10 CFR 765.12 - Inflation index adjustment procedures.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 4 2012-01-01 2012-01-01 false Inflation index adjustment procedures. 765.12 Section 765.12 Energy DEPARTMENT OF ENERGY REIMBURSEMENT FOR COSTS OF REMEDIAL ACTION AT ACTIVE URANIUM AND... Department shall adjust annually, using the CPI-U as defined in this part, amounts paid to an active uranium...

10 CFR 765.12 - Inflation index adjustment procedures.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 4 2013-01-01 2013-01-01 false Inflation index adjustment procedures. 765.12 Section 765.12 Energy DEPARTMENT OF ENERGY REIMBURSEMENT FOR COSTS OF REMEDIAL ACTION AT ACTIVE URANIUM AND... Department shall adjust annually, using the CPI-U as defined in this part, amounts paid to an active uranium...

10 CFR 765.12 - Inflation index adjustment procedures.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 10 Energy 4 2014-01-01 2014-01-01 false Inflation index adjustment procedures. 765.12 Section 765.12 Energy DEPARTMENT OF ENERGY REIMBURSEMENT FOR COSTS OF REMEDIAL ACTION AT ACTIVE URANIUM AND... Department shall adjust annually, using the CPI-U as defined in this part, amounts paid to an active uranium...

10 CFR 765.12 - Inflation index adjustment procedures.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 4 2010-01-01 2010-01-01 false Inflation index adjustment procedures. 765.12 Section 765.12 Energy DEPARTMENT OF ENERGY REIMBURSEMENT FOR COSTS OF REMEDIAL ACTION AT ACTIVE URANIUM AND... Department shall adjust annually, using the CPI-U as defined in this part, amounts paid to an active uranium...

Analysis of Differences in Phenology Extracted from the Enhanced Vegetation Index and the Leaf Area Index

PubMed Central

Wang, Cong; Li, Jing; Wu, Shanlong; Xia, Chuanfu

2017-01-01

Remote-sensing phenology detection can compensate for deficiencies in field observations and has the advantage of capturing the continuous expression of phenology on a large scale. However, there is some variability in the results of remote-sensing phenology detection derived from different vegetation parameters in satellite time-series data. Since the enhanced vegetation index (EVI) and the leaf area index (LAI) are the most widely used vegetation parameters for remote-sensing phenology extraction, this paper aims to assess the differences in phenological information extracted from EVI and LAI time series and to explore whether either index performs well for all vegetation types on a large scale. To this end, a GLASS (Global Land Surface Satellite Product)-LAI-based phenology product (GLP) was generated using the same algorithm as the MODIS (Moderate Resolution Imaging Spectroradiometer)-EVI phenology product (MLCD) over China from 2001 to 2012. The two phenology products were compared in China for different vegetation types and evaluated using ground observations. The results show that the ratio of missing data is 8.3% for the GLP, which is less than the 22.8% for the MLCD. The differences between the GLP and the MLCD become stronger as the latitude decreases, which also vary among different vegetation types. The start of the growing season (SOS) of the GLP is earlier than that of the MLCD in most vegetation types, and the end of the growing season (EOS) of the GLP is generally later than that of the MLCD. Based on ground observations, it can be suggested that the GLP performs better than the MLCD in evergreen needleleaved forests and croplands, while the MLCD performs better than the GLP in shrublands and grasslands. PMID:28867773

Environmental Humidity Regulates Effects of Experimental Warming on Vegetation Index and Biomass Production in an Alpine Meadow of the Northern Tibet

PubMed Central

Fu, Gang; Shen, Zhen Xi

2016-01-01

Uncertainty about responses of vegetation index, aboveground biomass (AGB) and gross primary production (GPP) limits our ability to predict how climatic warming will influence plant growth in alpine regions. A field warming experiment was conducted in an alpine meadow at a low (4313 m), mid- (4513 m) and high elevation (4693 m) in the Northern Tibet since May 2010. Growing season vapor pressure deficit (VPD), soil temperature (Ts) and air temperature (Ta) decreased with increasing elevation, while growing season precipitation, soil moisture (SM), normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), AGB and GPP increased with increasing elevation. The growing season Ta, Ts and VPD in 2015 was greater than that in 2014, while the growing season precipitation, SM, NDVI, SAVI, AGB and GPP in 2015 was lower than that in 2014, respectively. Compared to the mean air temperature and precipitation during the growing season in 1963–2015, it was a warmer and wetter year in 2014 and a warmer and drier year in 2015. Experimental warming increased growing season Ts, Ta,VPD, but decreased growing season SM in 2014–2015 at all the three elevations. Experimental warming only reduced growing season NDVI, SAVI, AGB and GPP at the low elevation in 2015. Growing season NDVI, SAVI, AGB and GPP increased with increasing SM and precipitation, but decreased with increasing VPD, indicating vegetation index and biomass production increased with environmental humidity. The VPD explained more variation of growing season NDVI, SAVI, AGB and GPP compared to Ts, Ta and SM at all the three elevations. Therefore, environmental humidity regulated the effect of experimental warming on vegetation index and biomass production in alpine meadows on the Tibetan Plateau. PMID:27798690

Effectiveness of Vegetation Index Transformation for Land Use Identifying and Mapping in the Area of Oil palm Plantation based on SPOT-6 Imagery (Case Study: PT.Tunggal Perkasa Plantations, Air Molek, Indragiri Hulu)

NASA Astrophysics Data System (ADS)

Setyowati, H. A.; S, S. H. Murti B.; Sukentyas, E. S.

2016-11-01

The reflection of land surface, atmosphere and vegetation conditions affect the reflectance value of the object is recorded on remote sensing image so that it can affect the outcome of information extraction from remote sensing imagery one multispectral classification. This study aims to assess the ability of the transformation of generic vegetation index (Wide Dynamic Range Vegetation Index), the vegetation index transformation that is capable reducing the influence of the atmosphere (Atmospherically Resistant Vegetation Index), and the transformation of vegetation index that is capable of reducing the influence of the background soil (Second Modified Soil Adjusted Vegetation Index) for the identification and mapping of land use in the oil palm plantation area based on SPOT-6 archived on June 13, 2013 from LAPAN. The study area selected oil palm plantations PT. Tunggal Perkasa Plantations, Air Molek, Indragiri Hulu, Riau Province. The method is using the transformation of the vegetation index ARVI, MSAVI2, and WDRVI. Sample selection method used was stratified random sampling. The test method used mapping accuracy of the confusion matrix. The results showed that the best transformation of the vegetation index for the identification and mapping of land use in the plantation area is ARVI transformation with a total of accuracy is 96%. Accuracy of mapping land use settlements 100%, replanting 82.35%, 81.25% young oil palm, old oil palm 99.46%, 100% bush, body of water 100%, and 100% bare-soil.

A short note on calculating the adjusted SAR index

USDA-ARS?s Scientific Manuscript database

A simple algebraic technique is presented for computing the adjusted SAR Index proposed by Suarez (1981). The statistical formula presented in this note facilitates the computation of the adjusted SAR without the use of either a look-up table, custom computer software or the need to compute exact a...

Multiscaling of vegetative indexes from remote sensing images obtained at different spatial resolutions

NASA Astrophysics Data System (ADS)

Alonso, Carmelo; Tarquis, Ana M.; Zuñiga, Ignacio; Benito, Rosa M.

2017-04-01

Vegetation indexes, such as Normalized Difference Vegetation Index (NDVI) and enhanced Vegetation index (EVI), can been used to estimate root zone soil moisture through high resolution remote sensing images. These indexes are based in red (R), near infrared (NIR) and blue (B) wavelengths data. In this work we have studied the scaling properties of both vegetation indexes analyzing the information contained in two satellite data: Landsat-7 and Ikonos. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends possible data archives from present time to over several decades back. For this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. To study the influence of the spatial resolution the vegetation indexes map estimated with Ikonos-2 coded in 8 bits, with a resolution of 4m, have been compared through a multifractal analysis with the ones obtained with Lansat-7 8 bits, of 30 m. resolution, on the same area of study. The scaling behaviour of NDVI and EVI presents several differences that will be discussed based on the multifractal parameters extracted from the analysis. REFERENCES Alonso, C., Tarquis, A. M., Benito, R. M. and Zuñiga, I. Correlation scaling properties between soil moisture and vegetation indices. Geophysical Research Abstracts, 11, EGU2009-13932, 2009. Alonso, C., Tarquis, A. M. and Benito, R. M. Comparison of fractal dimensions based on segmented NDVI fields obtained from different remote sensors. Geophysical Research Abstracts, 14, EGU2012-14342, 2012. Escribano Rodriguez, J., Alonso, C., Tarquis, A.M., Benito, R.M. and Hernandez Diaz-Ambrona, C. Comparison of NDVI fields obtained from different remote sensors. Geophysical Research Abstracts,15, EGU2013-14153, 2013. Lovejoy, S., Tarquis, A., Gaonac'h, H. and Schertzer, D. Single and multiscale remote sensing

Variability of the seasonally integrated normalized difference vegetation index across the north slope of Alaska in the 1990s

USGS Publications Warehouse

Stow, D.; Daeschner, Scott; Hope, A.; Douglas, David C.; Petersen, A.; Myneni, Ranga B.; Zhou, L.; Oechel, W.

2003-01-01

The interannual variability and trend of above-ground photosynthetic activity of Arctic tundra vegetation in the 1990s is examined for the north slope region of Alaska, based on the seasonally integrated normalized difference vegetation index (SINDVI) derived from local area coverage (LAC) National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data. Smaller SINDVI values occurred during the three years (1992-1994) following the volcanic eruption of Mt Pinatubo. Even after implementing corrections for this stratospheric aerosol effect and adjusting for changes in radiometric calibration coefficients, an apparent increasing trend of SINDVI in the 1990s is evident for the entire north slope. The most pronounced increase was observed for the foothills physiographical province.

Application of Hyperspectral Vegetation Indices to Detect Variations in High Leaf Area Index Temperate Shrub Thicket Canopies

DTIC Science & Technology

2011-01-01

sensing an attractive technique for estimating LAI. Many vegetation indices, such as Normalized Difference Vegetation Index ( NDVI ), tend to saturate at...little or no improvement over NDVI . Furthermore, indirect ground-sampling techniques often used to evaluate the potential of vegetation indices also...landscapes makes remote sensing an attractive technique for estimating LAI. Many vegetation indices, such as Normalized Difference Vegetation Index ( NDVI

Development of JPSS VIIRS Global Gridded Vegetation Index products for NOAA NCEP Environmental Modeling Systems

NASA Astrophysics Data System (ADS)

Vargas, Marco; Miura, Tomoaki; Csiszar, Ivan; Zheng, Weizhong; Wu, Yihua; Ek, Michael

2017-04-01

The first Joint Polar Satellite System (JPSS) mission, the Suomi National Polar-orbiting Partnership (S-NPP) satellite, was successfully launched in October, 2011, and it will be followed by JPSS-1, slated for launch in 2017. JPSS provides operational continuity of satellite-based observations and products for NOAA's Polar Operational Environmental Satellites (POES). Vegetation products derived from satellite measurements are used for weather forecasting, land modeling, climate research, and monitoring the environment including drought, the health of ecosystems, crop monitoring and forest fires. The operationally produced S-NPP VIIRS Vegetation Index (VI) Environmental Data Record (EDR) includes two vegetation indices: the Top of the Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI), and the Top of the Canopy (TOC) Enhanced Vegetation Index (EVI). For JPSS-1, the S-NPP Vegetation Index EDR algorithm has been updated to include the TOC NDV. The current JPSS operational VI products are generated in granule style at 375 meter resolution at nadir, but these products in granule format cannot be ingested into NOAA operational monitoring and decision making systems. For that reason, the NOAA JPSS Land Team is developing a new global gridded Vegetation Index (VI) product suite for operational use by the NOAA National Centers for Environmental Prediction (NCEP). The new global gridded VIs will be used in the Multi-Physics (MP) version of the Noah land surface model (Noah-MP) in NCEP NOAA Environmental Modeling System (NEMS) for plant growth and data assimilation and to describe vegetation coverage and density in order to model the correct surface energy partition. The new VI 4km resolution global gridded products (TOA NDVI, TOC NDVI and TOC EVI) are being designed to meet the needs of directly ingesting vegetation index variables without the need to develop local gridding and compositing procedures. These VI products will be consistent with the already

Non-Lambertian effects on remote sensing of surface reflectance and vegetation index

NASA Technical Reports Server (NTRS)

Lee, T. Y.; Kaufman, Y. J.

