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At least 145 records · Page 8

Modeling and Prediction of Wildfire Hazard in Southern California, Integration of Models with Imaging Spectrometry

Large urban wildfires throughout southern California have caused billions of dollars of damage and significant loss of life over the last few decades. Rapid urban growth along the wildland interface, high fuel loads and a potential increase in the frequency of large fires due to climatic change suggest that the problem will worsen in the future. Improved fire spread prediction and reduced uncertainty in assessing fire hazard would be significant, both economically and socially. Current problems in the modeling of fire spread include the role of plant community differences, spatial heterogeneity in fuels and spatio-temporal changes in fuels. In this research, we evaluated the potential of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data for providing improved maps of wildfire fuel properties. Analysis concentrated in two areas of Southern California, the Santa Monica Mountains and Santa Barbara Front Range. Wildfire fuel information can be divided into four basic categories: fuel type, fuel load (live green and woody biomass), fuel moisture and fuel condition (live vs senesced fuels). To map fuel type, AVIRIS data were used to map vegetation species using Multiple Endmember Spectral Mixture Analysis (MESMA) and Binary Decision Trees. Green live biomass and canopy moisture were mapped using AVIRIS through analysis of the 980 nm liquid water absorption feature and compared to alternate measures of moisture and field measurements. Woody biomass was mapped using L and P band cross polarimetric data acquired in 1998 and 1999. Fuel condition was mapped using spectral mixture analysis to map green vegetation (green leaves), nonphotosynthetic vegetation (NPV; stems, wood and litter), shade and soil. Summaries describing the potential of hyperspectral and SAR data for fuel mapping are provided by Roberts et al. and Dennison et al. To utilize remotely sensed data to assess fire hazard, fuel-type maps were translated into standard fuel models accessible to the FARSITE fire spread simulator. The FARSITE model and BEHAVE are considered industry standards for fire behavior analysis. Anderson level fuels map, generated using a binary decision tree classifier are available for multiple dates in the Santa Monica Mountains and at least one date for Santa Barbara. Fuel maps that will fill in the areas between Santa Barbara and the Santa Monica Mountains study sites are in progress, as part of a NASA Regional Earth Science Application Center, the Southern California Wildfire Hazard Center. Species-level maps, were supplied to fire managing agencies (Los Angeles County Fire, California Department of Forestry). Research results were published extensively in the refereed and non-refereed literature. Educational outreach included funding of several graduate students, undergraduate intern training and an article featured in the California Alliance for Minorities Program (CAMP) Quarterly Journal.

Roberts, Dar A.↗

Relating SMMR 37 GHz polarization difference to precipitation and atmospheric carbon dioxide concentration - A reappraisal

The relations of Scanning Multi-channel Microwave Radiometer (SMMR) 37 GHz polarization difference to precipitation and atmospheric carbon dioxide (CO2) concentrations are reviewed. Annual precipitation data, a surrogate for green leaf vegetation density, are compared with the coincident SMMR 37 GHz polarization difference from arid and semi-arid West Africa for 1982-85. The SMMR 37 GHz polarization difference was found to be poorly correlated with precipitation in arid and semi-arid zones, contrary to previous reports. Coincident SMMR 37 GHz polarization difference and atmospheric CO2 concentration data from July 1981 to June 1983 are also reviewed. Previously suggested relations of the SMMR 37 GHz polarization difference to atmospheric CO2 concentrations were found to be heavily biased by winter conditions in the Northern Hemisphere. The use of the SMMR 37 GHz polarization difference for determining green leaf vegetation density, net primary production, atmospheric CO2 draw-down and related processes is questioned.

Tucker, C. J.↗

The vegetative index number and crop identification

A vegetative index number of numerical value was calculated from the digital values of the LANDSAT system to provide some measure of green growing vegetation. The usefulness of the green numbers for schemes in crop identification and acreage estimation is investigated and the Ashburn vegetation index (AVI) is compared with the Kauth-Thomas vegetation index (KVI) for crop identification schemes. Results of wheat acreage estimation using LACIE Procedure 1 and the AVI for eight sample segments are given. Tables show comparisons between the AVI and the KVI as well as visual results of the AVI.

