels were measured relative to a permanent water control structure. Ice cover observations were visual estimates of the percent (%) surface of the reservoir covered with ice. Water level measurements and ice cover estimates are made at the same time. This database is updated periodically and maintenance is ongoing.
Data and code from: A mixture of grass-legume cover crop species may ameliorate water stress in a changing climate, a greenhouse experiment at Dickinson College in Carlisle, PA, USA, 2021.
Data and R code associated with a greenhouse study investigating the influence of water stress on growth, root traits, and biomass of rye and crimson clover seedlings grown separately or together. Data were collected in the Dr. Inge P. Stafford Greenhouse of Dickinson College (Carlisle PA, USA) in June 2021.
Seasonality of in-lake and meteorological data from seven lakes, including daily measurements of water temperature, chlorophyll-a, dissolved oxygen, ice cover, air temperature, and solar radiation
This data product supports the manuscript "Seasons and seasonality in lakes: a synthesis amid global change" (Lewis et al. 2026; in review). Data were analyzed to understand how seasonality varies among diverse lakes and variables. Specifically, this data publication includes daily mean water temperature, chlorophyll-a, and dissolved oxygen at multiple depths, ice cover (binary), air temperature and solar radiation. Data availability and collection methods differ among lakes, as described in the Methods.
Site environmental, climate, water levels and temperatures, vegetation cover, and GIS change detection for assessing permafrost change in fens on the Tanana Flats, central Alaska
This data package provides data used to assess the roles of climate extremes, ecological succession, and hydrology in repeated permafrost aggradation and degradation in fens on the Tanana Flats, central Alaska. The package provides data on site environmental information, Fairbanks climate, vegetation cover, water levels and temperatures, as well as GIS files for fen change detection. The Site data include information on observers, locations, geomorphology, hydrology, soils, vegetation, and disturbance. The table has numerous fields that uses coding for class characteristics and these codes are described in the metadata as well as compiled in the ELS_Arctic_Boreal_Site_Soil_Veg_Code_Sheet_2020.docx. Alaska Climate records for Fairbanks (UAF Experiment Station) from 1904 to 2019 were acquired from the National Oceanic and Atmospheric Administration (https://www.ncdc.noaa.gov/cdo-web/). Additional data were obtained for the Nenana station (about 70 km southwest of Fairbanks), to fill in small data gaps (particularly precipitation/snow depth ruler measurements) in the Fairbanks record. We attributed the data with fields for summer (May-September) and winter periods (November-March) and hydrologic year (October-September) and calculated mean air temperature, precipitation, and snow depth by seasonal period (average of daily values) and year. The broad summer and winter periods were of interest because warmer and wetter summers increase soil heat input and warmer and snowier winters reduce soil heat loss. Fen hydrology data include information on fen water level/pressure and temperatures collected every two hours at seven sites within fens from 2011 to 2014. Vegetation composition and cover of fens, scrub, and forests was sampled to assess effects of thermokarst on vegetation change. Plant cover was determined by point-sampling at 100 points (including repetitive “hits” for all layers) distributed along 5 equally spaced rows (4-m long, 20 points per row) across the 10-m l
GLOBMAP SWF: a global annual surface water cover frequency dataset since 2000 for change analysis of inland water bodies