1986-01-01

This paper discusses the effects of non-Lambertian reflection from a homogeneous surface on remote sensing of the surface reflectance and vegetation index from a satellite. Remote measurement of the surface characteristics is perturbed by atmospheric scattering of sun light. This scattering tends to smooth the angular dependence of non-Lambertian surface reflectances, an effect that is not present in the case of Lambertian surfaces. This effect is calculated to test the validity of a Lambertian assumption used in remote sensing. For the three types of vegetations considered in this study, the assumption of Lambertian surface can be used satisfactorily in the derivation of surface reflectance from remotely measured radiance for a view angle outside the backscattering region. Within the backscattering region, however, the use of the assumption can result in a considerable error in the derived surface reflectance. Accuracy also deteriorates with increasing solar zenith angle. The angular distribution of the surface reflectance derived from remote measurements is smoother than that at the surface. The effect of surface non-Lambertianity on remote sensing of vegetation index is very weak. Since the effect is similiar in the visible and near infrared part of the solar spectrum for the vegetations treated in this study, it is canceled in deriving the vegetation index. The effect of the diffuse skylight on surface reflectance measurements at ground level is also discussed.

Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico

USGS Publications Warehouse

Dye, Dennis G.; Middleton, Barry R.; Vogel, John M.; Wu, Zhuoting; Velasco, Miguel G.

2016-01-01

We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C4) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI2) data from Landsat to develop the NDPI, and MSAVI2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI2 and summer maximum MSAVI2), and two simple, conventional VI metrics (summer average MSAVI2, summer maximum MSAVI2). The NDPI in a scaled form (NDPIs) performed best in predicting variation in perennial C4 grass cover as estimated from landscape photographs at 92 sites (R2 = 0.76, p < 0.001), indicating improvement over the alternate DVP metric (R2 = 0.73, p < 0.001) and substantial improvement over the two conventional VI metrics (R2 = 0.62 and 0.56, p < 0.001). The results suggest DVP-based methods, and the NDPI in particular, can be effective for subpixel discrimination and mapping of exposed perennial C4 grass cover within mixed-composition landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

Stomatal conductance, canopy temperature, and leaf area index estimation using remote sensing and OBIA techniques

Treesearch

S. Panda; D.M. Amatya; G. Hoogenboom

2014-01-01

Remotely sensed images including LANDSAT, SPOT, NAIP orthoimagery, and LiDAR and relevant processing tools can be used to predict plant stomatal conductance (gs), leaf area index (LAI), and canopy temperature, vegetation density, albedo, and soil moisture using vegetation indices like normalized difference vegetation index (NDVI) or soil adjusted...

Mapping swamp timothy (Cripsis schenoides) seed productivity using spectral values and vegetation indices in managed wetlands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rahilly, P.J.A.; Li, D.; Guo, Q.

2010-01-15

This work examines the potential to predict the seed productivity of a key wetland plant species using spectral reflectance values and spectral vegetation indices. Specifically, the seed productivity of swamp timothy (Cripsis schenoides) was investigated in two wetland ponds, managed for waterfowl habitat, in California's San Joaquin Valley. Spectral reflectance values were obtained and associated spectral vegetation indices (SVI) calculated from two sets of high resolution aerial images (May 11, 2006 and June 9, 2006) and were compared to the collected vegetation data. Vegetation data were collected and analyzed from 156 plots for total aboveground biomass, total aboveground swamp timothymore » biomass, and total swamp timothy seed biomass. The SVI investigated included the Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Transformed Soil Adjusted Vegetation Index (TSAVI), Modified Soil Adjusted Vegetation Index (MSAVI), and Global Environment Monitoring Index (GEMI). We evaluated the correlation of the various SVI with in situ vegetation measurements for linear, quadratic, exponential and power functions. In all cases, the June image provided better predictive capacity relative to May, a result that underscores the importance of timing imagery to coincide with more favorable vegetation maturity. The north pond with the June image using SR and the exponential function (R{sup 2}=0.603) proved to be the best predictor of swamp timothy seed productivity. The June image for the south pond was less predictive, with TSAVI and the exponential function providing the best correlation (R{sup 2}=0.448). This result was attributed to insufficient vegetal cover in the south pond (or a higher percentage of bare soil) due to poor drainage conditions which resulted in a delay in swamp timothy germination. The results of this work suggest that spectral reflectance can be used to estimate seed productivity in managed

On the terminology of the spectral vegetation index (NIR – SWIR)/(NIR + SWIR)

USGS Publications Warehouse

Ji, Lel; Zhang, Li; Wylie, Bruce K.; Rover, Jennifer R.

2011-01-01

The spectral vegetation index (ρNIR – ρSWIR)/(ρNIR + ρSWIR), where ρNIR and ρSWIR are the near-infrared (NIR) and shortwave-infrared (SWIR) reflectances, respectively, has been widely used to indicate vegetation moisture condition. This index has multiple names in the literature, including infrared index (II), normalized difference infrared index (NDII), normalized difference water index (NDWI), normalized difference moisture index (NDMI), land surface water index (LSWI), and normalized burn ratio (NBR), etc. After reviewing each term’s definition, associated sensors, and channel specifications, we found that the index consists of three variants, differing only in the SWIR region (1.2–1.3 µm, 1.55–1.75 µm, or 2.05–2.45 µm). Thus, three terms are sufficient to represent these three SWIR variants; other names are redundant and therefore unnecessary. Considering the spectral representativeness, the term’s popularity, and the “rule of priority” in scientific nomenclature, NDWI, NDII, and NBR, each corresponding to the three SWIR regions, are more preferable terms.

Growing Degree Vegetation Production Index (GDVPI): A Novel and Data-Driven Approach to Delimit Season Cycles

NASA Astrophysics Data System (ADS)

Graham, W. D.; Spruce, J.; Ross, K. W.; Gasser, J.; Grulke, N.

2014-12-01

Growing Degree Vegetation Production Index (GDVPI) is a parametric approach to delimiting vegetation seasonal growth and decline cycles using incremental growing degree days (GDD), and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) 8-day composite cumulative integral data. We obtain a specific location's daily minimum and maximum temperatures from the nearest National Oceanic and Atmospheric Administration (NOAA) weather stations posted on the National Climate Data Center (NCDC) Climate Data Online (CDO) archive and compute GDD. The date range for this study is January 1, 2000 through December 31, 2012. We employ a novel process, a repeating logistic product (RLP), to compensate for short-term weather variability and data drops from the recording stations and fit a curve to the median daily GDD values, adjusting for asymmetry, amplitude, and phase shift that minimize the sum of squared errors when comparing the observed and predicted GDD. The resulting curve, here referred to as the surrogate GDD, is the time-temperature phasing parameter used to convert Cartesian NDVI values into polar coordinate pairs, multiplying the NDVI values as the radial by the cosine and sine of the surrogate GDD as the angular. Depending on the vegetation type and the original NDVI curve, the polar NDVI curve may be nearly circular, kidney-shaped, or pear-shaped in the case of conifers, deciduous, or agriculture, respectively. We examine the points of tangency about the polar coordinate NDVI curve, identifying values of 1, 0, -1, or infinity, as each of these represent natural inflection points. Lines connecting the origin to each tangent point illustrate and quantify the parametrically segmentation of the growing season based on the GDD and NDVI ostensible dependency. Furthermore, the area contained by each segment represents the apparent vegetation production. A particular benefit is that the inflection points are determined

Estimating fractional vegetation cover and the vegetation index of bare soil and highly dense vegetation with a physically based method

NASA Astrophysics Data System (ADS)

Song, Wanjuan; Mu, Xihan; Ruan, Gaiyan; Gao, Zhan; Li, Linyuan; Yan, Guangjian

2017-06-01

Normalized difference vegetation index (NDVI) of highly dense vegetation (NDVIv) and bare soil (NDVIs), identified as the key parameters for Fractional Vegetation Cover (FVC) estimation, are usually obtained with empirical statistical methods However, it is often difficult to obtain reasonable values of NDVIv and NDVIs at a coarse resolution (e.g., 1 km), or in arid, semiarid, and evergreen areas. The uncertainty of estimated NDVIs and NDVIv can cause substantial errors in FVC estimations when a simple linear mixture model is used. To address this problem, this paper proposes a physically based method. The leaf area index (LAI) and directional NDVI are introduced in a gap fraction model and a linear mixture model for FVC estimation to calculate NDVIv and NDVIs. The model incorporates the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) model parameters product (MCD43B1) and LAI product, which are convenient to acquire. Two types of evaluation experiments are designed 1) with data simulated by a canopy radiative transfer model and 2) with satellite observations. The root-mean-square deviation (RMSD) for simulated data is less than 0.117, depending on the type of noise added on the data. In the real data experiment, the RMSD for cropland is 0.127, for grassland is 0.075, and for forest is 0.107. The experimental areas respectively lack fully vegetated and non-vegetated pixels at 1 km resolution. Consequently, a relatively large uncertainty is found while using the statistical methods and the RMSD ranges from 0.110 to 0.363 based on the real data. The proposed method is convenient to produce NDVIv and NDVIs maps for FVC estimation on regional and global scales.

[Quantitative relationships between hyper-spectral vegetation indices and leaf area index of rice].

PubMed

Tian, Yong-Chao; Yang, Jie; Yao, Xia; Zhu, Yan; Cao, Wei-Xing

2009-07-01

Based on field experiments with different rice varieties under different nitrogen application levels, the quantitative relationships of rice leaf area index (LAI) with canopy hyper-spectral parameters at different growth stages were analyzed. Rice LAI had good relationships with several hyper-spectral vegetation indices, the correlation coefficient being the highest with DI (difference index), followed by with RI (ratio index), and NI (normalized index), based on the spectral reflectance or the first derivative spectra. The two best spectral indices for estimating LAI were the difference index DI (854, 760) (based on two spectral bands of 850 nm and 760 nm) and the difference index DI (D676, D778) (based on two first derivative bands of 676 nm and 778 nm). In general, the hyper-spectral vegetation indices based on spectral reflectance performed better than the spectral indices based on the first derivative spectra. The tests with independent dataset suggested that the rice LAI monitoring models with difference index DI (854,760) as the variable could give an accurate LAI estimation, being available for estimation of rice LAI.

RGB picture vegetation indexes for High-Throughput Phenotyping Platforms (HTPPs)

NASA Astrophysics Data System (ADS)

Kefauver, Shawn C.; El-Haddad, George; Vergara-Diaz, Omar; Araus, José Luis

2015-10-01

Extreme and abnormal weather events, as well as the more gradual meteorological changes associated with climate change, often coincide with not only increased abiotic risks (such as increases in temperature and decreases in precipitation), but also increased biotic risks due to environmental conditions that favor the rapid spread of crop pests and diseases. Durum wheat is by extension the most cultivated cereal in the south and east margins of the Mediterranean Basin. It is of strategic importance for Mediterranean agriculture to develop new varieties of durum wheat with greater production potential, better adaptation to increasingly adverse environmental conditions (drought) and better grain quality. Similarly, maize is the top staple crop for low-income populations in Sub-Saharan Africa and is currently suffering from the appearance of new diseases, which, together with increased abiotic stresses from climate change, are challenging the very sustainability of African societies. Current constraints in field phenotyping remain a major bottleneck for future breeding advances, but RGB-based High-Throughput Phenotyping Platforms (HTPPs) have shown promise for rapidly developing both disease-resistant and weather-resilient crops. RGB cameras have proven costeffective in studies assessing the effect of abiotic stresses, but have yet to be fully exploited to phenotype disease resistance. Recent analyses of durum wheat in Spain have shown RGB vegetation indexes to outperform multispectral indexes such as NDVI consistently in disease and yield prediction. Towards HTTP development for breeding maize disease resistance, some of the same RGB picture vegetation indexes outperformed NDVI (Normalized Difference Vegetation Index), with R2 values up to 0.65, compared to 0.56 for NDVI. . Specifically, hue, a*, u*, and Green Area (GA), as produced by FIJI and BreedPix open source software, performed similar to or better than NDVI in predicting yield and disease severity conditions

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 1; Theory

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Schull, Mitchell A.; Samanta, Arindam; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramakrishna R.; Knyazikhin, Yuri; Myneni, Ranga B.

2008-01-01

The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher

Implied adjusted volatility functions: Empirical evidence from Australian index option market

NASA Astrophysics Data System (ADS)

Harun, Hanani Farhah; Hafizah, Mimi

2015-02-01

This study aims to investigate the implied adjusted volatility functions using the different Leland option pricing models and to assess whether the use of the specified implied adjusted volatility function can lead to an improvement in option valuation accuracy. The implied adjusted volatility is investigated in the context of Standard and Poor/Australian Stock Exchange (S&P/ASX) 200 index options over the course of 2001-2010, which covers the global financial crisis in the mid-2007 until the end of 2008. Both in- and out-of-sample resulted in approximately similar pricing error along the different Leland models. Results indicate that symmetric and asymmetric models of both moneyness ratio and logarithmic transformation of moneyness provide the overall best result in both during and post-crisis periods. We find that in the different period of interval (pre-, during and post-crisis) is subject to a different implied adjusted volatility function which best explains the index options. Hence, it is tremendously important to identify the intervals beforehand in investigating the implied adjusted volatility function.

