Sources
Spatiotemporal observations data
- GBIF.org (01 October 2018) GBIF Occurrence Download doi.org/10.15468/dl.idyqvk
- eBird Basic Dataset. Version: EBD_relNov-2017. Cornell Lab of Ornithology, Ithaca, New York. Nov 2017.
- Movebank Data Repository
Temporal Layer Data
These layers have a temporal component, the annotation occurs in both space and time.
STOAT is warming up.
| Product | Variable | Spatial Resolution (m) | Revisit time (days) | Unit | Start Date | End Date | Buffers | Description | Source |
|---|---|---|---|---|---|---|---|---|---|
| SRTM Elevation | Elevation | 30 | 0 | meters | spatial: 1000 meters, temporal: 1 days spatial: 250 meters, temporal: 1 days spatial: 30 meters, temporal: 1 days | Source | |||
| SRTM Elevation | Aspect | 30 | 0 | degrees | spatial: 30 meters, temporal: 1 days spatial: 1000 meters, temporal: 1 days spatial: 250 meters, temporal: 1 days | Source | |||
| SRTM Elevation | Slope | 30 | 0 | degrees | spatial: 250 meters, temporal: 1 days spatial: 1000 meters, temporal: 1 days spatial: 30 meters, temporal: 1 days | Source | |||
| MODIS | Land Surface Temperature Day | 1000 | 1 | kelvin | 2000-02-24 | 2018-11-16 | spatial: 1000 meters, temporal: 90 days spatial: 1000 meters, temporal: 30 days spatial: 1000 meters, temporal: 1 days | Source | |
| MODIS | Enhanced Vegetation Index | 250 | 1 | EVI | 2000-02-24 | spatial: 250 meters, temporal: 30 days spatial: 1000 meters, temporal: 1 days spatial: 1000 meters, temporal: 30 days spatial: 250 meters, temporal: 1 days spatial: 250 meters, temporal: 90 days | Source | ||
| MODIS | Land Surface Temperature Night | 1000 | 1 | kelvin | 2000-02-24 | 2018-11-16 | spatial: 1000 meters, temporal: 1 days spatial: 1000 meters, temporal: 90 days spatial: 1000 meters, temporal: 30 days | Source | |
| MODIS | Normalized Difference Vegetation Index | 250 | 1 | NDVI | 2000-02-24 | spatial: 250 meters, temporal: 90 days spatial: 250 meters, temporal: 30 days spatial: 1000 meters, temporal: 30 days spatial: 1000 meters, temporal: 1 days spatial: 250 meters, temporal: 1 days | Source | ||
| Landsat 8 | Enhanced Vegetation Index | 30 | 16 | EVI | 2013-04-01 | spatial: 250 meters, temporal: 32 days spatial: 100 meters, temporal: 32 days spatial: 100 meters, temporal: 16 days spatial: 250 meters, temporal: 16 days spatial: 30 meters, temporal: 16 days spatial: 30 meters, temporal: 32 days spatial: 500 meters, temporal: 16 days spatial: 500 meters, temporal: 32 days | Source | ||
| ESA CCI | Landcover | 0.002777777778 | 365 | 1992-01-01 | 2018-12-31 | spatial: 1000 meters, temporal: 365 days spatial: 300 meters, temporal: 365 days | Source | ||
| ESA CCI | Landcover | 0.002777777778 | 365 | land cover class (ESA CCI) | 1992-01-01 | 2018-12-31 | spatial: 1000 meters, temporal: 365 days spatial: 300 meters, temporal: 365 days | Source | |
| EarthEnv-CHELSA v2.1 | Precipitation | 0.008333333299999999 | 1 | mm*0.01 | 1979-01-01 | 2018-12-31 | spatial: 1000 meters, temporal: 15 days spatial: 1000 meters, temporal: 30 days spatial: 5000 meters, temporal: 1 days spatial: 5000 meters, temporal: 15 days spatial: 5000 meters, temporal: 30 days spatial: 10000 meters, temporal: 1 days spatial: 10000 meters, temporal: 15 days spatial: 10000 meters, temporal: 30 days spatial: 1000 meters, temporal: 1 days | Source |
Static Layer Data
These layers have no temporal component, they are static and do not change in time.
