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At least 19 records

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

This report details one of three experiments performed during FY 2007 for the NASA RPC (Rapid Prototyping Capability) at Stennis Space Center. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria dispar). The intent of the RPC experiment was to assess the degree to which VIIRS data can provide forest disturbance monitoring information as an input to a forest threat EWS (Early Warning System) as compared to the level of information that can be obtained from MODIS data. The USDA Forest Service (USFS) plans to use MODIS products for generating broad-scaled, regional monitoring products as input to an EWS for forest health threat assessment. NASA SSC is helping the USFS to evaluate and integrate currently available satellite remote sensing technologies and data products for the EWS, including the use of MODIS products for regional monitoring of forest disturbance. Gypsy moth defoliation of the mid-Appalachian highland region was selected as a case study. Gypsy moth is one of eight major forest insect threats listed in the Healthy Forest Restoration Act (HFRA) of 2003; the gypsy moth threatens eastern U.S. hardwood forests, which are also a concern highlighted in the HFRA of 2003. This region was selected for the project because extensive gypsy moth defoliation occurred there over multiple years during the MODIS operational period. This RPC experiment is relevant to several nationally important mapping applications, including agricultural efficiency, coastal management, ecological forecasting, disaster management, and carbon management. In this experiment, MODIS data and VIIRS data simulated from MODIS were assessed for their ability to contribute broad, regional geospatial information on gypsy moth defoliation. Landsat and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data were used to assess the quality of gypsy moth defoliation mapping products derived from MODIS data and from simulated VIIRS data. The project focused on use of data from MODIS Terra as opposed to MODIS Aqua mainly because only MODIS Terra data was collected during 2000 and 2001-years with comparatively high amounts of gypsy moth defoliation within the study area. The project assessed the quality of VIIRS data simulation products. Hyperion data was employed to assess the quality of MODIS-based VIIRS simulation datasets using image correlation analysis techniques. The ART (Application Research Toolbox) software was used for data simulation. Correlation analysis between MODIS-simulated VIIRS data and Hyperion-simulated VIIRS data for red, NIR (near-infrared), and NDVI (Normalized Difference Vegetation Index) image data products collectively indicate that useful, effective VIIRS simulations can be produced using Hyperion and MODIS data sources. The r(exp 2) for red, NIR, and NDVI products were 0.56, 0.63, and 0.62, respectively, indicating a moderately high correlation between the 2 data sources. Temporal decorrelation from different data acquisition times and image misregistration may have lowered correlation results. The RPC experiment also generated MODIS-based time series data products using the TSPT (Time Series Product Tool) software. Time series of simulated VIIRS NDVI products were produced at approximately 400-meter resolution GSD (Ground Sampling Distance) at nadir for comparison to MODIS NDVI products at either 250- or 500-meter GSD. The project also computed MODIS (MOD02) NDMI (Normalized Difference Moisture Index) products at 500-meter GSD for comparison to NDVI-based products. For each year during 2000-2006, MODIS and VIIRS (simulated from MOD02) time series were computed during the peak gypsy moth defoliation time frame in the study area (approximately June 10 through July 27). Gypsy moth defoliation mapping products from simated VIIRS and MOD02 time series were produced using multiple methods, including image classification and change detection via image differencing. The latter enabled an automated defoliation detection product computed using percent change in maximum NDVI for a peak defoliation period during 2001 compared to maximum NDVI across the entire 2000-2006 time frame. Final gypsy moth defoliation mapping products were assessed for accuracy using randomly sampled locations found on available geospatial reference data (Landsat and ASTER data in conjunction with defoliation map data from the USFS). Extensive gypsy moth defoliation patches were evident on screen displays of multitemporal color composites derived from MODIS data and from simulated VIIRS vegetation index data. Such defoliation was particularly evident for 2001, although widespread denuded forests were also seen for 2000 and 2003. These visualizations were validated using aforementioned reference data. Defoliation patches were visible on displays of MODIS-based NDVI and NDMI data. The viewing of apparent defoliation patches on all of these products necessitated adoption of a specialized temporal data processing method (e.g., maximum NDVI during the peak defoliation time frame). The frequency of cloud cover necessitated this approach. Multitemporal simulated VIIRS and MODIS Terra data both produced effective general classifications of defoliated forest versus other land cover. For 2001, the MOD02-simulated VIIRS 400-meter NDVI classification produced a similar yet slightly lower overall accuracy (87.28 percent with 0.72 Kappa) than the MOD02 250-meter NDVI classification (88.44 percent with 0.75 Kappa). The MOD13 250-meter NDVI classification had a lower overall accuracy (79.13 percent) and a much lower Kappa (0.46). The report discusses accuracy assessment results in much more detail, comparing overall classification and individual class accuracy statistics for simulated VIIRS 400-meter NDVI, MOD02 250-meter NDVI, MOD02-500 meter NDVI, MOD13 250-meter NDVI, and MOD02 500-meter NDMI classifications. Automated defoliation detection products from simulated VIIRS and MOD02 data for 2001 also yielded similar, relatively high overall classification accuracy (85.55 percent for the VIIRS 400-meter NDVI versus 87.28 percent for the MOD02 250-meter NDVI). In contrast, the USFS aerial sketch map of gypsy moth defoliation showed a lower overall classification accuracy at 73.64 percent. The overall classification Kappa values were also similar for the VIIRS (approximately 0.67 Kappa) versus the MOD02 (approximately 0.72 Kappa) automated defoliation detection product, which were much higher than the values exhibited by the USFS sketch map product (overall Kappa of approximately 0.47). The report provides additional details on the accuracy of automated gypsy moth defoliation detection products compared with USFS sketch maps. The results suggest that VIIRS data can be effectively simulated from MODIS data and that VIIRS data will produce gypsy moth defoliation mapping products that are similar to MODIS-based products. The results of the RPC experiment indicate that VIIRS and MODIS data products have good potential for integration into the forest threat EWS. The accuracy assessment was performed only for 2001 because of time constraints and a relative scarcity of cloud-free Landsat and ASTER data for the peak defoliation period of the other years in the 2000-2006 time series. Additional work should be performed to assess the accuracy of gypsy moth defoliation detection products for additional years.The study area (mid-Appalachian highlands) and application (gypsy moth forest defoliation) are not necessarily representative of all forested regions and of all forest threat disturbance agents. Additional work should be performed on other inland and coastal regions as well as for other major forest threats.

