Trenton D. Benedict Matthew B. Rigge 20260925 raster digital data Phenology Metrics Version 4 Sioux Falls, SD U.S. Geological Survey Reed, B.C., Schwartz, M.D., Xiao, X., 2009. Remote Sensing Phenology, in: Noormets, A. (ED.). Phenology of Ecosystem Processes: Applications in Global Change Research. Springer New York: New York, NY, p. 231-246. https://www.usgs.gov/special-topics/remote-sensing-phenology https://earthexplorer.usgs.gov https://dx.doi.org/10.5066/F7PC30G1 https://doi.org/10.5066/P9PZTNBI Phenological dynamics of terrestrial ecosystems reflect the response of the Earth's vegetation canopy to changes in climate and hydrology and are thus important to monitor operationally. Researchers at the U.S. Geological Survey (USGS), Earth Resources Observation and Science (EROS) Center have developed methods for documenting the seasonal dynamics of vegetation in an operational fashion from satellite time-series data. The USGS made the decision to develop 2025 CONUS phenology metrics using Suomi National Polar-Orbiting Partnership (S-NPP) and Joint Polar-orbiting Satellite System-1 (JPSS-1) Visible Infrared Imaging Radiometer Suite (VIIRS) because of the decommissioning of Aqua C6 MODIS sensor. The readily available and consistently processed smoothed EROS VIIRS (eVIIRS) maximum Normalized Difference Vegetation Index (NDVI) weekly composites are the key input for the phenological metrics data. The weighted least-square approach for temporal smoothing (Swets et. al., 1999) was adopted for the NDVI time series to eliminate anomalously low vegetation index values and reduce time shifts caused by overgeneralization of the NDVI signal. This approach uses a moving temporal window to calculate a family of regression lines that are associated with each observation; the family of lines is then averaged at each point and interpolated between points to provide a continuous temporal NDVI signal. While interpolating values between points, a weighting factor is applied that favors peak (high value) points over valley points. Smoothed NDVI data were stacked in an ascending three year 156 NDVI composite file (52 NDVI composites per year). The three years include the previous year and the following year (e.g., 2025 phenology metrics included 2024, 2025, and 2026 smoothed NDVI). In instances where the full 52 composites are not achieved, an average for each remaining weekly composite from the processed year and three previous years are used to fill those composites in the latter year to reach 156 composites (to fill 2026, composites from years 2023, 2024, and 2025 were averaged). The smoothed NDVI data were subsequently ingested into a model developed in the Interactive Data Language (IDL) to quantify following phenological events: Start of Season Time (SOST); Start of Season NDVI (SOSN); End of Season Time (EOST); End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); Amplitude (AMP); and Time Integrated NDVI (TIN). For details about the algorithms and the data scaling for each of these seasonal phenological metrics, refer to the data creation process section of this metadata. References: Swets, D. L., Reed, B. C., Rowland, J. R., and S. E. Marko, 1999, "A Weighted Least-squares Approach to Temporal Smoothing of NDVI," In Proceedings of the 1999 ASPRS Annual Conference, from Image to Information, Portland, Oregon, May 17-21, 1999, Bethesda, Maryland, American Society for Photogrammetry and Remote Sensing, CD-ROM, 1 disc. The goal of this project is to provide USGS and other researchers with complete and consistent public domain information on the vegetation phenology across the conterminous U.S. at a 375-m spatial resolution. 20241231 20251229 ground condition Complete Every year, synchronized with the update of eVIIRS NDVI data and contingent upon availability of funding. -97.6095 -65.3946 51.7713 22.4794 USGS Thesaurus Vegetation Phenology EROS Visible Infrared Imaging Radiometer Suite (eVIIRS) Drought Phenology Metrics Remote Sensing Normalized Difference Vegetation Index (NDVI) Phenology Metrics Phenology Start of Season Time (SOST) Start of Season NDVI (SOSN) End of Season Time (EOST) End of Season NDVI (EOSN) Time of Maximum (MAXT) Maximum NDVI (MAXN) Duration (DUR) Amplitude (AMP) Time Integrated NDVI (TIN) Common geographic areas Conterminous U.S. (CONUS) Any downloading and use of these data signify a user's agreement to comprehension and compliance of the USGS Standard Disclaimer. Ensure all portions of metadata are read and clearly understood before using these data in order to protect both user and USGS interests. There is no guarantee of warranty concerning the accuracy of the data. Users should be aware that temporal changes may have occurred since this data set was collected and that some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations. Acknowledgement of the originating agencies would be appreciated in products derived from these data. Any user who modifies the data is obligated to describe the types of modifications they perform. User specifically agrees not to misrepresent the data, nor to imply that changes made were approved or endorsed by the U.S. Geological Survey. Please refer to http://www.usgs.gov/privacy.html for the USGS disclaimer. Trenton (Contractor) D Benedict U.S. Geological Survey, CORE SCIENCE SYSTEMS mailing address