<p>The extent of surface water has been changing significantly due to climatic change and human activities. However, it is challenging to capture the interannual changes and trends of inland water bodies due to their high seasonal variation and abrupt change. We generated a global annual surface water cover frequency dataset (GLOBMAP SWF) from the MODIS land surface reflectance products to describe the seasonal and interannual dynamics of surface water. Surface water cover frequency (SWF) was proposed as the percentage of the time period when a pixel is covered by water in a year. Instead of determination of the water observations directly, the SWF was estimated indirectly by identifying land observations among annual clear-sky observations to reduce the influence of clouds and variability of water body and surface background characteristics, which helps to improve the applicability of the algorithm for different regions across the globe. Regional analysis demonstrates that our estimation results show reasonable performances on frozen water, saline lake, bright surface and cloud-frequent regions. This dataset can be used to analyze the interannual variation and change trend of highly dynamic inland water body extent with consideration of its seasonal variation.</p> <p>The GLOBMAP SWF dataset is provided in Version 1.0 (https://zenodo.org/record/6462883#.YxC16HZBw2w). Here we provide the number of MOD09A1 (MODIS 8-day composite land surface reflectance) clear-sky snow/ice-free observations (<em>N<sub>Clear</sub></em>) data as a quality dataset of GLOBMAP SWF product. The clear-sky observation refers to the valid MOD09A1 observation that not covered with clouds and snow/ice. The more available clear-sky observations, the more reliable the estimated SWF.</p> <p>The <em>N<sub>Clear </sub></em>dataset is provided by 296 1200 km × 1200 km tiles at annual temporal and 500 m spatial resolutions in the sinusoidal projection with Geotiff format for each year during 2000-2020. The file is named as "GLOBMAPClearCount. AYYYY001.hHHvVV.V01.tif", where “YYYY” refers to the year of the file, and “HH” and “VV” explains the number of tiles that are the same with MODIS standard tile. The valid range is 0-46, scale factor is 1.0. The <em>N<sub>Clear </sub></em>of permanent water (land obervation count of 46), permanent snow/ice and terrain shadows are set to 50.</p>
Рис. 5. Дополнительные структуры, служаЩие укреплению Замочного краЯ и раковины у Laternula elliptica: А – дополнительнаЯ поддерживаюЩаЯ пластинка прикрывает макушечную Щель; Б – утолЩение ранее поврежденного краЯ раковины; В – пример воЗникновениЯ двух поддерживаюЩих пластинок. ОбоЗначениЯ: мщ – макушечнаЯ Щель; хр – хондрофор; ппЛ – поддерживаюЩаЯ пластинка; дпЛ – дополнительные пластинки; уКр – утолЩениЯ Задне-дорсального краЯ и краЯ сифонального ЗиЯниЯ. Fig. 5. Additional structures serving for consolidation of hinge margin and for restoration of shell edge in Laternula elliptica: А – the umbonal crack covered by additional buttress; Б – thickening of damaged edge; В – appearance of two supporting plates. Notes: мщ – umbonal crack; хр – chondrophore; ппЛ – buttress; дпЛ – additional supporting plate; уКр – thickening of posterior-dorsal margin. in Species of warm-water origin Laternula elliptica (King, 1832) (Mollusca: Bivalvia: Laternulidae), a widespread mollusk in recent Antarctica
Рис. 5. Дополнительные структуры, служаЩие укреплению Замочного краЯ и раковины у Laternula elliptica: А – дополнительнаЯ поддерживаюЩаЯ пластинка прикрывает макушечную Щель; Б – утолЩение ранее поврежденного краЯ раковины; В – пример воЗникновениЯ двух поддерживаюЩих пластинок. ОбоЗначениЯ: мщ – макушечнаЯ Щель; хр – хондрофор; ппЛ – поддерживаюЩаЯ пластинка; дпЛ – дополнительные пластинки; уКр – утолЩениЯ Задне-дорсального краЯ и краЯ сифонального ЗиЯниЯ. Fig. 5. Additional structures serving for consolidation of hinge margin and for restoration of shell edge in Laternula elliptica: А – the umbonal crack covered by additional buttress; Б – thickening of damaged edge; В – appearance of two supporting plates. Notes: мщ – umbonal crack; хр – chondrophore; ппЛ – buttress; дпЛ – additional supporting plate; уКр – thickening of posterior-dorsal margin.
