Mark E. Jakubauskas

Crop identification using harmonic analysis of time-series AVHRR NDVI data

Harmonic analysis of a time series of National Oceanic and Atmospheric Administration (NOAA) advanced very high resolution radiometer normalized difference vegetation index (NDVI) data was used to develop an innovative technique for crop type identification based on temporal changes in NDVI values. Different crops (corn, soybeans, alfalfa) exhibit distinctive seasonal patterns of NDVI variation that have strong periodic characteristics. Harmonic analysis, or Fourier analysis, decomposes a time-dependent periodic phenomenon into a series of constituent sinusoidal functions, or terms, each defined by a unique amplitude and phase value. Amplitude and phase angle images were produced by analysis of the time-series NDVI data and used within a discriminant analysis to develop a methodology for crop type identification. For crops that have a single distinct growing season and period of peak greenness, such as corn, the majority of the variance was captured by the first and additive terms, while winter wheat exhibited a bimodal NDVI periodicity with the majority of the variance accounted for by the second harmonic term.

A remote sensing and GIS-based model of habitats and biodiversity in the Greater Yellowstone Ecosystem

We used remotely sensed data and geographical information systems (GIS) to categorize habitats, then determined the relationship between remotely sensed habitat categorizations and species distribution patterns. Three forest types and six meadow types in the Greater Yellowstone Ecosystem, USA, were classified using Landsat TM data. All plant species with 5% cover or greater, 31% of the butterfly species, and 20% of the bird species exhibited significant differences in distribution among meadow types. Sites of highest species richness coincided for plants, birds, and butterflies and were found in mesic meadows.

Thematic Mapper characterization of lodgepole pine seral stages in Yellowstone National Park, USA☆

Landsat Thematic Mapper multispectral data were used to identify the spectral reflectance characteristics of Yellowstone lodgepole pine (Pinus contorta var latifolia) successional stages, and to examine the relationships between spectral and biophysical factors. Ten spectrally defined forest cover types were created from unsupervised classification of the Landsat TM data, using a geographic information system to restrict data analysis to areas of similar slope, elevation, and surficial geology within the Central Plateau region of the park. Biotic data on forest overstory and understory conditions were collected from 69 sample sites within the 10 spectral cover classes. Field data were used to regroup the 69 sites into six biotically and spectrally distinct cover types, ranging from early postfire regeneration (LPO) to late-stage (LP3) subalpine fir succession. Increased absorption in the visible (TM 1, 2, and 3) and middle-infrared (TM 5 and 7) bands were related to the age and development of a stand. Changes in absorption were rapid during the initial stages of stand regeneration, but the rate of change slowed as stands progressed into later successional stages. Biotic factors relating to the physical structure of the forest canopy (height, basal area, biomass, and LAI) are correlated with the visible and middle-infrared bands of the Thematic Mapper. Understory factors were poorly correlated with spectral response, except soil and fireweed, which are dominant early in succession, but rapidly decrease in later stages. The spectral reflectance of a successional forest stand over time is a function of the combined effects of the overstory canopy, the amount of shadow within a canopy, and the condition of the forest understory. As a forest develops from a disturbance to old-growth, the spectral response of a stand progresses along a vector or vectors linking the three factors. Spectral response changes are nonlinear with respect to time, as large-magnitude changes are observed in the first 20–30 years following a disturbance, and the rate of change lessens as forests develop into old-growth.

A comparison of satellite data and landscape variables in predicting bird species occurrences in the Greater Yellowstone Ecosystem. USA

We compare the accuracy of predicting the occurrence of 11 bird species in montane meadows of the Greater Yellowstone National Park ecosystem, in the states of Montana and Wyoming, USA. We used remotely sensed, landscape, and habitat data. The meadow type, as determined from the remotely sensed data, was highly correlated with abundances of six of the 11 bird species. Landscape variables significant in predicting occurrence were selected using a stepwise multiple regression for each bird species. These variables were then used in a multiple regression with the variable meadow type. As expected, the abundances of the generalist species (American Robin, Dark-eyed Junco, White-crowned Sparrow, Brewers Blackbird, and Chipping Sparrow) were not strongly correlated with landscape variables or meadow type. Conversely, abundances of the Common Snipe, Common Yellowthroat, Lincolns Sparrow, Savannah Sparrow, Vesper Sparrow, and Yellow Warbler were highly correlated with meadow type and landscape variables such as percent cover of willow (Salix spp.), graminoid, woody vegetation, sagebrush (Artemisia spp.), and graminoid and shrub biomass. The results from our study indicate that remotely sensed data are applicable for estimating potential habitats for bird species in the different types of montane meadows. However, to improve predictions about species in specific sites or areas, we recommend the use of additional landscape metrics and habitat data collected in the field.

Identifying wetland meadows in Grand Teton National Park using remote sensing and average wetland values

Six spectrally and ecologically distinct montane meadow community types were identified and mapped within Grand Teton National Park by analysis of Indian IRS-1B LISS-II imagery. A distinct to-xeric-hydric gradient among the meadow types was predicted by analysis of the satellite data. Thirty sites (five replicates for each of six meadow typ were selected for intensive field sampling. At each of the 30 sites, meadow vegetation was sampled in 20 m by 20 m square plots for canopy cover of all species. Using wetland indexes (on a scale of 1–5, where obligate wetland species = 1, facultative land = 2, facultative = 3, facultative upland = 4 and upland species = 5), average wetland values were calculated and ranged from 1.88 for A-type meadows and 2.86 for B meadows to 4.40, 4.49, 4.74, and 4.43 for C, D, E and F meadows, respectively. Because average wetland values of A and B meadows were < 3.00, they were determined to be indicative of wetlands. Eight out of ten obligate wetland plants had their greatest cover on A meadows (the wettest of the gradient) and had significant cover differe among meadow types using the non-parametric Kruskal-Wallis test. Average wetland values and plant species cover were used, in conjunction with remotely sensed data, to identify as wetlands 1,258 hectares of A meadows and 1,711 hectares of B meadows in Grand Teton National Park.