47914 252nd Street

Sioux Falls SD 57198 US 605-594-2861 tbenedict@contractor.usgs.gov U.S. Geological Survey, Earth Resources Observation and Science Center The major processes include smoothing eVIIRS NDVI, stacking, resizing, mosaicking, calculating band math, and water masking. These processes are completed in ENVI 6.1 (64 bit) tool. The smoothed NDVI data were subsequently ingested into a model developed in the Interactive Data Language (IDL) to quantify specific phenological events (see 1 - 9 below). The current suites of 375-m spatial resolution phenological metrics are as follows: 1. Start of Season Time (SOST): starting time of the onset of the growing season (in day of the year). 2. Start of Season NDVI (SOSN): NDVI value at the starting time of the onset of the growing season (unitless- based on NDVI units). 3. End of Season Time (EOST): ending time of the growing season (in day of the year). 4. End of Season NDVI (EOSN): NDVI value at the ending time of the growing season (unitless-based on NDVI units). 5. Maximum Time (MAXT): the day of the year when the NDVI reaches its maximum during the growing season (in day of the year). 6. Maximum NDVI (MAXN): the highest (or peak) value in NDVI observed in a growing season (unitless-based on NDVI units). 7. Duration (DUR): the length of the growing season-the time between the start of season and end of season (in number of days). 8. Amplitude (AMP): the difference between the Maximum NDVI and NDVI at the day of start of season (unitless-based on NDVI units). 9. Time Integrated NDVI (TIN): the cumulative value of NDVI from the start to the end of the growing season (unitless-based on accumulated NDVI units). ESRI ArcGIS Pro 2.5.0 was used to convert ‘.bsq’ files to ‘grid’; and preparing maps. After completion of data production, USGS Metadata wizard tool was used to write and format metadata associated with these data. Total size of these 9 phenological metrics is 1.14 GB. A formal ground-based validation of phenological metrics data is important in order to evaluate the suitability of using these metrics in various applications. However, comprehensive ground validation is a challenge. Existing ground phenology data are not comprehensive; they do not comprehensively document phenological stages for all biomes, vegetation types, and years. Further, most existing ground observations are based on individual plants or plant species and do not document phenological events as they occur across vegetated canopies at the scales that are observed by broad-scale remotely sensed data. Another difficulty in evaluating these metrics is determining the appropriate ground-based phenological event they best represent. For example, ground phenological observations may document plant-specific events such as "first bud", "first leaf", and "first flower", for example. However, the SOST phenological metric, using the curve derivative approach, might represent leaf expansion in over 25 percent of the vegetated canopy. A few studies have evaluated the curve derivative method used in the processing of the SOST and EOST. Reed et al. (1994) reported that curve derivative phenological metrics show strong coincidence with expected phenological characteristics for various land cover types. The metrics were consistent with climatic reports, they illustrated the phenological consistency of corn and soybeans, characterized the phenology of four types of grassland, and established phenological consistency of deciduous and coniferous forests across the conterminous U.S. Schwartz et al. (2002) stated that the Delayed Moving Average (DMA) method results in early detection of start of season (SOS) because the DMA detected the first sustained flux of greenness rather than the initial leaf expansion of the dominant overstory species. Schwartz and Crawford (2001) reported that the use of DMA led to a systematic bias toward earlier SOS at higher latitudes due to the ability of northern plant species to initiate growth with less energy. Cook et al. (2005) reported good agreement (R2 = 0.63) between observed historical NDVI-derived start of season dates compared to dates predicted by hindcasting in a growing