STOAT is warming up.
| Product | Variable | Spatial Resolution (m) | Unit | Buffers | Description | Source |
|---|---|---|---|---|---|---|
| TNC Global Human Modification | Human Modification (Static) | 0.009857533316 | degrees | spatial: 1000 meters, temporal: 1 days spatial: 10000 meters, temporal: 1 days spatial: 5000 meters, temporal: 1 days | From source: "The global Human Modification map (HM) provides a cumulative measure of human modification of terrestrial lands across the globe at a 1-km resolution. It is a continuous 0-1 metric that reflects the proportion of a landscape modified based on modeling the physical extents of 13 anthropogenic stressors and their estimated impacts using spatially-explicit global datasets with a median year of 2016." See: https://figshare.com/articles/Global_Human_Modification/7283087. This layer contains proportion of modified landscape at 1000 m. | Source |
| SRTM Elevation | Elevation variables (Static) | 30 | meters | From source: "NASA Shuttle Radar Topography Mission (SRTM) datasets result from a collaborative effort by the National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA - previously known as the National Imagery and Mapping Agency, or NIMA), as well as the participation of the German and Italian space agencies. The purpose of SRTM was to generate a near-global digital elevation model (DEM) of the Earth using radar interferometry. SRTM was a primary component of the payload on the Space Shuttle Endeavour during its STS-99 mission. Endeavour launched February 11, 2000 and flew for 11 days." This layer contains SRTM altitude, aspect, and slope at 30m resolution.. | Source | |
| MODIS | Summer EVI (Static) | 0.008333333299999999 | degrees | Long-term-average MODIS layers generated by the Jetz Lab at Yale University. Values are the cloud optimised means across the specified months from 2000-2019 using EVI values published by MODIS (MOD13A2 v006). The months used are June-August for the Summer layer, and November-February for the Winter layer.. | Source | |
| MODIS | Winter EVI (Static) | 0.008333333299999999 | degrees | Long-term-average MODIS layers generated by the Jetz Lab at Yale University. Values are the cloud optimised means across the specified months from 2000-2019 using EVI values published by MODIS (MOD13A2 v006). The months used are June-August for the Summer layer, and November-February for the Winter layer.. | Source | |
| EarthEnv Topography | Terrain Ruggedness Index (Static) | 0.008333333333000001 | degrees | spatial: 1000 meters, temporal: 1 days | From source: "We provide a fully standardized and global multivariate product of different terrain features has the potential to support many large-scale research applications. The product is based on the digital elevation model products of global 250 m GMTED2010 and near-global 90 m SRTM4.1dev. We provide the following topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile/tangential curvature, first/second order partial derivative, and 10 geomorphological landform classes. Each variable is provided at different aggregations from 1, 5, 10, 50 to 100 km spatial grains." See: https://www.earthenv.org/topography. This layer contains terrain ruggedness index at 1000 m, median aggregation, GMTED2010. | Source |
| EarthEnv Topography | Topographic Position Index (Static) | 0.008333333333000001 | degrees | spatial: 1000 meters, temporal: 1 days | From source: "We provide a fully standardized and global multivariate product of different terrain features has the potential to support many large-scale research applications. The product is based on the digital elevation model products of global 250 m GMTED2010 and near-global 90 m SRTM4.1dev. We provide the following topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile/tangential curvature, first/second order partial derivative, and 10 geomorphological landform classes. Each variable is provided at different aggregations from 1, 5, 10, 50 to 100 km spatial grains." See: https://www.earthenv.org/topography. This layer contains topographic position index at 1000 m, median aggregation, GMTED2010. | Source |
| EarthEnv Habitat Heterogeneity | Homogeneity (Static) | 0.008333333333000001 | degrees | spatial: 1000 meters, temporal: 1 days | From source: "The full datasets contain 14 metrics quantifying spatial heterogeneity of global habitat at multiple resolutions based on the textural features of Enhanced Vegetation Index (EVI) imagery acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS)." See: https://www.earthenv.org/texture. This layer contains homogeneity (similarity of EVI between adjacent pixels) at 1000 m. | Source |