Normalized difference vegetation index (NDVI) variation among cultivars and environments

USDA-ARS?s Scientific Manuscript database

Although Nitrogen (N) is an essential nutrient for crop production, large preplant applications of fertilizer N can result in off-field loss that causes environmental concerns. Canopy reflectance is being investigated for use in variable rate (VR) N management. Normalized difference vegetation index...

Modulation Index Adjustment for Recovery of Pure Wavelength Modulation Spectroscopy Second Harmonic Signal Waveforms.

PubMed

Wei, Wei; Chang, Jun; Wang, Qiang; Qin, Zengguang

2017-01-15

A new technique of modulation index adjustment for pure wavelength modulation spectroscopy second harmonic signal waveforms recovery is presented. As the modulation index is a key parameter in determining the exact form of the signals generated by the technique of wavelength modulation spectroscopy, the method of modulation index adjustment is applied to recover the second harmonic signal with wavelength modulation spectroscopy. By comparing the measured profile with the theoretical profile by calculation, the relationship between the modulation index and average quantities of the scanning wavelength can be obtained. Furthermore, when the relationship is applied in the experimental setup by point-by-point modulation index modification for gas detection, the results show good agreement with the theoretical profile and signal waveform distortion (such as the amplitude modulation effect caused by diode laser) can be suppressed. Besides, the method of modulation index adjustment can be used in many other aspects which involve profile improvement. In practical applications, when the amplitude modulation effect can be neglected and the stability of the detection system is limited by the sampling rate of analog-to-digital, modulation index adjustment can be used to improve detection into softer inflection points and solve the insufficient sampling problem. As a result, measurement stability is improved by 40%.

Modulation Index Adjustment for Recovery of Pure Wavelength Modulation Spectroscopy Second Harmonic Signal Waveforms

PubMed Central

Wei, Wei; Chang, Jun; Wang, Qiang; Qin, Zengguang

2017-01-01

A new technique of modulation index adjustment for pure wavelength modulation spectroscopy second harmonic signal waveforms recovery is presented. As the modulation index is a key parameter in determining the exact form of the signals generated by the technique of wavelength modulation spectroscopy, the method of modulation index adjustment is applied to recover the second harmonic signal with wavelength modulation spectroscopy. By comparing the measured profile with the theoretical profile by calculation, the relationship between the modulation index and average quantities of the scanning wavelength can be obtained. Furthermore, when the relationship is applied in the experimental setup by point-by-point modulation index modification for gas detection, the results show good agreement with the theoretical profile and signal waveform distortion (such as the amplitude modulation effect caused by diode laser) can be suppressed. Besides, the method of modulation index adjustment can be used in many other aspects which involve profile improvement. In practical applications, when the amplitude modulation effect can be neglected and the stability of the detection system is limited by the sampling rate of analog-to-digital, modulation index adjustment can be used to improve detection into softer inflection points and solve the insufficient sampling problem. As a result, measurement stability is improved by 40%. PMID:28098842

A Candidate Vegetation Index of Biological Integrity Based on Species Dominance and Habitat Fidelity

USGS Publications Warehouse

Gara, Brian D; Stapanian, Martin A.

2015-01-01

Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas of the USA and are used in some states to make critical management decisions. An underlying concept of all VIBIs is that they respond negatively to disturbance. The Ohio VIBI (OVIBI) is calculated from 10 metrics, which are different for each wetland vegetation class. We present a candidate vegetation index of biotic integrity based on floristic quality (VIBI-FQ) that requires only two metrics to calculate an overall score regardless of vegetation class. These metrics focus equally on the critical ecosystem elements of diversity and dominance as related to a species’ degree of fidelity to habitat requirements. The indices were highly correlated but varied among vegetation classes. Both indices responded negatively with a published index of wetland disturbance in 261 Ohio wetlands. Unlike VIBI-FQ, however, errors in classifying wetland vegetation may lead to errors in calculating OVIBI scores. This is especially critical when assessing the ecological condition of rapidly developing ecosystems typically associated with wetland restoration and creation projects. Compared to OVIBI, the VIBI-FQ requires less field work, is much simpler to calculate and interpret, and can potentially be applied to all habitat types. This candidate index, which has been “standardized” across habitats, would make it easier to prioritize funding because it would score the “best” and “worst” of all habitats appropriately and allow for objective comparison across different vegetation classes.

Vegetation index anomaly response to varying lengths of drought across vegetation and climatic gradients in Hawaii

NASA Astrophysics Data System (ADS)

Lucas, M.; Miura, T.; Trauernicht, C.; Frazier, A. G.

2017-12-01

A drought which results in prolonged and extended deficit in naturally available water supply and creates multiple stresses across ecosystems is classified as an ecological drought. Detecting and understanding the dynamics and response of such droughts in tropical systems, specifically across various vegetation and climatic gradients is fairly undetermined, yet increasingly important for better understandings of the ecological effects of drought. To understanding the link between what lengths and intensities of known meteorological drought triggers detectable ecological vegetation responses, a landscape scale regression analysis evaluating the response (slope) and relationship strength (R-squared) of several cumulative SPI (standard precipitation index) lengths(1, 3, 6, 12, 18, 24, 36, 48, and 60 month), to various satellite derived monthly vegetation indices anomalies (NDVI, EVI, EVI2, and LSWI) was performed across a matrix of dominant vegetation covers (grassland, shrubland, and forest) and climatic moisture zones (arid, dry, mesic, and wet). The nine different SPI lags across these climactic and vegetation gradients was suggest that stronger relationships and steeper slopes were found in dryer climates (across all vegetation covers) and finer vegetation types (across all moisture zones). Overall NDVI, EVI and EVI2 showed the best utility in these dryer climatic zones across all vegetation types. Within arid and dry areas "best" fits showed increasing lengths of cumulative SPI were with increasing vegetation coarseness respectively. Overall these findings suggest that rainfall driven drought may have a stronger impact on the ecological condition of vegetation in water limited systems with finer vegetation types ecologically responding more rapidly to meteorological drought events than coarser woody vegetation systems. These results suggest that previously and newly documented trends of decreasing rainfall and increasing drought in Hawaiian drylands may have

Adjusting Spectral Indices for Spectral Response Function Differences of Very High Spatial Resolution Sensors Simulated from Field Spectra

PubMed Central

Cundill, Sharon L.; van der Werff, Harald M. A.; van der Meijde, Mark

2015-01-01

The use of data from multiple sensors is often required to ensure data coverage and continuity, but differences in the spectral characteristics of sensors result in spectral index values being different. This study investigates spectral response function effects on 48 spectral indices for cultivated grasslands using simulated data of 10 very high spatial resolution sensors, convolved from field reflectance spectra of a grass covered dike (with varying vegetation condition). Index values for 48 indices were calculated for original narrow-band spectra and convolved data sets, and then compared. The indices Difference Vegetation Index (DVI), Global Environmental Monitoring Index (GEMI), Enhanced Vegetation Index (EVI), Modified Soil-Adjusted Vegetation Index (MSAVI2) and Soil-Adjusted Vegetation Index (SAVI), which include the difference between the near-infrared and red bands, have values most similar to those of the original spectra across all 10 sensors (1:1 line mean 1:1R2 > 0.960 and linear trend mean ccR2 > 0.997). Additionally, relationships between the indices’ values and two quality indicators for grass covered dikes were compared to those of the original spectra. For the soil moisture indicator, indices that ratio bands performed better across sensors than those that difference bands, while for the dike cover quality indicator, both the choice of bands and their formulation are important. PMID:25781511

MODIS normalized difference vegetation index (NDVI) and vegetation phenology dynamics in the Inner Mongolia grassland

NASA Astrophysics Data System (ADS)

Gong, Z.; Kawamura, K.; Ishikawa, N.; Goto, M.; Wulan, T.; Alateng, D.; Yin, T.; Ito, Y.

2015-11-01

The Inner Mongolia grassland, one of the most important grazing regions in China, has long been threatened by land degradation and desertification, mainly due to overgrazing. To understand vegetation responses over the last decade, this study evaluated trends in vegetation cover and phenology dynamics in the Inner Mongolia grassland by applying a normalized difference vegetation index (NDVI) time series obtained by the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) during 2002-2014. The results showed that the cumulative annual NDVI increased to over 77.10 % in the permanent grassland region (2002-2014). The mean value of the total change showed that the start of season (SOS) date and the peak vegetation productivity date of the season (POS) had advanced by 5.79 and 2.43 days, respectively. The end of season (EOS) was delayed by 5.07 days. These changes lengthened the season by 10.86 days. Our results also confirmed that grassland changes are closely related to spring precipitation and increasing temperature at the early growing period because of global warming. Overall, productivity in the Inner Mongolia Autonomous Region tends to increase, but in some grassland areas with grazing, land degradation is ongoing.

Predicting Vegetation Condition from ASCAT Soil Water Index over Southwest India

NASA Astrophysics Data System (ADS)

Pfeil, Isabella Maria; Hochstöger, Simon; Amarnath, Giriraj; Pani, Peejush; Enenkel, Markus; Wagner, Wolfgang

2017-04-01

In India, extreme water scarcity events are expected to occur on average every five years. Record-breaking droughts affecting millions of human beings and livestock are common. If the south-west monsoon (summer monsoon) is delayed or brings less rainfall than expected, a season's harvest can be destroyed despite optimal farm management, leading to, in the worst case, life-threatening circumstances for a large number of farmers. Therefore, the monitoring of key drought indicators, such as the healthiness of the vegetation, and subsequent early warning is crucial. The aim of this work is to predict vegetation state from earth observation data instead of relying on models which need a lot of input data, increasing the complexity of error propagation, or seasonal forecasts, that are often too uncertain to be used as a regression component for a vegetation parameter. While precipitation is the main water supply for large parts of India's agricultural areas, vegetation datasets such as the Normalized Difference Vegetation Index (NDVI) provide reliable estimates of vegetation greenness that can be related to vegetation health. Satellite-derived soil moisture represents the missing link between a deficit in rainfall and the response of vegetation. In particular the water available in the root zone plays an important role for near-future vegetation health. Exploiting the added-value of root zone soil moisture is therefore crucial, and its use in vegetation studies presents an added value for drought analyses and decision-support. The soil water index (SWI) dataset derived from the Advanced Scatterometer (ASCAT) on board the Metop satellites represents the water content that is available in the root zone. This dataset shows a strong correlation with NDVI data obtained from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is exploited in this study. A linear regression function is fit to the multi-year SWI and NDVI dataset with a temporal

5 CFR 591.224 - How does OPM adjust price indexes between surveys?

Code of Federal Regulations, 2011 CFR

2011-01-01

... price indexes between the triennial surveys in each COLA area that is not surveyed in that year. To do this, OPM uses the annual or biennial change in the Consumer Price Index (CPI) for the COLA area... Islands, OPM will adjust as warranted the price indexes and COLA rates for Puerto Rico, the U.S. Virgin...

5 CFR 591.224 - How does OPM adjust price indexes between surveys?

Code of Federal Regulations, 2010 CFR

2010-01-01

... price indexes between the triennial surveys in each COLA area that is not surveyed in that year. To do this, OPM uses the annual or biennial change in the Consumer Price Index (CPI) for the COLA area... Islands, OPM will adjust as warranted the price indexes and COLA rates for Puerto Rico, the U.S. Virgin...

5 CFR 591.224 - How does OPM adjust price indexes between surveys?

Code of Federal Regulations, 2014 CFR

2014-01-01

... price indexes between the triennial surveys in each COLA area that is not surveyed in that year. To do this, OPM uses the annual or biennial change in the Consumer Price Index (CPI) for the COLA area... Islands, OPM will adjust as warranted the price indexes and COLA rates for Puerto Rico, the U.S. Virgin...

5 CFR 591.224 - How does OPM adjust price indexes between surveys?

Code of Federal Regulations, 2012 CFR

2012-01-01

... price indexes between the triennial surveys in each COLA area that is not surveyed in that year. To do this, OPM uses the annual or biennial change in the Consumer Price Index (CPI) for the COLA area... Islands, OPM will adjust as warranted the price indexes and COLA rates for Puerto Rico, the U.S. Virgin...

5 CFR 591.224 - How does OPM adjust price indexes between surveys?

Code of Federal Regulations, 2013 CFR

2013-01-01

... price indexes between the triennial surveys in each COLA area that is not surveyed in that year. To do this, OPM uses the annual or biennial change in the Consumer Price Index (CPI) for the COLA area... Islands, OPM will adjust as warranted the price indexes and COLA rates for Puerto Rico, the U.S. Virgin...

A new casemix adjustment index for hospital mortality among patients with congestive heart failure.

