Andrew J. Elmore

Quantifying Vegetation Change in Semiarid Environments: Precision and Accuracy of Spectral Mixture Analysis and the Normalized Difference Vegetation Index

Abstract Because in situ techniques for determining vegetation abundance in semiarid regions are labor intensive, they usually are not feasible for regional analyses. Remotely sensed data provide the large spatial scale necessary, but their precision and accuracy in determining vegetation abundance and its change through time have not been quantitatively determined. In this paper, the precision and accuracy of two techniques, Spectral Mixture Analysis (SMA) and Normalized Difference Vegetation Index (NDVI) applied to Landsat TM data, are assessed quantitatively using high-precision in situ data. In Owens Valley, California we have 6 years of continuous field data (1991–1996) for 33 sites acquired concurrently with six cloudless Landsat TM images. The multitemporal remotely sensed data were coregistered to within 1 pixel, radiometrically intercalibrated using temporally invariant surface features, and geolocated to within 30 m. These procedures facilitated the accurate location of field-monitoring sites within the remotely sensed data. Formal uncertainties in the registration, radiometric alignment, and modeling were determined. Results show that SMA absolute percent live cover (%LC) estimates are accurate to within ±4.0%LC and estimates of change in live cover have a precision of ±3.8%LC. Furthermore, even when applied to areas of low vegetation cover, the SMA approach correctly determined the sense of change (i.e., positive or negative) in 87% of the samples. SMA results are superior to NDVI, which, although correlated with live cover, is not a quantitative measure and showed the correct sense of change in only 67% of the samples.

REGIONAL PATTERNS OF PLANT COMMUNITY RESPONSE TO CHANGES IN WATER: OWENS VALLEY, CALIFORNIA

The conversion of large natural basins to managed watersheds for the purpose of providing water to urban centers has had a negative impact on semiarid ecosystems, worldwide. We view semiarid plant communities as being adapted to short, regular periods of drought; however, human induced changes in the water balance often remove these systems from the range of natural variability that has been historically established. This article explores vegetation changes over a 13-yr period for an entire water management area in eastern California. Using remotely sensed measurements of vegetation live cover, a recent vegetation map, field data and observations, precipitation records, and data on water table depth, we characterize the responses of xeric, phreatophytic, and exotic Great Basin plant communities. Despite the complexity of plant communities and land-use history, our technique was successful in identifying discrete modes of response. Differences in vegetation response were attributable to available groundwater resources (modified by water management activities), annual precipitation, and land cultivation history. Fifty-one percent of our study area, including phreatophytic and xeric communities, showed unchanging vegetation conditions and had experienced relatively minimal human disturbance. Nineteen percent of the area exhibited a linear decline in live cover during a drought when ground- water pumping lowered water tables. In portions of these areas, the decline in native phreatophytic cover was followed by an increase in exotic, nonphreatophytic species when the drought ended; in the remainder, cover was suppressed. Finally, vast regions that had been significantly disturbed showed live cover changes that were amplified with respect to precipitation, indicating the presence of exotic annuals. We view the increase in exotic species across the entire study area to be indicative of a fundamental shift in ecosystem function from one buffered from drought by stable ground water conditions to one sensitive to small changes in precipitation. The tools and techniques used here are applicable wherever large regions of land are being managed in an era of changing environmental conditions.

Satellite Monitoring of Vegetation Phenology and Fire Fuel Conditions in Hawaiian Drylands

Abstract Grass-fueled fires accelerate grassland expansion into dry Hawaiian woodlands by destroying native forests and by producing a disturbance regime that favors grass-dominated plant communities. Knowledge of grassland phenology is a key component of ecosystem assessments and fire management in Hawaii, but diverse topographic relief and poor field-sampling capabilities make ground studies impractical. Remote sensing offers the best approach for large-scale, spatially contiguous measurements of dryland vegetation phenology and fire fuel conditions. A 500-m spatial resolution, 8-day temporal resolution Terra Moderate Resolution Imaging Spectroradiometer (MODIS) satellite time series of photosynthetic vegetation (PV), nonphotosynthetic vegetation (NPV), and exposed substrate conditions was developed for the island of Hawaii between 2000 and 2004. The results compared favorably with similar measurements of drylands from higher-resolution aircraft data. The satellite time series was compared with availabl...

Agricultural Legacies in the Great Basin Alter Vegetation Cover, Composition, and Response to Precipitation

The land-use history of an ecosystem influences current structure and possibly response to modern disturbances and stresses. In semiarid systems the nature of land-use legacies is poorly understood, confounding efforts to establish sustainable management approaches. We compare previously cultivated and non-cultivated lands in Owens Valley, California, where cultivation once extended to 34% of the valley floor but was largely discontinued by 1940, to measure the influence of past disturbance on modern vegetation. We combined historic maps of cultivated and non-cultivated land with an extensive vegetation survey, historic aerial photographs, and satellite measurements of vegetation response to precipitation variability to examine the importance of land-use history in determining the sensitivity of vegetation to annual variations in precipitation. Remote sensing analysis showed that total plant cover on previously cultivated lands was lower and fluctuations in cover were marginally more dependent on precipitation compared with plant cover on non-cultivated lands. We then compared modern plant assemblages within cultivated and non-cultivated land to determine if compositional differences could explain the current patterns of vegetation cover. We found lower species richness on previously cultivated parcels, and higher frequency and cover of perennial grasses on non-cultivated lands. Therefore, we showed differences in land-cover patterns, isolated a mechanism that could account for the differences (species differences), and developed a method for remotely analyzing land regions that have experienced historic anthropogenic disturbance.

Precision and accuracy of EO-1 Advanced Land Imager (ALI) data for semiarid vegetation studies

Landsat Thematic Mapper (TM) data and spectral mixture analysis have been used to estimate vegetation green cover in the Great Basin, western United States, to /spl plusmn/4.0% green cover (%GC). In this paper, we compare estimates of percent green cover derived from EO-1 Advanced Land Imager (ALI) data to estimates derived from field-based analyses and to results derived from Landsat Enhanced Thematic Mapper plus (ETM+) data. These analyses define the precision and accuracy of ALI and ETM+ for making quantitative measurements of earth for semiarid ecological studies. The benefits of using ALI were not observed in the calculated uncertainty values (/spl plusmn/5.61%GC and /spl plusmn/6.15%GC for ETM+ and ALI, respectively). However, ALI did not return as many negative green cover estimates and exhibited lower spatial variance in regions of low green cover. These results were attributed to the better signal to noise and data precision inherent to the ALI sensor, and not to the increased number of multispectral bands. ALI was found to be internally inconsistent in that the third sensor chip assembly image swath contained multispectral band coregistration errors. This caused a less than 25%GC error in the ALI estimate of percent green cover along large vegetation gradients.