degree day climatic model over forested locations in Europe. Most studies conclude that satellite-derived phenological metrics are able to consistently identify a particular time in the time-series vegetation index profile of a pixel that corresponds to the stages of spring greenup and senescence conditions of the mosaic vegetation within that cell. Validating remote sensed phenological metrics is an active area of research and is being supported by efforts of the U.S. National Phenological Network (https://www.usanpn.org/&gt). Extensive ground measurements, ground campaigns that are specifically designed for evaluating remote sensing-based phenology, and phenocams (Richardson et al. 2007) will contribute to validation efforts in the future. References: Reed, B.C., Brown, J.F., VanderZee, D., Loveland, T.R., Merchant, J.W. and Ohlen, D.O., 1994. Measuring phenological variability from satellite imagery, Journal of Vegetation Science, 5:703-714. Cook, B.I., Smith, T.M., and M.E. Mann, 2005. The North Atlantic Oscillation and Regional Phenology prediction over Europe, Global Change Biology, 11(6):919-926. Richardson, A.D., J.P. Jenkins, B.H. Braswell, D.Y. Hollinger, S.V. Ollinger, and M-L. Smith 2007. Use of digital webcam images to track spring green-up in a deciduous broadleaf forest. Oecologia, 152: 323-334. Schwartz, M.D., and T.M. Crawford, 2001. Detecting energy balance modifications at the onset of spring, Physical Geography, 5, 394-409. Schwartz, M.D., B.C. Reed, and M.A.White, 2002, Assessing satellite-derived start-of-season measures in the conterminous USA, International Journal of Climatology, 22, 1793-1805. A formal and comprehensive accuracy assessment of these eVIIRS NDVI-based phenological metrics has yet to be conducted. Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. N/A N/A U.S. Geological Survey 20260925 raster digital data Digital and/or Hardcopy 20241231 20251229 ground condition Band, Startdate, Enddate, StartDOY-EndDOY 1 31-Dec 6-Jan 366006 2 7-Jan 13-Jan 007013 3 14-Jan 20-Jan 014020 4 21-Jan 27-Jan 021027 5 28-Jan 3-Feb 028034 6 4-Feb 10-Feb 035041 7 11-Feb 17-Feb 042048 8 18-Feb 24-Feb 049055 9 25-Feb 3-Mar 056062 10 4-Mar 10-Mar 063069 11 11-Mar 17-Mar 070076 12 18-Mar 24-Mar 077083 13 25-Mar 31-Mar 084090 14 1-Apr 7-Apr 091097 15 8-Apr 14-Apr 098104 16 15-Apr 21-Apr 105111 17 22-Apr 28-Apr 112118 18 29-Apr 5-May 119125 19 6-May 12-May 126132 20 13-May 19-May 133139 21 20-May 26-May 140146 22 27-May 2-Jun 147153 23 3-Jun 9-Jun 154160 24 10-Jun 16-Jun 161167 25 17-Jun 23-Jun 168174 26 24-Jun 30-Jun 175181 27 1-Jul 7-Jul 182188 28 8-Jul 14-Jul 189195 29 15-Jul 21-Jul 196202 30 22-Jul 28-Jul 203209 31 29-Jul 4-Aug 210216 32 5-Aug 11-Aug 217223 33 12-Aug 18-Aug 224230 34 19-Aug 25-Aug 231237 35 26-Aug 1-Sep 238244 36 2-Sep 8-Sep 245251 37 9-Sep 15-Sep 252258 38 16-Sep 22-Sep 259265 39 23-Sep 29-Sep 266272 40 30-Sep 6-Oct 273279 41 7-Oct 13-Oct 280286 42 14-Oct 20-Oct 287293 43 21-Oct 27-Oct 294300 44 28-Oct 3-Nov 301307 45 4-Nov 10-Nov 308314 46 11-Nov 17-Nov 315321 47 18-Nov 24-Nov 322328 48 25-Nov 1-Dec 329335 49 2-Dec 8-Dec 336342 50 9-Dec 15-Dec 343349 51 16-Dec 22-Dec 350356 52 23-Dec 29-Dec 357363 The major steps in processing eVIIRS phenology metrics are: 1. Smoothing eVIIRS NDVI, 2. IDL Processing, and 3. Post processing. 1. Smoothing eVIIRS NDVI: The NDVI is affected by a number of phenomena including cloud contamination, atmospheric perturbations, and variable viewing geometry of the sensor; all of which usually reduce the NDVI value. To minimize these effects on the NDVI value and at the same time to maximize the total number of observations per year, weekly composites of maximum NDVI value were used. However, composited data may still show lingering effects that tend to reduce the NDVI value and, more importantly, disturb the temporal profile of the vegetation signal. Spikes (mostly downward) are common phenomena in time-series NDVI data. These abrupt shifts in NDVI are frequently too short-lived to be a function of a real change in vegetation condition and can affect algorithms that are searching for increasing or decreasing trends representing real phenological shifts. Therefore, a temporal smoothing of the time series data is performed to reduce or eliminate spurious data spikes. For the purpose of extracting phenological metrics, a method of temporal smoothing of NDVI data was adopted that does not over-generalize the time-series profile but eliminates spurious spikes in the NDVI while retaining sustained changes in NDVI that are representative of vegetation phenological dynamics. The weighted least-square approach for temporal smoothing (Swets et. al., 1999) was adopted for the conterminous U.S. NDVI time series to eliminate anomalously low