PubMed

Polanczyk, C A; Rohde, L E; Philbin, E A; Di Salvo, T G

1998-10-01

Comparative analysis of hospital outcomes requires reliable adjustment for casemix. Although congestive heart failure is one of the most common indications for hospitalization, congestive heart failure casemix adjustment has not been widely studied. The purposes of this study were (1) to describe and validate a new congestive heart failure-specific casemix adjustment index to predict in-hospital mortality and (2) to compare its performance to the Charlson comorbidity index. Data from all 4,608 admissions to the Massachusetts General Hospital from January 1990 to July 1996 with a principal ICD-9-CM discharge diagnosis of congestive heart failure were evaluated. Massachusetts General Hospital patients were randomly divided in a derivation and a validation set. By logistic regression, odds ratios for in-hospital death were computed and weights were assigned to construct a new predictive index in the derivation set. The performance of the index was tested in an internal Massachusetts General Hospital validation set and in a non-Massachusetts General Hospital external validation set incorporating data from all 1995 New York state hospital discharges with a primary discharge diagnosis of congestive heart failure. Overall in-hospital mortality was 6.4%. Based on the new index, patients were assigned to six categories with incrementally increasing hospital mortality rates ranging from 0.5% to 31%. By logistic regression, "c" statistics of the congestive heart failure-specific index (0.83 and 0.78, derivation and validation set) were significantly superior to the Charlson index (0.66). Similar incrementally increasing hospital mortality rates were observed in the New York database with the congestive heart failure-specific index ("c" statistics 0.75). In an administrative database, this congestive heart failure-specific index may be a more adequate casemix adjustment tool to predict hospital mortality in patients hospitalized for congestive heart failure.

Development Of Index To Assess Drought Conditions Using Geospatial Data A Case Study Of Jaisalmer District, Rajasthan, India

NASA Astrophysics Data System (ADS)

Chhajer, Vaidehi; Prabhakar, Sumati; Rama Chandra Prasad, P.

2015-12-01

The Jaisalmer district of Rajasthan province of India was known to suffer with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. However flood-like situation prevails in the drought prone Jaisalmer district of Rajasthan as torrential rains are seen to affect the region in the recent years. In the present study, detailed analysis of meteorological, hydrological and satellite data of the Jaisalmer district has been carried out for the years 2006-2008. Standardized Precipitation Index (SPI), Consecutive Dry Days (CDD) and Effective Drought Index (EDI) have been used to quantify the precipitation deficit. Standardized Water-Level Index (SWI) has been developed to assess ground-water recharge-deficit. Vegetative drought indices like Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Normalized Difference Vegetation Index (NDVI) and Modified Soil-Adjusted Vegetation Index 2 have been calculated. We also introduce two new indices Soil based Vegetation Condition Index (SVCI) and Composite Drought Index (CDI) specifically for regions like Jaisalmer where aridity in soil and affects vegetation and water-level.

5 CFR 591.228 - How does OPM convert the price index plus adjustment factor to a COLA rate?

Code of Federal Regulations, 2013 CFR

2013-01-01

... adjustment factor to a COLA rate? 591.228 Section 591.228 Administrative Personnel OFFICE OF PERSONNEL... adjustment factor to a COLA rate? (a) OPM converts the price index plus the adjustment factor to a COLA rate as shown in the following table: Price index plus adjustment factor COLA rate subject to paragraph (b...

5 CFR 591.228 - How does OPM convert the price index plus adjustment factor to a COLA rate?

Code of Federal Regulations, 2012 CFR

2012-01-01

... adjustment factor to a COLA rate? 591.228 Section 591.228 Administrative Personnel OFFICE OF PERSONNEL... adjustment factor to a COLA rate? (a) OPM converts the price index plus the adjustment factor to a COLA rate as shown in the following table: Price index plus adjustment factor COLA rate subject to paragraph (b...

5 CFR 591.228 - How does OPM convert the price index plus adjustment factor to a COLA rate?

Code of Federal Regulations, 2011 CFR

2011-01-01

... adjustment factor to a COLA rate? 591.228 Section 591.228 Administrative Personnel OFFICE OF PERSONNEL... adjustment factor to a COLA rate? (a) OPM converts the price index plus the adjustment factor to a COLA rate as shown in the following table: Price index plus adjustment factor COLA rate subject to paragraph (b...

5 CFR 591.228 - How does OPM convert the price index plus adjustment factor to a COLA rate?

Code of Federal Regulations, 2014 CFR

2014-01-01

... adjustment factor to a COLA rate? 591.228 Section 591.228 Administrative Personnel OFFICE OF PERSONNEL... adjustment factor to a COLA rate? (a) OPM converts the price index plus the adjustment factor to a COLA rate as shown in the following table: Price index plus adjustment factor COLA rate subject to paragraph (b...

A Rapidly Prototyped Vegetation Dryness Index Developed for Wildfire Risk Assessment at Stennis Space Center

NASA Technical Reports Server (NTRS)

Ross, Kenton; Graham, William D.; Prados, Donald; Spruce, Joseph

2006-01-01

A remote sensing index was developed to allow improved monitoring of vegetation dryness conditions on a regional basis. This remote sensing index was rapidly prototyped at Stennis Space Center in response to drought conditions in the local area in spring 2006.

Relating seasonal patterns of the AVHRR vegetation index to simulated photosynthesis and transpiration of forests in different climates

NASA Technical Reports Server (NTRS)

Running, Steven W.; Nemani, Ramakrishna R.

1988-01-01

Weekly AVHRR Normalized Difference Vegetation Index (NDVI) values for 1983-1984 for seven sites of diverse climate in North America were correlated with results of an ecosystem simulation model of a hypothetical forest stand for the corresponding period at each site. The tendency of raw NDVI data to overpredict photosynthesis and transpiration on water limited sites was shown to be partially corrected by using an aridity index of annual radiation/annual precipitation. The results suggest that estimates of vegetation productivity using the global vegetation index are only accurate as annual integrations, unless unsubsampled local area coverage NDVI data can be tested against forest photosynthesis, transpiration and aboveground net primary production data measured at shorter time intervals.

Diet and endometrial cancer: a focus on the role of fruit and vegetable intake, Mediterranean diet and dietary inflammatory index in the endometrial cancer risk.

PubMed

Ricceri, Fulvio; Giraudo, Maria Teresa; Fasanelli, Francesca; Milanese, Dario; Sciannameo, Veronica; Fiorini, Laura; Sacerdote, Carlotta

2017-11-13

Endometrial cancer is the fourth most common cancer in European women. The major risk factors for endometrial cancer are related to the exposure of endometrium to estrogens not opposed to progestogens, that can lead to a chronic endometrial inflammation. Diet may play a role in cancer risk by modulating chronic inflammation. In the framework of a case-control study, we recruited 297 women with newly diagnosed endometrial cancer and 307 controls from Northern Italy. Using logistic regression, we investigated the role of fruit and vegetable intake, adherence to the Mediterranean diet (MD), and the dietary inflammatory index (DII) in endometrial cancer risk. Women in the highest quintile of vegetable intake had a statistically significantly lower endometrial cancer risk (adjusted OR 5th quintile vs 1st quintile: 0.34, 95% CI 0.17-0.68). Women with high adherence to the MD had a risk of endometrial cancer that was about half that of women with low adherence to the MD (adjusted OR: 0.51, 95% CI 0.39-0.86). A protective effect was detected for all the lower quintiles of DII, with the highest protective effect seen for the lowest quintile (adjusted OR 5th quintile vs 1st quintile: 3.28, 95% CI 1.30-8.26). These results suggest that high vegetable intake, adherence to the MD, and a low DII are related to a lower endometrial cancer risk, with several putative connected biological mechanisms that strengthen the biological plausibility of this association.

NDVI saturation adjustment: a new approach for improving cropland performance estimates in the Greater Platte River Basin, USA

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.; Howard, Daniel M.; Phuyal, Khem P.; Ji, Lei

2013-01-01

In this study, we developed a new approach that adjusted normalized difference vegetation index (NDVI) pixel values that were near saturation to better characterize the cropland performance (CP) in the Greater Platte River Basin (GPRB), USA. The relationship between NDVI and the ratio vegetation index (RVI) at high NDVI values was investigated, and an empirical equation for estimating saturation-adjusted NDVI (NDVIsat_adjust) based on RVI was developed. A 10-year (2000–2009) NDVIsat_adjust data set was developed using 250-m 7-day composite historical eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. The growing season averaged NDVI (GSN), which is a proxy for ecosystem performance, was estimated and long-term NDVI non-saturation- and saturation-adjusted cropland performance (CPnon_sat_adjust, CPsat_adjust) maps were produced over the GPRB. The final CP maps were validated using National Agricultural Statistics Service (NASS) crop yield data. The relationship between CPsat_adjust and the NASS average corn yield data (r = 0.78, 113 samples) is stronger than the relationship between CPnon_sat_adjust and the NASS average corn yield data (r = 0.67, 113 samples), indicating that the new CPsat_adjust map reduces the NDVI saturation effects and is in good agreement with the corn yield ground observations. Results demonstrate that the NDVI saturation adjustment approach improves the quality of the original GSN map and better depicts the actual vegetation conditions of the GPRB cropland systems.

Long-term channel adjustment and geomorphic feature creation by vegetation in a lowland, low energy river

NASA Astrophysics Data System (ADS)

Grabowski, Robert; Gurnell, Angela

2016-04-01

Physical habitat restoration is increasingly being used to improve the ecological status of rivers. This is particularly true for lowland streams which are perceived to lack sufficient energy to create new features or to flush out fine sediment derived from agricultural and urban sources. However, this study has found that even in low-energy, base-flow dominated chalk streams, physical habitat improvement can happen naturally without direct human intervention. Furthermore this positive change is achieved by components of the river that are often regarded as management problems: in-stream macrophytes (i.e. weed), riparian trees, woody debris, and most importantly fine sediment. This project investigated the long-term changes in channel planform for the River Frome (Dorset, UK) over the last 120 years and the role of aquatic and riparian vegetation in driving this change. Agricultural census data, historical maps, recent aerial images and field observations were analysed within a process-based, hierarchical framework for hydromorphological assessment, developed in the EU FP7 REFORM project, to investigate the source and timing of fine sediment production in the catchment, to quantify the reach-scale geomorphic response, and to identify vegetation-related bedforms that could be responsible for the adjustment. The analysis reveals that the channel has narrowed and become more sinuous in the last 50-60 years. The timing of this planform adjustment correlates with substantial changes in land use and agricultural practices (post-World War II) that are known to increase soil erosion and sediment connectivity. The field observations and recent aerial images suggest that the increased delivery of fine sediment to the channel has been translated into geomorphic adjustment and diversification though the interactions between vegetation, water flow and sediment. Emergent aquatic macrophytes are retaining fine sediment, leading to the development of submerged shelves that aggrade

Evaluating high temporal and spatial resolution vegetation index for crop yield prediction

USDA-ARS?s Scientific Manuscript database

Remote sensing data have been widely used in estimating crop yield. Remote sensing derived parameters such as Vegetation Index (VI) were used either directly in building empirical models or by assimilating with crop growth models to predict crop yield. The abilities of remote sensing VI in crop yiel...

Evaluating the potential of vegetation indices for winter wheat LAI estimation under different fertilization and water conditions

NASA Astrophysics Data System (ADS)

Xie, Qiaoyun; Huang, Wenjiang; Dash, Jadunandan; Song, Xiaoyu; Huang, Linsheng; Zhao, Jinling; Wang, Renhong

2015-12-01

Leaf area index (LAI) is an important indicator for monitoring crop growth conditions and forecasting grain yield. Many algorithms have been developed for remote estimation of the leaf area index of vegetation, such as using spectral vegetation indices, inversion of radiative transfer models, and supervised learning techniques. Spectral vegetation indices, mathematical combination of reflectance bands, are widely used for LAI estimation due to their computational simplicity and their applications ranged from the leaf scale to the entire globe. However, in many cases, their applicability is limited to specific vegetation types or local conditions due to species specific nature of the relationship used to transfer the vegetation indices to LAI. The overall objective of this study is to investigate the most suitable vegetation index for estimating winter wheat LAI under eight different types of fertilizer and irrigation conditions. Regression models were used to estimate LAI using hyperspectral reflectance data from the Pushbroom Hyperspectral Imager (PHI) and in-situ measurements. Our results showed that, among six vegetation indices investigated, the modified soil-adjusted vegetation index (MSAVI) and the normalized difference vegetation index (NDVI) exhibited strong and significant relationships with LAI, and thus were sensitive across different nitrogen and water treatments. The modified triangular vegetation index (MTVI2) confirmed its potential on crop LAI estimation, although second to MSAVI and NDVI in our study. The enhanced vegetation index (EVI) showed moderate performance. However, the ratio vegetation index (RVI) and the modified simple ratio index (MSR) predicted the least accurate estimations of LAI, exposing the simple band ratio index's weakness under different treatment conditions. The results support the use of vegetation indices for a quick and effective LAI mapping procedure that is suitable for winter wheat under different management practices.