Ashburn, P.↗

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

The author has identified the following significant results. The Great Plains Corridor rangeland project utilizes natural vegetation systems as phenological indicators of seasonal development and climatic effects upon regional growth conditions. A method has been developed for quantitative measurement of vegetation conditions over broad regions using ERTS-1 MSS data. Radiance values recorded in ERTS-1 spectral bands 5 and 7, corrected for sun angle, are used to compute a band ratio parameter which is shown to be correlated with green biomass and vegetation moisture content. This report details the progress being made toward determining factors associated with the transformed vegetation index (TVI) and limitations on the method. During the first year of ERTS-1 operation (cycles 1-20), an average of 50% usable ERTS-1 data was obtained for the ten Great Plains Corridor test sites.

Rouse, J. W., Jr.↗

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

The author has identified the following significant results. Preliminary evaluation of autumnal phase ground truth data suggests that the sampling procedures at the Great Plains Corridor network test sites are adequate to show relatively small temporal changes in above-ground vegetation biomass and vegetation condition. Vegetation changes measured August through December, reflect grazing intensity and environmental conditions at the test sites. Preliminary analysis of black and white imagery suggests that detail in vegetation patterns is much greater than originally anticipated. A first look analysis of single band imagery and digital data at two locations shows that woodland, grassland, and cropland areas are easily delineated. Computer derived grey-scale maps from MSS digital data were shown to be useful in identifying the location of small fields and features of the natural and cultivated lands. Single band imagery and digital data are believed to have important application for synoptic land use mapping and inventory. Initial ratio analysis, using band 5 and 7 data, suggests the applicability in the greenness of a vegetative scene.

Rouse, J. W., Jr.↗

Estimation of Crop Gross Primary Production (GPP): Fapar(sub Chl) Versus MOD15A2 FPAR

Photosynthesis (PSN) is a pigment level process in which antenna pigments (predominately chlorophylls) in chloroplasts absorb photosynthetically active radiation (PAR) for the photochemical process. PAR absorbed by foliar non-photosynthetic components is not used for PSN. The fraction of PAR absorbed (fAPAR) by a canopy/vegetation (i.e., fAPAR(sub canopy)) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) images, referred to as MOD15A2 FPAR, has been used to compute absorbed PAR (APAR) for PSN (APARPSN) which is utilized to produce the standard MODIS gross primary production (GPP) product, referred to as MOD17A2 GPP. In this study, the fraction of PAR absorbed by chlorophyll throughout the canopy (fAPAR(sub chl)) was retrieved from MODIS images for three AmeriFlux crop fields in Nebraska. There are few studies in the literature that compare the performance of MOD15A2 FPAR versus fAPAR(sub chl) in GPP estimation. In our study MOD15A2 FPAR and the retrieved fAPAR(sub chl) were compared with field fAPAR(sub canopy) and the fraction of PAR absorbed by green leaves of the vegetation (fAPAR(sub green)). MOD15A2 FPAR overestimated field fAPAR(sub canopy) in spring and in fall, and underestimated field fAPAR(sub canopy) in midsummer whereas fAPAR(sub chl) correctly captured the seasonal phenology. The retrieved fAPAR(sub chl) agreed well with field fAPAR(sub green) at early crop growth stage in June, and was less than field fAPAR(sub green) in late July, August and September. GPP estimates with fAPAR(sub chl) and with MOD15A2 FPAR were compared to tower flux GPP. GPP simulated with fAPAR(sub chl) was corroborated with tower flux GPP. Improvements in crop GPP estimation were achieved by replacing MOD15A2 FPAR with fAPAR(sub chl) which also reduced uncertainties of crop GPP estimates by 1.12-2.37 g C m(sup −2) d(sup −1).