Рис. 3. Фотографии Laternula elliptica, сделанные около cтанции «Прогресс», ВосточнаЯ Антарктида. L. elliptica на морском дне с медкими камнЯми или гравием, глубина 27 м (А); несколько сифональных отверстий L. elliptica над поверхностью мЯгких осадков вокруг голотурии Staurocucumis turqueti, глубина 27 м (В); раковина L. elliptica (длина около 110 мм) на снегу около майны сраЗу после иЗвлечениЯ иЗ воды (С); пустые раковины L. elliptica на морском дне, глубина 56 м (D); раковина L. elliptica (вид с дорсального краЯ) на мЯгких осадках с камнЯми, покрытыми иЗвестковыми водорослЯми, глубина 30 м (Е); пара сифональных отверстий L. elliptica на поверхности мЯгких осадков, глубина 27 м (F). Фотографии О. Савинкина (A, B, D–F) и В. Потина (С). Fig. 3. Photographs of Laternula elliptica taken near «Progress» Research Station (East Antarctica). Softshelled clam L. elliptica on sea bottom with small stowns or gravel, depth 27 m (A); several open siphons of L. elliptica above soft bottom sediments around holothurian Staurocucumis turqueti, depth 27 m (B); a shell of L. elliptica (length about 110 mm) on snow near a dive hole just after dragging out of water (C); empty shells of L. elliptica on seafloor, depth 56 m (D); a shell of Laternula elliptica (dorsal view) on soft deposits among stones, covering by Lithothamnion, depth 30 m (E); pair of siphonal opening of L. elliptica on surface of soft sediments, depth 27 m (F). Photographs are taken by O. Savinkin (A, B, D–F) and V. Potin (C). in Species of warm-water origin Laternula elliptica (King, 1832) (Mollusca: Bivalvia: Laternulidae), a widespread mollusk in recent Antarctica
Рис. 3. Фотографии Laternula elliptica, сделанные около cтанции «Прогресс», ВосточнаЯ Антарктида. L. elliptica на морском дне с медкими камнЯми или гравием, глубина 27 м (А); несколько сифональных отверстий L. elliptica над поверхностью мЯгких осадков вокруг голотурии Staurocucumis turqueti, глубина 27 м (В); раковина L. elliptica (длина около 110 мм) на снегу около майны сраЗу после иЗвлечениЯ иЗ воды (С); пустые раковины L. elliptica на морском дне, глубина 56 м (D); раковина L. elliptica (вид с дорсального краЯ) на мЯгких осадках с камнЯми, покрытыми иЗвестковыми водорослЯми, глубина 30 м (Е); пара сифональных отверстий L. elliptica на поверхности мЯгких осадков, глубина 27 м (F). Фотографии О. Савинкина (A, B, D–F) и В. Потина (С). Fig. 3. Photographs of Laternula elliptica taken near «Progress» Research Station (East Antarctica). Softshelled clam L. elliptica on sea bottom with small stowns or gravel, depth 27 m (A); several open siphons of L. elliptica above soft bottom sediments around holothurian Staurocucumis turqueti, depth 27 m (B); a shell of L. elliptica (length about 110 mm) on snow near a dive hole just after dragging out of water (C); empty shells of L. elliptica on seafloor, depth 56 m (D); a shell of Laternula elliptica (dorsal view) on soft deposits among stones, covering by Lithothamnion, depth 30 m (E); pair of siphonal opening of L. elliptica on surface of soft sediments, depth 27 m (F). Photographs are taken by O. Savinkin (A, B, D–F) and V. Potin (C).
MODIS Daily Cloud-gap-filled Fractional Snow Cover Dataset of the Asian Water Tower Region (2000-2022)
<p>The Asia Water Tower region, with the Qinghai-Tibet Plateau at its core, is the most widespread region of snow cover on Earth, except for the North and South Poles. The topographic heterogeneity of the Asian Water Tower region is so great that the snow cover is thin and patchy, resulting in a highly time-varying snow cover in the region, and therefore daily-scale fractional snow cover data are urgently needed. This dataset is based on the MODIS surface reflectance product MO/YD09GA product, and the MODIS daily cloud-free fractional snow cover dataset for the Asian Water Tower region from 2000 to 2022 was produced using the MESMA-AGE algorithm and the MSTI algorithm. The high spatial resolution Landsat-8 image was taken as the "ground truth", the RMSE was 0.16, and the MAE was 0.10. This dataset has a time series from 26 February 2000 to 31 December 2022 with a spatial resolution of 0.005°, which can provide quantitative snow cover information on the spatial distribution of snow for mountain hydrological models, land surface models, numerical weather forecasts, etc.</p>
Validation dataset of 30 m resolution Landsat-8 fractional snow cover in the Asian Water Tower region (2013-2022)
<p>This dataset is the validation dataset for the article 'MODIS Daily Cloud-gap-filled Fractional Snow Cover Dataset of the Asian Water Tower Region (2000-2022)', which is a 30m resolution Landsat-8 fractional snow cover dataset for the time period 2013-2022 in the Asian Water Tower Region. This dataset is based on 3046 scene Landsat-8 surface reflectance data and uses the MESMA-AGE algorithm to retrieve the fractional snow cover. Gaofen-2 images with higher resolution were used to evaluate the accuracy, and the results showed that the accuracy was better, with OA of 94.46% and RMSE of 0.094. The cloud cover of each image in this dataset is less than 10% and the snow cover is more than 30%, which can be used to validate medium- or coarse-scale snow products and to study the spatial distribution of snow at high spatial resolution.</p>
Snow cover and snow water equivalent for: How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?
