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Adherence drives efficacy in PrEP clinical trials. We compared drug concentrations and self-reported adherence in HPTN069/ACTG5305, a double-blinded, randomized trial of the safety and tolerability of candidate PrEP regimens that included maraviroc (MVC), tenofovir (TDF), and emtricitabine (FTC). Plasma drug concentrations and self-reported adherence by computer-assisted self-interview (CASI) were assessed at study weeks 24 and 48. Descriptive statistics and a generalized linear model were used to assess the association between selected demographic factors, self-report of daily medication adherence and plasma drug concentrations consistent with daily adherence. Among 718 paired observations from 370 participants, 43% (306/718) reported daily adherence by CASI, 65% (467/718) had drug concentrations consistent with daily adherence and 11% (81/718) had CASI responses that reported daily adherence despite having drug concentrations consistent with less-than-daily adherence. In adjusted analyses, participants who were assigned male at birth (aOR 1.42 [95% CI 1.02, 1.97]), older (5-year increments aOR 1.10 [95% CI 1.09, 1.11]), White (aOR 2.2 [95% CI 1.88, 2.56]), had advanced education (aOR 3.89 [95% CI 2.97, 5.09]), were employed (aOR 1.89 [95% CI 1.50, 2.40]), or partnered/married (aOR 2 [95% CI 1.72, 2.32]) were more likely to have drug concentrations consistent with daily adherence. Participants who were not employed (aOR 2.7 [95% CI 1.31, 5.55]) or who were single/not partnered (aOR 2.33 [CI 95% 1.25, 4.34]) were more likely to have drug concentrations that did not reflect daily adherence despite self-reported PrEP adherence. These findings support the need for ongoing adherence counseling in clinical trials of new PrEP regimens. [ABSTRACT FROM AUTHOR]

Restored wetlands should be closely monitored to fully evaluate the effectiveness of restoration efforts. However, regular post-restoration monitoring can be time-consuming and expensive, and is often absent or inadequate. Satellite and airborne remote sensing systems have proven to be cost-effective tools in many fields, but they have not been widely used to monitor ecological restoration. This study assessed the potential of airborne hyperspectral remote sensing to monitor water mass characteristics of experimental temporary ponds in the Mediterranean region. These ponds were created during marsh restoration in Doñana National Park (south-west Spain). We used hyperspectral images acquired by the CASI-1500 hyperspectral airborne sensor to estimate and map water depth, turbidity and chlorophyll a in a subset of the 96 new ponds. The high spatial and spectral resolution of the CASI sensor allowed us to detect differences between ponds in water depth, turbidity and chlorophyll a, providing accurate mapping of these three variables, and a useful method to assess restoration success. High levels of spatial variation were recorded between different ponds, which likely generates high diversity in the animal and plant species that they contain. These results highlight the great potential of hyperspectral sensors for the long-term monitoring of wetland complexes in the Mediterranean region and elsewhere. [ABSTRACT FROM AUTHOR]

An empirical study assessing the suitability of laser speckle patterns for use in experimental mechanics research conducted at hypersonic conditions is presented. Speckle patterns generated via coherent optical scattering from a gold-coated graphite surface inserted into a Mach 10 air stream were collected and analyzed using Computer-Aided Speckle Interferometry using two methodologies: a typical spanwise approach involving increasing temporal span between image pairs, and a sequential approach that utilizes a combination of temporal re-referencing and spatial resampling. Results were characterized for spatial-temporal stability and variance. Our observations demonstrate that optical methods relying on stable and properly formed speckle patterns can be used in a hypersonic regime at various Reynolds numbers and common camera frame rates, but the technique is sensitive to the conditions of the airflow and the processing methodology chosen. [ABSTRACT FROM AUTHOR]

Advanced manufacturing (AM) processes such as laser powder bed fusion (LPBF) are increasingly capable of fabricating components with useful and unprecedented mechanical properties by incorporating complex internal bracing structures. From the standpoint of quality control and assessment, however, internally complex assemblies present significant build-verification challenges. Here we propose a hybrid approach to the inspection involving the application of computer-aided speckle interferometry (CASI) and morphological image processing as a rapid, inexpensive, and facile method for AM quality control. The described methodology has low capital equipment costs, is full-field and non-contact, can be used in an industrial setting, and has very low requirements in terms of operator training and expertise. Consisting primarily of the combination of image processing software with a simple optical system of variable sensitivity, the method is shown to be effective for inspection of a titanium honeycomb component subjected to differential pressure. Results are compared to those achieved with computed tomography (CT), immersion ultrasound testing (UT), and optical holographic interferometry. Lastly, we propose several possible processing strategies for automated quality assessment based on this powerful hybrid approach. [ABSTRACT FROM AUTHOR]

Background In 2018, the municipal Sexual Health Clinic in Seattle, implemented trans-inclusive questions about sexual behavior, anatomy, gender-affirming surgeries, and sexually transmitted infection (STI) symptoms in the clinic's computer-assisted self-interview (CASI) to improve care for transgender and nonbinary (TNB) patients. Methods We calculated test positivity, the proportion of TNB patient visits that received testing for human immunodeficiency virus (HIV); syphilis; pharyngeal, rectal, and urogenital gonorrhea (GC); and chlamydia (CT) before (5/2016–12/2018) and after (12/2018–2/2020) implementation of new CASI questions, and the proportion of asymptomatic patients who received anatomic site–specific screening based on reported exposures. Results There were 434 TNB patients with 489 and 337 clinic visits during each period, respectively. Nonbinary patients assigned male at birth (AMAB) had the highest prevalence of GC (10% pharyngeal, 14% rectal, 12% urogenital). Transgender women, transgender men, and nonbinary people AMAB had a high prevalence of rectal CT (10%, 9%, and 13%, respectively) and syphilis (9%, 5%, and 8%). Asymptomatic transgender women, transgender men, and nonbinary patients AMAB were more likely to receive extragenital GC/CT screening compared with nonbinary patients assigned female at birth. After implementation of trans-inclusive questions, there was a 33% increase in the number of annual TNB patient visits but no statistically significant increase in HIV/STI testing among TNB patients. Conclusions TNB people had a high prevalence of extragenital STIs and syphilis. Implementation of trans-inclusive medical history questions at a clinic that serves cisgender and transgender patients was feasible and important for improving the quality of affirming and inclusive sexual healthcare. [ABSTRACT FROM AUTHOR]