Spruce, Joseph P.↗

Estimating the Effect of Gypsy Moth Defloiation Using MODIS

The area of North American forests affected by gypsy moth defoliation continues to expand despite efforts to slow the spread. With the increased area of infestation, ecological, environmental and economic concerns about gypsy moth disturbance remain significant, necessitating coordinated, repeatable and comprehensive monitoring of the areas affected. In this study, our primary objective was to estimate the magnitude of defoliation using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery for a gypsy moth outbreak that occurred in the US central Appalachian Mountains in 2000 and 2001. We focused on determining the appropriate spectral MODIS indices and temporal compositing method to best monitor the effects of gypsy moth defoliation. We tested MODIS-based Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI), and two versions of the Normalized Difference Infrared index (NDIIb6 and NDIIb7, using the channels centered on 1640 nm and 2130 nm respectively) for their capacity to map defoliation as estimated by ground observations. In addition, we evaluated three temporal resolutions: daily, 8-day and 16-day data. We validated the results through quantitative comparison to Landsat based defoliation estimates and traditional sketch maps. Our MODIS based defoliation estimates based on NDIIb6 and NDIIb7 closely matched Landsat defoliation estimates derived from field data as well as sketch maps. We conclude that daily MODIS data can be used with confidence to monitor insect defoliation on an annual time scale, at least for larger patches (greater than 0.63 km2). Eight-day and 16-day MODIS composites may be of lesser use due to the ephemeral character of disturbance by the gypsy moth.

deBeurs, K. M.↗

Potential of VIIRS Data for Regional Monitoring of Gypsy Moth Defoliation: Implications for Forest Threat Early Warning System