vegetation index values and reduce time shifts caused by overgeneralization of the NDVI signal. This approach uses a moving temporal window to calculate a family of regression lines that are associated with each observation; the family of lines is then averaged at each point and interpolated between points to provide a continuous temporal NDVI signal. While interpolating values between points, a weighting factor is applied that favors peak (high value) points over valley points. Smoothed NDVI data were stacked in an ascending three year 156 NDVI composite file (52 NDVI composites per year). The three years include the previous year and the following year (e.g. 2025 phenology metrics included 2024, 2025, and 2026 smoothed NDVI). In instances where the full 52 composites are not achieved, an average for each remaining weekly composite from the processed year and two previous years are used to fill those composites in the latter year to reach 156 composites (to fill 2026, composites from years 2023, 2024, and 2025 were averaged). NDVI composites for 2024 from week 22 and onward were made from JPSS-1 platform. 2. IDL Processing: The smoothed NDVI data were subsequently ingested into a model developed in the Interactive Data Language (IDL) to quantify specific phenological events: Start of Season Time (SOST); Start of Season NDVI (SOSN); End of Season Time (EOST); End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); Amplitude (AMP); and Time Integrated NDVI (TIN). 3. Post processing: Each of these phenology metrics has 156 bands (52 bands from each year: 2024, 2025, and 2026). The 3-yr stack was resized to 1-yr stack (52 bands). Then a band math was run in ENVI software and water layer was masked. ArcGIS Pro 2.5.0 was used to convert ‘.bsq’ files to Geotiff, and preparing maps. References: Swets, D. L., Reed, B. C., Rowland, J. R., and S. E. Marko, 1999, "A Weighted Least-squares Approach to Temporal Smoothing of NDVI," In Proceedings of the 1999 ASPRS Annual Conference, from Image to Information, Portland, Oregon, May 17-21, 1999, Bethesda, Maryland, American Society for Photogrammetry and Remote Sensing, CD-ROM, 1 disc. 20260714 Trenton (Contractor) D Benedict U.S. Geological Survey, CORE SCIENCE SYSTEMS mailing address

47914 252nd Street

Sioux Falls SD 57198 US 605-594-2861 tbenedict@contractor.usgs.gov Detailed description of processes involved in phenological metrics production: Start of Season Time (SOST): The SOST metric identifies the day of the year when photosynthesis of the vegetated canopy begins significant activity above a winter (or non-growing season) baseline at each 375-m pixel. The SOST method employs a curve-derivative approach wherein time-series smoothed NDVI data are compared to a delayed moving average (DMA) NDVI. In this method, the individual NDVI observations in a smoothed-time series are compared with the average value of the previous (backward-looking) NDVI observations (Reed et. al., 1994) to identify departures from an established trend. For version 1 phenology metrics, the backward-looking DMA window length parameter was set for 36 weeks. Therefore, the average NDVI of the prior 36 weekly observations served as a predicted value that compared each period to the actual NDVI. A trend change was detected when the actual NDVI value exceeded or crossed over the value of the DMA. The day of year when the DMA NDVI prediction exceeded the actual NDVI value was defined as the Start of Season (SOST). The precision of the SOST is one day. This one-day increment was achieved by interpolating daily NDVI between the 7-day composite NDVI observations assuming a linear relationship between change in NDVI observations and time increment for each period. Positive values indicate a SOST in the current year whereas negative values indicate a SOST day in the previous year (for example, a SOST value of -10 for 2025 indicates a start of season day of 355 in 2024). Valid values range from -150 to 365. In the SOST data layer, a cell value of 1000 represents water bodies, and a cell value of -1000 represents an area where SOST could not be detected due to insufficient change in time-series NDVI, or due to lack of sufficient input data. Start of Season NDVI (SOSN): The SOSN metric identifies the NDVI value on the day of the year when the SOST occurs for each 375-m pixel. The SOSN is based on NDVI values (unitless) with a scaling factor applied, and valid values range from 101 to 200. A scale factor [(NDVI*100) + 100] is applied to the actual NDVI values to depict them in byte range. To revert to unscaled NDVI, a scale factor [(SOSN-100) * 0.01] should be applied. In the SOSN data layer, a cell value of 255 represents water bodies, and a cell value of 100 represents the area where