This dataset includes vegetation cover maps, Normalized Difference Vegetation Index (NDVI) maps, snow depth and thaw depth data that were obtained as part of a biocomplexity project on the North Slope of Alaska, USA, and the Northwest Territories (NWT), Canada. In Alaska, seven sites are located along the Dalton Highway and in the Prudhoe Bay Oilfield area, forming a transect across the climate gradient of the North Slope. From South to North, the sites are Happy Valley, Sagwon (an acidic and nonacidic site), Franklin Bluffs, Deadhorse, West Dock and Howe Island. Four sites are in the NWT, forming a latitudinal gradient from South to North; the sites include Inuvik, Green Cabin, Mould Bay, and Isachsen.

The Global Inventory Modelling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 22-year satellite record of monthly changes in terrestrial vegetation. This data set contains three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude with data from July 1981 through December 2002. New features include reduced NDVI variations arising from calibration, view geometry, volcanic aerosols, and other effects not related to actual vegetation change. In particular, NOAA-9 descending node data from September 1994 to January 1995, volcanic stratospheric aerosol correction for 1982-1984 and 1991-1994, and improved NDVI using empirical mode decomposition/reconstruction (EMD) to minimize effects of orbital drift. Global NDVI was generated to provide inputs for computing the time series of biophysical parameters contained in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II collection. NDVI is used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface.

These files were used in the analysis for "Greenness, mortality and mental health prescription rates in urban Scotland - a population level, observational study" Hyam. Submitted to RIO 2020.

Extract on construction of data

NDVI data was downloaded from the United States Geological Survey (USGS) Land Satellites Data System (LSDS) Science Research and Development (LSRD) (United States Geological Survey 2018). Which produces Level 2 and Level 3 data products from the Level 1 data of instruments aboard Landsat Satellites. For this study Surface Reflectance data generated by the Landsat Surface Reflectance Code (LaSRC) from the Operational Land Imager (OLI) instrument aboard the Landsat 8 satellite was used (United States Geological Survey 2018). The Surface Reflectance NDVI (sr_ndvi) product and Level-2 Pixel Quality Assessment band (pixel_qa) were downloaded for Landsat scenes 204/21, 205/21, 206/21, 204/20, 205/20, 206/20 WRS-2 (NASA 2018) for the calendar years 2013 to 2016. These scenes cover most of Scotland and include all the major urban areas. A full list of the 333 products is given in supplemental material. Suppl. material 2

All of Scotland is over 54° North and so for many satellite images the sun is at too low an angle to give reliable surface reflectance data especially in the winter months. Scotland also has an oceanic climate so the ground is often obscured by cloud or mist. To build a detailed, contiguous NDVI map of the whole country therefore requires combining images taken on many satellite passes especially if points are to be sampled multiple times to overcome measurement errors. The images downloaded from USGS were therefore combined. A cloud free version of each NDVI image was created by setting the pixels that corresponded to cloud, snow or water in the Quality Assurance Assessment band to NA. These cloud free images were then combined into a single, mosaic stack of images to cover all of the study area and then averaged down to a single layer as a tiff image. This was done for two seasonal periods, Winter (October, November, December of 2013, 2014, 2015 and 2016 combined with January, February, March of 2014, 2015, 2016) and summer (April, May, June, July, August, September of 2014, 2015, and 2016). The resulting two images covering most of Scotland for winters and summers between 2013 and 2016 and formed the basis of subsequent analysis.

These two files are included here along with a list of the Landsat products used to produce them.

A Normalized Difference Vegetation Index (NDVI) was applied to the source NAIP 2020 60cm imagery. NDVI=(NearIR-Red)/(NearIR+Red). The color ramp (produced by ESRI) goes from brown (less healthy vegetation) to red to green (healthier vegetation or more "greenness").This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

These images were produced by averaging the 1-km FASIR-NDVI maps by Jing Chen to a 10' (horizontal) by 5' (vertical) pixel size in a straight latitude/longitude grid. Each pixel represents the average NDVI of the 1-km pixels that fall in each 10' by 5' pixel, where more than 50% of the 1-km pixels in the 10' by 5' area are not cloud and are not missing. If more than 50% of the 1-km pixels are missing or cloudy, a value of 0 is assigned to the 10' by 5' pixel.

