Development, Processing, and Distribution of Satellite Data Products for Monitoring Landscape Processes in Alaska National Parks (FY2014)

Description

This announcement is to provide public notice of the National Park Service (NPS), intention to fund the following project with University of Alaska Fairbanks under a Cooperative Ecosystem Studies Unit (CESU) program. CESUs are partnerships that provide research, technical assistance, and education. The project 2014 intended award is $44,890. STATUTORY AUTHORITY: Agreements Concerning Cooperative Research and Training on NPS Resources (16 U.S.C. § 1a-2(j)): The Secretary may enter into agreements with public or private educational institutions, States and their political subdivisions, for the purpose of developing adequate, coordinated, cooperative research and training programs concerning the resources of the National Park System, and pursuant to such agreements, to accept from and make available to the cooperator such technical and support staff, financial assistance for mutually agreed upon research projects, supplies and equipment, facilities, and administrative services relating to cooperative research units as the Secretary deems appropriate. This project will establish a collaborative effort between the National Park Service (NPS) Alaska Region Inventory and Monitoring Program (AKR I&M) and the University of Alaska Fairbanks (UAF) Geographic Information Network of Alaska (GINA). The project will augment GINA¿s current satellite data holdings with Vegetative Greenness (NDVI) and Snow products, which are currently being used to monitor landscape processes by NPS staff within the AKR I&M. This collaborative effort seeks to build upon on-going work between NPS and GINA. The project will leverage GINA¿s expertise in satellite data acquisition, processing, management, and distribution, and it will streamline procedures employed by AKR I&M to measure ecological processes such as the onset and freeze-up of ice on large freshwater bodies, pattern and timing of snow cover, as well as determining trends in vegetative growing seasons. This project is a continuation of recent collaborative studies between AKR I&M and GINA which emphasized the development, processing, and distribution of historical NDVI and Snow products from MODIS and AVHRR satellite sensors. STATEMENT OF JOINT OBJECTIVES/PROJECT MANAGEMENT PLAN The intent of this project is to continue collaborative efforts between the AKRO I&M and GINA to augment GINA¿s AVHRR and MODIS holdings with current NDVI and Snow metrics products. In addition to maintaining MODIS archives and metric products by GINA, the project will also produce AVHRR-derived NDVI and Snow metrics for the NPS Alaska Region. This collaborative effort will once again leverage GINA¿s expertise in satellite data acquisition, processing, management, and distribution capabilities of AVHRR and MODIS satellite imagery, and streamline procedures currently employed by NPS I&M staff when measuring the onset and freeze-up of ice on large freshwater bodies, pattern and timing of snow cover, and trends and changes in vegetation growing season. There will be four primary objectives of the project ¿ Update existing MODIS NDVI and Snow metric products with the most recent year¿s data ¿ Develop an AVHRR processing algorithm to generate NDVI metrics for Alaska ¿ Evaluate AVHRR satellite sensor data for the production of snow metrics for Alaska ¿ Distribute satellite imagery, including derived snow and NDVI metrics data, to NPS and public users through Web Coverage Services (WCS), HTTP, and FTP mechanisms. RECIPIENT INVOLVEMENT UAF-GINA will perform the following: 1. MODIS NDVI Metrics Updates, Maintenance, and Delivery: Updates to MODIS NDVI metrics will include the estimation of a threshold greenness beyond the start of season (e.g., date of 20% of maximum NDVI). Maintenance of the data stack will include processing of the most recent year¿s NDVI metrics, to be updated annually. Working in coordination with NPS I&M staff, GINA will develop and serve the data products to NPS staff using publicly available WCS/WMS feeds and a designated, publicly accessible FTP site. a. Outcome: NDVI metrics algorithm sub-routine to include the estimation of a threshold greenness beyond the start of season (e.g., date of 20% of maximum NDVI). b. Outcome: Publicly accessible WCS/WMS raster data feeds and data sets showing yearly NDVI metrics for the following: i. onp ¿ time of onset of greenness (day) ii. lfonp ¿ time of threshold greenness ¿ TBD (day) iii. endp ¿ time of end of greenness (day) iv. durp ¿ duration of greenness (days) v. maxv - maximum NDVI value vi. maxp - time of maximum NDVI (day) c. Outcome: Electronic report documenting MODIS NDVI processing algorithm and estimation of threshold greenness date. d. Outcome: Copy of IDL code (processing scripts) to accompany documentation, delivered via hard drive. e. Outcome: Maintenance of project website for NPS and GINA staff to provide MODIS NDVI Metrics 2. MODIS Snow Metrics Updates, Maintenance: Updates to MODIS Snow metrics will include refining the continuous snow season definition and processing the most recent snow year¿s metrics, to be updated annually. Working in coordination