| EarthEnv Habitat Heterogeneity | Coefficient of Variation (Static) | 0.008333333333000001 | degrees | spatial: 1000 meters, temporal: 1 days | From source: "The full datasets contain 14 metrics quantifying spatial heterogeneity of global habitat at multiple resolutions based on the textural features of Enhanced Vegetation Index (EVI) imagery acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS)." See: https://www.earthenv.org/texture. This layer contains coefficient of variation (Normalized despersion of EVI) at 1000 m. | Source |
| EarthEnv Habitat Heterogeneity | Homogeneity (Static) | 0.008333333333000001 | degrees | spatial: 1000 meters, temporal: 1 days | From source: "The full datasets contain 14 metrics quantifying spatial heterogeneity of global habitat at multiple resolutions based on the textural features of Enhanced Vegetation Index (EVI) imagery acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS)." See: https://www.earthenv.org/texture. This layer contains homogeneity (similarity of EVI between adjacent pixels) at 1000 m. | Source |
| EarthEnv Cloud Cover | Intra-annual Variability (Static) | 0.008333333333000001 | degrees | From source: "The full datasets integrate 15 years of twice-daily remote sensing-derived cloud observations at 1-km resolution." See: https://www.earthenv.org/cloud. This layer contains intra-annual cloud cover variability (standard deviation of mean monthly cloud frequencies 2000-2014). | Source | |
| EarthEnv-CHELSA | Mean Annual Precipitation (Static) | 0.008333333299999999 | degrees | spatial: 1000 meters, temporal: 0 days | From source: "CHELSA is a high resolution (30 arc sec) climate data set for the earth land surface areas currently hosted by the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. It includes monthly mean temperature and precipitation patterns for various time periods. CHELSA is based on a quasi-mechanistical statistical downscaling of reanalysis and global circulation model output and is freely available." See http://chelsa-climate.org. This layer contains mean annual precipitation (static) at 1000 m resolution. | Source |
| EarthEnv-CHELSA | Precipitation Seasonality (Static) | 0.008333333299999999 | degrees | spatial: 1000 meters, temporal: 0 days | From source: "CHELSA is a high resolution (30 arc sec) climate data set for the earth land surface areas currently hosted by the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. It includes monthly mean temperature and precipitation patterns for various time periods. CHELSA is based on a quasi-mechanistical statistical downscaling of reanalysis and global circulation model output and is freely available." See http://chelsa-climate.org. This layer contains precipitation seasonality (coefficient of variation) at 1000 m resolution. | Source |
| EarthEnv-CHELSA | Precipitation of Warmest Quarter (Static) | 0.008333333299999999 | degrees | spatial: 1000 meters, temporal: 0 days | From source: "CHELSA is a high resolution (30 arc sec) climate data set for the earth land surface areas currently hosted by the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. It includes monthly mean temperature and precipitation patterns for various time periods. CHELSA is based on a quasi-mechanistical statistical downscaling of reanalysis and global circulation model output and is freely available." See http://chelsa-climate.org. This layer contains cumulative precipitation of the warmest quarter of the year at 1000 m resolution. | Source |
| EarthEnv-CHELSA | Mean Annual Temperature (Static) | 0.008333333299999999 | degrees | spatial: 1000 meters, temporal: 0 days | From source: "CHELSA is a high resolution (30 arc sec) climate data set for the earth land surface areas currently hosted by the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. It includes monthly mean temperature and precipitation patterns for various time periods. CHELSA is based on a quasi-mechanistical statistical downscaling of reanalysis and global circulation model output and is freely available." See http://chelsa-climate.org. This layer contains mean annual temperature (static) at 1000 m resolution.. | Source |