GCOM-C/SGLI L3 Map Normalized Difference Vegetation Index (NDVI) (8-Days,1/24 deg) is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is Sun-synchronous sub-recurrent Orbit satellite launched on December 23, 2017, which mounts SGLI and conducts long-term global observations of geophysical variables related to the global climate system across 28 items including aerosol and vegetation over 4 areas of atmosphere, land, ocean, and cryosphere. The data will be used to contribute to higher accuracy of global warming prediction. The SGLI has swath of 1150 km in the visible band and 1400 km in the infrared band. Level 3 products are defined to be products derived from Level 1B and Level 2 products by statistically processing the Level 1B and Level 2 products in time and space domains.This dataset is 8 days map-projected statistics product. This dataset includes NDVI: Normalized Difference Vegetation Index and QA_flag. Physical quantity unit is dimensionless. The stored statistics values are average (AVE) and quality flag (QA_flag). The statistical period is 8 days, also 1 day and 1 month statistics are available. The projection method is EQR. The generation unit is Global. The current version of the product is Version 3. The Version 2 is also available.

A Normalized Differential Vegetation Index (NDVI) was applied to the source 2005 1-meter resolution color infrared (CIR) imagery. NDVI=(NearIR-Red)/(NearIR+Red). The color ramp (produced by ESRI) goes from brown (less healthy vegetation) to red to green (healthier vegetation or more "greenness"). Lack of statewide color balancing of the source CIR imagery shows inconsistencies in NDVI results between adjacent areas. No access constraints, but there are use constraints (see source product metadata).The source color infrared (CIR) imagery was acquired during NAIP 2005 flights. The imagery was purchased from the North West Group (NWG) by three state agencies (California Dept. of Fish and Game, California Dept. of Transportation, and California Dept. of Water Resources). No access constraints, but there are use constraints. CIR coverage was not available in all areas. THIS IMAGERY IS NOT A NAIP PRODUCT. Band1=NearIR, Band2=R, Band3=G.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

Maps of 99 Landscape Assessment plots. These maps include the Landscape Assessment plot (circular 1000 m²) and surroundings. The maps display high-resolution orthophotos as true-color RGB composites (5 cm spatial resolution), canopy height (1 m), normalized difference vegetation index (NDVI; 1 m) and 3d representation of LiDAR point cloud. The original data can be found for the RGB composites here: https://doi.org/10.25625/1RB4CC the canopy height model here: https://doi.org/10.25625/CKLY7X the NDVI here: https://doi.org/10.25625/AIDFG2

This Normalized Difference Vegetation Index (NDVI) imagery layer features recent high-resolution (1m or better) aerial imagery for the continental United States, made available by the USDA Farm Production and Conservation Business Center (FPAC). The National Agriculture Imagery Program (NAIP) acquires aerial imagery during the agricultural growing seasons in the continental United States. Approximately half of the US is collected each year and each state is typically collected every other year.This imagery layer is updated annually as new imagery is made available. The NAIP program aims to make the imagery available to governmental agencies and to the public within a year of collection. The imagery is published in 4-bands (Red, Green, Blue, and Near Infrared) where available. Additional NAIP renderings include Natural Color and Color Infrared.This layer currently includes NAIP imagery from 2010 through 2023. You can discover and access other maps and layers available for NAIP through the Living Atlas of the World and through the NAIP Imagery group.All imagery in this layer is sourced from the NAIP Registry of Open Data on AWS.