Editorial

CaSi nanowires were synthesized on a Si substrate by a reactive deposition technique. A large amount of Ca vapor reacted with the surface of the cleaned Si substrate, and CaSi nanowires were grown on the as-synthesized CaSi film. The diameter of the nanowires reached a minimum value of about 25 nm. The CaSi nanowires were self-oriented along the 〈001〉 direction. We can control the length of the nanowires, to a maximum of 4 μ m, by adjusting the experimental parameter settings, such as the amount of Ca source, duration and temperature. The mechanism of formation of Ca silicides on a Si substrate is discussed in detail. Raman spectroscopy confirmed the nanosized character of the CaSi phase. These results give us greater expectations for the application of CaSi, not only in hydrogen storage but also as a new inorganic semiconductor. [ABSTRACT FROM AUTHOR]

This work, descriptive-interpretative and quantitative, offers a review and update of the uses of casi ('almost') in current Spanish. In the first part, the grammatical description of casi focuses on presenting its modification and position, the combination with other elements, its flexion and derivation, as well as the alternation with other units. In the second part, the pragmatic description deals with its attenuating value, its focality, and other considerations such as its interpolation and the combination with the verb ser ('to be'). [ABSTRACT FROM AUTHOR]

Este trabajo aborda la estimación de variables biofísicas de un pastizal de dehesa a partir de información óptica generada por sensores próximos y remotos. Las variables de contenido de humedad del combustible (FMC), contenido de agua del dosel (CWC), índice de área foliar (LAI), materia seca (Cm) y biomasa superficial (AGB) fueron estimadas en laboratorio a partir de muestras de vegetación tomadas simultáneamente a la adquisición de datos hiperespectrales del sensor Compact Airbone Spectrographic Imager (CASI) y del espectro-radiómetro de campo ASD FieldSpec® 3. A partir de la información espectral se han calculado diversos índices extraídos de la literatura y se han analizado las relaciones lineales existentes con las variables biofísicas medidas en campo. Los resultados muestran relaciones consistentes entre las variables biofísicas y los índices espectrales, especialmente en el caso de los índices basados en bandas del infrarrojo medio de onda corta (SWIR) y del red-edge, poniendo de manifiesto la importancia de estas regiones en la estimación de variables biofísicas en cubiertas de pastizal. Se han obteniendo coeficientes de determinación (R2) superiores a 0,91 y un error cuadrático medio relativo (RRMSE) de 21,4%, para los índices espectrales calculados con datos ASD; y R2 de 0,91 y RRMSE de 15,5% para los índices espectrales calculados con datos CASI. .

The use of cutting-edge geospatial technologies to monitor ecosystems and the development of tailored tools for assessing such natural areas is a fundamental task. In this context, the growing availability of hyperspectral (HS) imagery from satellite and aerial platforms can provide valuable information for the sustainable management of ecosystems. However, in some cases, the spectral richness provided by HS sensors is at the expense of spatial quality. To alleviate this inconvenience, which can be critical to monitor some heterogeneous and mixed natural areas, a number of HS sharpening techniques have been developed to increase the spatial resolution while trying to preserve the spectral content. This image processing field has attracted the interest of the scientific community, and many research studies have been conducted to assess the performance of different HS sharpening algorithms. In the last decade, however, many comparative studies rely upon simulated data. In this work, the challenging application of sharpening methods in real situations using multiplatform or multisensor data is also addressed. Thus, experiments with real data have been conducted, in addition to a thorough assessment of HS sharpening techniques using simulated imagery in scenarios with different spatial resolution ratios and registration errors. In particular, airborne and satellite HS imageries have been pansharpened with drone, orthophotos, and satellite high spatial resolution data evaluating 11 fusion algorithms. After a comprehensive analysis, considering different visual and quantitative quality indicators, the algorithm characteristics have been summarized and the methods with higher performance and robustness have been identified. [ABSTRACT FROM AUTHOR]

Maps of submerged aquatic vegetation (SAV) are of primary importance for the sustainable management of coastal areas and serve as a basis for fundamental ecological studies. Various water column correction (WCC) models are successfully applied in clear Case-1 waters to compensate for the variable water depth effect. The performance of the WCC in less clear Case-2 waters is rarely assessed. In this study, the performance and applicability of model-based WCC algorithms in the complex Baltic Sea were analyzed. The bottom reflectance was retrieved from the Compact Airborne Spectrographic Imager (CASI) water surface reflectance by applying the Maritorena and Lee WCC algorithms. The Maritorena model retrieved bottom spectra that showed large variations in reflectance magnitudes. The Lee model was more successful in retrieving reasonable spectral magnitudes, although only in a rather narrow wavelength region (550–600 nm). Shorter and longer spectral regions were significantly overcorrected, resulting in unrealistic spectral shapes. Sensitivity analysis indicated that slight under- or overestimation of water depth and water column constituents affect retrieval of correct bottom spectra in Case-2 waters. To assess the performance of WCC models in improving the SAV quantification, the surface reflectance, as well as the retrieved bottom reflectance, were correlated with the corresponding in situ estimated SAV percent cover (%SAV). Although the quality of the Lee WCC model was not considered high, the spectral region least affected by the input parameters variations (550–600 nm) can be used for the SAV quantification. Application of the Lee model provided better results in %SAV assessment than not performing the WCC correction.

High spatial resolution airborne data with little sub-pixel heterogeneity were used to evaluate the suitability of the temperature/vegetation (Ts/VI) space method developed from satellite observations, and were explored to improve the performance of the Ts/VI space method for estimating soil moisture (SM). An evaluation of the airborne ΔTs/Fr space (incorporated with air temperature) revealed that normalized difference vegetation index (NDVI) saturation and disturbed pixels were hindering the appropriate construction of the space. The non-disturbed ΔTs/Fr space, which was modified by adjusting the NDVI saturation and eliminating the disturbed pixels, was clearly correlated with the measured SM. The SM estimations of the non-disturbed ΔTs/Fr space using the evaporative fraction (EF) and temperature vegetation dryness index (TVDI) were validated by using the SM measured at a depth of 4 cm, which was determined according to the land surface types. The validation results show that the EF approach provides superior estimates with a lower RMSE (0.023 m3·m−3) value and a higher correlation coefficient (0.68) than the TVDI. The application of the airborne ΔTs/Fr space shows that the two modifications proposed in this study strengthen the link between the ΔTs/Fr space and SM, which is important for improving the precision of the remote sensing Ts/VI space method for monitoring SM.