a SOSN could not be detected due to insufficient change in time-series NDVI, or insufficient input data. End of Season Time (EOST): The EOST metric identifies the day of the year when photosynthesis of the vegetated canopy has reached the end of senescence and approaches the winter (or non-growing season) baseline at each 375-m pixel. The EOST method employs a curve-derivative approach wherein time-series smoothed NDVI are compared to a forward-looking moving average NDVI. In this method, the individual NDVI observations in the time series are compared with the average value of the subsequent (forward-looking) NDVI observations (Reed et. al., 1994) to identify departures from a future trend. For version 1 phenology metrics, the forward-looking DMA window length parameter was set for 36 weeks. Therefore, the average NDVI of the following 36 weekly observations served as a predicted value that compared each period to the actual NDVI. A trend change was detected when the actual NDVI value fell below or crossed over the predicted moving average NDVI. When the actual NDVI falls below the forward-looking moving average NDVI prediction, this event is defined as the EOST. The precision of the EOST is one day. This one-day increment was achieved by interpolating daily NDVI between the 7-day composite NDVI observations assuming a linear relationship between change in NDVI and time increment for that period. The EOST units indicate the day of the year between 1 and 365. Values over 365 indicate a growing season end that falls beyond the calendar year (for example, an EOST value of 370 for 2025 describes that the end of season occurred on day 5 of 2026). Valid data ranges from 1 to 450. In the EOST data layer, a cell value of 1000 represents water bodies and a cell value of -1000 represents the area where the EOST could not be detected due to insufficient change in time-series NDVI, or due to lack of sufficient input data. End of Season NDVI (EOSN): The EOSN metric identifies the NDVI value on the day of the year when the EOST occurs for each 375-m pixel. The EOSN is based on NDVI values (unitless) with a scaling factor applied, and valid values range from 101 to 200. The same scale factor as mentioned in SOSN is also used for EOSN. For more details, please revert to SOSN scaling information and cell value representations. Maximum Time (MAXT): The MAXT metric indicates the day of the year when photosynthesis of the vegetated canopy reached its maximum in an annual growing season at each 375-m pixel. The MAXT method is based on time-series smoothed NDVI, the SOST, and the EOST. MAXT is identified by searching the corresponding date for the highest observed NDVI value between SOST and EOST days. The unit of the MAXT is day of the year and the values range from 1 to 365. In the MAXT data layer, a cell value of 1000 represents water bodies and a cell value of -1000 represents the area where a MAXT (SOST or EOST) could not be detected due to insufficient change in time-series NDVI, or due to lack of sufficient input data. Maximum NDVI (MAXN): The MAXN metric identifies the value of maximum NDVI observed when the MAXT occurs for at each 375-m pixel. The MAXN is based on NDVI values (unitless), and values range from 101 to 200. The same scale factor as mentioned in SOSN is also used for MAXN. For more details, please refer to SOSN scaling information and cell value representations. Duration (DUR): The DUR metric identifies the length of the growing season at each 375-m pixel. The DUR method employs other metrics (the SOST and EOST) and indicates the absolute number of days between the SOST and EOST. It is calculated by subtracting SOST from EOST for each annual growing season. The unit of the DUR is in days and valid values range from 1 to 365. In the DUR data layer, a cell value of 1000 represents water bodies and a cell value of -1000 represents the areas where a DUR could not be detected due to insufficient change in time-series NDVI, or due to lack of sufficient input data. Amplitude (AMP): The AMP metric identifies the seasonal range of photosynthetic activity from the baseline to the maximum amount for each 375-m pixel. The AMP method employs other metrics (SOSN and MAXN) and indicates the NDVI range between SOSN and MAXN. It is calculated by subtracting the value of SOSN from the value of MAXN. The AMP is based on NDVI values (unitless) with a scaling factor applied, and valid values range from 1 to 100. A scale factor [(AMP) * 0.01] should be applied to revert to unscaled NDVI. In the AMP data layer, a cell value of 255 represents water bodies and a cell value of 0 represents the area where an AMP could not be detected due to insufficient change in time-series NDVI, or due to lack of sufficient