Zones of information in the AVIRIS spectra

To make the best use of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data an investigator needs to know the ratio of signal to random variability or noise (S/N ratio). The signal is land-cover dependent and decreases with both wavelength and atmospheric absorption and random noise comprises sensor noise and intra-pixel variability. The three existing methods for estimating the S/N ratio are inadequate as typical laboratory methods inflate, while dark current and image methods deflate the S/N ratio. We propose a new procedure called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intra-pixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season

Estimating the signal-to-noise ratio of AVIRIS data

To make the best use of narrowband airborne visible/infrared imaging spectrometer (AVIRIS) data, an investigator needs to know the ratio of signal to random variability or noise (signal-to-noise ratio or SNR). The signal is land cover dependent and varies with both wavelength and atmospheric absorption; random noise comprises sensor noise and intrapixel variability (i.e., variability within a pixel). The three existing methods for estimating the SNR are inadequate, since typical laboratory methods inflate while dark current and image methods deflate the SNR. A new procedure is proposed called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intrapixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season and could be applied to remotely sensed data from broadband sensors

Seasonal LAI in slash pine estimated with LANDSAT TM

The leaf area index (LAI, total area of leaves per unit area of ground) of most forest canopies varies throughout the year, yet for logistical reasons it is difficult to estimate anything more detailed than a seasonal maximum LAI. To determine if remotely sensed data can be used to estimate LAI seasonally, field measurements of LAI were compared to normalized difference vegetation index (NDVI) values derived using LANDSAT Thematic Mapper (TM) data, for 16 fertilized and control slash pine plots on 3 dates. Linear relationships existed between NDVI and LAI with R(sup 2) values of 0.35, 0.75, and 0.86 for February 1988, September 1988, and March, 1989, respectively. This is the first reported study in which NDVI is related to forest LAI recorded during the month of sensor overpass. Predictive relationships based on data from eight of the plots were used to estimate the LAI of the other eight plots with a root-mean-square error of 0.74 LAI, which is 15.6 percent of the mean LAI. This demonstrates the potential use of LANDSAT TM data for studying seasonal dynamics in forest canopies

The effect of signal noise on the remote sensing of Foliar biochemical concentration

Spectral measurements made using an imaging spectrometer contain systematic and random noise, while the former can be corrected the latter remains a source of error in the remotely sensed signal. A number of investigators have tried to determine the signal-to-noise-ratio (SNR) of the instrument, or the resultant imagery. However, the level of noise at which spectra are too noisy to be useful is not usually determined. The first attempt was by Goetz and Calvin, who suggested that the depth of the absorption feature should be at least an order of magnitude greater than the noise and more recently Dekker suggested a SNR of around 600:1 was required in visible/near infrared wavelengths to measure a 1/gl change in chlorophyll a concentration water. The wide range of applications of imaging spectroscopy make it difficult to set SNR specifications as they are dependent on a number of factors, one of the most important being reflectance of a particular target. For example, the SNR of imagery for vegetated targets is relatively low simply because vegetation has a relatively low level of reflectance. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is being used to estimate the concentration of biochemicals within vegetation canopies. This paper reports a study undertaken to identify first, wavebands that were highly correlated with foliar biochemical concentration and second, to determine how sensitive these correlations were to sensor noise

Exploring the remote sensing of foliar biochemical concentrations with AVIRIS data

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data shows promise for the estimation of foliar biochemical concentrations at the scale of the canopy. There are, however, several problems associated with the use of AVIRIS data in this way and these are detailed in recent Plant Biochemical Workshop Report. The research reported was concentrated upon three of these problems: field sampling of forest canopies, wet laboratory assay of foliar chemicals, and the visualization of AVIRIS data

AVIRIS spectra correlated with the chlorophyll concentration of a forest canopy

Imaging spectrometers have many potential applications in the environmental sciences. One of the more promising applications is that of estimating the biochemical concentrations of key foliar biochemicals in forest canopies. These estimates are based on spectroscopic theory developed in agriculture and could be used to provide the spatial inputs necessary for the modeling of forest ecosystem dynamics and productivity. Several foliar biochemicals are currently under investigation ranging from those with primary absorption features in visible to middle infrared wavelengths (e.g., water, chlorophyll) to those with secondary to tertiary absorption features in this part of the spectrum (e.g., nitrogen, lignin). The foliar chemical of interest in this paper is chlorophyll; this is a photoreceptor and catalyst for the conversion of sunlight into chemical energy and as such plays a vital role in the photochemical synthesis of carbohydrates in plants. The aim of the research reported here was to determine if the chlorophyll concentration of a forest canopy could be correlated with the reflectance spectra recorded by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

Phase i study of \u27dose-dense\u27 pemetrexed plus carboplatin/radiotherapy for locally advanced non-small cell lung carcinoma.