Peatlands cover very large extents in northern regions and play a significant role in the global carbon cycle by functioning as a carbon sink. Large-scale satellite based monitoring systems, such as the Sentinel-2 Multispectral Instrument (MSI), are necessary to improve our understanding of how these ecosystems respond to climate change by providing verifiable land products. For instance, satellite-based land product validation approaches can benefit from airborne hyperspectral imagery and in-situ data, which provide higher spatial and spectral resolution baselines, ideal for measuring vegetation changes (e.g. phenology, LAI) at local scales. Here, we assessed the short-term phenospectral dynamics (spectral changes indicated by specific spectral features as a function of phenology) of five ombrotrophic peatland vegetation physiognomies over four dates at the Mer Bleue bog in Canada. We took advantage of a unique remote sensing data acquisition campaign aiming to validate Sentinel-2A land products, and analyzed three spatially and spectrally distinctive datasets (i.e. field spectra, VISNIR airborne hyperspectral imagery (HSI) and Sentinel-2A imagery) over the first half of the 2016 growing season. By implementing a bottom-up approach, first we assessed the airborne HSI's capability to detect phenological changes as compared to in-situ acquired field spectroscopy measurements in a 10 ha area at Mer Bleue and evaluated the spectral features characteristic of these phenological changes. Second, over the entire Mer Bleue area (28,000 ha), we compared a series of four Sentinel-2A images to four airborne HSI mosaics (spatially and spectrally resampled to Sentinel-2A) to assess the utility of Sentinel-2A for detecting small spectral variations due to phenological changes (i.e. greening). In addition, for this second comparison, three spectral vegetation indices were derived from the Sentinel-2A images and the airborne HSI mosaics. The spectral comparisons between the airborne HSI and the field spectroscopy data revealed clear phenological changes from the airborne HSI. For instance, a closer agreement between reflectance measured by the field spectrometer and the airborne HSI spectral response was found in the visible region (450–680 nm). A greater difference however, was consistently seen in the near-infrared region (681–866 nm) across the four dates. Narrow spectral features in three regions of the visible range (global minima, red absorption, green peak), indicating changes in vegetation colour, were consistent for both datasets and with expected phenological patterns at Mer Bleue. At the landscape level, Sentinel-2A mirrored the spectral changes depicted by the resampled HSI data. However, band level, pair-wise comparisons showed significant differences ( p  < 0.001) in reflectance for each band, with Sentinel-2A exhibiting higher reflectance values than the HSI for the first three dates. Only for the last date (June 23rd) did the airborne HSI have higher reflectance values or no significant difference with the Sentinel-2A data. Overall, our three datasets captured the short-term phenological changes at Mer Bleue and have provided promising results in terms of using the Sentinel-2A MSI sensor to monitor these changes at the landscape level. [ABSTRACT FROM AUTHOR]

ABSTRACTBackground:Dementia screening is a public health priority in Taiwan, where the prevalence of dementia is increasing because of an aging population. However, the reasons affect community-dwelling people to accept a referral to memory specialist clinic after dementia screening was still unclear. To investigate the feasibility, acceptability, sensitivity, and specificity of the ascertain dementia 8-item informant questionnaire (AD8) to screen for patients with cognitive impairments in Taiwan's primary healthcare system.Methods: Researchers invited community-dwelling people whose age was above 50-year-old to attend the Memory Screening Project. AD8 was used to perform the informant interview with adult patients who were attending the Memory Screening Project in Taiwan. Individuals who scored ≥2 on the AD8 was suggested to accept referral for further cognitive performance evaluation tests, which included three validated dementia tests, i.e. the Mini-Mental Screening Examination (MMSE), the Cognitive Abilities Screening Instrument (CASI), and the Clinical Dementia Rating (CDR).Results: Of the 102 participants who scored ≥2 on the AD8, only 25.5% attended the referral appointment. In participants who had achieved six or more years of education, AD8 scores were not significantly different between groups and could not differentiate between the non-dementia and patients with dementia in the receiver-operator characteristics curve analysis. In contrast, in those participants who had received less than six years of education, the AD8 scores significantly differentiated between non-dementia and patients with dementia (p = 0.03).Conclusions: There was a low rate of attendance at a specialist memory clinic following referral after the AD8 interview. Higher levels of education facilitated individuals to make a decision to accept the recommended referral appointment, while the AD8 showed a higher rate of differentiation between individuals who had received an education of less than six years. [ABSTRACT FROM AUTHOR]

Background The number of sexual partners is one of the most important risk factors for sexually transmissible infections (STIs), including HIV. The aim of the present study was to examine the association between declining to report the number of partners using computer-assisted self-interviewing (CASI) and HIV or STI positivity at a public sexual health centre in Melbourne, Australia, in 2016.Methods: Individuals were categorised into three risk populations: women, men who have sex with women only (MSW) and men who have sex with men (MSM). Logistic regression analysis was used to examine the association between declining to report the number of sexual partners in the past 12 months and HIV or STI positivity for women and MSW, with generalised estimating equations (GEE) used for estimation in MSM to address repeated-measures within individuals.Results: In all, 18085 individuals (5579 women, 6013 MSW, 6493 MSM) were included in the final analysis. There was no association between chlamydia positivity and declining to respond among women and MSW. MSM who declined to respond were more likely to be chlamydia positive (adjusted odds ratio1.21; 95% confidence interval (CI) 1.01-1.43). Known HIV-positive MSM and MSM newly diagnosed with HIV had 3.31-fold (95% CI 2.48-4.42) and 2.82-fold (95% CI 1.84-4.32) greater odds respectively of declining to respond compared with HIV-negative MSM. Gonorrhoea and syphilis positivity in MSM were not associated with declining to respond.Conclusions: There was no association between declining to report the number of partners and chlamydia positivity among women and MSW. However, MSM who declined to report the number of partners were slightly more likely to have chlamydia and substantially more likely to be HIV positive. [ABSTRACT FROM AUTHOR]

Background & objectives: There is a paucity of trained professionals for the diagnosis of autism spectrum disorder (ASD), and a large number of cases go undetected and are diagnosed only during adolescence. There is no screening instrument specifically developed for screening of Indian population for ASD. This study was undertaken to develop a screening instrument to screen ASD in north Indian Hindi speaking population by multipurpose health workers. Methods: A 37-item instrument in Hindi with dichotomous yes/no responses [Chandigarh Autism Screening Instrument (CASI)] was developed to be applied on children aged 1.5-10 yr. The instrument was pilot tested and then reliability and validity of this instrument were tested. The sample included children with intellectual disability (n=75), ASD (n=83), other developmental disorders (n=87) and typically developing children (n=160). Results: Reliability, construct and content validity testing of the instrument were performed, and a score of 10 as cut-off had sensitivity of 89.16 per cent, specificity of 89.13 per cent, positive predictive value of 67.89 per cent and negative predictive value of 96.96 per cent. A shorter four-item version (CASI Bref) has also been developed with good sensitivity (73.49%) and specificity (90.68%) at a cut-off score of 2. Interpretation & conclusions: CASI was found to be a valid instrument for screening general Hindi speaking population of north India with adequate sensitivity and specificity. [ABSTRACT FROM AUTHOR]