The normalized difference vegetation index (NDVI) is a measure of greenness. NDVI was calculated as: NDVI = (NIR - R) / (NIR + R), where NIR is the spectral reflectance in the AVHRR near-infrared channel (0.725-1.1 µm, channel 2) where light-reflectance from the plant canopy is dominant, and R is the reflectance in the red channel (0.5 to 0.68 µm, channel 1), the portion of the spectrum where chlorophyll absorbs maximally. Trend in Arctic NDVI was calculated from a linear regression of NDVI values for all years 1982-2010. Pixels with significant trends (p < 0.05) were retained. Back to Circumpolar Arctic Vegetation Map Go to Website Link :: Toolik Arctic Geobotanical Atlas below for details on legend units, photos of map units and plant species, glossary, bibliography and links to ground data. Map Themes: AVHRR Biomass 2010, AVHRR Biomass Trend 1982-2010, AVHRR False Color Infrared 1993-1995, AVHRR NDVI 1993-1995, AVHRR NDVI Trend 1982-2010, AVHRR Summer Warmth Index 1982-2003, Bioclimate Subzone, Coastline and Treeline, Elevation, Floristic Provinces, Lake Cover, Landscape Physiography, Landscape Age, Substrate Chemistry, Vegetation References Bhatt, U. S., D. A. Walker, M. K. Raynolds, J. C. Comiso, H. E. Epstein, G. J. Jia, R. Gens, J. E. Pinzon, C. J. Tucker, C. E. Tweedie, and P. J. Webber. 2010. Circumpolar arctic tundra vegetation change is linked to sea ice decline. Earth Interactions 14:1-20. doi: 10.1175/2010EI1315.1171.

The normalized difference vegetation index (NDVI) is a measure of greenness. NDVI was calculated as: NDVI = (NIR - R) / (NIR + R), where NIR is the spectral reflectance in the AVHRR near-infrared channel (0.725-1.1 µm, channel 2) where light-reflectance from the plant canopy is dominant, and R is the reflectance in the red channel (0.5 to 0.68 µm, channel 1), the portion of the spectrum where chlorophyll absorbs maximally. Advanced Very High Resolution Radiometer (AVHRR) data were obtained from the USGS Global AVHRR 10-day composite data (http://edcdaac.usgs.gov/1KM/1kmhomepage.asp). Glaciers and oceans were masked out using information from the Digital Chart of the World (ESRI 1993). The image is composed of 1 x 1-km pixels. The color of each pixel was determined by its reflectance at the time of maximum greenness, selected from 10-day composite images from 11 July to 30 August 1993 and 1995 (Markon et al. 1995). These intervals cover the vegetation green-up-to-senescence period during two relatively warm years when summer-snow cover was at a minimum in the Arctic (Markon et al. 1995). Back to Circumpolar Arctic Vegetation Map Go to Website Link :: Toolik Arctic Geobotanical Atlas below for details on legend units, photos of map units and plant species, glossary, bibliography and links to ground data. Map Themes: AVHRR Biomass 2010, AVHRR Biomass Trend 1982-2010, AVHRR False Color-Infrared 1993-1995, AVHRR NDVI 1993-1995, AVHRR NDVI Trend 1982-2010, AVHRR Summer Warmth Index 1982-2003, Bioclimate Subzone, Coastline and Treeline, Elevation, Floristic Provinces, Lake Cover, Landscape Physiography, Landscape Age, Substrate Chemistry, Vegetation References Markon, C. J., M. D. Fleming, and E. F. Binnian. 1995. Characteristics of vegetation phenology over the Alaskan landscape using AVHRR time-series data. Polar Record 31:179-190.

This dataset holds the Global Inventory Modeling and Mapping Studies-3rd Generation V1.2 (GIMMS-3G+) data for the Normalized Difference Vegetation Index (NDVI). NDVI was based on corrected and calibrated measurements from Advanced Very High Resolution Radiometer (AVHRR) data with a spatial resolution of 0.0833 degree and global coverage for 1982 to 2022. Maximum NDVI values are reported within twice monthly compositing periods (two values per month). The dataset was assembled from different AVHRR sensors and accounts for various deleterious effects, such as calibration loss, orbital drift, and volcanic eruptions. The data are provided in NetCDF format.