Metrics for determining hydrophytic vegetation in wetland delineation: a clarification on the prevalence index

Treesearch

Diane De Steven

2015-01-01

A recent publication and an article in Wetland Science & Practice (Lichvar and Gillrich 2014b, 2014a) discuss two metrics for determining if vegetation is hydrophytic for purposes of U.S. wetland delineations, the Prevalence Index (PI) and a proposed Hydrophytic Cover Index (HCI). Based on Wentworth et al. (1988), the PI is a weighted average of ordinal scores (1-5...

Calibration of UAS imagery inside and outside of shadows for improved vegetation index computation

NASA Astrophysics Data System (ADS)

Bondi, Elizabeth; Salvaggio, Carl; Montanaro, Matthew; Gerace, Aaron D.

2016-05-01

Vegetation health and vigor can be assessed with data from multi- and hyperspectral airborne and satellite- borne sensors using index products such as the normalized difference vegetation index (NDVI). Recent advances in unmanned aerial systems (UAS) technology have created the opportunity to access these same image data sets in a more cost effective manner with higher temporal and spatial resolution. Another advantage of these systems includes the ability to gather data in almost any weather condition, including complete cloud cover, when data has not been available before from traditional platforms. The ability to collect in these varied conditions, meteorological and temporal, will present researchers and producers with many new challenges. Particularly, cloud shadows and self-shadowing by vegetation must be taken into consideration in imagery collected from UAS platforms to avoid variation in NDVI due to changes in illumination within a single scene, and between collection flights. A workflow is presented to compensate for variations in vegetation indices due to shadows and variation in illumination levels in high resolution imagery collected from UAS platforms. Other calibration methods that producers may currently be utilizing produce NDVI products that still contain shadow boundaries and variations due to illumination, whereas the final NDVI mosaic from this workflow does not.

View angle effects on relationships between leaf area index in wheat and vegetation indices

NASA Astrophysics Data System (ADS)

Chen, H.; Li, W.; Huang, W.; Niu, Z.

2016-12-01

The effects of plant types and view angles on the canopy-reflected spectrum can not be ignored in the estimation of leaf area index (LAI) using remote sensing vegetation indices. While vegetation indices derived from nadir-viewing remote sensors are insufficient in leaf area index (LAI) estimation because of its misinterpretation of structural characteristecs, vegetation indices derived from multi-angular remote sensors have potential to improve detection of LAI. However, view angle effects on relationships between these indices and LAI for low standing crops (i.e. wheat) has not been fully evaluated and thus limits them to applied for consistent and accurate monitoring of vegetation. View angles effects of two types of winter wheat (wheat 411, erectophile; and wheat 9507, planophile) on relationship between LAI and spectral reflectance are assessed and compared in this study. An evaluation is conducted with in-situ measurements of LAI and bidirectional reflectance in the principal plane from -60° (back-scattering direction ) ot 60° (forward scattering direction) in the growth cycle of winter wheat. A variety of vegetation indices (VIs) published are calculated by BRDF. Additionally, all combinations of the bands are used in order to calculate Normalized difference Spectral Indices (NDSI) and Simple Subtraction Indices (SSI). The performance of the above indices along with raw reflectance and reflectance derivatives on LAI estimation are examined based on a linearity comparison. The results will be helpful in further developing multi-angle remote sensing models for accurate LAI evaluation.

Effects of vegetation types on soil moisture estimation from the normalized land surface temperature versus vegetation index space

NASA Astrophysics Data System (ADS)

Zhang, Dianjun; Zhou, Guoqing

2015-12-01

Soil moisture (SM) is a key variable that has been widely used in many environmental studies. Land surface temperature versus vegetation index (LST-VI) space becomes a common way to estimate SM in optical remote sensing applications. Normalized LST-VI space is established by the normalized LST and VI to obtain the comparable SM in Zhang et al. (Validation of a practical normalized soil moisture model with in situ measurements in humid and semiarid regions [J]. International Journal of Remote Sensing, DOI: 10.1080/01431161.2015.1055610). The boundary conditions in the study were set to limit the point A (the driest bare soil) and B (the wettest bare soil) for surface energy closure. However, no limitation was installed for point D (the full vegetation cover). In this paper, many vegetation types are simulated by the land surface model - Noah LSM 3.2 to analyze the effects on soil moisture estimation, such as crop, grass and mixed forest. The locations of point D are changed with vegetation types. The normalized LST of point D for forest is much lower than crop and grass. The location of point D is basically unchanged for crop and grass.

Analysis of regional-scale vegetation dynamics of Mexico using stratified AVHRR NDVI data. [Normalized Difference Vegetaion Index

NASA Technical Reports Server (NTRS)

Turcotte, Kevin M.; Kramber, William J.; Venugopal, Gopalan; Lulla, Kamlesh

1989-01-01

Previous studies have shown that a good relationship exists between AVHRR Normalized Difference Vegetation Index (NDVI) measurements, and both regional-scale patterns of vegetation seasonality and productivity. Most of these studies used known samples of vegetation types. An alternative approach, and the objective was to examine the above relationships by analyzing one year of AVHRR NDVI data that was stratified using a small-scale vegetation map of Mexico. The results show that there is a good relationship between AVHRR NDVI measurements and regional-scale vegetation dynamics of Mexico.

On the characterization of vegetation recovery after fire disturbance using Fisher-Shannon analysis and SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series

NASA Astrophysics Data System (ADS)

Lasaponara, Rosa; Lanorte, Antonio; Lovallo, Michele; Telesca, Luciano

2015-04-01

Time series can fruitfully support fire monitoring and management from statistical analysis of fire occurrence (Tuia et al. 2008) to danger estimation (lasaponara 2005), damage evaluation (Lanorte et al 2014) and post fire recovery (Lanorte et al. 2014). In this paper, the time dynamics of SPOT-VEGETATION Normalized Difference Vegetation Index (NDVI) time series are analyzed by using the statistical approach of the Fisher-Shannon (FS) information plane to assess and monitor vegetation recovery after fire disturbance. Fisher-Shannon information plane analysis allows us to gain insight into the complex structure of a time series to quantify its degree of organization and order. The analysis was carried out using 10-day Maximum Value Composites of NDVI (MVC-NDVI) with a 1 km × 1 km spatial resolution. The investigation was performed on two test sites located in Galizia (North Spain) and Peloponnese (South Greece), selected for the vast fires which occurred during the summer of 2006 and 2007 and for their different vegetation covers made up mainly of low shrubland in Galizia test site and evergreen forest in Peloponnese. Time series of MVC-NDVI have been analyzed before and after the occurrence of the fire events. Results obtained for both the investigated areas clearly pointed out that the dynamics of the pixel time series before the occurrence of the fire is characterized by a larger degree of disorder and uncertainty; while the pixel time series after the occurrence of the fire are featured by a higher degree of organization and order. In particular, regarding the Peloponneso fire, such discrimination is more evident than in the Galizia fire. This suggests a clear possibility to discriminate the different post-fire behaviors and dynamics exhibited by the different vegetation covers. Reference Lanorte A, R Lasaponara, M Lovallo, L Telesca 2014 Fisher-Shannon information plane analysis of SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series to

Developing the vegetation drought response index for South Korea (VegDRI-SKorea) to assess the vegetation condition during drought events

USDA-ARS?s Scientific Manuscript database

Drought poses significant water and food security concerns in many parts of the world and can lead to negative agricultural, economic, and environmental impacts. The Vegetation Drought Response Index (VegDRI) approach has the flexibility to be adapted for other regions of the world using the climate...

Using Linear and Non-Linear Temporal Adjustments to Align Multiple Phenology Curves, Making Vegetation Status and Health Directly Comparable

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Norman, S. P.; Kumar, J.; Hoffman, F. M.

2017-12-01

National-scale polar analysis of MODIS NDVI allows quantification of degree of seasonality expressed by local vegetation, and also selects the most optimum start/end of a local "phenological year" that is empirically customized for the vegetation that is growing at each location. Interannual differences in timing of phenology make direct comparisons of vegetation health and performance between years difficult, whether at the same or different locations. By "sliding" the two phenologies in time using a Procrustean linear time shift, any particular phenological event or "completion milestone" can be synchronized, allowing direct comparison of differences in timing of other remaining milestones. Going beyond a simple linear translation, time can be "rubber-sheeted," compressed or dilated. Considering one phenology curve to be a reference, the second phenology can be "rubber-sheeted" to fit that baseline as well as possible by stretching or shrinking time to match multiple control points, which can be any recognizable phenological events. Similar to "rubber sheeting" to georectify a map inside a GIS, rubber sheeting a phenology curve also yields a warping signature that shows at every time and every location how many days the adjusted phenology is ahead or behind the phenological development of the reference vegetation. Using such temporal methods to "adjust" phenologies may help to quantify vegetation impacts from frost, drought, wildfire, insects and diseases by permitting the most commensurate quantitative comparisons with unaffected vegetation.

Adjustable internal structure for reconstructing gradient index profile of crystalline lens.

PubMed

Bahrami, Mehdi; Goncharov, Alexander V; Pierscionek, Barbara K

2014-03-01

Employing advanced technologies in studying the crystalline lens of the eye has improved our understanding of the refractive index gradient of the lens. Reconstructing and studying such a complex structure requires models with adaptable internal geometry that can be altered to simulate geometrical and optical changes of the lens with aging. In this Letter, we introduce an optically well-defined, geometrical structure for modeling the gradient refractive index profile of the crystalline lens with the advantage of an adjustable internal structure that is not available with existing models. The refractive index profile assigned to this rotationally symmetric geometry is calculated numerically, yet it is shown that this does not limit the model. The study provides a basis for developing lens models with sophisticated external and internal structures without the need for analytical solutions to calculate refractive index profiles.

Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data

USGS Publications Warehouse

Gallo, Kevin P.; Ji, Lei; Reed, Bradley C.; Eidenshink, Jeffery C.; Dwyer, John L.

2005-01-01

The relationship between AVHRR-derived normalized difference vegetation index (NDVI) values and those of future sensors is critical to continued long-term monitoring of land surface properties. The follow-on operational sensor to the AVHRR, the Visible/Infrared Imager/Radiometer Suite (VIIRS), will be very similar to the NASA Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. NDVI data derived from visible and near-infrared data acquired by the MODIS (Terra and Aqua platforms) and AVHRR (NOAA-16 and NOAA-17) sensors were compared over the same time periods and a variety of land cover classes within the conterminous United States. The results indicate that the 16-day composite NDVI values are quite similar over the composite intervals of 2002 and 2003, and linear relationships exist between the NDVI values from the various sensors. The composite AVHRR NDVI data included water and cloud masks and adjustments for water vapor as did the MODIS NDVI data. When analyzed over a variety of land cover types and composite intervals, the AVHRR derived NDVI data were associated with 89% or more of the variation in the MODIS NDVI values. The results suggest that it may be possible to successfully reprocess historical AVHRR data sets to provide continuity of NDVI products through future sensor systems.

Combining ground-based measurements and satellite-based spectral vegetation indices to track biomass accumulation in post-fire chaparral

NASA Astrophysics Data System (ADS)

Uyeda, K. A.; Stow, D. A.; Roberts, D. A.; Riggan, P. J.

2015-12-01

Multi-temporal satellite imagery can provide valuable information on patterns of vegetation growth over large spatial extents and long time periods, but corresponding ground-referenced biomass information is often difficult to acquire, especially at an annual scale. In this study, I test the relationship between annual biomass estimated using shrub growth rings and metrics of seasonal growth derived from Moderate Resolution Imaging Spectroradiometer (MODIS) spectral vegetation indices (SVIs) for a small area of southern California chaparral to evaluate the potential for mapping biomass at larger spatial extents. The site had most recently burned in 2002, and annual biomass accumulation measurements were available from years 5 - 11 post-fire. I tested metrics of seasonal growth using six SVIs (Normalized Difference Vegetation Index, Enhanced Vegetation Index, Soil Adjusted Vegetation Index, Normalized Difference Water Index, Normalized Difference Infrared Index 6, and Vegetation Atmospherically Resistant Index). While additional research would be required to determine which of these metrics and SVIs are most promising over larger spatial extents, several of the seasonal growth metrics/ SVI combinations have a very strong relationship with annual biomass, and all SVIs have a strong relationship with annual biomass for at least one of the seasonal growth metrics.

Heat index and adjusted temperature as surrogates for wet bulb globe temperature to screen for occupational heat stress.