A NASA RPC (Rapid Prototyping Capability) experiment was conducted to assess the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) data for monitoring non-native gypsy moth (Lymantria dispar) defoliation of forests. This experiment compares defoliation detection products computed from simulated VIIRS and from MODIS (Moderate Resolution Imaging Spectroradiometer) time series products as potential inputs to a forest threat EWS (Early Warning System) being developed for the USFS (USDA Forest Service). Gypsy moth causes extensive defoliation of broadleaved forests in the United States and is specifically identified in the Healthy Forest Restoration Act (HFRA) of 2003. The HFRA mandates development of a national forest threat EWS. This system is being built by the USFS and NASA is aiding integration of needed satellite data products into this system, including MODIS products. This RPC experiment enabled the MODIS follow-on, VIIRS, to be evaluated as a data source for EWS forest monitoring products. The experiment included 1) assessment of MODIS-simulated VIIRS NDVI products, and 2) evaluation of gypsy moth defoliation mapping products from MODIS-simulated VIIRS and from MODIS NDVI time series data. This experiment employed MODIS data collected over the approximately 15 million acre mid-Appalachian Highlands during the annual peak defoliation time frame (approximately June 10 through July 27) during 2000-2006. NASA Stennis Application Research Toolbox software was used to produce MODIS-simulated VIIRS data and NASA Stennis Time Series Product Tool software was employed to process MODIS and MODIS-simulated VIIRS time series data scaled to planetary reflectance. MODIS-simulated VIIRS data was assessed through comparison to Hyperion-simulated VIIRS data using data collected during gypsy moth defoliation. Hyperion-simulated MODIS data showed a high correlation with actual MODIS data (NDVI R2 of 0.877 and RMSE of 0.023). MODIS-simulated VIIRS data for the same date showed moderately high correlation with Hyperion-simulated VIIRS data (NDVI R2 of 0.62 and RMSE of 0.035), even though the datasets were collected about a half an hour apart during changing weather conditions. MODIS products (MOD02, MOD09, and MOD13) and MOD02-simulated VIIRS time series data were used to generate defoliation mapping products based on image classification and image differencing change detection techniques. Accuracy of final defoliation mapping products was assessed by image interpreting over 170 randomly sampled locations found on Landsat and ASTER data in conjunction with defoliation map data from the USFS. The MOD02-simulated VIIRS 400-meter NDVI classification produced a similar overall accuracy (87.28 percent with 0.72 Kappa) to the MOD02 250-meter NDVI classification (86.71 percent with 0.71 Kappa). In addition, the VIIRS 400-meter NDVI, MOD02 250-meter NDVI, and MOD02 500-meter NDVI showed good user and producer accuracies for the defoliated forest class (70 percent) and acceptable Kappa values (0.66). MOD02 and MOD02-simulated VIIRS data both showed promise as data sources for regional monitoring of forest disturbance due to insect defoliation.

Spruce, Joseph P.↗

Climate change drives reduced biocontrol of the invasive spongy moth

The effects of climate change on forest-defoliating insects are poorly understood, but could severely reduce forest productivity, biodiversity and timber production. For decades following its introduction in 1869, the spongy moth ( Lymantria dispar ) severely defoliated North American forests, but the introduction of the fungal pathogen Entomophaga maimaiga in 1989 suppressed spongy moth defoliation for 27 years. E. maimaiga , however, needs cool, moist conditions, whereas climate change is bringing hot, dry conditions to the range of the insect. Here, in this work, we use an empirically verified eco-climate model to project that climate change will sharply reduce E. maimaiga infection rates, thereby increasing spongy moth defoliation. Recent rebounds in defoliation are consistent with our projections. Our work demonstrates that the effects of climate change on species interactions can have important consequences for natural ecosystems.

climate-change ecology↗

Biomechanical drivers of the evolution of butterflies and moths with a coilable proboscis

Current biomechanical models suggest that butterflies and moths use their proboscis as a drinking straw pulling nectar as a continuous liquid column. Our analyses revealed an alternative mode for fluid uptake: drinking bubble trains that help defeat drag. We combined X-ray phase-contrast imaging, optical video microscopy, micro-computed tomography, phylogenetic models of evolution and fluid mechanics models of bubble-train formation to understand the biomechanics of butterfly and moth feeding. Our models suggest that the bubble-train mechanism appeared in the early evolution of butterflies and moths with a proboscis long enough to coil. We propose that, in addition to the ability to drink a continuous column of fluid from pools, the ability to exploit fluid films by capitalizing on bubble trains would have expanded the range of available food sources, facilitating diversification of Lepidoptera.

Palaoro, Alexandre V.↗

Computer analysis and mapping of gypsy moth levels in Pennsylvania using LANDSAT-1 digital data

The effectiveness of using LANDSAT-1 multispectral digital data and imagery, supplemented by ground truth and aerial photography, was investigated as a new method of surveying gypsy moth (Porthetria dispar (L.)) (Lepidoptera; Lymantriidae) defoliation, which has greatly increased in Pennsylvania in recent years. Since the acreage and severity of gypsy moth defoliation reaches a peak from mid-June through the first few days of July, the July 8, 1973, LANDSAT-1 scene was chosen for analysis. Results indicate that LANDSAT-1 data can be used to discriminate between defoliated and healthy vegetation in Pennsylvania and that digital processing methods can be used to map the extent and degree of defoliation.

Williams, D. L.↗

Gypsy moths and American dog ticks: Space partners

An experiment intended for the space shuttle and designed to investigate the effects of weightlessness and total darkness on gypsy moth eggs and engorged American dog ticks is described. The objectives are: (1) to reevaluate the effects of zero gravity on the termination of diapause/hibernation of embryonated gypsy moth eggs, (2) to determine the effect of zero gravity on the ovipositions and subsequent hatch from engorged female American dog ticks that have been induced to diapause in the laboratory, and (3) to determine whether morphological or biochemical changes occur in the insects under examination. Results will be compared with those from a similar experiment conducted on Skylab 4.

