Geology topics

David Aaron

Publications and source records attributed to David Aaron.

6 recordsLinked to original sources

USGS2025

The relative influence of geographic and environmental factors on rare plant translocation outcomes

Conservation translocations are an established method for reducing the extinction risk of plant species through intentional movement within or outside the indigenous range. Unsuitable environmental conditions at translocation recipient sites and a lack of understanding of species–environment relationships are often identified as critical barriers to translocation success. However, previous syntheses have drawn these inferences from analyses of qualitative feedback rather than quantitative environmental data. In this study, we use a data set of 235 translocations conducted in the US to understand the influences of geographic and environmental factors on three metrics of translocation success: population persistence, next-generation recruitment and next-generation maturity. We use random forest models to quantify the relative importance of geographic and environmental factors that characterize dissimilarity between source and recipient locations, the position of recipient sites relative to species' ranges and niche metrics derived from these ranges. We also compare the importance of these variables with more conventional predictors (e.g. founder population size). Our results indicate that geographic and environmental variables can be as insightful as conventional variables for predicting plant translocation outcomes. The climate suitability of recipient sites, estimated using species distribution models, was the strongest relative predictor of whether a population persisted, with populations situated in more suitable climates displaying greater persistence. Next-generation recruitment and maturity were best predicted by niche metrics; species in more biotically limiting environments, including tropical regions and soils with high relative nutrient retention, as well as species with the broadest precipitation niches, were the least likely to attain these next-generation benchmarks. Synthesis and applications . Our study is one of the first to quantify the important role of spatial and climatic factors in rare plant translocation outcomes. We provide a novel geographic and environmental perspective on outcomes in plant translocations and demonstrate opportunities to improve translocation success not only by adhering to established best practice guidelines but also by integrating spatial modelling approaches into planning and management processes.

Journal of Applied Ecology↗

USGS2014

Radiometric cross calibration of Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+)

This study evaluates the radiometric consistency between Landsat-8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) using cross calibration techniques. Two approaches are used, one based on cross calibration between the two sensors using simultaneous image pairs, acquired during an underfly event on 29–30 March 2013. The other approach is based on using time series of image statistics acquired by these two sensors over the Libya 4 pseudo invariant calibration site (PICS) (+28.55°N, +23.39°E). Analyses from these approaches show that the reflectance calibration of OLI is generally within ±3% of the ETM+ radiance calibration for all the reflective bands from visible to short wave infrared regions when the ChKur solar spectrum is used to convert the ETM+ radiance to reflectance. Similar results are obtained comparing the OLI radiance calibration directly with the ETM+ radiance calibration and the results in these two different physical units (radiance and reflectance) agree to within ±2% for all the analogous bands. These results will also be useful to tie all the Landsat heritage sensors from Landsat 1 MultiSpectral Scanner (MSS) through Landsat-8 OLI to a consistent radiometric scale.

Remote Sensing↗

USGS2013

Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study

Cross-calibration of satellite sensors permits the quantitative comparison of measurements obtained from different Earth Observing (EO) systems. Cross-calibration studies usually use simultaneous or near-simultaneous observations from several spaceborne sensors to develop band-by-band relationships through regression analysis. The investigation described in this paper focuses on evaluation of the uncertainties inherent in the cross-calibration process, including contributions due to different spectral responses, spectral resolution, spectral filter shift, geometric misregistrations, and spatial resolutions. The hyperspectral data from the Environmental Satellite SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY and the EO-1 Hyperion, along with the relative spectral responses (RSRs) from the Landsat 7 Enhanced Thematic Mapper (TM) Plus and the Terra Moderate Resolution Imaging Spectroradiometer sensors, were used for the spectral uncertainty study. The data from Landsat 5 TM over five representative land cover types (desert, rangeland, grassland, deciduous forest, and coniferous forest) were used for the geometric misregistrations and spatial-resolution study. The spectral resolution uncertainty was found to be within 0.25%, spectral filter shift within 2.5%, geometric misregistrations within 0.35%, and spatial-resolution effects within 0.1% for the Libya 4 site. The one-sigma uncertainties presented in this paper are uncorrelated, and therefore, the uncertainties can be summed orthogonally. Furthermore, an overall total uncertainty was developed. In general, the results suggested that the spectral uncertainty is more dominant compared to other uncertainties presented in this paper. Therefore, the effect of the sensor RSR differences needs to be quantified and compensated to avoid large uncertainties in cross-calibration results.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2012