The MODIS/Terra Gap-Filled, Smoothed NDVI 8-Day L4 500m SIN Grid product, with short-name MOD09A1G_NDVI is calculated from MODIS surface reflectance products (MOD09), at 500-m resolution. MODIS time series contains occasional lower quality data, gaps from persistent clouds, cloud contamination, and other gaps. Many modeling efforts, such as those used in NACP, that use MODIS data as input, require gap-free data. The procedure contains two algorithm stages, one for smoothing and one for gap filling, which attempt to maximize the use of high-quality data to replace missing or poor-quality observations.

The mapping results of urban health determinates (Normalized difference vegetation index (NDVI)) in 350m hexagonal grids of Inner London

This dataset is a normalised difference vegetation index (NDVI) representing vegetation 'greenness' across the City of Port Adelaide Enfield Council. It is based on 4-band multispectral Beijing-3 (BJ3A1) satellite imagery captured between January and February 2022 and has a spatial resolution of 0.5m.This data can be used to describe the 'greenness' across the Council for the purposes of urban planning, conservation and decision making.

Appendix 4, Figure 1: Max NDVI of each pixel in the period from 01-05-2022 to 01-10-2022.

Sentinel-2, 10m Multispectral 13-band imagery, rendered on-the-fly. Available for visualization and analytics, this Imagery Layer pulls directly from the Sentinel-2 on AWS collection and is updated daily with new imagery.This imagery layer can be used for multiple purposes including but not limited to vegetation, land cover, plant health, deforestation and environmental monitoring.Geographic CoverageGlobalContinental land masses from 65.4° South to 72.1° North, with these special guidelines:All coastal waters up to 20 km from the shoreAll islands greater than 100 km2All EU islandsAll closed seas (e.g. Caspian Sea)The Mediterranean SeaNote: Areas of interest going beyond the Mission baseline (as laid out in the Mission Requirements Document) will be assessed, and may be added to the baseline if sufficient resources are identified.Temporal CoverageThe revisit time for each point on Earth is every 5 days.This layer is updated daily with new imagery.This imagery layer is designed to include imagery collected within the past 14 months. Custom Image Services can be created for access to images older than 14 months.The number of images available will vary depending on location.Image Selection/FilteringThe most recent and cloud free image, for any location, is displayed by default.Any image available, within the past 14 months, can be displayed via custom filtering.Filtering can be done based on Acquisition Date, Estimated Cloud Cover, and Tile ID.Tile_ID is computed as [year][month][day]T[hours][minutes][seconds]_[UTMcode][latitudeband][square]_[sequence]. More…NOTE: Not using filters, and loading the entire archive, may affect performance.Analysis ReadyThis imagery layer is analysis ready with TOA correction applied.Visual RenderingDefault rendering is NDVI Colormap (Normalized Difference vegetation index with colormap) computed as NIR(Band8)-Red(Band4)/NIR(Band8)+Red(Band4) . The raw version of this layer is NDVI-Raw.Green represents vigorous vegetation and brown represents sparse vegetation.Rendering (or display) of band combinations and calculated indices is done on-the-fly from the source images via Raster Functions.Various pre-defined Raster Functions can be selected or custom functions created.Available renderings include: Agriculture with DRA, Bathymetric with DRA, Color-Infrared with DRA, Natural Color with DRA, Short-wave Infrared with DRA, Geology with DRA, NDMI Colorized, Normalized Difference Built-Up Index (NDBI), NDWI Raw, NDWI - with VRE Raw, NDVI – with VRE Raw (NDRE), NDVI - VRE only Raw, NDVI Raw, Normalized Burn RatioMultispectral BandsBandDescriptionWavelength (µm)Resolution (m)1Coastal aerosol0.433 - 0.453602Blue0.458 - 0.523103Green0.543 - 0.578104Red0.650 - 0.680105Vegetation Red Edge0.698 - 0.713206Vegetation Red Edge0.733 - 0.748207Vegetation Red Edge0.773 - 0.793208NIR0.785 - 0.900108ANarrow NIR0.855 - 0.875209Water vapour0.935 - 0.9556010SWIR – Cirrus1.365 - 1.3856011SWIR-11.565 - 1.6552012SWIR-22.100 - 2.28020Additional NotesOverviews exist with a spatial resolution of 150m and are updated every quarter based on the best and latest imagery available at that time.To work with source images at all scales, the ‘Lock Raster’ functionality is available.NOTE: ‘Lock Raster’ should only be used on the layer for short periods of time, as the imagery and associated record Object IDs may change daily.This ArcGIS Server dynamic imagery layer can be used in Web Maps and ArcGIS Desktop as well as Web and Mobile applications using the REST based Image services API.Images can be exported up to a maximum of 4,000 columns x 4,000 rows per request.Data SourceSentinel-2 imagery is the result of close collaboration between the (European Space Agency) ESA, the European Commission and USGS. Data is hosted by the Amazon Web Services as part of their Registry of Open Data. Users can access the imagery from Sentinel-2 on AWS , or alternatively access Sentinel2Look Viewer, EarthExplorer or the Copernicus Open Access Hub to download the scenes.For information on Sentinel-2 imagery, see Sentinel-2.

