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The hemlock woolly adelgid (HWA) (Adelges tsugae Annand) is an invasive insect in the eastern United States. Since its initial detection in Richmond, Virginia, in 1951, HWA has spread to half of the eastern hemlock (Tsuga canadensis (L.) Carr.) natural range. Detection of early infestation symptoms via remote sensing requires the knowledge of the changes in reflectance resulting from physiological changes in the host as inflicted by the insect and the selection of equipment with the appropriate sensor characteristics. Laboratory-based reflectance measurements of infested and non-infested hemlock foliage collected from four sites in southern New Hampshire and Maine occurred biweekly over 6 months in 2012 and weekly over 5 weeks in 2013. Vegetation indices (red edge inflection point (REIP), normalized difference vegetation index (NDVI), moisture stress index (MSI), and near infrared (NIR) 3/1 ratio) were associated with concurrent chlorophyll and moisture content data. Infested first-year foliage contained greater concentrations of chlorophyll and moisture, resulting in reduced visible spectral reflectance, greater REIP and NDVI values, and lower MSI and NIR 3/1 values than non-infested foliage. Furthermore, fluorescence measurements indicated greater photosystem function during the early stages of infestation, suggesting a possible compensatory response by hemlock to infestation. Significant differences in reflectance between infested and non-infested foliage were observed in late June and July in the weeks immediately following HWA settlement on new growth. Implementing these observations during remote sensing mission planning may increase the likelihood of detecting early HWA infestation symptoms at landscape scales. Key words: Adelges tsugae, hemlock woolly adelgid, remote sensing, vegetation indices, fluorescence, chlorophyll. Le puceron lanigere de la pruche (PLP) (Adelges tsugae Annand) est un insecte invasif dans l'est des Etats-Unis. Depuis qu'il a ete detecte pour la premiere fois a Richmond en Virginie, en 1951, le PLP a envahi la moitie de l'aire de repartition naturelle de la pruche du Canada (Tsuga canadensis (L.) Carr.). Pour detecter les symptomes precoces d'infestation au moyen de la teledetection il faut connaitre les changements dans la reflectance dus aux modifications physiologiques chez l'hote causees par l'insecte et choisir l'equipement dont les capteurs ont les caracteristiques appropriees. Des mesures de reflectance ont ete effectuees en laboratoire sur du feuillage de pruche infeste ou non preleve a quatre endroits dans le sud du New Hampshire et du Maine a toutes les deux semaines durant six mois en 2012 et a toutes les semaines durant cinq semaines en 2013. Des indices de vegetation (REIP, NDVI, MSI et NIR 3/1) ont ete associes aux donnees simultanees de teneur en humidite et en chlorophylle. Le feuillage d'un an infeste contenait de plus fortes concentrations de chlorophylle et d'humidite qui se traduisaient par une diminution de la reflectance spectrale dans le visible, des valeurs plus elevees de REIP et NDVI et plus fables de MSI er NIR 3/1 que dans le feuillage non infeste. De plus, des mesures de fluorescence ont montre que le photosysteme fonctionnait davantage durant les premiers stades de l'infestation, ce qui suggere possiblement une reaction compensatoire de la pruche a l'infestation. Des differences significatives de reflectance entre le feuillage infeste et non infeste ont ete observees a la fin du mois de juin et en juillet durant les semaines qui ont immediatement suivi l'etablissement du PLP sur les nouvelles pousses. L'integration de ces observations durant la planification des missions de teledetection pourrait augmenter les chances de detecter les symptomes precoces d'infestation du PLP a l'echelle du paysage. [Traduit par la Redaction] Mots-cles: Adelges tsugae, puceron lanigere de la pruche, teledetection, indices de vegetation, fluorescence, chlorophylle., 1. Introduction Eastern hemlock (Tsuga canadensis (L.) Carr.) is a foundation tree species in the northeastern United States (Ellison et al. 2005). Often found on steep slopes and in riparian [...]

A detection scheme that uses classical and spatial statistics has been developed to identify roadways with the most severe safety needs. It is based on the null hypothesis that all roadways have the same crash risk, that is, all have the same nonfatal and fatal crash rates throughout the entire study region. Fatal and nonfatal crash rates, which are assumed to be randomly distributed as Poisson processes, are modeled with a marked homogeneous Poisson process model. Since the traffic exposures are typically unknown at the crash sites, they are predicted with a geostatistical model. Locations, where the null hypothesis is rejected, are safety treatment candidates. P-value risk rankings are used to identify locations with the most severe safety needs. The results from alternative analyses--one using vehicle miles traveled and another using population as measures of traffic exposure--are conducted and compared. The state of New Hampshire is used in a case study. The effects of analyzing areas with small traffic exposures, the so-called 'small-area estimation' problem, and the aim to develop a data-driven detection scheme that meets the requirements as an objective decision-making tool are discussed. DOI: 10.1061/(ASCE)TE.1943-5436.0000048 CE Database subject headings: Traffic safety; Traffic models; Spatial analysis; Spatial data; Spatial distribution; Statistics; Stochastic processes. Author keywords: Traffic safety; Traffic models; Spatial analysis; Spatial data; Spatial distribution; Statistics; Stochastic processes.

