One challenge to implementing spectral change detection algorithms using multitemporal Landsat data is that key dates and periods are often missing from the record due weather disturbances lapses in continuous coverage. This paper presents a method utilizes residuals harmonic regression over years of data, conjunction with statistical quality control charts, signal subtle vegetative cover. These charts able detect changes both deforestation subtler forest degradation thinning. First,...

With the advent of free Landsat data stretching back decades, there has been a surge interest in utilizing remotely sensed multitemporal analysis for estimation biophysical parameters. Such is confounded by cloud cover and other image-specific problems, which result missing at various aperiodic times year. While wealth information contained time series, such series severely limited due to data. This paper illustrates technique can greatly expand possibilities analyses, Fourier regression...

Machine learning approaches such as random forest have increased for the spatial modeling and mapping of continuous variables.Random is a non-parametric ensemble approach, unlike traditional regression there no direct quantification prediction error.Understanding uncertainty important when using model-based maps inputs to other applications fire modeling.Here we use Monte Carlo approach quantify models.We test by simulating dependent independent variables with known characteristics comparing...

Abstract. As a primary flux in the global water cycle, evapotranspiration (ET) connects hydrologic and biological processes is directly affected by land management, use change climate variability. Satellite remote sensing provides an effective means for diagnosing ET patterns over heterogeneous landscapes; however, limitations on spatial temporal resolution of satellite data, combined with effects cloud contamination, constrain amount detail that single can provide. In this study, we...

Light detection and ranging (lidar) is becoming an increasingly popular technology among scientists for the development of predictive models forest biophysical variables. However, before this can be adopted with confidence long-term monitoring applications in Canada, robust must developed that applied validated over large complex forested areas. This will require "scaling-up" from current high-density lidar data to low-density collected at higher altitudes. paper investigates effect lowering...

Abstract Purpose: The steroid hormone 1,25-dihydroxyvitamin D3 is thought to protect against breast cancer. actions of are mediated via the vitamin D receptor (VDR), and a number polymorphisms in VDR gene have been identified. These result distinct genotypes, some which may alter susceptibility We investigated whether specific associated with cancer risk United Kingdom Caucasian population. Experimental Design: In retrospective case-control study, female patients (n = 398) control women 427)...

There is increasing evidence that vitamin D can protect against breast cancer. The actions of are mediated via the receptor (VDR). We have investigated whether polymorphisms in VDR gene associated with altered cancer risk a UK Caucasian population. recruited 241 women following negative screening mammogram and 181 known polymorphism BsmI, an intronic 3′ variant, was significantly increased risk: odds ratio bbvs BBgenotype = 2.32 (95% CI, 1.23–4.39). BsmI linkage disequilibrium candidate...

The objective of this study was to determine whether leaf area index (LAI) can be accurately estimated in intensively managed pine plantations using multiple-return airborne laser scanner (lidar) data. In situ measurements LAI were made the LiCor LAI-2000 Plant Canopy Analyzer on 109 plots under a variety stand conditions (i.e., age, nutritional regime, and stem density) North Carolina Virginia, USA late summer, 2008. Distributional metrics calculated for each plot small footprint lidar data...

Forest ecosystem services such as clean water, wildlife habitat, and timber supplies are increasingly threatened by drought disturbances (e.g., harvesting, fires conversion to other uses), which can have great impacts on stand development water balance. Improved understanding of the hydrologic response forested systems disturbance at spatiotemporal resolutions commensurate with these is important for effective forest management. Evapotranspiration (ET) a key variable in assessing functioning...

Abstract Sense of place holds promise to understand how people perceive and respond social ecological change; however, using this concept explore vulnerability adaptation first depends on identifying the multiple ways define their relationship with a place. We introduce meaning‐dependence framework account for broad array person–place connections within social–ecological landscapes. applied private landowners in Southern Great Plains United States, working landscape experiencing...

The efficient inversion of complex, three-dimensional (3-D) radiative transfer models (RTMs), such as the discrete anisotropy (DART) model, can be achieved using a look-up table (LUT) approach. A pressing research priority in LUT-based for 3-D model is to determine optimal LUT grid size and density. We present simple computationally approach populating an database with DART simulations over large number spectral bands. In first step, we built preliminary parameters coarse increments simulate...

The need for an efficient and standard technique optimal spectral sampling of hyperspectral data during the inversion canopy reflectance models has been subject many studies. objective this study was to investigate utility discrete wavelet transform (DWT) extracting useful features from with which forest LAI can be estimated through a three dimensional radiative transfer model, Discrete Anisotropy Radiative Transfer (DART) model. DART, coupled leaf optical properties model PROSPECT, inverted...

Autoimmune diabetes mellitus affects >50% of diabetes-prone BB (DP BB) rats but <1% diabetes-resistant (DR rats. We report an outbreak spontaneous among DR that coincided with serologic evidence the onset viral infection. This apparent link between a change in environment and expression then led us to study interaction environmental exposure pathogens this disorder virally seropositive seronegative populations polyinosinic–polycytidylic acid (poly I:C), interferon inducer known...

This study investigates the ability to predict forest diameter distributions from light detection and ranging (LiDAR) data using Weibull modelling for stands in central Ontario. Results suggest that unimodal 2-parameter model is a promising technique prediction of class distributions, with strong relationships evident several subgroups (at 95% confidence, r 2 adj =0.83, 0.78, 0.88, 0.80, 0.83, 0.65, validation RMSE 4.09 m /ha, 0.61 stems/ha, 6.05, 0.64, 4.73, 0.09 basal area, stem density, b...

The competitive neighbourhood surrounding an individual tree can have a significant influence on its diameter at breast height (DBH) and stem volume (SV). Distance dependent competition index metrics are rarely recorded in traditional field campaigns because they laborious to collect spatially limited. Remote sensing data could overcome these limitations while providing estimation of forest attributes over large area. We used unoccupied aerial vehicle laser scanning delineate crowns (ITCs)...

This study investigates the potential of lidar and hyperspectral data for prediction canopy chlorophyll (Chl) carotenoid concentrations a spatially complex boreal mixedwood. First, scale application reflectance derivative indices are used to estimate Chl concentration. Second, analyses is conducted identify structural metrics related Third, combined determine if concentration estimates can be improved further. Of considered, only index (DCI) red‐edge inflection point (λp) shown good...