Close-range remote sensing of aquatic macrophyte vegetation cover.

This study used ground-based hyperspectral radiometry to examine variations in visible and near-infrared spectral reflectance of spatterdock (Nuphar polysepalum Engelm.) as a function of vegetation cover. Sites were sampled in Swan Lake in Grand Teton National Park, Wyoming, using a 512-band spectroradiometer to measure reflectance over the range 326.5-1055.3nm (visible-nearinfrared) and simultaneous estimates of spatterdock cover. Linear correlations between spatterdock cover and spectral reflectance were statistically significant at the 0.05 significance level in two specific ranges of the spectrum: 518-607 nm; and 697-900nm. Predictability of spatterdock cover using spectral variables was best using an NDVI transformation of the data in a non-linear equation (r 2 = 0.95).

MONTANE MEADOWS AS INDICATORS OF ENVIRONMENTAL CHANGE

We used a time series of satellite multispectral imagery for mapping and monitoring six classes of montane meadows arrayed along a moisture gradient (from hydric to mesic to xeric). We hypothesized that mesic meadows would support the highest species diversity of plants, birds, and butterflies because they are more moderate environments. We also hypothesized that mesic meadows would exhibit the greatest seasonal and interannual variability in spectral response across years. Field sampling in each of the meadow types was conducted for plants, birds, and butterflies in 1997 and 1998. Mesic meadows supported the highest plant species diversity, but there was no significant difference in bird or butterfly species diversity among meadow types. These data show that it may be easier to detect significant differences in more species rich taxa (e.g., plants) than taxa that are represented by fewer species (e.g., butterflies and birds). Mesic meadows also showed the greatest seasonal and interannual variability in spectral response. Given the rich biodiversity of mesic montane meadows and their sensitivity to variations in temperature and moisture, they may be important to monitor in the context of environmental change

Canonical correlation analysis of coniferous forest spectral and biotic relations

Abstract Canonical correlation analysis was used to examine the relations between the six reflective Thematic Mapper bands and six forest structural variables for 70 lodgepole pine forest stands in Yellowstone National Park, U.S.A. Two significant canonical variate pairs were extracted, accounting for 96·4 per cent of the total information in the overall canonical correlation analysis. Results of the canonical redundancy analysis indicate that 78 per cent of the overall unstandardized variance in spectral data is explained by the first two spectral canonical variates, while the first and second biotic canonical variates explain 59 per cent and 5·9 per cent of the raw variance in the spectral data. The first two biotic canonical variates collectively explain 59 per cent of the raw variance in the biotic data, and the first and second spectral canonical variates explain 41 per cent and 6 per cent of the raw variance in the biotic data, respectively. Height, live basal area, leaf area index (LAI), and size d...

Quantifying Relationships Between Bird And Butterfly Community Shifts And Environmental Change

Quantifying the manner in which ecological communities respond during a time of decreasing precipitation is a first step in understanding how they will respond to longer-term climate change. Here we coupled analysis of interannual variability in remotely sensed data with analyses of bird and butterfly community changes in montane meadow communities of the Greater Yellowstone Ecosystem. Landsat satellite imagery was used to classify these meadows into six types along a hydrological gradient. The northern portion of the ecosystem, or Gallatin region, has smaller mean patch sizes separated by ridges of mountains, whereas the southern portion of the ecosystem, or Teton region, has much larger patches within the Jackson Hole valley. Both support a similar suite of butterfly and bird species. The Gallatin region showed more overall among-year variation in the normalized difference vegetation index (NDVI) when meadow types were pooled within regions, perhaps because the patch sizes are smaller on average. Bird and butterfly communities showed significant relationships relative to meadow type and NDVI. We identified several key species that are tightly associated with specific meadow types along the hydrological gradient. Comparing taxonomic groups, fewer birds showed specific habitat affinities than butterflies, perhaps because birds are responding to differences in habitat structure among meadow types and using the landscape at a coarser scale than the butterflies. Comparing regions, the Teton region showed higher predictability of community assemblages as compared to the Gallatin region. The Gallatin region exhibited more significant temporal trends with respect to butterflies. Butterfly communities in wet meadows showed a distinctive shift along the hydrological gradient during a drought period (1997-2000). These results imply that the larger Teton meadows will show more predictable (i.e., static) species-habitat associations over the long term, but that the smaller Gallatin meadows may be an area that will exhibit the effects of global climate change faster.

Spectral and biophysical relationships of montane sagebrush communities in multi-temporal SPOT XS data

Correlation and multiple regression analysis was used to examine the relationships between spectral and biotic factors within the sagebrush communities of Grand Teton National Park, Wyoming. Field-sampled data on biophysical factors were regressed against June 1996 and September 1996 SPOT multi-spectral reflectance data for fifty-one plots. Highest r 2 values were generated for regression models using June reflectance data alone for predicting biophysical factors. Predictability of bitterbrush cover was improved using September reflectance data alone. Models predicting biophysical characteristics of sagebrush communities generally were not improved by using a combined June-September data set. Regression models for big sagebrush height, low sagebrush cover, and rock/soil cover were improved slightly using the combined two-date data set. Selection of remotely sensed data for biophysical studies of vegetation communities should be driven by the ecological and phenological characteristics of the vegetation community to be studied.