Landsat-7 ETM+: 12 years on-orbit reflective-band radiometric performance

The Landsat-7 ETM+ sensor has been operating on orbit for more than 12 years, and characterizations of its performance have been ongoing over this period. In general, the radiometric performance of the instrument has been remarkably stable: 1) noise performance has degraded by 2% or less overall, with a few detectors displaying step changes in noise of 2% or less; 2) coherent noise frequencies and magnitudes have generally been stable, though the within-scan amplitude variation of the 20 kHz noise in bands 1 and 8 disappeared with the failure of the scan line corrector and a new similar frequency noise (now about 18 kHz) has appeared in two detectors in band 5 and increased in magnitude with time; 3) bias stability has been better than 0.25 DN out of a normal value of 15 DN in high gain; 4) relative gains, the differences in response between the detectors in the band, have generally changed by 0.1% or less over the mission, with the exception of a few detectors with a step response change of 1% or less; and 5) gain stability averaged across all detectors in a band, which is related to the stability of the absolute calibration, has been more stable than the techniques used to measure it. Due to the inability to confirm changes in the gain (beyond a few detectors that have been corrected back to the band average), ETM+ reflective band data continues to be calibrated with the prelaunch measured gains. In the worst case, some bands may have changed as much as 2% in uncompensated absolute calibration over the 12 years.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2012

Radiometric calibration of the Landsat MSS sensor series

Multispectral remote sensing of the Earth using Landsat sensors was ushered on July 23, 1972, with the launch of Landsat-1. Following that success, four more Landsat satellites were launched, and each of these carried the Multispectral Scanner System (MSS). These five sensors provided the only consistent multispectral space-based imagery of the Earth's surface from 1972 to 1982. This work focuses on developing both a consistent and absolute radiometric calibration of this sensor system. Cross-calibration of the MSS was performed through the use of pseudoinvariant calibration sites (PICSs). Since these sites have been shown to be stable for long periods of time, changes in MSS observations of these sites were attributed to changes in the sensors themselves. In addition, simultaneous data collections were available for some MSS sensor pairs, and these were also used for cross-calibration. Results indicated substantial differences existed between instruments, up to 16%, and these were reduced to 5% or less across all MSS sensors and bands. Lastly, this paper takes the calibration through the final step and places the MSS sensors on an absolute radiometric scale. The methodology used to achieve this was based on simultaneous data collections by the Landsat-5 MSS and Thematic Mapper (TM) instruments. Through analysis of image data from a PICS location and through compensating for the spectral differences between the two instruments, the Landsat-5 MSS sensor was placed on an absolute radiometric scale based on the Landsat-5 TM sensor. Uncertainties associated with this calibration are considered to be less than 5%.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2010

Use of EO-1 Hyperion data to calculate spectral band adjustment factors (SBAF) between the L7 ETM+ and Terra MODIS sensors

Different applications and technology developments in Earth observations necessarily require different spectral coverage. Thus, even for the spectral bands designed to look at the same region of the electromagnetic spectrum, the relative spectral responses (RSR) of different sensors may be different. In this study, spectral band adjustment factors (SBAF) are derived using hyperspectral Earth Observing-1 (EO-1) Hyperion measurements to adjust for the spectral band differences between the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) top-of-atmosphere (TOA) reflectance measurements from 2000 to 2009 over the pseudo-invariant Libya 4 reference standard test site.

Conference Paper↗