Open the record for dataset details and reuse information.
Data: On the role of water table depth, and urban and vegetation cover on groundwater dry period susceptibility
Open the record for dataset details and reuse information.
Urban stormwater pond water quality and vegetation cover data
<p>These data include measurements of water physical and chemical parameters and littoral vegetation measurements in urban stormwater ponds located in three different urban land use types in Orlando, Florida, USA.</p>
Santa Rita Experimental Range site, station Pasture 5N at Santa Rita Experimental Range, study of plant cover of Lycium andersonii (water jacket) in units of percent on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Santa Rita Experimental Range (SRE) contains plant cover of Lycium andersonii (water jacket) measurements in percent units and were aggregated to a yearly timescale.
Santa Rita Experimental Range site, station Pasture 6B at Santa Rita Experimental Range, study of plant cover of Lycium andersonii (water jacket) in units of percent on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Santa Rita Experimental Range (SRE) contains plant cover of Lycium andersonii (water jacket) measurements in percent units and were aggregated to a yearly timescale.
Santa Rita Experimental Range site, station Santa Rita Experimental Range pastures where the existing mesquite were killed and the pastures were grazed: pastures 3, 5N, 5S, 6B and 12B, study of plant cover of Lycium andersonii (water jacket) in units of percent on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Santa Rita Experimental Range (SRE) contains plant cover of Lycium andersonii (water jacket) measurements in percent units and were aggregated to a yearly timescale.
Plant species percent cover data: Distribution of Wetland Plant Species in Relation to the Level of the Water Table
This study established permanent plots along transects in fifteen wetlands covering a range of wetland types. The plot are used to: 1) characterize the non-wooded wetlands at CCESR; 2) determine correlations of plant community type with environmental factors; 3) examine changes over a five year period.
Plant species percent cover data:Biodiversity: A field test of biofuel production and ground-water quality
Bioenergy could be an important part of the solution to the projected climate problems of the future, and in addition could provide auxiliary ecological services. The project described here aims to parameterize expected benefits of diverse prairie biofuel plantations for groundwater quality, and also to further evaluate its biofuel potential. This project, done in cooperation with the USGS, grows out of purely scientific discoveries in other Cedar Creek experiments. We know that diverse prairie systems are better able to retain inorganic nitrogen than monoculture systems (e.g., Dijkstra etal. 2007). However, nitrogen is just one pollutant of many being delivered to surface-water and ground-water from agricultural systems. There are a number of others including phosphorus, pesticides, and veterinary pharmaceuticals. This fact combined with the rising demand for corn grain ethanol could lead to further declines in the water quality of agricultural regions in the United States. Perennial vegetative buffers, in particular diverse prairies and/or hay (CRP), are proposed solutions. The vegetation in such buffers can be used for biofuel and simultaneously appear to be attenuate leaching of agricultural compounds through the unsaturated zone to groundwater. This 3-year cooperative USGS and UMN study will (1) examine the ability of prairies and hay (CRP) to attenuate leaching of agricultural compounds to ground-water (2) compare biofuel production of four cropping systems: diverse prairie, hay (CRP), corn grown with chemical fertilizer, and corn grown with a combination of manure and chemical fertilizer, (3) provide for future investigations into microbial antibiotic resistance and (4) provide a better understanding of the unsaturated zone hydrology and shallow groundwater recharge at Cedar Creek. The project will take place in the E120 field.
SGS-LTER Effects of water and nitrogen additions on plant species density and cover in shortgrass ecosystems on the Central Plains Experimental Range, Nunn, Colorado, USA 1997-2011, ARS Study Number 143
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. The objective of this research is to evaluate the long-term response of shortgrass ecosystems to additional water and nitrogen inputs. An experiment was conducted during the IBP project (1970-1975) in which water and nitrogen were applied (Lauenroth et al. 1978, Dodd and Lauenroth 1979, Milchunas and Lauenroth 1995). While we gained an enormous increment in our knowledge about shortgrass ecosystems from this experiment it raised as many questions as it answered. One of the problems was that the treatments were very high levels of nitrogen (100-150kg/ha N) and water (600 mm/growing season) additions. Additional information and referenced materials can be found: http://hdl.handle.net/10217/85629.
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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.