This study used a reef-up approach to map coral reef benthos, substrates and bathymetry, with high spatial resolution hyperspectral image data. It investigated a physics-based inversion method for mapping coral reef benthos and substrates using readily available software: Hydrolight and ENVI. Compact Airborne Spectrographic Imager (CASI) data were acquired over Heron Reef in July 2002. The spectral reflectance of coral reef benthos and substrate types were measured in-situ, and using the HydroLight 4.2 radiative transfer model a spectral reflectance library of subsurface reflectance was simulated using water column depths from 0.5–10.0 m at 0.5 m intervals. Using the Spectral Angle Mapper algorithm, sediment, benthic micro-algae, algal turf, crustose coralline algae, macro-algae, and live coral were mapped with an overall accuracy of 65% to a depth of around 8.0 m; in waters deeper than 8.0 m the match between the classified image and field validation data was poor. Qualitative validation of the maps showed accurate mapping of areas dominated by sediment, benthic micro-algae, algal turf, live coral, and macro-algae. A bathymetric map was produced for water column depths 0.5–10.0 m, at 0.5 m intervals, and showed high correspondence with in-situ sonar data (R2 value of 0.93).

Taijiang National Park (TNP) of Taiwan is the northernmost geographical position of mangrove habitats in the Northern Hemisphere. Instead of occupying a vast region with a single species, the mangroves in TNP are usually mingled with other plants in a narrow corridor along the water or in groups on a small sandbank. The multi-spectral images acquired from the spaceborne platforms are therefore limited in mapping the abundance and distribution of the mangrove species in TNP. We report the work of mapping pure mangrove patches in small corridors and sandbanks in TNP using airborne Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery. Bu considering the similarity of spectral reflectance among three species of mangrove and other plants, we followed the concept of supervised classification to select a few training areas with known mangrove trees, where the training areas are determined from the detailed map of mangrove distribution derived from the field investigation. The Hourglass hyperspectral analysis technique was employed to identify the endmembers of pure mangrove in the training areas. The results are consistent with the current distribution of mangrove trees, and the remarkable feature of a “mangrove desert” highlights a fact that biodiversity can be easily and quickly destroyed if no protection is provided. Some remnant patches located by this research are very important to the management of mangrove trees.

Sand dunes are complex systems that contain several habitats, often as mosaics or transitions between types. Several of these habitats are afforded protection under European Legislation and in the UK nationally within Special Areas of Conservation (SAC) and Sites of Special Scientific Interest (SSSI). Natural England has a statutory duty to report to Europe on the conservation status and condition of sand dunes; and is required to report to the UK Government on designated sites. To achieve this we have sought ways of capturing, analysing and interpreting data on the extent and location of sand dune habitats. This requires an ability to be able to obtain data over large areas of coastline in an efficient way. Natural England and Environment Agency Geomatics have worked collaboratively for over 16 years, sharing data and ecological knowledge. In 2012 work started to evaluate the use of remote sensing to map UK BAP and Annex I sand dune habitats. A methodology has now been developed and tested to map sand dune habitats. The key objective was to provide an operational tool that will help to map these habitats and understand change on sites around England. This has been achieved through analysis of LIDAR and Compact Airborne Spectrographic Imager (CASI) data using Object Orientated Image Analysis. Quality Control (QC) and accuracy assessments have shown this approach to be successful and 11 sites have been mapped to date. These techniques are providing a new approach to monitoring change in coastal vegetation communities and informing management of protected sites. [ABSTRACT FROM AUTHOR]

CaAgSi (0 ≤ x ≤ 0.1) with 47.5% excess of Ca alloys were fabricated by melting in a tantalum tube and hot pressing technique. Phase structures of the samples were studied by means of x-ray diffraction. The electrical conductivity and Seebeck coefficient of CaAgSi alloys were studied in the temperature range of 300-873 K. The electrical conductivity of the Ag-doped samples increases within the whole test temperature range. All samples show p-type semiconductor behavior. The electrical conductivity decreases with increasing temperature from 300 K to 873 K, which is typically observed for a degenerate semiconductor. Compared with the undoped samples, Ag-doping ( x = 0.04-0.1) results in decreases of Seebeck coefficient, especially CaAgSi with x = 0.1. The thermal conductivity of the doped samples gradually increases with increasing the Ag-doping content. The CaAgSi with x = 0.02 sample exhibits the lowest thermal conductivity within the whole test temperature range. The ZT values of CaAgSi with x = 0.02 sample have an enhancement in the temperature range of 300-873 K by contrast with those of the CaSi sample. The maximum ZT value is 0.16 at 837 k, which is observed for the CaAgSi with x = 0.04 sample. [ABSTRACT FROM AUTHOR]

We compared 2 rating scales with different manic symptom items on diagnostic accuracy for detecting pediatric bipolar spectrum disorder (BPSDs) in outpatient mental health clinics. Participants were 681 parents/guardians of eligible children (465 male, mean age = 9.34) who completed the Parent General Behavior Inventory-10-item Mania (PGBI-10 M) and mania subscale of the Child and Adolescent Symptom Inventory-Revised (CASI-4R). Diagnoses were based on KSADS interviews with parent and youth. Receiver operating characteristic (ROC) analyses and diagnostic likelihood ratios (DLRs) determined discriminative validity and provided clinical utility, respectively. Logistic regressions tested for incremental validity in the CASI-4R mania subscale and PGBI-10 M in predicting youth BPSD status above and beyond demographic and common diagnostic comorbidities. Both CASI-4R and PGBI-10 M scales significantly distinguished BPSD (N = 160) from other disorders (CASI-4R: Area under curve (AUC) = .80, p < 0.0005; PGBI-10 M: AUC = 0.79, p < 0.0005) even though scale items differed. Both scales performed equally well in differentiating BPSDs (Venkatraman test p > 0.05). Diagnostic likelihood ratios indicated low scores on either scale (CASI: 0-5; PGBI-10 M: 0-6) cut BPSD odds to 1/5 of those with high scores (CASI DLR- = 0.17; PGBI-10 M DLR- = 0.18). High scores on either scale (CASI: 14+; PGBI-10 M: 20+) increased BPSD odds about fourfold (CASI DLR+ = 4.53; PGBI-10 M DLR+ = 3.97). Logistic regressions indicated the CASI-4R mania subscale and PGBI-10 M each provided incremental validity in predicting youth BPSD status. The CASI-4R is at least as valid as the PGBI-10 M to help identify BPSDs, and can be considered as part of an assessment battery to screen for pediatric BPSDs. [ABSTRACT FROM AUTHOR]

