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395 records · Page 22

Role of MODIS Vegetation Phenology Products in the U.S. for Warn Early Warning System for Forest Threats

U.S. forests occupy approx 751 million acres (approx 1/3 of total land). Several abiotic and biotic damage agents disturb, damage, kill, and/or threaten these forests. Regionally extensive forest disturbances can also threaten human life and property, bio-diversity and water supplies. timely regional forest disturbance monitoring products are needed to aid forest health management work at finer scales. daily MODIS data provide a means to monitor regional forest disturbances on a weekly basis, leveraging vegetation phenology. In response, the USFS and NASA began collaborating in 2006 to develop a Near Real Time (NRT) forest monitoring capability, based on MODIS NDVI data, as part of a national forest threat Early Warning System (EWS).

Spruce, Joseph↗

Contribution of Near Real Time MODIS-Based Forest Disturbance Detection Products to a National Forest Threat Early Warning System

U.S. forests occupy approx. 751 million acres (approx. 1/3 of total land). These forests are exposed to multiple biotic and abiotic threats that collectively damage extensive acreages each year. Hazardous forest disturbances can threaten human life and property, bio-diversity and water supplies. Timely regional forest monitoring products are needed to aid forest management and decision making by the US Forest Service and its state and private partners. Daily MODIS data products provide a means to monitor regional forest disturbances on a weekly basis. In response, we began work in 2006 to develop a Near Real Time (NRT) forest monitoring capability, based on MODIS NDVI data, as part of a national forest threat early warning system (EWS)

Spruce, Joseph↗

Recent Efforts to Improve the Near Real Time Forest Disturbance Monitoring Capabilities of the ForWarn System

This presentation discusses the development of anew method for computing NDVI temporal composites from near real time eMODIS data This research is being conducted to improve forest change products used in the ForWarn system for monitoring regional forest disturbances in the United States. ForWarn provides nation-wide NDVI-based forest disturbance detection products that are refreshed every 8 days. Current eMODIS and historical MOD13 24 day NDVI data are used to compute the disturbance detection products. The eMODIS 24 day NDVI data re-aggregated from 7 day NDVI products. The 24 day eMODIS NDVIs are generally cloud free, but do not necessarily use the freshest quality data. To shorten the disturbance detection time, a method has been developed that performs adaptive length/maximum value compositing of eMODIS NDVI, along with cloud and shadow "noise" mitigation. Tests indicate that this method can reduce detection rates by 8-16 days for known recent disturbance events, depending on the cloud frequencies and disturbance type. The noise mitigation in these tests, though imperfect, helped to improve quality of the resulting NDVI and forest change products.

Spruce, Joseph↗

Monitoring Regional Forest Disturbances across the US with near Real Time MODIS NDVI Products Resident to the ForWarn Forest Threat Early Warning System

Forest threats across the US have become increasingly evident in recent years. Sometimes these have resulted in regionally evident disturbance progressions (e.g., from drought, bark beetle outbreaks, and wildfires) that can occur across multiyear durations and have resulted in extensive forest overstory mortality. In addition to stand replacement disturbances, other forests are subject to ephemeral, sometimes yearly defoliation from various insects and varying types and intensities of ephemeral damage from storms. Sometimes, after prolonged severe disturbance, signs of recovery in terms of Normalized Difference Vegetation Index (NDVI) can occur. The growing prominence and threat of forest disturbances in part have led to the formation and implementation of the 2003 Healthy Forest Restoration Act which mandated that national forest threat early warning system be developed and deployed. In response, the US Forest Service collaborated with NASA, DOE Oakridge National Laboratory, and the USGS Eros Data Center to build and roll-out the near real time ForWarn early warning system for monitoring regionally evident forest disturbances. Given the diversity of disturbance types, severities, and durations, ForWarn employs multiple historical baselines that are used with current NDVI to derive a suite of six forest change products that are refreshed every 8 days. ForWarn employs daily quarter kilometer MODIS NDVI data from the Aqua and Terra satellites, including MOD13 data for deriving historical baseline NDVIs and eMODIS 7 NDVI for compiling current NDVI. In doing so, the Time Series Product Tool and the Phenological Parameters Estimation Tool are used to temporally de-noise, fuse, and aggregate current and historical MODIS NDVIs into 24 day composites refreshed every 8 days with 46 dates of products per year. The 24 day compositing interval enables disturbances to be detected, while minimizing the frequency of residual atmospheric contamination. Forest change products are computed versus the previous 1, previous 3, and all previous years in the MODIS record for a given 24 day interval. Other "weekly" forest change products include one computed using an adaptive length compositing method for quicker detection of disturbances, two others that adjust for seasonal fluctuations in normal vegetation phenology (e.g., early versus late springs). This overall approach enables forest disturbance dynamics from a variety of regionally evident biotic and abiotic forest disturbances to be viewed and assessed through the calendar year. The change products are also being utilized for forest change trend analysis and for developing regional forest overstory mortality products. ForWarn's forest change products are used to alert forest health specialists about new forest disturbances. Such alerts are also typically based on available Landsat, aerial, and ground data as well as communications with forest health specialists and previous experience. ForWarn products have been used to detect and track many types of regional disturbances to multiple forest types, including defoliation from caterpillars and severe storms, as well as mortality from both biotic and abiotic agents (e.g., bark beetles, drought, fire, anthropogenic clearing). ForWarn offers products that could be combined with other geospatial data on forest biomass to assess forest disturbance carbon impacts within the conterminous US.