Since 1997 UMAC has been recieving weekly or biweekly AVHRR composite NDVI and departure from average data for the conterminous United States. These data are obtained from the EROS Data Center on a weekly basis. The data are then zipped and archived on cd. Due to the nature of our applications, the data are only acquired during the growing season of the midwestern states, from about the 10th week of the year to the 40th week. The NDVI composite is developed by taking the highest NDVI value perpixel over the composite period. The departure from average is the departure of each pixel in the composite from an average calculated over the period from the beginning of the project in 1989.

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/about/competitive-programs/measures) Vegetation Index and Phenology (VIP) global datasets were created using Advanced Very High Resolution Radiometer (AVHRR) N07, N09, N11, and N14 datasets (1981 - 1999) and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra MOD09 surface reflectance data (2000 - 2014). The VIP Vegetation Index (VI) product was developed to provide consistent measurements of the Normalized Difference Vegetation Index (NDVI) and modified Enhanced Vegetation Index (EVI2) spanning more than 30 years of data from multiple sensors. The EVI2 is a backward extension of AVHRR. Vegetation indices such as NDVI and EVI2 are useful for assessing the biophysical properties of the land surface, and are used to characterize vegetation phenology. Phenology tracks the seasonal life cycle of vegetation, and provides information on the biotic response to environmental changes. The VIP01 VI data product is a daily global file at 0.05 degree (5600 meter (m)) spatial resolution in geographic (Lat/Lon) grid format. The data are stored in Hierarchical Data Format-Earth Observing System (HDF-EOS) file format. The VIP01 VI product contains 11 Science Datasets (SDS), which includes the calculated VIs (NDVI and EVI2) as well as information on the quality assurance/pixel reliability, the input Visible/Near Infrared (VNIR) surface reflectance data, and viewing geometry. The Blue and Middle Infrared (MIR) surface reflectance data are only available for the MODIS era (2000 - 2014). Gaps in the daily product are filled using long term mean VI records derived from the more than 30 year time series of data, and are indicated as gap-filled in the Pixel Reliability SDS. A low resolution browse image showing NDVI as a color map is also available.Known Issues The Relative Azimuth Angle (RAA) for the input MODIS data is computed based on absolute values of the finer resolution pixels resulting in positive values and has minor usefulness. The RAA for the input AVHRR data contain values in the -360° to 360° range. The routine to restrict the values in the -180° to 180° range was accidentally missed and can be corrected using the following routine described in Section 4.2.1 of the User Guide and Algorithm Theoretical Basis Document: * SinRelativeAz=sin(RAA) CosRelativeAz=cos(RAA) Correct-RAA = atan2(SinRelativeAz,CosRelativeAz)