An increasingly common requirement in remote sensing is the integration of hyperspectral data collected simultaneously from different sensors (and fore-optics) operating across different wavelength ranges. Data from one module are often relied on to correct information in the other, such as aerosol optical thickness (AOT) and columnar water vapor (CWV). This paper describes problems associated with this process and recommends an improved strategy for processing remote sensing data, collected from both visible to near-infrared and shortwave infrared modules, to retrieve accurate AOT, CWV, and surface reflectance values. This strategy includes a workflow for radiometric and spatial cross-calibration and a method to retrieve atmospheric parameters and surface reflectance based on a radiative transfer function. This method was tested using data collected with the Compact Airborne Spectrographic Imager (CASI) and SWIR Airborne Spectrographic Imager (SASI) from a site in Huailai County, Hebei Province, China. Various methods for retrieving AOT and CWV specific to this region were assessed. The results showed that retrieving AOT from the remote sensing data required establishing empirical relationships between 465.6 nm/659 nm and 2105 nm, augmented by ground-based reflectance validation data, and minimizing the merit function based on AOT@550 nm optimization. The paper also extends the second-order difference algorithm (SODA) method using Powell’s methods to optimize CWV retrieval. The resulting CWV image has fewer residual surface features compared with the standard methods. The derived remote sensing surface reflectance correlated significantly with the ground spectra of comparable vegetation, cement road and soil targets. Therefore, the method proposed in this paper is reliable enough for integrated atmospheric correction and surface reflectance retrieval from hyperspectral remote sensing data. This study provides a good reference for surface reflectance inversion that lacks synchronized atmospheric parameters. [ABSTRACT FROM AUTHOR]

Frequent wildfires in the north-west region of Spain affect soil organic matter. Soil properties can be estimated both spatially and temporally using remote sensing. A wide range of satellite and airborne hyperspectral and multispectral sensors are currently available. The spectral resolution varies substantially among sensors, making it difficult to identify the most suitable sensors and spectral regions for a specific application. This study aims to identify the sensors and wavelengths with the greatest potential for topsoil organic C mapping. Total (TOC) and oxidisable organic carbon (OC) content were measured in 89 soil samples collected in a mountain region of north-western Spain. Reflectance spectra of the samples in the spectral region 400-2450 nm were resampled to the bands of five sensors: Compact Airborne Spectrographic Imager (CASI), Airborne Hyperspectral Scanner (AHS), Hyperion, Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS). Calibration models obtained using partial least-squares regression proved to be effective for hyperspectral sensors and also for the multispectral sensor MODIS (R2=0.75-0.89), which suggests that hyperspectral capability is not required to accurately predict topsoil organic C. Models based on Landsat performed well, but with an error ~30-45% greater than that obtained for the hyperspectral sensors and MODIS. [ABSTRACT FROM AUTHOR]

Coral reefs are complex, heterogeneous environments where it is common for the features of interest to be smaller than the spatial dimensions of imaging sensors. While the coverage of live coral at any point in time is a critical environmental management issue, image pixels may represent mixed proportions of coverage. In order to address this, we describe the development, application, and testing of a spectral index for mapping live coral cover using CASI-2 airborne hyperspectral high spatial resolution imagery of Heron Reef, Australia. Field surveys were conducted in areas of varying depth to quantify live coral cover. Image statistics were extracted from co-registered imagery in the form of reflectance, derivatives, and band ratios. Each of the spectral transforms was assessed for their correlation with live coral cover, determining that the second derivative around 564 nm was the most sensitive to live coral cover variations(r2 = 0.63). Extensive field survey was used to transform relative to absolute coral cover, which was then applied to produce a live coral cover map of Heron Reef. We present the live coral cover index as a simple and viable means to estimate the amount of live coral over potentially thousands of km2 and in clear-water reefs.

The structure of benthic macrophyte habitats is known to indicate the quality of coastal water. Thus, a large-scale analysis of the spatial patterns of coastal marine habitats enables us to adequately estimate the status of valuable coastal marine habitats, provide better evidence for environmental changes and describe processes that are behind the changes. Knowing the spatial distribution of benthic habitats is also important from the coastal management point of view. A big challenge in remote sensing mapping of benthic habitats is to define appropriate mapping classes that are also meaningful from the ecological point of view. In this study, the benthic habitat classification scheme was defined for the study areas in the relatively turbid north-eastern Baltic Sea coastal environment. Two different classification methods—image-based and the spectral library—method were used for image classification. The image-based classification method can provide benthic habitat maps from coastal areas, but requires extensive field studies. An alternative approach in image classification is to use measured and/or modelled spectral libraries. This method does not require fieldwork at the time of image collection if preliminary information about the potential benthic habitats and their spectral properties, as well as variability in optical water properties exists from earlier studies. A spectral library was generated through radiative transfer model HydroLight computations using measured reflectance spectra from representative benthic substrates and water quality measurements. Our previous results have shown that benthic habitat mapping should be done at high spatial resolution, owing to the small-scale heterogeneity of such habitats in the Estonian coastal waters. In this study, the capability of high spatial resolution hyperspectral airborne a Compact Airborne Spectrographic Imager (CASI) sensor and a high spatial resolution multispectral WorldView-2 satellite sensor were tested for mapping benthic habitats. Initial evaluations of habitat maps indicate that image-based classification provides higher quality benthic maps compared to the spectral library method.

We test the use of hyperspectral sensors for the early detection of the invasive denseflowered cordgrass (Spartina densiflora Brongn.) in the Guadalquivir River marshes, Southwestern Spain. We flew in tandem a CASI-1500 (368-1052 nm) and an AHS (430-13,000 nm) airborne sensors in an area with presence of S. densiflora. We simplified the processing of hyperspectral data (no atmospheric correction and no data-reduction techniques) to test if these treatments were necessary for accurate S. densiflora detection in the area. We tested several statistical signal detection algorithms implemented in ENVI software as spectral target detection techniques (matched filtering, constrained energy minimization, orthogonal subspace projection, target-constrained interference minimized filter, and adaptive coherence estimator) and compared them to the well-known spectral angle mapper, using spectra extracted from ground-truth locations in the images. The target S. densiflora was easy to detect in the marshes by all algorithms in images of both sensors. The best methods (adaptive coherence estimator and target-constrained interference minimized filter) on the best sensor (AHS) produced 100% discrimination (Kappa = 1, AUC = 1) at the study site and only some decline in performance when extrapolated to a new nearby area. AHS outperformed CASI in spite of having a coarser spatial resolution (4-m vs. 1-m) and lower spectral resolution in the visible and near-infrared range, but had a better signal to noise ratio. The larger spectral range of AHS in the short-wave and thermal infrared was of no particular advantage. Our conclusions are that it is possible to use hyperspectral sensors to map the early spread S. densiflora in the Guadalquivir River marshes. AHS is the most suitable airborne hyperspectral sensor for this task and the signal processing techniques target-constrained interference minimized filter (TCIMF) and adaptive coherence estimator (ACE) are the best performing target detection techniques that can be employed operationally with a simplified processing of hyperspectral images. [ABSTRACT FROM AUTHOR]