A physical and chemical heterogeneity study of glaciofluvial deposit in Deerfield, New Hampshire, was conducted in order to understand the processes controlling the spatial variation of sediment properties. The findings suggest that lithofacies and color information could aid the characterization and modeling of heterogeneity at similar carbon-poor glaciofluvial sites.

Reoccurring seasonal cyanobacterial harmful algal blooms (CHABs) persist in many waters, and recent work has shown links between CHAB and elevated risk of amyotrophic lateral sclerosis (ALS). Quantifying the exposure levels of CHAB as a potential risk factor for ALS is complicated by human mobility, potential pathways, and data availability. In this work, we develop phycocyanin concentration (i.e., CHAB exposure) maps using satellite remote sensing across northern New England to assess relationships with ALS cases using a spatial epidemiological approach. Strategic semi-analytical regression models integrated Landsat and in situ observations to map phycocyanin concentration (PC) for all lakes greater than 8 ha ( n = 4117) across the region. Then, systematic versions of a Bayesian Poisson Log-linear model were fit to assess the mapped PC as a risk factor for ALS while accounting for model uncertainty and modifiable area unit problems. The satellite remote sensing of PC had strong overall ability to map conditions (adj. R2, 0.86; RMSE, 11.92) and spatial variability across the region. PC tended to be positively associated with ALS risk with the level of significance depending on fixed model components. Meta-analysis shows that when average PC exposure is 100 μg/L, an all model average odds ratio is 1.48, meaning there is about a 48% increase in average ALS risk. This research generated the first regionally comprehensive map of PC for thousands of lakes and integrated robust spatial uncertainty. The outcomes support the hypothesis that cyanotoxins increase the risk of ALS, which helps our understanding of the etiology of ALS. [ABSTRACT FROM AUTHOR]

Abstract: Spatio-temporal correlation analyses were performed on time series of daily freshwater discharge, wind fields, and SeaWiFS-derived surface particle concentrations in the northern Gulf of Mexico. The influences of discharge and winds on surface particle concentrations were investigated by mapping temporal correlation coefficients at each pixel for the whole time series (1997–2000) and for each season during 1999 and 2000. Maps of the correlation between suspended particulate matter concentration (SPM) and river discharge suggest regions that are fluvially influenced. The particulate matter may be sediments carried by the river plume or biogenic particles (e.g., detritus) stimulated by the river discharge. The algorithm used to estimate SPM concentrations does not differentiate between sediment and detritus. Maps of the correlation between wind stress and SPM suggest regions where wind mixing accounts for particulate resuspension and subsequent transport. Regions of significant positive wind-SPM correlation were independent, and often spatially separated, from regions of strong positive discharge-SPM correlation. Thus, the influences of winds and discharge on particle distributions can be investigated independently. Regions of high wind-SPM correlation were associated with shallow shelf areas, as correlation contours generally followed the bathymetric contours, and expanded in size under offshore wind regimes. These areas exhibited less spatial and temporal variability than the regions of high discharge-SPM correlation associated with the Mississippi-Atchafalaya river system. There was no apparent relationship between the magnitude of Mississippi- Atchafalaya discharge and the spatial extent of the region of high discharge-SPM correlation during seasonal analyses. Instead, the spatial extent and orientation of the discharge-SPM correlation field appeared to be a function of winds (both their direction and speed) and the buoyancy of the plume. [Copyright &y& Elsevier]

Abstract: In this paper, we present a theoretical and modeling framework to estimate the fractions of photosynthetically active radiation (PAR) absorbed by vegetation canopy (FAPARcanopy), leaf (FAPARleaf ), and chlorophyll (FAPARchl), respectively. FAPARcanopy is an important biophysical variable and has been used to estimate gross and net primary production. However, only PAR absorbed by chlorophyll is used for photosynthesis, and therefore there is a need to quantify FAPARchl. We modified and coupled a leaf radiative transfer model (PROSPECT) and a canopy radiative transfer model (SAIL-2), and incorporated a Markov Chain Monte Carlo (MCMC) method (the Metropolis algorithm) for model inversion, which provides probability distributions of the retrieved variables. Our two-step procedure is: (1) to retrieve biophysical and biochemical variables using coupled PROSPECT+SAIL-2 model (PROSAIL-2), combined with multiple daily images (five spectral bands) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor; and (2) to calculate FAPARcanopy, FAPARleaf and FAPARchl with the estimated model variables from the first step. We evaluated our approach for a temperate forest area in the Northeastern US, using MODIS data from 2001 to 2003. The inverted PROSAIL-2 fit the observed MODIS reflectance data well for the five MODIS spectral bands. The estimated leaf area index (LAI) values are within the range of field measured data. Significant differences between FAPARcanopy and FAPARchl are found for this test case. Our study demonstrates the potential for using a model such as PROSAIL-2, combined with an inverse approach, for quantifying FAPARchl, FAPARleaf, FAPARcanopy, biophysical variables, and biochemical variables for deciduous broadleaf forests at leaf- and canopy-levels over time. [Copyright &y& Elsevier]