Spruce, Joseph P.↗

Monitoring Regional Forest Disturbances across the US with Near Real Time MODIS NDVI Products included in the ForWarn Forest Threat Early Warning System

U.S. forests occupy approx.1/3 of total land area (approx. 304 million ha). Since 2000, a growing number of regionally evident forest disturbances have occurred due to abiotic and biotic agents. Regional forest disturbances can threaten human life and property, bio-diversity and water supplies. Timely regional forest disturbance monitoring products are needed to aid forest health management work. Near Real Time (NRT) twice daily MODIS NDVI data provide a means to monitor U.S. regional forest disturbances every 8 days. Since 2010, these NRT forest change products have been produced and posted on the US Forest Service ForWarn Early Warning System for Forest Threats.

Spruce, Joseph↗

Potential of Pest and Host Phenological Data in the Attribution of Regional Forest Disturbance Detection Maps According to Causal Agent

Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced since 2010 for the conterminous U.S., as part of the on-line ForWarn national forest threat early warning system. The latter has been used by the forest health community to identify and track many regional forest disturbances caused by multiple biotic and abiotic damage agents. Attribution of causal agents for detected disturbances has been a goal since project initiation in 2006. Combined with detailed cover type maps, geospatial pest phenology data offer a potential means for narrowing the candidate causal agents responsible for a given biotic disturbance. U.S. Aerial Detection Surveys (ADS) employ such phenology data. Historic ADS products provide general locational data on recent insect-induced forest type specific disturbances that may help in determining candidate causal agents for MODIS-based disturbance maps, especially when combined with other historic geospatial disturbance data (e.g., wildfire burn scars and drought maps). Historic ADS disturbance detection polygons can show severe and extensive regional forest disturbances, though they also can show polygons with sparsely scattered or infrequent disturbances. Examples will be discussed that use various historic disturbance data to help determine potential causes of MODIS-detected regional forest disturbance anomalies.

Spruce, Joseph↗

Potential for Expanding the Near Real Time ForWarn Regional Forest Monitoring System to Include Alaska

The on-line near real time (NRT) ForWarn system is currently deployed to monitor regional forest disturbances within the conterminous United States (CONUS), using daily MODIS Aqua and Terra NDVI data to derive monitoring products. The Healthy Forest Restoration Act of 2003 mandated such a system. Work on ForWarn began in 2006 with development and validation of retrospective MODIS NDVI-based forest monitoring products. Subsequently, NRT forest disturbance monitoring products were demonstrated, leading to the actual system deployment in 2010. ForWarn provides new CONUS forest disturbance monitoring products every 8 days, using USGS eMODIS data for current NDVI. ForWarn currently does not cover Alaska, which includes extensive forest lands at risk to multiple biotic and abiotic threats. This poster discusses a case study using Alaska eMODIS Terra data to derive ForWarn like forest change products during the 2010 growing season. The eMODIS system provides current MODIS Terra NDVI products for Alaska. Resulting forest change products were assessed with ground, aerial, and Landsat reference data. When cloud and snow free, these preliminary products appeared to capture regional forest disturbances from insect defoliation and fires; however, more work is needed to mitigate cloud and snow contamination, including integration of eMODIS Aqua data.