with NPS I&M staff, GINA will continue to develop MODIS snow products and serve the data products to NPS staff using publicly accessible WCS feed and a designated, publicly accessible HTTP or FTP site. a. Outcome: Publicly accessible HTTP or FTP site and WCS raster data feed showing yearly 12-band snow metric images to include the following bands: i. first_snow_day, first day of the full snowo season (FSS start day) ii. last_snow_day, last day of the full snow season (FSS end day) iii. fss_range, last_snow_day-first_snow_day +1 iv. longest_css_first_day, first day of the longest CSS segment (CSS start day) v. longest_css_last_day, last day of the longest CSS segment (CSS end day) vi. longest_css_day_range, longest_css_last_day-longest_css_first_day +1 vii. snow_days, the number of snow days viii. no_snow_days, the number of no snow days ix. css_segment_num, the number of CSS segments x. mflag, pixel type (ocean, land, or lake/inland water) and type of snow (no snow, broken snow, or continuous snow) xi. cloud_days, number of cloud days xii. tot_css_days, total number of all days within CSS segments b. Outcome: Programming code used to produce snow metrics. 3. AVHRR NDVI Metrics Development, Documentation: GINA will process NDVI datasets and seasonal metrics of the 1989-present AVHRR 7- and 14-day NDVI products for the geographic extent of the state of Alaska. Working with NPS staff and other subject matter experts , GINA will port the MODIS NDVI metrics algorithm to accommodate AVHRR satellite data. After porting the MODIS NDVI code, the AVHRR products will be reviewed for QA/QC by NPS and science partners. Upon successful QA/QC review, GINA will process the entire AVHRR archive, and deliver the NDVI data products and yearly metrics via HTTP or FTP and hard drive to NPS. a. Outcome: Complete set of existing AVHRR raster data archive, and AVHRR-derived NDVI metrics data for Alaska,conveyed via HTTP or FTP and hard drive to NPS. b. Outcome: Electronic report documenting AVHRR NDVI and seasonal metrics data processing algorithm. c. Outcome: Copy of programming code (processing scripts) to accompany documentation, delivered via hard drive. NATIONAL PARK SERVICE INVOLVEMENT Substantial involvement on the part of the National Park Service is anticipated for the successful completion of the objectives to be funded by this award. In particular, the National Park Service will be responsible for the following: 1) NPS I&M staff will collaborate with GINA analysts to automate manual process flows related to the following image analysis processes: a. Estimating variability and long-term trends in the timing and duration of lake ice formation (freeze-up). b. Estimating variability and long-term trends in the timing and duration of snow cover (establishment of snowpack; snowmelt). c. Estimating variability and long-term trends in growing season NDVI (start-and end-of-season dates; duration of growing season; maximum NDVI). 2) NPS will work with GINA staff to develop efficient query-based web-delivery methods through web coverage services (WCS) of AVHRR and MODIS imagery, NDVI, and Snow products. 3) NPS staff will provide QA/QC of product deliverables developed by GINA for this project. 4) NPS will host ¿Product Delivery and Training Meetings¿ with GINA at NPS offices in Fairbanks and Anchorage to review NDVI and Snow product deliverables, and to receive training by GINA in the use of the Vegetation and Snow Extents web services. 5) NPS will cite cooperation with GINA in publications using AVHRR and MODIS NDVI and Snow products obtained through the efforts of this project.SINGLE-SOURCE JUSTIFICATION: Department of the Interior Policy (505 DM 2) requires a written justification which explains why competition is not practicable for each single-source award . The National Park Service did not solicit full and open competition for this award based the following criteria: Continuation and Unique Qualifications - The UAF Geographic Information Network of Alaska (GINA) is satellite data downlink, processing, archive, and distribution facility at the Geophysical Institute at the University of Alaska Fairbanks (UAF). GINA functions as a mechanism for collecting, organizing, and sharing diverse geospatial data and technological capabilities, and it acts as a clearinghouse for geospatial data specific to Alaska. Currently, GINA manages a large database of satellite imagery collected by polar-orbiting and geostationary satellites, which includes both the AVHRR and MODIS sensors. Through several on-line user interfaces, users are able to search for, view, and download images pertaining to specific satellite sensors such as AVHRR and MODIS. This project is part of an on-going collaborative e

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Grants.gov lists this opportunity under eligibility category code 06. These codes correspond to applicant types (state/local government, tribal organization, nonprofit, educational institution, individual, small business, etc.) defined in Grants.gov's own eligibility reference. See the current Grants.gov eligibility categories or check the official listing below for this opportunity's exact eligibility statement.

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