Hyperspectral data have been widely and successfully used in lithological mapping and mineral exploration for decades. However, different lithologies always show quite similar spectral shape and it is hard to distinguish them by conventional algorithms. This paper gives a new method for lithology feature extraction from hyperspectral data. The fractal signal image of airborne hyperspectral data of compact airborne spectrographic imager is calculated and used for lithology feature extraction. The results indicate that fractal signal analysis enable enhancement of lithologic information in hyperspectral images and eventually allow lithologic mapping by fractal signal algorithms. The influencing factor of the fractal signal and characterized scale are also discussed, it indicates that the iteration step size have influence on both the fractal signal and characterized scale. Little research has been made on the fractal signal features of spectral curves, and their physical implications and quantification are yet to be further studied. [ABSTRACT FROM PUBLISHER]

In recent decades, many spectral vegetation indices (SVIs) have been proposed to estimate the leaf nitrogen concentration (LNC) of crops. However, most of these indices were based on the field hyperspectral reflectance. To test whether they can be used in aerial remote platform effectively, in this work a comparison of the sensitivity between several broad-band and red edge-based SVIs to LNC is investigated over different crop types. By using data from experimental LNC values over 4 different crop types and image data acquired using the Compact Airborne Spectrographic Imager (CASI) sensor, the extensive dataset allowed us to evaluate broadband and red edge-based SVIs. The result indicated that NDVI performed the best among the selected SVIs while red edge-based SVIs didn't show the potential for estimating the LNC based on the CASI data due to the spectral resolution. In order to search for the optimal SVIs, the band combination algorithm has been used in this work. The best linear correlation against the experimental LNC dataset was obtained by combining the 626.20nm and 569.00nm wavebands. These wavelengths correspond to the maximal chlorophyll absorption and reflection position region, respectively, and are known to be sensitive to the physiological status of the plant. Then this linear relationship was applied to the CASI image for generating an LNC map, which can guide farmers in the accurate application of their N fertilization strategies. [ABSTRACT FROM AUTHOR]

To achieve high return among secondary respondents, primary respondents’ consent rates must be high. In the German Family Panel (pairfam), a large, randomly sampled panel study, primary respondents’ consent rates to surveying their parents were found to be low. Since we suspected that the underlying reason could be interviewer behavior, we tested in an experiment if placing the consent questions in the self-interview (CASI) part of the interview would increase consent rates. Results show that bypassing interviewers by asking respondents directly in the CASI section did not increase consent rates. [ABSTRACT FROM AUTHOR]

Vascular dementia and vascular cognitive impairment have attracted more attention recently due to their association with increased risk of death and institutionalization. The purpose of the present study was to detect and identify the characteristics of cognitive impairments during the early stage of lacunar stroke. The subjects consisted of 23 consecutive first-ever acute lacunar infarction patients who were admitted to the Department of Neurology, Kaohsiung Municipal Hsiao-Kang Hospital, Taiwan, from November 2001 to October 2002. The National Institutes of Health Stroke Scale and Cognitive Abilities Screening Instrument (CASI) were used to evaluate stroke severity and cognitive function, and assessments were performed by a neurologist and psychologist, within 10 days of stroke onset. Of the 23 patients, 21 (91.3%) had CASI scores below their respective cutoff values and all patients had cognitive impairment in at least one cognitive domain in CASI. There were no significant correlations between CASI abnormality (below the cutoff value) and patient age, education, or the interval from stroke onset. Recent memory impairment was the most often impaired cognitive domain on CASI (19 patients, 82.6%). There were significant correlations between recent memory and “attention or concentration” (correlation coefficient, 0.52; p < 0.05), and “abstraction and judgment” (correlation coefficient, 0.44; p < 0.05). The correlations between recent memory and other domains were not significant. It was concluded that cognitive impairment after acute lacunar infarct is quite common and recent memory is the most often impaired cognitive domain. This may have been caused by the location of the specific lesion as well as by the impairment in “attention or concentration” or “abstraction and judgment”.

The airborne spectroradiometers AHS and CASI were used as a source of hyperspectral and thermal remote sensing data during the REFLEX campaign. Data geolocation and a first simple atmospheric correction was performed by INTA in near-real time with a specific on-site setup and distributed to all campaign participants. In this paper we present briefly the AHS and CASI REFLEX flight campaign followed by a detailed description of the methodology used for image processing and finally the results obtained in terms of image quality. As a conclusion, near-real time processing for AHS and CASI level 1 geolocated products was successful as most of CASI level 2 results but further work is needed for achieving accurate AHS level 2 products. [ABSTRACT FROM AUTHOR]

The relationship between spectral reflectance and foliar chlorophyll (Chl) and nitrogen (N) was examined for 19 species over a six-month growing period at Mer Bleue, an ombrotrophic bog located near Ottawa, Ontario, Canada. The goal of this study was to model total Chl and N concentration at the landscape-scale from remotely sensed data utilizing a model insensitive to plant functional type (PFT), species and season. To date the relationship between spectral reflectance and foliar properties is poorly understood in peatlands owing to the scarcity of studies examining the spectral variability between mosses and vascular plants. A model that comprised a continuous wavelet transform coupled with a neural network was constructed to predict Chl and N content from selected wavelet features (coefficients) at both leaf and airborne image scales. The model was compared to thirteen common spectral indices used to determine vegetation properties in forest environments. The heterogeneity of the vascular plant/moss cover over small spatial scales (< 1 m) and the spectral complexity of the vegetation cover, precluded a regression model to be derived from the spectral indices for all species across seasons; the best model for all species combined was R 2 = 0.3. The final continuous wavelet model resulted in a noticeable improvement with R 2 values ranging from 0.8 to 0.9 (for both Chl and N content). We scaled up our predictive model from the leaf/capitulum level data to 40 cm spatial resolution 72-band airborne imagery (CASI-2 429.6–968.8 nm) to create surfaces of Chl and N content for the study area. [ABSTRACT FROM AUTHOR]

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Surveys are conducted using many different modes (e.g. face-to-face, mail, telephone, Internet). Because different modes have different error structures, it is very important to understand the advantages and disadvantages associated with each mode. In recent years there have been major changes in the modes typically utilized in surveys. In particular, there has been increases in the use of computers in data collection, self-administration, and mixed-mode designs. The implications of these and future changes are considered. [ABSTRACT FROM AUTHOR]