GPM↗

Applied regional monitoring of the vernal advancement and retrogradation (Green wave effect) of natural vegetation in the Great Plains corridor

The author has identified the following significant results. LANDSAT 2 has shown that digital data products can be effectively employed on a regional basis to monitor changes in vegetation conditions. The TV16 was successfully applied to an extended test site and the Great Plains Corridor in tests of the ability to assess green forage biomass on rangelands as an index to vegetation condition. A strategy for using TV16 on a regional basis was developed and tested. These studies have shown that: (1) for rangelands with good vegetative cover, such as most of the Great Plains, and which are not heavily infested with brush or undesirable weed species, the LANDSAT digital data can provide a good estimate (within 250 kg/ha) of the quantity of green forage biomass, and (2) at least five levels of pasture and range feed conditions can be adequately mapped for extended regions.

Rouse, J. W., Jr.↗

A spectral method for determining the percentage of green herbage material in clipped samples

A laboratory radiometric method for the rapid determination of green and brown vegetation percentages in clipped grass samples has been developed and tested. The method uses red and photographic infrared radiance or reflectance differences between green and brown vegetation. Mixtures of green and brown material were found to have radiances or reflectances proportional to the percentage of green material present. This method may permit the use of rapid green/brown radiometric determinations to replace the tedious hand sorting now generally used. It may also have application in remote sensing of vegetation ground-truth work where the determination of dry green biomass in clipped samples is necessary.

Tucker, C. J.↗

A review of remote sensing and grasslands literature

Studies between 1971 and 1980 dealing with remote sensing of rangelands/grasslands in the multispectral band are summarized and evaluated. Vegetation and soil reflectance properties are described. In the majority of the studies, the effect of the reflectance of green rangelands vegetation on the reflectance from the total scene is the primary concern. Developments in technique are summarized and recommendations for further research are presented.

Tappan, G.↗

African land-cover classification using satellite data

Data from the advanced very high resolution radiometer sensor on the National Oceanic and Atmospheric Administration's operational series of meteorological satellites were used to classify land cover and monitor vegetation dynamics for Africa over a 19-month period. There was a correspondence between seasonal variations in the density and extent of green leaf vegetation and the patterns of rainfall associated with the movement of the Intertropical Convergence Zone. Regional variations, such as the 1983 drought in the Sahel of western Africa, were observed. Integration of the weekly satellite data with respect to time for a 12-month period produced a remotely sensed estimate of primary production based upon the density and duration of green leaf biomass. Eight of the 21-day composited data sets covering an 11-month period were used to produce a general land-cover classification that corresponded well with those of existing maps.

Tucker, C. J.↗

Changes in Vegetation Cover of Yukon River Drainages in Interior Alaska Estimated from MODIS Greenness Trends, 2000 to 2018

Trends and transitions in the growing season MODerate resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time-series at 250-m resolution were analyzed for the period from 2000 to 2018 to understand recent patterns of vegetation change in ecosystems of the Yukon River basin in interior Alaska. Statistical analysis of changes in the NDVI time series was conducted using the "Breaks for Additive Seasonal and Trend" method (BFAST). This structural change analysis indicated that NDVI breakpoints and negative 18-yr trends in vegetation greenness over the years since 2000 could be explained in large part by the impacts of severe wildfires, commonly affecting shrubland and forested ecosystems at relatively low elevations (< 300 m).

Potter, Christopher↗

Continental land cover classification using meteorological satellite data

The use of the National Oceanic and Atmospheric Administration's advanced very high resolution radiometer satellite data for classifying land cover and monitoring of vegetation dynamics over an extremely large area is demonstrated for the continent of Africa. Data from 17 imaging periods of 21 consecutive days each were composited by a technique sensitive to the in situ green-leaf biomass to provide cloud-free imagery for the whole continent. Virtually cloud-free images were obtainable even for equatorial areas. Seasonal variation in the density and extent of green leaf vegetation corresponded to the patterns of rainfall associated with the inter-tropical convergence zone. Regional variations, such as the 1982 drought in east Africa, were also observed. Integration of the weekly satellite data with respect to time produced a remotely sensed assessment of biological activity based upon density and duration of green-leaf biomass. Two of the 21-day composited data sets were used to produce a general land cover classification. The resultant land cover distributions correspond well to those of existing maps.