input data. Time Integrated NDVI (TIN): The TIN metric identifies the seasonal net accumulation of photosynthetic activity above the non-growing season baseline in the vegetated canopy at each 375-m pixel. The method for TIN incorporates time-series smoothed NDVI and four other phenological metrics (SOST, SOSN, EOST, and EOSN) Time integrated NDVI is computed by accumulating daily NDVI between SOST and EOST above the baseline indicated by SOST and EOST. The TIN is unitless and valid values range from 1 to 200. In the TIN data layer, a cell value of 255 represents water bodies and a cell value of 0 represents the area where TIN could not be detected due to insufficient change in time-series NDVI or due to lack of sufficient input data. 20260714 Raster Grid Cell 6115 7704 1 Lambert Azimuthal Equal Area -100.0 45.0 0.0 0.0 row and column 375.0 375.0 meters D_Sphere_ARC_INFO Sphere_ARC_INFO 6370997.0 298.257222101 Start of Season Time (SOST) Value Producer Defined Value Starting time of the onset of the growing season (in day of the year) Producer Defined -1000.0 1000.0 Start of Season NDVI (SOSN) Value Producer Defined Value NDVI value at the starting time of the onset of the growing season (unitless- based on scaled NDVI units) Producer Defined 255 NoData Producer defined 100 200 End of Season Time (EOST) Value Producer Defined Value Ending time of the growing season (in day of the year) Producer Defined -1000.0 1000.0 End of Season NDVI (EOSN) Value Producer Defined Value NDVI value at the ending time of the growing season (unitless-based on scaled NDVI units) Producer Defined 255 NoData Producer defined 100 200 Maximum Time (MAXT) Value Producer Defined Value The day of the year when the NDVI reaches its maximum during the growing season (in day of the year) Producer Defined -1000.0 1000.0 Maximum NDVI (MAXN Value Producer Defined Value The highest (or peak) value in NDVI observed in a growing season (unitless-based on scaled NDVI units) Producer Defined 255 NoData Producer defined 100 200 Amplitude (AMP) Value Producer Defined Value The difference between the Maximum NDVI and NDVI at the day of start of season (unitless-based on scaled NDVI units) Producer Defined 255 NoData Producer defined 0 100 Duration (DUR) Value Producer Defined Value The length of the growing season-the time between the start of season and end of season (in number of days) Producer Defined -1000.0 1000.0 Time Integrated NDVI (TIN) Value Producer Defined Value The cumulative value of NDVI from the start to the end of the growing season (unitless-based on accumulated NDVI units) Producer Defined 255 NoData Producer defined 0 200 The current suite of the phenology metrics across the conterminous U.S based on 375-m eVIIRS are: Start of Season Time (SOST); Start of Season NDVI (SOSN); End of Season Time (EOST); End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); Amplitude (AMP); and Time Integrated NDVI (TIN). Benedict, T.D. and Rigge, M.B., 2022, eVIIRS 375-m Remote Sensing Phenology Metrics - across the conterminous U.S. U.S. Geological Survey data release. https://doi.org/10.5066/P9PZTNBI. U.S. Geological Survey Customer Services Representative Customer Services Representative mailing and physical

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Sioux Falls SD 57198 USA 605-594-6151 605-594-6589 custserv@usgs.gov Although these data have been processed successfully on a computer system at the USGS, no warranty expressed or implied is made by the USGS regarding the use of the data on any other system, nor does the act of distribution constitute any such warranty. Data may have been compiled from various outside sources. Spatial information may not meet National Map Accuracy Standards. This information may be updated without notification. The USGS shall not be liable for any activity involving these data, installation, fitness of the data for a particular purpose, its use, or analyses results. The eVIIRS phenology data are available through the USGS Remote Sensing Phenology (http://phenology.cr.usgs.gov/get_data_main.php) and USGS EarthExplorer (http://earthexplorer.usgs.gov/) websites. The data are downloaded in a zip file that contains the necessary files for the respective format. The http://phenology.cr.usgs.gov/get_data_main.php interface offers quick and easy downloads by clicking on a file name. The http://earthexplorer.usgs.gov/ site is a more interactive interface that offers browse images and additional options for modifying search criteria. 20260925 U.S. Geological Survey, CORE SCIENCE SYSTEMS Trenton (Contractor) D Benedict Scientist II mailing address

47914 252nd Street

Sioux Falls SD 57198 US 605-594-2861 tbenedict@contractor.usgs.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998