La réglementation communautaire sur les biocarburants a été mise en place à partir de 2003 pour répondre à un triple objectif : réduction des émissions de gaz à effet de serre, réduction de la dépendance énergétique, et soutien à la production agricole dans un contexte où 10 % des terres étaient obligatoirement gelées. Cette réglementation a été renforcée en 2009 dans le cadre du « paquet énergie » par l’introduction par la directive energie renouvelable d’un objectif obligatoire d’incorporation de 10 % d’énergie renouvelable dans les carburants à l’horizon 2020. Cette législation est complétée par une directive qualité des carburants qui impose une réduction de 6 % d’ici 2020 de l’empreinte carbone des carburants. La forte diésélisation du parc de véhicule en Europe a conduit à une rapide progression de la consommation de biodiesel (11 millions de tonnes dont 9 produites dans l’UE). L’huile de colza est la principale matière première du biodiesel. L’augmentation de la production de colza a permis de répondre à cette demande, tout en fournissant un coproduit protéique permettant de réduire significativement le déficit en protéines européen. Le débat sur l’impact du CASI (changement indirect d’affectation des sols) des biocarburants, ainsi que celui sur l’équilibre alimentaire, a conduit la Commission européenne, 3 ans après avoir défini sa politique, à proposer de plafonner les carburants issus des cultures (1ere génération) à 5 % et à introduire des « facteurs CASI » dans l’évaluation des effets de réduction des gaz à effets de serre. Cette proposition qui pourrait fortement remettre en cause le développement du biodiesel...et de la culture de colza fait à la date de rédaction de cet article (juillet 2013) l’objet de difficiles négociations à Bruxelles, dont l’issue est difficile à prédire.

Objectives: To compare the data quality, logistics, and cost of a self-administered sexual behavior questionnaire administered either using a computer-assisted survey instrument (CASI) or by paper and pencil in a primary care clinic. Study Design and Setting: A self-administered sexual behavior questionnaire was administered to 16-29 year olds attending general practice. Questionnaires were administered by either paper and pencil (paper) or CASI. A personal digital assistant was used to selfadminister the CASI. Results: A total of 4,491 people completed the questionnaire, with 46.9% responses via CASI and 53.2% by paper. Completion of questions was greater for CASI than for paper for sexual behavior questions: number of sexual partners [odds ratio (OR), 6.85; 95% confidence interval (CI): 3.32, 14.11] and ever having had sex with a person of the same gender (OR, 2.89; 95% CI: 1.52, 5.49). The median number of questions answered was higher for CASI than for paper (17.6 vs. 17.2; P ! 0.01). CASI was cheaper to run at $8.18 per questionnaire compared with $11.83 for paper. Conclusion: Electronic devices using CASI are a tool that can increase participants' questionnaire responses and deliver more complete data for a sexual behavior questionnaire in primary care clinics. [ABSTRACT FROM AUTHOR]

The present work deals with the study of the reaction of hydrogen desorption from the CaSiH hydride by means of the calorimetric method. The dehydrogenation of the CaSiH hydride was carried out at 548 K. For a calorimetric study, the installation composed of the differential heat-conducting Tian-Calvet type calorimeter connected with a conventional Sieverts-type apparatus was employed. Such installation permitted us to obtain simultaneously the P- X isotherms ( P-equilibrium hydrogen pressure, X = H/CaSi) and variation of the partial molar enthalpies of the reaction of hydrogen desorption from CaSiH with the hydrogen concentration in the metallic matrix. It was ascertained that in the CaSi-H system there was one region where values of the partial molar enthalpy of the reaction of hydrogen desorption from the CaSiH hydride remained constant. This means that formation of one hydride phase in the CaSi-H system took place. The enthalpy and entropy values for the reaction of hydrogen desorption from the CaSiH in the plateau range are Δ H = 53.8 ± 1.2 kJ mol H and Δ S = 94.2 ± 2.7 J mol H K (Δ H and Δ S-the differential molar enthalpy and entropy desorption, respectively). [ABSTRACT FROM AUTHOR]

This study used a reef-up approach to map coral reef benthos, substrates and bathymetry, with high spatial resolution hyperspectral image data. It investigated a physics-based inversion method for mapping coral reef benthos and substrates using readily available software: Hydrolight and ENVI. Compact Airborne Spectrographic Imager (CASI) data were acquired over Heron Reef in July 2002. The spectral reflectance of coral reef benthos and substrate types were measured in-situ, and using the HydroLight 4.2 radiative transfer model a spectral reflectance library of subsurface reflectance was simulated using water column depths from 0.5-10.0 m at 0.5 m intervals. Using the Spectral Angle Mapper algorithm, sediment, benthic micro-algae, algal turf, crustose coralline algae, macro-algae, and live coral were mapped with an overall accuracy of 65% to a depth of around 8.0 m; in waters deeper than 8.0 m the match between the classified image and field validation data was poor. Qualitative validation of the maps showed accurate mapping of areas dominated by sediment, benthic micro-algae, algal turf, live coral, and macro-algae. A bathymetric map was produced for water column depths 0.5-10.0 m, at 0.5 m intervals, and showed high correspondence with in-situ sonar data (R2 value of 0.93). [ABSTRACT FROM AUTHOR]

Highlights: [•] We propose a robust chlorophyll content (Chl) mapping method over urban vegetation. [•] We have calibrated SPAD-502 based on four urban tree species to measure Chl. [•] The spectral NAOC (Normalized Area Over reflectance Curve) index is related to Chl. [•] NAOC was calibrated and validated from airborne CASI data to map Chl over Valencia. [•] The method provides a quantitative bioindicator of urban vegetation's health status. [Copyright &y& Elsevier]

Coral reefs are complex, heterogeneous environments where it is common for the features of interest to be smaller than the spatial dimensions of imaging sensors. While the coverage of live coral at any point in time is a critical environmental management issue, image pixels may represent mixed proportions of coverage. In order to address this, we describe the development, application, and testing of a spectral index for mapping live coral cover using CASI-2 airborne hyperspectral high spatial resolution imagery of Heron Reef, Australia. Field surveys were conducted in areas of varying depth to quantify live coral cover. Image statistics were extracted from co-registered imagery in the form of reflectance, derivatives, and band ratios. Each of the spectral transforms was assessed for their correlation with live coral cover, determining that the second derivative around 564 nm was the most sensitive to live coral cover variations(r2 = 0.63). Extensive field survey was used to transform relative to absolute coral cover, which was then applied to produce a live coral cover map of Heron Reef. We present the live coral cover index as a simple and viable means to estimate the amount of live coral over potentially thousands of km2 and in clear-water reefs. [ABSTRACT FROM AUTHOR]