Tucker, C. J.↗

Applied regional monitoring of the vernal advancement and retrogradation (green wave effect) of natural vegetation in the Great Plains corridor

The author has identified the following significant results. Rangelands in southwest Texas were used to establish threshold values and limitations on measuring herbaceous biomass under typical arid and semi-arid range conditions. Previous regression relationships established between ND6 and green biomass for two different ecosystems were similar. The west Texas data set for brush-free sites was too small to be statistically conclusive. It appears that a line with a third (and steeper) slope would be best for the west Texas data, and that line would intersect the other two. Results show that similar relationships exist between ND6 and green biomass under low brush canopy cover conditions, but local variations require a calibration to determine the best fit for an ecosystem. The brush canopy has a detrimental effect on the ND6 vs. herbaceous green biomass relationship.

Harlan, J. C.↗

Use of satellite imagery for wildland resource evaluation in the Great Basin

The author has identified the following significant results. Color composites and diazachrome transparencies of ERTS-1 imagery have greatly increased interpretation capabilities. Vegetation green-up and flooding due to late summer precipitation has been identified on such imagery. MSS imagery in all bands has not proven as valuable for similar determinations. Snow cover has been found to be valuable in the identification of fire scars, pinyon/juniper chainings, and subtle ecotones not previously identified with any other type of imagery. It is felt that a greater understanding of the effects of snow cover on vegetation remote sensing will enable investigators to extend capabilities relating to the mapping and identification of these resources. Highly reflective phreatophytic vegetation has been mapped and quantified using the MSS 5 and 7 bands and diazachrome color composites. Approximately 10 man-hours were required to complete the entire state. Native meadow and hay meadow vegetation has been mapped in Elko County, Nevada, using ERTS-1 imagery. Future plans include a statewide inventory of this resource.

Tueller, P. T.↗

Estimation of Crop Gross Primary Production (GPP): Do Scaled (MODIS) Vegetation Indices Improve Performance? - 2

Satellite remote sensing estimates of Gross Primary Production (GPP) have routinely been made using spectral Vegetation Indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI, WDRVIgreen, or CIgreen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPARchl) and the VIs, and (2) whether the scaled VIs developed in (1) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPARchl of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS) satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the scaled EVI or NDVI in estimating crop daily GPP at these agricultural fields. The scaled VIs are more physiologically meaningful than original un-scaled VIs, but scaling factors and offsets may vary across crop types and surface conditions.

Vegetation Index↗

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

The author has identified the following significant results. The asserted homogeneity of the Great Plains Corridor was established, as evidenced from test site characteristic determinations. First-look visual analysis of ERTS-1 black and white images reveals the ability to locate network test sites. Geological formations associated with major vegetation types are readily apparent on the imagery. Grasslands are readily distinguishable from forested and cropped areas. Under magnification, pastures as small as five to ten acres can be recognized in areas of contrasting vegetation. Bodies of water (rivers, lakes, and large farm ponds) are easily located on bands 6 and 7. Urban areas and major highways are also easily observed and useful as landmarks.

Rouse, J. W., Jr.↗

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

The author has identified the following significant results. Continued evaluation of autumnal phase and early vernal phase data indicate that the quality of ERTS-1 imagery over the Great Plains Corridor test sites are adequate to show relatively small temporal changes in the condition and quantity of vegetation at the several test sites. Vegetation changes measured from August through April are observable in reflectance changes recorded by ERTS-1. Vegetation changes due to grazing treatment and environmental conditions at the test sites are being monitored with ground data and ERTS-1 data, and appear adequate to complete all phases of the Great Plains Corridor investigation. NASA high flight aerial photography proved to be an indispensable tool for locating the Great Plains Corridor test sites on the computer derived grey maps of ERTS-1 digital data.

Rouse, J. W., Jr.↗