Spruce, Joseph P.↗

MODIS NDVI Change Detection Techniques and Products Used in the Near Real Time ForWarn System for Detecting, Monitoring, and Analyzing Regional Forest Disturbances

This presentation discusses MODIS NDVI change detection methods and products used in the ForWarn Early Warning System (EWS) for near real time (NRT) recognition and tracking of regionally evident forest disturbances throughout the conterminous US (CONUS). The latter has provided NRT forest change products to the forest health protection community since 2010, using temporally processed MODIS Aqua and Terra NDVI time series data to currently compute and post 6 different forest change products for CONUS every 8 days. Multiple change products are required to improve detectability and to more fully assess the nature of apparent disturbances. Each type of forest change product reports per pixel percent change in NDVI for a given 24 day interval, comparing current versus a given historical baseline NDVI. EMODIS 7 day expedited MODIS MOD13 data are used to obtain current and historical NDVIs, respectively. Historical NDVI data is processed with Time Series Product Tool (TSPT); and 2) the Phenological Parameters Estimation Tool (PPET) software. While each change products employ maximum value compositing (MVC) of NDVI, the design of specific products primarily differs in terms of the historical baseline. The three main change products use either 1, 3, or all previous years of MVC NDVI as a baseline. Another product uses an Adaptive Length Compositing (ALC) version of MVC to derive an alternative current NDVI that is the freshest quality NDVI as opposed to merely the MVC NDVI across a 24 day time frame. The ALC approach can improve detection speed by 8 to 16 days. ForWarn also includes 2 change products that improve detectability of forest disturbances in lieu of climatic fluctuations, especially in the spring and fall. One compares current MVC NDVI to the zonal maximum under the curve NDVI per pheno-region cluster class, considering all previous years in the MODIS record. The other compares current maximum NDVI to the mean of maximum NDVI for all previous MODIS years.

Spruce, Joseph P.↗

Recent Climate and Ice-Sheet Changes in West Antarctica Compared with the Past 2,000 Years

Changes in atmospheric circulation over the past five decades have enhanced the wind-driven inflow of warm ocean water onto the Antarctic continental shelf, where it melts ice shelves from below1-3. Atmospheric circulation changes have also caused rapid warming4 over the West Antarctic Ice Sheet, and contributed to declining sea-ice cover in the adjacent Amundsen-Bellingshausen seas5. It is unknown whether these changes are part of a longer-term trend. Here, we use waterisotope (Delta O-18) data from an array of ice-core records to place recent West Antarctic climate changes in the context of the past two millennia. We find that the δ18O of West Antarctic precipitation has increased significantly in the past 50 years, in parallel with the trend in temperature, and was probably more elevated during the 1990s than at any other time during the past 200 years. However, Delta O-18 anomalies comparable to those of recent decades occur about 1% of the time over the past 2,000 years. General circulation model simulations suggest that recent trends in Delta O-18 and climate in West Antarctica cannot be distinguished from decadal variability that originates in the tropics. We conclude that the uncertain trajectory of tropical climate variability represents a significant source of uncertainty in projections of West Antarctic climate and ice-sheet change.

Ice-sheet↗

Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid Hydrologic Modeling and Basin Planning

This paper discusses research methodology to develop Land Use Land Cover (LULC) mapsfor the Lower Mekong Basin (LMB) for basin planning, using both MODIS and Landsat satellitedata. The 2010 MODIS MOD09 and MYD09 8-day reflectance data was processed into monthlyNDVI maps with the Time Series Product Tool software package and then used to classify regionallycommon forest and agricultural LULC types. Dry season circa 2010 Landsat top of atmosphere reflectance mosaics were classified to map locally common LULC types. Unsupervised ISODATAclustering was used to derive most LULC classifications. MODIS and Landsat classifications werecombined with GIS methods to derive final 250-m LULC maps for Sub-basins (SBs) 1–8 of the LMB.The SB 7 LULC map with 14 classes was assessed for accuracy. This assessment compared randomlocations for sampled types on the SB 7 LULC map to geospatial reference data such as Landsat RGBs,MODIS NDVI phenologic profiles, high resolution satellite data, and Mekong River Commissiondata (e.g., crop calendars). The SB 7 LULC map showed an overall agreement to reference data of~81%. By grouping three deciduous forest classes into one, the overall agreement improved to ~87%.The project enabled updated regional LULC maps that included more detailed agriculture LULCtypes. LULC maps were supplied to project partners to improve use of Soil andWater AssessmentTool for modeling hydrology and water use, plus enhance LMB water and disaster managementin a region vulnerable to flooding, droughts, and anthropogenic change as part of basin planningand assessment.