The structure of benthic macrophyte habitats is known to indicate the quality of coastal water. Thus, a large-scale analysis of the spatial patterns of coastal marine habitats enables us to adequately estimate the status of valuable coastal marine habitats, provide better evidence for environmental changes and describe processes that are behind the changes. Knowing the spatial distribution of benthic habitats is also important from the coastal management point of view. A big challenge in remote sensing mapping of benthic habitats is to define appropriate mapping classes that are also meaningful from the ecological point of view. In this study, the benthic habitat classification scheme was defined for the study areas in the relatively turbid north-eastern Baltic Sea coastal environment. Two different classification methods - image-based and the spectral library - method were used for image classification. The image-based classification method can provide benthic habitat maps from coastal areas, but requires extensive field studies. An alternative approach in image classification is to use measured and/or modelled spectral libraries. This method does not require fieldwork at the time of image collection if preliminary information about the potential benthic habitats and their spectral properties, as well as variability in optical water properties exists from earlier studies. A spectral library was generated through radiative transfer model HydroLight computations using measured reflectance spectra from representative benthic substrates and water quality measurements. Our previous results have shown that benthic habitat mapping should be done at high spatial resolution, owing to the small-scale heterogeneity of such habitats in the Estonian coastal waters. In this study, the capability of high spatial resolution hyperspectral airborne a Compact Airborne Spectrographic Imager (CASI) sensor and a high spatial resolution multispectral WorldView-2 satellite sensor were tested for mapping benthic habitats. Initial evaluations of habitat maps indicate that image-based classification provides higher quality benthic maps compared to the spectral library method. [ABSTRACT FROM AUTHOR]

Knowledge of spatio-spectral heterogeneity within multisensor remote sensing images across visible, near-infrared and short wave infrared spectra is important. Till now, little comparative research on spatio-spectral heterogeneity has been conducted on real multisensor images, especially on both multispectral and hyperspectral airborne images. In this study, four airborne images, Airborne Thematic Mapper, Compact Airborne Spectrographic Imager, Specim AISA Eagle and AISI Hawk hyperspectral airborne images of woodland and heath landscapes at Harwood, UK, were applied to quantify and evaluate the differences in spatial heterogeneity through semivariogram modelling. Results revealed that spatial heterogeneity of multisensor airborne images has a close relationship with spatial and spectral resolution and wavelength. Within the visible, near-infrared spectra and short wave infrared spectra, greater spatial heterogeneity is generally observed from the relatively longer wavelength in short wave infrared spectra. There are dramatic changes across the red and red edge spectra, and the peak value is generally examined in the red middle or red edge wavelength across the visible and near-infrared spectra for vegetation or non-vegetation landscape respectively. In all, for real multisensor airborne images, the change in spatial heterogeneity with spatial resolution will accord with the change of support theory depending on whether dramatic change exists across the corresponding wavelength. Besides, if with close spatial resolution, the spatial heterogeneity of multispectral images might be far from the overall integration of these bands from the hyperspectral images involved. A comparative assessment of spatio-spectral heterogeneity using real hyperspectral and multispectral airborne images provides practical guidance for designing the placement and width of a spectral band for different applications and also makes a contribution to the understanding of how to reconcile spatial patterns generated by multisensors. [ABSTRACT FROM PUBLISHER]

Precise and spatially-explicit knowledge of leaf chlorophyll content (Chl) is crucial to adequately interpret the chlorophyll fluorescence (ChF) signal from space. Accompanying information about the reliability of the Chl estimation becomes more important than ever. Recently, a new statistical method was proposed within the family of nonparametric Bayesian statistics, namely Gaussian Processes regression (GPR). GPR is simpler and more robust than their machine learning family members while maintaining very good numerical performance and stability. Other features include: i) GPR requires a relatively small training data set and can adopt very flexible kernels, ii) GPR identifies the relevant bands and observations in establishing relationships with a variable, and finally iii) along with pixelwise estimations GPR provides accompanying confidence intervals. We used GPR to retrieve Chl from hyperspectral reflectance data and evaluated the portability of the regression model to other images. Based on field Chl measurements from the SPARC dataset and corresponding spaceborne CHRIS spectra (acquired in 2003, Barrax, Spain), GPR developed a regression model that was excellently validated (r^2: 0.96, RMSE: 3.82 \mug/cm^2). The SPARC-trained GPR model was subsequently applied to CHRIS images (Barrax, 2003, 2009) and airborne CASI flightlines (Barrax 2009) to generate Chl maps. The accompanying confidence maps provided insight in the robustness of the retrievals. Similar confidences were achieved by both sensors, which is encouraging for upscaling Chl estimates from field to landscape scale. Because of its robustness and ability to deliver confidence intervals, GPR is evaluated as a promising candidate for implementation into ChF processing chains. [ABSTRACT FROM PUBLISHER]

Abstract: Earth observation offers effective spatial and temporal coverage to monitor coral reefs in addition to in situ monitoring. Effective monitoring requires that significant substratum features are detectable by a sensor. This detectability is a function of the sensor spectral resolution, the depth and composition of the water column and the spectral characteristics of the substratum. Most broadband multispectral satellite sensors are ineffective in resolving reef substrata at depth due to a lack of spectral specificity. The aim of this simulation study was to quantify the level to which substrata can be classified by sensors with variable spectral resolutions over a range of depths and water qualities and also to improve and quantify the definition of substratum detectability (the measure to which a substratum can be resolved from the water column) and substratum separability (the measure to which a substratum pair can be resolved from each other and from the water column). Three sensors were selected, representing hyperspectral data (CASI with 30 spectral bands) and multispectral data (WorldView-2 with 8 bands, and QuickBird with 4 bands). Spectral separability of substratum reflectance spectra (convolved to the spectral resolution of the three sensors) were compared within two contrasting water columns (reef-oceanic and coastal) over a range of water column depths. Metrics for substratum detectability and substratum separability were determined. As spectral resolution increases from QB to WV2 to CASI, end-members can be resolved to greater depths (e.g. from two to six meters in a coastal water column). The additional three spectral bands in the visible part of the spectrum of the WV2 sensor, as compared to QB, increase the applicability of multispectral sensors to systematic coral reef remote sensing. Increase in water column attenuation, due to higher concentrations of water column constituents, causes loss of substratum detectability and substratum separability. This effect can be partly compensated for by increased spectral resolution. For example, although the CASI and WV2 sensor performed comparably in a very shallow coastal water column (e.g. at 2m depth), the higher spectral resolution of the CASI sensor enhanced spectral separability, resulting in higher substratum separability in deeper water than WV2. With more spectral bands, more substratum end-member reflectances are distinct from the water column signal to greater depth. This implies that higher spectral resolution will enhance bathymetry retrieval, especially within coastal waters. The quantitative framework of this study extends findings of previous contextual coral reef substratum mapping studies. It confirms that higher spectral resolution (i.e. WV2 and CASI) earth observation data significantly enhances coral reef classification capability to increased depths or to the same depth in a more turbid water column. The conclusions of this study can also be extended to coastal ecosystems. [Copyright &y& Elsevier]