BACKGROUND: This phase I study investigates the feasibility of carboplatin plus dose-dense (q2-week) pemetrexed given concurrently with radiotherapy (XRT) for locally advanced and oligometastatic non-small cell lung cancer (NSCLC). METHODS: Eligible patients had Stage III or IV (oligometastatic) NSCLC. Patients received XRT to 63 Gy in standard fractionation. Patients received concurrent carboplatin (AUC = 6) during weeks 1 and 5 of XRT, and pemetrexed during weeks 1, 3, 5, and 7 of XRT. The starting dose level (level 1) of pemetrexed was 300 mg/m2. Following the finding of dose limiting toxicity (DLT) in dose level 1, an amended dose level (level 1A) continued pemetrexed at 300 mg/m2, but with involved field radiation instead of extended nodal irradiation. Consolidation consisted of carboplatin (AUC = 6) and pemetrexed (500 mg/m2) q3 weeks × 2 -3 cycles. RESULTS: Eighteen patients were enrolled. Fourteen patients are evaluable for toxicity analysis. Of the initial 6 patients treated on dose level 1, two experienced DLTs (one grade 4 sepsis, one prolonged grade 3 esophagitis). There was one DLT (grade 5 pneumonitis) in the 8 patients treated on dose level 1A. In 16 patients evaluable for response (4 with oligometastatic stage IV disease and 12 with stage III disease), the median follow-up time is 17.8 months. Thirteen of 16 patients had in field local regional response. The actuarial median survival time was 28.6 months in all patients and 34.7 months (estimated) in stage III patients. CONCLUSIONS: Concurrent carboplatin with dose-dense (q2week) pemetrexed at 300 mg/m2 with involved field XRT is feasible and encouraging in patients with locally advanced and oligometastatic NSCLC

Patient Perspectives on Medication Assisted Therapy in Vermont

Introduction. Medication-Assisted Therapy (MAT) for opioid addiction has dramatically increased in Vermont, supported by a novel statewide system that integrates specialty treatment centers ( Hubs ) with primary care office-based opioid therapy ( Spokes ). In 2010, Vermont had the highest per capita buprenorphine use in the US. Previous studies of patient perspectives of MAT have identified social barriers, rigid program rules, and concerns about withdrawal and relapse as common causes of treatment failure. Our goal was to elicit patient perspectives on barriers and enablers of successful MAT to further inform system refinement. Methods. An interview guide was developed based on previous literature as well as discussions with program leadership, staff and clinicians, and community stakeholders. Responses were organized using thematic content analysis with consensus across seven interviewers and two analysts. The interviews were conducted with 44 patients enrolled in MAT at two Hub sites in Burlington, VT in October 2016. Results. The median age of subjects was 34 years, 34% were employed at least part-time, and 72% were female. Half reported a mental health condition and 20% reported chronic pain. Barriers included transportation (25%), lack of stable housing, and stigma (41%). Enablers included feeling supported (82% felt well-supported; 52% felt supported by healthcare professionals). Subjects expressed high confidence in the treatment system and high self-efficacy for sobriety. Conclusions. Patients in MAT have complex medical, mental health, social, personal, and work lives. A comprehensive system that addresses this wide range of domains is critical to achieving optimal outcomes.https://scholarworks.uvm.edu/comphp_gallery/1245/thumbnail.jp

Causal correlation of foliar biochemical concentrations with AVIRIS spectra using forced entry linear regression

A major goal of airborne imaging spectrometry is to estimate the biochemical composition of vegetation canopies from reflectance spectra. Remotely-sensed estimates of foliar biochemical concentrations of forests would provide valuable indicators of ecosystem function at regional and eventually global scales. Empirical research has shown a relationship exists between the amount of radiation reflected from absorption features and the concentration of given biochemicals in leaves and canopies (Matson et al., 1994, Johnson et al., 1994). A technique commonly used to determine which wavelengths have the strongest correlation with the biochemical of interest is unguided (stepwise) multiple regression. Wavelengths are entered into a multivariate regression equation, in their order of importance, each contributing to the reduction of the variance in the measured biochemical concentration. A significant problem with the use of stepwise regression for determining the correlation between biochemical concentration and spectra is that of 'overfitting' as there are significantly more wavebands than biochemical measurements. This could result in the selection of wavebands which may be more accurately attributable to noise or canopy effects. In addition, there is a real problem of collinearity in that the individual biochemical concentrations may covary. A strong correlation between the reflectance at a given wavelength and the concentration of a biochemical of interest, therefore, may be due to the effect of another biochemical which is closely related. Furthermore, it is not always possible to account for potentially suitable waveband omissions in the stepwise selection procedure. This concern about the suitability of stepwise regression has been identified and acknowledged in a number of recent studies (Wessman et al., 1988, Curran, 1989, Curran et al., 1992, Peterson and Hubbard, 1992, Martine and Aber, 1994, Kupiec, 1994). These studies have pointed to the lack of a physical link between wavelengths chosen by stepwise regression and the biochemical of interest, and this in turn has cast doubts on the use of imaging spectrometry for the estimation of foliar biochemical concentrations at sites distant from the training sites. To investigate this problem, an analysis was conducted on the variation in canopy biochemical concentrations and reflectance spectra using forced entry linear regression

Integrative Approach for a Transformative Freshman-Level STEM Curriculum

In 2014 Wesley College adopted a unified undergraduate program of evidence-based high-impact teaching practices. Through foundation and federal and state grant support, the college completely revised its academic core curriculum and strengthened its academic support structures by including a comprehensive early alert system for at-risk students. In this core, science, technology, engineering, and mathematics (STEM) faculty developed fresh manifestations of integrated concept-based introductory courses and revised upper-division STEM courses around student-centered learning. STEM majors can participate in specifically designed paid undergraduate research experiences in directed research elective courses. Such a college-wide multi-tiered approach results in institutional cultural change