Hayes, D. K.↗

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

The Healthy Forest Restoration Act of 2003 mandated that a national forest threat Early Warning System (EWS) be developed. The USFS (USDA Forest Service) is currently building this EWS. NASA is helping the USFS to integrate remotely sensed data into the EWS, including MODIS data for monitoring forest disturbance at broad regional scales. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for contribution to the EWS. In doing so, the RPC project employed multitemporal simulated VIIRS and MODIS data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria despar). Gypsy moth is an invasive species threatening eastern U.S. hardwood forests. It is one of eight major forest insect threats listed in the Healthy Forest Restoration Act of 2003. This RPC experiment is relevant to several nationally important mapping applications, including carbon management, ecological forecasting, coastal management, and disaster management

Spruce, Joseph P.↗

Assessing MODIS-based Products and Techniques for Detecting Gypsy Moth Defoliation

The project showed potential of MODIS and VIIRS time series data for contributing defoliation detection products to the USFS forest threat early warning system. This study yielded the first satellite-based wall-to-wall 2001 gypsy moth defoliation map for the study area. Initial results led to follow-on work to map 2007 gypsy moth defoliation over the eastern United States (in progress). MODIS-based defoliation maps offer promise for aiding aerial sketch maps either in planning surveys and/or adjusting acreage estimates of annual defoliation. More work still needs to be done to assess potential of technology for "now casts"of defoliation.

Spruce, Joseph P.↗

The De Havilland "Moth"

Officially designated D.H. 60, De Havilland's Moth is a small, simply made, 770 lb. aircraft. It has had it's fittings reduced in number to assist in this, seats 2 (including pilot) and uses a Cirrus 60 HP. engine.

AIRPLANES - DEHAVILLAND 60 MOTH (BRIT )↗

The De Havilland "Tiger Moth"a low wing monoplane

With a speed of 186.5 M.P.H. and an operational altitude of 20,000 feet the De Havilland Tiger Moth has caused comment as it was introduced just before the King's Cup race of 1927. It is a single seater with unusual control configuration due to the cramped cockpit area.

AIRPLANES - DEHAVILLAND TIGER MOTH (BRIT )↗

Mapping Historic Gypsy Moth Defoliation with MODIS Satellite Data: Implications for Forest Threat Early Warning System

This viewgraph presentation reviews a project, the goal of which is to study the potential of MODIS data for monitoring historic gypsy moth defoliation. A NASA/USDA Forest Service (USFS) partnership was formed to perform the study. NASA is helping USFS to implement satellite data products into its emerging Forest Threat Early Warning System. The latter system is being developed by the USFS Eastern and Western Forest Threat Assessment Centers. The USFS Forest Threat Centers want to use MODIS time series data for regional monitoring of forest damage (e.g., defoliation) preferably in near real time. The study's methodology is described, and the results of the study are shown.

Spurce, Joseph P.↗

Interpretation and mapping of gypsy moth defoilation from ERTS (LANDSAT)-1 temporal composites

The author has identified the following significant results. Photointerpretation of temporally composited color Diazo transparencies of ERTS(LANDSAT) images is a practical method for detecting and locating levels of widespread defoliation. ERTS 9 x 9 inch images are essentially orthographic and are produced at a nearly constant 1:1,000,000 scale. This allows direct superposition of scenes for temporal composites. ERTS coverage provides a sweeping 180 km (110 mile) wide view, permitting one interpreter to rapidly delineate defoliation in an area requiring days and weeks of work by aerial surveys or computerized processing. Defoliation boundaries can be located on the images within maximum errors on the order of hundreds of meters. The enhancement process is much less expensive than aerial surveys or computerized processing. Maps produced directly from interpretation are manageable working products. The 18 day periodic coverage of ERTS is not frequent enough to replace aerial survey mapping because defoliation and refoliation move as waves.

Mcmurtry, G. J.↗

Gypsy moth defoliation assessment: Forest defoliation in detectable from satellite imagery

The author has identified the following significant results. ERTS-1 imagery obtained over eastern Pennsylvania during July 1973, indicates that forest defoliation is detectable from satellite imagery and correlates well with aerial visual survey data. It now appears that two damage classes (heavy and moderate-light) and areas of no visible defoliation can be detected and mapped from properly prepared false composite imagery. In areas where maple is the dominant species or in areas of small woodlots interspersed with agricultural areas, detection and subsequent mapping is more difficult.

Moore, H. J.↗

Monitoring gypsy moth defoliation by applying change detection techniques to Landsat imagery

The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.

Williams, D. L.↗