PubMed

Bernard, Thomas E; Iheanacho, Ivory

2015-01-01

Ambient temperature and relative humidity are readily ava-ilable and thus tempting metrics for heat stress assessment. Two methods of using air temperature and relative humidity to create an index are Heat Index and Adjusted Temperature. The purposes of this article are: (1) to examine how well Heat Index and Adjusted Temperature estimated the wet bulb globe temperature (WBGT) index, and (2) to suggest how Heat Index and Adjusted Temperature can be used to screen for heat stress level. Psychrometric relationships were used to estimate values of actual WBGT for conditions of air temperature, relative humidity, and radiant heat at an air speed of 0.5 m/s. A relationship between Heat Index [°F] and WBGT [°C] was described by WBGT = -0.0034 HI(2) + 0.96 HI - 34. At lower Heat Index values, the equation estimated WBGTs that were ± 2 °C-WBGT around the actual value, and to about ± 0.5 °C-WBGT for Heat Index values > 100 °F. A relationship between Adjusted Temperature [°F] and WBGT [°C] was described by WBGT = 0.45 Tadj - 16. The actual WBGT was between 1 °C-WBGT below the estimated value and 1.4 °C-WBGT above. That is, there was a slight bias toward overestimating WBGT from Adjusted Temperature. Heat stress screening tables were constructed for metabolic rates of 180, 300, and 450 W. The screening decisions were divided into four categories: (1) < alert limit, (2) < exposure limit, (3) hourly time-weighted averages (TWAs) of work and recovery, and (4) a caution zone for an exposure > exposure limit at rest. The authors do not recommend using Heat Index or Adjusted Temperature instead of WBGT, but they may be used to screen for circumstances when a more detailed analysis using WBGT is appropriate. A particular weakness is accounting for radiant heat; and neither air speed nor clothing was considered.

How does spatial and temporal resolution of vegetation index impact crop yield estimation?

USDA-ARS?s Scientific Manuscript database

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing data have long been used in crop yield estimation for decades. The process-based approach uses light use efficiency model to estimate crop yield. Vegetation index (VI) ...

Atmospheric effects on the NDVI - Strategies for its removal. [Normalized Difference Vegetation Index

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Tanre, D.; Holben, B. N.; Markham, B.; Gitelson, A.

1992-01-01

The compositing technique used to derive global vegetation index (NDVI) from the NOAA AVHRR radiances reduces the residual effect of water vapor and aerosol on the NDVI. The reduction in the atmospheric effect is shown using a comprehensive measured data set for desert conditions, and a simulation for grass with continental aerosol. A statistical analaysis of the probability of occurrence of aerosol optical thickness and precipitable water vapor measured in different climatic regimes is used for this simulation. It is concluded that for a long compositing period (e.g., 27 days), the residual aerosol optical thickness and precipitable water vapor are usually too small to be corrected. For a 9-day compositing, the residual average aerosol effect may be about twice the correction uncertainty. For Landsat TM or Earth Observing System Moderate Resolution Imaging Spectrometer (EOS-MODIS) data, the newly defined atmospherically resistant vegetation index (ARVI) is more promising than possible direct atmospheric correction schemes, except for heavy desert dust conditions.

[Vegetation index estimation by chlorophyll content of grassland based on spectral analysis].

PubMed

Xiao, Han; Chen, Xiu-Wan; Yang, Zhen-Yu; Li, Huai-Yu; Zhu, Han

2014-11-01

Comparing the methods of existing remote sensing research on the estimation of chlorophyll content, the present paper confirms that the vegetation index is one of the most practical and popular research methods. In recent years, the increasingly serious problem of grassland degradation. This paper, firstly, analyzes the measured reflectance spectral curve and its first derivative curve in the grasslands of Songpan, Sichuan and Gongger, Inner Mongolia, conducts correlation analysis between these two spectral curves and chlorophyll content, and finds out the regulation between REP (red edge position) and grassland chlorophyll content, that is, the higher the chlorophyll content is, the higher the REIP (red-edge inflection point) value would be. Then, this paper constructs GCI (grassland chlorophyll index) and selects the most suitable band for retrieval. Finally, this paper calculates the GCI by the use of satellite hyperspectral image, conducts the verification and accuracy analysis of the calculation results compared with chlorophyll content data collected from field of twice experiments. The result shows that for grassland chlorophyll content, GCI has stronger sensitivity than other indices of chlorophyll, and has higher estimation accuracy. GCI is the first proposed to estimate the grassland chlorophyll content, and has wide application potential for the remote sensing retrieval of grassland chlorophyll content. In addition, the grassland chlorophyll content estimation method based on remote sensing retrieval in this paper provides new research ideas for other vegetation biochemical parameters' estimation, vegetation growth status' evaluation and grassland ecological environment change's monitoring.

Measurement of physiological traits of paddy rice in temperature gradient chamber using Normalized Difference Vegetation Index and Photochemical Reflectance Index

NASA Astrophysics Data System (ADS)

Ryu, J. H.; Oh, D.; Cho, J.

2017-12-01

Global warming has been affecting the phenological and physiological conditions of crop plants due to heat stress. Thus, the scientific understanding of not only crop-yield change, but also growth progress during high temperature condition is necessary. In this study, growth response and yield of paddy rice depending on air temperature (Ta) has been studied in a Temperature Gradient Chamber (TGC) that is composed of higher Ta than actual Ta (ambient temperature). The results on imitating experiment of global warming provided the reduced production of crop by heat stress. Therefore, it is important to quickly detect the condition of a plant in order to minimize damage to heat stress on global warming. Phenological and physiological changes depending on Ta was detected using optical spectroscopy sensors because remote sensing is useful and efficient technology to monitor quickly and continually. Two vegetation indices, Normalized Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI), were applied to monitor paddy rice growth using hyperspectral and multispectral radiometer. Ta in TGC was gradually set from actual Ta + 0 ° to actual Ta + 3 °. The variations of NDVI and PRI were different during rice growth period, and also these patterns were changed depending on Ta condition. NDVI and PRI under +3 ° condition increase faster than ambient temperature. After heading stage, the values of NDVI and PRI were dropped. However, the NDVI and PRI of rice under heat stress were relatively slowly decreased. In addition, we found that the yield of rice decreased in the case of delayed drop patterns of NDVI and PRI after heading stage. Our results will be useful to understand crop plant conditions using vegetation index under global warming situations.

Development and characterization of adjustable refractive index scattering epoxy acrylate polymer layers

NASA Astrophysics Data System (ADS)

Eiselt, Thomas; Preinfalk, Jan; Gleißner, Uwe; Lemmer, Uli; Hanemann, Thomas

2017-03-01

Several polymer films for improved optical properties in optoelectronic devices are presented. In such optical applications, it is sometimes important to have a film with an adjusted refractive index, scattering properties, and a low surface roughness. These diffusing films can be used to increase the efficiency of optoelectronic components, such as organic light-emitting diodes. Three different epoxy acrylate mixtures containing Syntholux 291 EA, bisphenol A glycerolate dimethacrylate, and Sartomer SR 348 L are characterized and optimized with different additives. The adjustable refractive index of the material is achieved by chemical doping using 9-vinylcarbazole. Titanium nanoparticles in the mixtures generate light scattering and increase the refractive index additionally. A high-power stirrer is used to mix and disperse all chemical substances together to a homogenous mixture. The viscosity behavior of the mixtures is an important property for the selection of the production method and, therefore, the viscosity measurement results are presented. After the mixing, the monomer mixture is applied on glass substrates by screen printing. To initiate polymerization, the produced films are irradiated for 10 min with ultraviolet radiation and heat. Transmission measurements of the polymer matrix and roughness measurements complement the characterization.

Forecasting vegetation greenness with satellite and climate data

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2004-01-01

A new and unique vegetation greenness forecast (VGF) model was designed to predict future vegetation conditions to three months through the use of current and historical climate data and satellite imagery. The VGF model is implemented through a seasonality-adjusted autoregressive distributed-lag function, based on our finding that the normalized difference vegetation index is highly correlated with lagged precipitation and temperature. Accurate forecasts were obtained from the VGF model in Nebraska grassland and cropland. The regression R2 values range from 0.97-0.80 for 2-12 week forecasts, with higher R2 associated with a shorter prediction. An important application would be to produce real-time forecasts of greenness images.

Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index.

PubMed

Li, Zheng; Zhou, Tao; Zhao, Xiang; Huang, Kaicheng; Gao, Shan; Wu, Hao; Luo, Hui

2015-07-08

Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI), from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months). When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation's responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April-October). The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages.

Semisupervised GDTW kernel-based fuzzy c-means algorithm for mapping vegetation dynamics in mining region using normalized difference vegetation index time series

NASA Astrophysics Data System (ADS)

Jia, Duo; Wang, Cangjiao; Lei, Shaogang

2018-01-01

Mapping vegetation dynamic types in mining areas is significant for revealing the mechanisms of environmental damage and for guiding ecological construction. Dynamic types of vegetation can be identified by applying interannual normalized difference vegetation index (NDVI) time series. However, phase differences and time shifts in interannual time series decrease mapping accuracy in mining regions. To overcome these problems and to increase the accuracy of mapping vegetation dynamics, an interannual Landsat time series for optimum vegetation growing status was constructed first by using the enhanced spatial and temporal adaptive reflectance fusion model algorithm. We then proposed a Markov random field optimized semisupervised Gaussian dynamic time warping kernel-based fuzzy c-means (FCM) cluster algorithm for interannual NDVI time series to map dynamic vegetation types in mining regions. The proposed algorithm has been tested in the Shengli mining region and Shendong mining region, which are typical representatives of China's open-pit and underground mining regions, respectively. Experiments show that the proposed algorithm can solve the problems of phase differences and time shifts to achieve better performance when mapping vegetation dynamic types. The overall accuracies for the Shengli and Shendong mining regions were 93.32% and 89.60%, respectively, with improvements of 7.32% and 25.84% when compared with the original semisupervised FCM algorithm.

Social Security cost-of-living adjustments and the Consumer Price Index.

PubMed

Burdick, Clark; Fisher, Lynn

2007-01-01

OASDI benefits are indexed for inflation to protect beneficiaries from the loss of purchasing power implied by inflation. In the absence of such indexing, the purchasing power of Social Security benefits would be eroded as rising prices raise the cost of living. By statute, cost-of-living adjustments (COLAs) for Social Security benefits are calculated using the Bureau of Labor Statistics (BLS) Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W). Some argue that this index does not accurately reflect the inflation experienced by the elderly population and should be changed to an elderly-specific price index such as the Experimental Consumer Price Index for Americans 62 Years of Age and Older, often referred to as the Consumer Price Index for the Elderly (CPI-E). Others argue that the measure of inflation underlying the COLA is technically biased, causing it to overestimate changes in the cost of living. This argument implies that current COLAs tend to increase, rather than merely maintain, the purchasing power of benefits over time. Potential bias in the CPI as a cost-of-living index arises from a number of sources, including incomplete accounting for the ability of consumers to substitute goods or change purchasing outlets in response to relative price changes. The BLS has constructed a new index called the Chained Consumer Price Index for All Urban Consumers (C-CPI-U) that better accounts for those consumer adjustments. Price indexes are not true cost-of-living indexes, but approximations of cost-of-living indexes (COLI). The Bureau of Labor Statistics (2006a) explains the difference between the two: As it pertains to the CPI, the COLI for the current month is based on the answer to the following question: "What is the cost, at this month ' market prices, of achieving the standard of living actually attained in the base period?" This cost is a hypothetical expenditure-the lowest expenditure level necessary at this month's prices to achieve the

The association between smoking and psychopathology adjusted for body mass index and gender.

PubMed

Dimitriadis, Dimitrios G; Mamplekou, Efterpi; Dimitriadis, Panayiotis G; Dimitriadis, George D; Papageorgiou, Charalambos

2016-10-01

This study examined the correlation between smoking habits and psychopathology status, as well as the impact of confounders such as body mass index and gender. A total of 134 non-smokers and 152 smokers were enrolled in this study. We measured psychopathology features using Symptom Checklist 90-Revised. We ran logistic regression models testing the smoking-psychopathology association, controlling for body mass index and gender. Smoking was positively correlated with depression, interpersonal sensitivity, hostility, somatization, paranoid ideation and psychoticism (P<0.05). Adjusting for body mass index and gender, the results remained largely unchanged, with a slight independent effect of body mass index. Our data suggest that smoking is a stronger predictor of psychopathology than body mass index and gender. © The Royal Australian and New Zealand College of Psychiatrists 2016.

Interannual growth dynamics of vegetation in the Kuparuk River watershed, Alaska based on the Normalized Difference Vegetation Index

USGS Publications Warehouse

Hope, A.S.; Boynton, W.L.; Stow, D.A.; Douglas, David C.

2003-01-01

Interannual above-ground production patterns are characterized for three tundra ecosystems in the Kuparuk River watershed of Alaska using NOAA-AVHRR Normalized Difference Vegetation Index (NDVI) data. NDVI values integrated over each growing season (SINDVI) were used to represent seasonal production patterns between 1989 and 1996. Spatial differences in ecosystem production were expected to follow north-south climatic and soil gradients, while interannual differences in production were expected to vary with variations in seasonal precipitation and temperature. It was hypothesized that the increased vegetation growth in high latitudes between 1981 and 1991 previously reported would continue through the period of investigation for the study watershed. Zonal differences in vegetation production were confirmed but interannual variations did not covary with seasonal precipitation or temperature totals. A sharp reduction in the SINDVI in 1992 followed by a consistent increase up to 1996 led to a further hypothesis that the interannual variations in SINDVI were associated with variations in stratospheric optical depth. Using published stratospheric optical depth values derived from the SAGE and SAGE-II satellites, it is demonstrated that variations in these depths are likely the primary cause of SINDVI interannual variability.

Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

USGS Publications Warehouse

Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick

2013-01-01

Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.

Integrated NDVI images for Niger 1986-1987. [Normalized Difference Vegetation Index

NASA Technical Reports Server (NTRS)

Harrington, John A., Jr.; Wylie, Bruce K.; Tucker, Compton J.

1988-01-01

Two NOAA AVHRR images are presented which provide a comparison of the geographic distribution of an integration of the normalized difference vegetation index (NDVI) for the Sahel zone in Niger for the growing seasons of 1986 and 1987. The production of the images and the application of the images for resource management are discussed. Daily large area coverage with a spatial resolution of 1.1 km at nadir were transformed to the NDVI and geographically registered to produce the images.

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

PubMed

Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

2016-09-01

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for

Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index

PubMed Central

Li, Zheng; Zhou, Tao; Zhao, Xiang; Huang, Kaicheng; Gao, Shan; Wu, Hao; Luo, Hui

2015-01-01

Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI), from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months). When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation’s responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April–October). The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages. PMID:26184243

Estimation for sparse vegetation information in desertification region based on Tiangong-1 hyperspectral image.

PubMed

Wu, Jun-Jun; Gao, Zhi-Hai; Li, Zeng-Yuan; Wang, Hong-Yan; Pang, Yong; Sun, Bin; Li, Chang-Long; Li, Xu-Zhi; Zhang, Jiu-Xing

2014-03-01

In order to estimate the sparse vegetation information accurately in desertification region, taking southeast of Sunite Right Banner, Inner Mongolia, as the test site and Tiangong-1 hyperspectral image as the main data, sparse vegetation coverage and biomass were retrieved based on normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), combined with the field investigation data. Then the advantages and disadvantages between them were compared. Firstly, the correlation between vegetation indexes and vegetation coverage under different bands combination was analyzed, as well as the biomass. Secondly, the best bands combination was determined when the maximum correlation coefficient turned up between vegetation indexes (VI) and vegetation parameters. It showed that the maximum correlation coefficient between vegetation parameters and NDVI could reach as high as 0.7, while that of SAVI could nearly reach 0.8. The center wavelength of red band in the best bands combination for NDVI was 630nm, and that of the near infrared (NIR) band was 910 nm. Whereas, when the center wavelength was 620 and 920 nm respectively, they were the best combination for SAVI. Finally, the linear regression models were established to retrieve vegetation coverage and biomass based on Tiangong-1 VIs. R2 of all models was more than 0.5, while that of the model based on SAVI was higher than that based on NDVI, especially, the R2 of vegetation coverage retrieve model based on SAVI was as high as 0.59. By intersection validation, the standard errors RMSE based on SAVI models were lower than that of the model based on NDVI. The results showed that the abundant spectral information of Tiangong-1 hyperspectral image can reflect the actual vegetaion condition effectively, and SAVI can estimate the sparse vegetation information more accurately than NDVI in desertification region.

A possible dose-response association between distance to farmers' markets and roadside produce stands, frequency of shopping, fruit and vegetable consumption, and body mass index among customers in the Southern United States.

PubMed

Jilcott Pitts, Stephanie B; Hinkley, Jedediah; Wu, Qiang; McGuirt, Jared T; Lyonnais, Mary Jane; Rafferty, Ann P; Whitt, Olivia R; Winterbauer, Nancy; Phillips, Lisa

2017-01-11

The association between farmers' market characteristics and consumer shopping habits remains unclear. Our objective was to examine associations among distance to farmers' markets, amenities within farmers' markets, frequency of farmers' market shopping, fruit and vegetable consumption, and body mass index (BMI). We hypothesized that the relationship between frequency of farmers' market shopping and BMI would be mediated by fruit and vegetable consumption. In 15 farmers' markets in northeastern North Carolina, July-September 2015, we conducted a cross-sectional survey among 263 farmers' market customers (199 provided complete address data) and conducted farmers' market audits. To participate, customers had to be over 18 years of age, and English speaking. Dependent variables included farmers' market shopping frequency, fruit and vegetable consumption, and BMI. Analysis of variance, adjusted multinomial logistic regression, Poisson regression, and linear regression models, adjusted for age, race, sex, and education, were used to examine associations between distance to farmers' markets, amenities within farmers' markets, frequency of farmers' market shopping, fruit and vegetable consumption, and BMI. Those who reported shopping at farmers' markets a few times per year or less reported consuming 4.4 (standard deviation = 1.7) daily servings of fruits and vegetables, and those who reported shopping 2 or more times per week reported consuming 5.5 (2.2) daily servings. There was no association between farmers' market amenities, and shopping frequency or fruit and vegetable consumption. Those who shopped 2 or more times per week had a statistically significantly lower BMI than those who shopped less frequently. There was no evidence of mediation of the relationship between frequency of shopping and BMI by fruit and vegetable consumption. More work should be done to understand factors within farmers' markets that encourage fruit and vegetable purchases.

Vegetation classification and soil moisture calculation using land surface temperature (LST) and vegetation index (VI)

NASA Astrophysics Data System (ADS)

Liu, Liangyun; Zhang, Bing; Xu, Genxing; Zheng, Lanfen; Tong, Qingxi

2002-03-01

In this paper, the temperature-missivity separating (TES) method and normalized difference vegetation index (NDVI) are introduced, and the hyperspectral image data are analyzed using land surface temperature (LST) and NDVI channels which are acquired by Operative Module Imaging Spectral (OMIS) in Beijing Precision Agriculture Demonstration Base in Xiaotangshan town, Beijing in 26 Apr, 2001. Firstly, the 6 kinds of ground targets, which are winter wheat in booting stage and jointing stage, bare soil, water in ponds, sullage in dry ponds, aquatic grass, are well classified using LST and NDVI channels. Secondly, the triangle-like scatter-plot is built and analyzed using LST and NDVI channels, which is convenient to extract the information of vegetation growth and soil's moisture. Compared with the scatter-plot built by red and near-infrared bands, the spectral distance between different classes are larger, and the samples in the same class are more convergent. Finally, we design a logarithm VIT model to extract the surface soil water content (SWC) using LST and NDVI channel, which works well, and the coefficient of determination, R2, between the measured surface SWC and the estimated is 0.634. The mapping of surface SWC in the wheat area are calculated and illustrated, which is important for scientific irrigation and precise agriculture.

Identifying high production, low production and degraded rangelands in Senegal with normalized difference vegetation index data

USGS Publications Warehouse

Tappan, G. Gray; Wood, Lynette; Moore, Donald G.

1993-01-01

Seasonal herbaceous vegetation production on Senegal's native rangelands exhibits high spatial and temporal variability. This variability can be monitored using normalized difference vegetation index (NDVI) data computed from 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) image data. Although annual fluctuations in rainfall account for some of the variability, numerous long-term production patterns are evident in the AVHRR time-series data. Different n productivity reflect variations in the region's climate, topography, soils, and land use. Areas of overgrazing and intensive cultivation have caused long-term soil and vegetation degradation. Rangelands of high and low productivity, and degraded rangelands were identified using NDVI. Time-series image data from 1987 though 1992 were used to map relative rangeland productivity. The results were compared to detailed resource maps on soils, vegetation and land use. Much of the variation in rangeland productivity correlated well to the known distribution of resources. The study developed an approach that identified a number of areas of degraded soils and low vegetation production.

Shelter Index and a simple wind speed parameter to characterize vegetation control of sand transport threshold and Flu

NASA Astrophysics Data System (ADS)

Gillies, J. A.; Nield, J. M.; Nickling, W. G.; Furtak-Cole, E.

2014-12-01

Wind erosion and dust emissions occur in many dryland environments from a range of surfaces with different types and amounts of vegetation. Understanding how vegetation modulates these processes remains a research challenge. Here we present results from a study that examines the relationship between an index of shelter (SI=distance from a point to the nearest upwind vegetation/vegetation height) and particle threshold expressed as the ratio of wind speed measured at 0.45 times the mean plant height divided by the wind speed at 17 m when saltation commences, and saltation flux. The results are used to evaluate SI as a parameter to characterize the influence of vegetation on local winds and sediment transport conditions. Wind speed, wind direction, saltation activity and point saltation flux were measured at 35 locations in defined test areas (~13,000 m2) in two vegetation communities: mature streets of mesquite covered nebkhas and incipient nebkhas dominated by low mesquite plants. Measurement positions represent the most open areas, and hence those places most susceptible to wind erosion among the vegetation elements. Shelter index was calculated for each measurement position for each 10° wind direction bin using digital elevation models for each site acquired using terrestrial laser scanning. SI can show the susceptibility to wind erosion at different time scales, i.e., event, seasonal, or annual, but in a supply-limited system it can fail to define actual flux amounts due to a lack of knowledge of the distribution of sediment across the surface of interest with respect to the patterns of SI.

Preliminary comparison of landscape pattern-normalized difference vegetation index (NDVI) relationships to central plains stream conditions

USGS Publications Warehouse

Griffith, J.A.; Martinko, E.A.; Whistler, J.L.; Price, K.P.

2002-01-01

We explored relationships of water quality parameters with landscape pattern metrics (LPMs), land use-land cover (LULC) proportions, and the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) or NDVI-derived metrics. Stream sites (271) in Nebraska, Kansas, and Missouri were sampled for water quality parameters, the index of biotic integrity, and a habitat index in either 1994 or 1995. Although a combination of LPMs (interspersion and juxtaposition index, patch density, and percent forest) within Ozark Highlands watersheds explained >60% of the variation in levels of nitrite-nitrate nitrogen and conductivity, in most cases the LPMs were not significantly correlated with the stream data. Several problems using landscape pattern metrics were noted: small watersheds having only one or two patches, collinearity with LULC data, and counterintuitive or inconsistent results that resulted from basic differences in land use-land cover patterns among ecoregions or from other factors determining water quality. The amount of variation explained in water quality parameters using multiple regression models that combined LULC and LPMs was generally lower than that from NDVI or vegetation phenology metrics derived from time-series NDVI data. A comparison of LPMs and NDVI indicated that NDVI had greater promise for monitoring landscapes for stream conditions within the study area.

Preliminary comparison of landscape pattern-normalized difference vegetation index (NDVI) relationships to Central Plains stream conditions.

PubMed

Griffith, Jerry A; Martinko, Edward A; Whistler, Jerry L; Price, Kevin P

2002-01-01

We explored relationships of water quality parameters with landscape pattern metrics (LPMs), land use-land cover (LULC) proportions, and the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) or NDVI-derived metrics. Stream sites (271) in Nebraska, Kansas, and Missouri were sampled for water quality parameters, the index of biotic integrity, and a habitat index in either 1994 or 1995. Although a combination of LPMs (interspersion and juxtaposition index, patch density, and percent forest) within Ozark Highlands watersheds explained >60% of the variation in levels of nitrite-nitrate nitrogen and conductivity, in most cases the LPMs were not significantly correlated with the stream data. Several problems using landscape pattern metrics were noted: small watersheds having only one or two patches, collinearity with LULC data, and counterintuitive or inconsistent results that resulted from basic differences in land use-land cover patterns among ecoregions or from other factors determining water quality. The amount of variation explained in water quality parameters using multiple regression models that combined LULC and LPMs was generally lower than that from NDVI or vegetation phenology metrics derived from time-series NDVI data. A comparison of LPMs and NDVI indicated that NDVI had greater promise for monitoring landscapes for stream conditions within the study area.

Limited Area Coverage/High Resolution Picture Transmission (LAC/HRPT) data vegetative index calculation processor user's manual

NASA Technical Reports Server (NTRS)

Obrien, S. O. (Principal Investigator)

1980-01-01

The program, LACVIN, calculates vegetative indexes numbers on limited area coverage/high resolution picture transmission data for selected IJ grid sections. The IJ grid sections were previously extracted from the full resolution data tapes and stored on disk files.

Tropical forest biomass and successional age class relationships to a vegetation index derived from Landsat TM data

NASA Technical Reports Server (NTRS)

Sader, Steven A.; Waide, Robert B.; Lawrence, William T.; Joyce, Armond T.

1989-01-01

Forest stand structure and biomass data were collected using conventional forest inventory techniques in tropical, subtropical, and warm temperate forest biomes. The feasibility of detecting tropical forest successional age class and total biomass differences using Landsat-Thematic mapper (TM) data, was evaluated. The Normalized Difference Vegetation Index (NDVI) calculated from Landsat-TM data were not significantly correlated with forest regeneration age classes in the mountain terrain of the Luquillo Experimental Forest, Puerto Rico. The low sun angle and shadows cast on steep north and west facing slopes reduced spectral reflectance values recorded by TM orbital altitude. The NDVI, calculated from low altitude aircraft scanner data, was significatly correlated with forest age classes. However, analysis of variance suggested that NDVI differences were not detectable for successional forests older than approximately 15-20 years. Also, biomass differences in young successional tropical forest were not detectable using the NDVI. The vegetation index does not appear to be a good predictor of stand structure variables (e.g., height, diameter of main stem) or total biomass in uneven age, mixed broadleaf forest. Good correlation between the vegetation index and low biomass in even age pine plantations were achieved for a warm temperate study site. The implications of the study for the use of NDVI for forest structure and biomass estimation are discussed.