land use land cover mapping; SWAT hydrologic model↗

Ground and Satellite Based Observation Datasets for the Lower Mekong River Basin

In ‘Satellite observations and modeling to understand the Lower Mekong River Basin streamflow variability’ [1] hydrological fluxes, meteorological variables, land cover land use maps, and soil characteristics and parameters data were compiled and processed for the Lower Mekong River Basin. In this work, daily streamflow time series data at nine gauges located at five different countries in the Mekong region (Thailand, Laos People׳s Democratic Republic (PDR), Myanmar, Cambodia, and Viet Nam) is presented. Satellite-based daily precipitation and air temperature (minimum & maximum) data is processed and provided over the entire basin as part of the dataset provided in this work. Moreover, land cover land use raster data that contains 18 classes that cover agriculture, urban, range and forests land cover land use classes for the basin is offered. In addition, a soil data that contains physical and chemical characteristics needed by physically based hydrological models to simulate the cycling of water and air is also provided.

Streamflow↗

Feasibility Study to Interactive Workshop: Building End-user Capacity to Integrate Earth Observation Data into Federally Endangered Atlantic Salmon (Salmo salar) Habitat Monitoring in Main

Changes in temperature and precipitation patterns, along with alterations in land cover threaten ongoing conservation efforts for Federally Endangered Atlantic salmon (Salmo salar) in Maine. Earth observation data offers a unique perspective for habitat monitoring that can complement habitat restoration and conservation activity on the ground. As a dual capacity building program, the NASA DEVELOP National Program strives to build the capacity of program participants by leveraging Earth observation data to address environmental concerns across the globe, while also building capacity in partner organizations to integrate Earth observation data into their decision making practices. Between September 2021 and August 2022, three NASA DEVELOP teams demonstrated the feasibility of utilizing NASA Earth observations including Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Terra MODIS, Landsat 5 Thematic Mapper (TM), Landsat 8 Operation Land Imager (OLI), and Shuttle Radar Topography Mission (SRTM) in conjunction with Sentinel-2 MultiSpectral Instrument (MSI) to assess temperature, precipitation, and land use land cover (LULC) over time throughout salmon habitat in Maine. While the first two teams completed projects that were categorized as NASA DEVELOP’s traditional feasibility projects, the third and final project team generated resources and planned an interactive workshop to transfer project methods to end-user organizations. Ultimately, the goal of this work was to not only inform the partner’s ongoing salmon population recovery and habitat restoration initiatives but provide tools that allow partner organizations to continue integrating Earth observation data into their work beyond their partnership with the program. This project serves as a case study within the NASA DEVELOP Program and provides lessons learned for moving beyond traditional feasibility studies to more interactive partner engagement and knowledge transfer practices.

Nicole Ramberg-Pihl↗

Assessing Change in Aspen Extent in Northern Yellowstone National Park

The trophic cascade among wolves, elk, and aspen has influenced the landscape of Yellowstone National Park. Aspen promote greater biodiversity and have been indirectly affected by the 1926 removal and 1995 reintroduction of wolves in the park. Partnered with Yellowstone National Park, Utah State University, and the University of Wisconsin–Stevens Point, NASA DEVELOP analyzed the change in aspen stand extent from 1954 to 2021 over the elk wintering range that occurs in the northern part of Yellowstone and southern Montana. Focusing on 113 stands corresponding with belt transects monitored annually since 1999, the team georeferenced and digitized 1954 historical aerial imagery to determine aspen stand extent. From 1986 to 2019, the team processed Landsat 5 Thematic Mapper (TM) and Sentinel-2 Multispectral Instrument (MSI) imagery for the entire elk wintering range using a random forest model to classify landcover types. Outputs were refined using a phenological approach that distinguishes between deciduous and evergreen landcover by differencing summer and fall vegetation indices. Finally, the team conducted a similar analysis for 2021, utilizing both Landsat 8 Operational Land Imager (OLI) and Sentinel-2 MSI imagery. The team again focused on the stands associated with belt transects for this analysis to compare the beginning and end of the study period. Preliminary results indicate a slight decline over time. These results expand the understanding of the role of wolves on aspen in the Yellowstone ecosystem and inform future rewilding decisions within the park and beyond.

Vanessa Bailey↗