Performance of the Enhanced Vegetation Index to Detect Inner-annual Dry Season and Drought Impacts on Amazon Forest Canopies

NASA Astrophysics Data System (ADS)

Brede, B.; Verbesselt, J.; Dutrieux, L.; Herold, M.

2015-04-01

The Amazon rainforests represent the largest connected forested area in the tropics and play an integral role in the global carbon cycle. In the last years the discussion about their phenology and response to drought has intensified. A recent study argued that seasonality in greenness expressed as Enhanced Vegetation Index (EVI) is an artifact of variations in sun-sensor geometry throughout the year. We aimed to reproduce these results with the Moderate-Resolution Imaging Spectroradiometer (MODIS) MCD43 product suite, which allows modeling the Bidirectional Reflectance Distribution Function (BRDF) and keeping sun-sensor geometry constant. The derived BRDF-adjusted EVI was spatially aggregated over large areas of central Amazon forests. The resulting time series of EVI spanning the 2000-2013 period contained distinct seasonal patterns with peak values at the onset of the dry season, but also followed the same pattern of sun geometry expressed as Solar Zenith Angle (SZA). Additionally, we assessed EVI's sensitivity to precipitation anomalies. For that we compared BRDF-adjusted EVI dry season anomalies to two drought indices (Maximum Cumulative Water Deficit, Standardized Precipitation Index). This analysis covered the whole of Amazonia and data from the years 2000 to 2013. The results showed no meaningful connection between EVI anomalies and drought. This is in contrast to other studies that investigate the drought impact on EVI and forest photosynthetic capacity. The results from both sub-analyses question the predictive power of EVI for large scale assessments of forest ecosystem functioning in Amazonia. Based on the presented results, we recommend a careful evaluation of the EVI for applications in tropical forests, including rigorous validation supported by ground plots.

Chlorophyll fluorescence, photochemical reflective index and normalized difference vegetative index during plant senescence.

PubMed

Cordon, Gabriela; Lagorio, M Gabriela; Paruelo, José M

2016-07-20

The relationship between the Photochemical Reflectance Index (PRI), Normalized Difference Vegetation Index (NDVI) and chlorophyll fluorescence along senescence was investigated in this work. Reflectance and radiance measurements were performed at canopy level in grass species presenting different photosynthetic metabolism: Avena sativa (C3) and Setaria italica (C4), at different stages of the natural senescence process. Sun induced-chlorophyll fluorescence at 760nm (SIF 760 ) and the apparent fluorescence yield (SIF 760 /a, with a=irradiance at time of measurement) were extracted from the radiance spectra of canopies using the Fraunhofer Line Discrimination-method. The photosynthetic parameters derived from Kautsky kinetics and pigment content were also calculated at leaf level. Whilst stand level NDVI patterns were related to changes in the structure of canopies and not in pigment content, stand level PRI patterns suggested changes both in terms of canopy and of pigment content in leaves. Both SIF 760 /a and Φ PSII decreased progressively along senescence in both species. A strong increment in NPQ was evident in A. sativa while in S. italica NPQ values were lower. Our most important finding was that two chlorophyll fluorescence signals, Φ PSII and SIF 760 /a, correlated with the canopy PRI values in the two grasses assessed, even when tissues at different ontogenic stages were present. Even though significant changes occurred in the Total Chlr/Car ratio along senescence in both studied species, significant correlations between PRI and chlorophyll fluorescence signals might indicate the usefulness of this reflectance index as a proxy of photosynthetic RUE, at least under the conditions of this study. The relationships between stand level PRI and the fluorescence estimators (Φ PSII and SIF 760 /a) were positive in both cases. Therefore, an increase in PRI values as in the fluorescence parameters would indicate higher RUE. Copyright © 2016 Elsevier GmbH. All

A Methodology for Soil Moisture Retrieval from Land Surface Temperature, Vegetation Index, Topography and Soil Type

NASA Astrophysics Data System (ADS)

Pradhan, N. R.

2015-12-01

Soil moisture conditions have an impact upon hydrological processes, biological and biogeochemical processes, eco-hydrology, floods and droughts due to changing climate, near-surface atmospheric conditions and the partition of incoming solar and long-wave radiation between sensible and latent heat fluxes. Hence, soil moisture conditions virtually effect on all aspects of engineering / military engineering activities such as operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, peaking factor analysis in dam design etc. Like other natural systems, soil moisture pattern can vary from completely disorganized (disordered, random) to highly organized. To understand this varying soil moisture pattern, this research utilized topographic wetness index from digital elevation models (DEM) along with vegetation index from remotely sensed measurements in red and near-infrared bands, as well as land surface temperature (LST) in the thermal infrared bands. This research developed a methodology to relate a combined index from DEM, LST and vegetation index with the physical soil moisture properties of soil types and the degree of saturation. The advantage in using this relationship is twofold: first it retrieves soil moisture content at the scale of soil data resolution even though the derived indexes are in a coarse resolution, and secondly the derived soil moisture distribution represents both organized and disorganized patterns of actual soil moisture. The derived soil moisture is used in driving the hydrological model simulations of runoff, sediment and nutrients.

Crop Surveillance Demonstration Using a Near-Daily MODIS Derived Vegetation Index Time Series

NASA Technical Reports Server (NTRS)

McKellip, Rodney; Ryan, Robert E.; Blonski, Slawomir; Prados, Don

2005-01-01

Effective response to crop disease outbreaks requires rapid identification and diagnosis of an event. A near-daily vegetation index product, such as a Normalized Difference Vegetation Index (NDVI), at moderate spatial resolution may serve as a good method for monitoring quick-acting diseases. NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flown on the Terra and Aqua satellites has the temporal, spatial, and spectral properties to make it an excellent coarse-resolution data source for rapid, comprehensive surveillance of agricultural areas. A proof-of-concept wide area crop surveillance system using daily MODIS imagery was developed and tested on a set of San Joaquin cotton fields over a growing season. This area was chosen in part because excellent ground truth data were readily available. Preliminary results indicate that, at least in the southwestern part of the United States, near-daily NDVI products can be generated that show the natural variations in the crops as well as specific crop practices. Various filtering methods were evaluated and compared with standard MOD13 NDVI MODIS products. We observed that specific chemical applications that produce defoliation, which would have been missed using the standard 16-day product, were easily detectable with the filtered daily NDVI products.

Fruit and vegetable consumption is inversely associated with having pancreatic cancer.

PubMed

Jansen, Rick J; Robinson, Dennis P; Stolzenberg-Solomon, Rachael Z; Bamlet, William R; de Andrade, Mariza; Oberg, Ann L; Hammer, Traci J; Rabe, Kari G; Anderson, Kristin E; Olson, Janet E; Sinha, Rashmi; Petersen, Gloria M

2011-12-01

Studies on fruit, vegetable, fiber, and grain consumption and pancreatic cancer risk are inconclusive. We used a clinic-based case-control study specifically designed to address limitations of both cohort and case-control studies to examine the relationship. Participants were excluded who reported changing their diet within 5 years prior to study entry. And 384 rapidly ascertained cases and 983 controls (frequency matched on age (±5 years), race, sex, and residence) completed epidemiologic surveys and 144-item food frequency questionnaires. Odds ratios (OR) and 95% confidence intervals were calculated using logistic regression adjusted for age, sex, smoking, body mass index, energy intake, and alcohol consumption. Comparing highest to lowest quintiles, we observed significant inverse associations (OR < 0.8) with significant trends (p (trend) < 0.05) for citrus, melon, and berries, other fruits, dark green vegetables, deep yellow vegetables, tomato, other vegetables, dry bean and pea, insoluble fiber, soluble fiber, whole grains, and orange/grapefruit juice, and an increased association with non-whole grains. Results were similar after adjusting for diabetes or total sugar intake. We provide evidence that lower consumption of fruits, vegetables, whole grains, and fiber is associated with having pancreatic cancer. This may have a role in developing prevention strategies.

Fruit and vegetable consumption is inversely associated with having pancreatic cancer

PubMed Central

Robinson, Dennis P.; Stolzenberg-Solomon, Rachael Z.; Bamlet, William R.; de Andrade, Mariza; Oberg, Ann L.; Hammer, Traci J.; Rabe, Kari G.; Anderson, Kristin E.; Olson, Janet E.; Sinha, Rashmi; Petersen, Gloria M.

2012-01-01

Objective Studies on fruit, vegetable, fiber, and grain consumption and pancreatic cancer risk are inconclusive. We used a clinic-based case–control study specifically designed to address limitations of both cohort and case–control studies to examine the relationship. Methods Participants were excluded who reported changing their diet within 5 years prior to study entry. And 384 rapidly ascertained cases and 983 controls (frequency matched on age (±5 years), race, sex, and residence) completed epidemiologic surveys and 144-item food frequency questionnaires. Odds ratios (OR) and 95% confidence intervals were calculated using logistic regression adjusted for age, sex, smoking, body mass index, energy intake, and alcohol consumption. Results Comparing highest to lowest quintiles, we observed significant inverse associations (OR < 0.8) with significant trends (ptrend < 0.05) for citrus, melon, and berries, other fruits, dark green vegetables, deep yellow vegetables, tomato, other vegetables, dry bean and pea, insoluble fiber, soluble fiber, whole grains, and orange/grapefruit juice, and an increased association with non-whole grains. Results were similar after adjusting for diabetes or total sugar intake. Conclusions We provide evidence that lower consumption of fruits, vegetables, whole grains, and fiber is associated with having pancreatic cancer. This may have a role in developing prevention strategies. PMID:21915615

Comparison of Landsat-8 and Sentinel-2A reflectance and normalized difference vegetation index

NASA Astrophysics Data System (ADS)

Zhang, H.; Roy, D. P.; Yan, L.; Li, Z.; Huang, H.

2017-12-01

The moderate spatial resolution satellite data from the polar-orbiting Landsat-8 (launched 2013) and Sentinel-2A (launched 2015) sensors provide 10 m to 30 m multi-spectral global coverage with a better than 5-day revisit. Although a national laboratory traceable cross-calibration comparison of the Landsat-8 Operational Land Imager (OLI) and the Sentinel-2A MultiSpectral Instrument (MSI) was undertaken pre-launch, there are a number of other sensor differences, notably due to spectral, spatial and angular differences. To examine these in a comprehensive way, Landsat-8 and Sentinel-2A data for approximately 20° × 10° of southern Africa acquired in the summer (January to March) and winter (July to September) of 2016 were compared. Only Landsat-8 and Sentinel-2A observations acquired within one-day apart were considered. The sensor data were registered and then each orbit projected into 30 m fixed global Web Enabled Landsat Data (GWELD) tiles defined in the MODIS sinusoidal equal area projection. Only corresponding sensor observations of each 30 m tile pixel that were flagged as cloud and snow-free, unsaturated, and that had no significant change in their one day separation, were compared. Both the Landsat-8 and Sentinel-2A data were atmospherically corrected using the Landsat Surface Reflectance Code (LaSRC) and were also corrected to nadir BRDF adjusted reflectance (NBAR). Top of atmosphere and surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared OLI and MSI bands, and derived normalized difference vegetation index (NDVI), were compared and their differences quantified using regression analyses. The resulting statistical transformations may be used to improve the consistency between the Landsat-8 OLI and Sentinel-2A MSI data. The importance and sensitivity of the results to correct filtering, atmospheric correction and adjustment to NBAR is demonstrated.

5 CFR 591.228 - How does OPM convert the price index plus adjustment factor to a COLA rate?

Code of Federal Regulations, 2010 CFR

2010-01-01

... than 124.50 Price index plus the adjustment factor, minus 100, expressed to the nearest whole percent... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false How does OPM convert the price index plus... Differential-Nonforeign Areas Cost-Of-Living Allowances § 591.228 How does OPM convert the price index plus...

Development and characterization of adjustable refractive index scattering epoxy acrylate polymer layers

NASA Astrophysics Data System (ADS)

Eiselt, Thomas; Preinfalk, Jan; Gleißner, Uwe; Lemmer, Uli; Hanemann, Thomas

2016-09-01

This work presents different polymer diffusing films for optical components. In optical applications it is sometimes important to have a film with an adjusted refractive index, scattering properties and a low surface roughness. These diffusing films can be used to increase the efficiency of optical components like organic light emitting diodes (OLEDs). In this study three different epoxy acrylate mixtures containing Syntholux 291 EA, bisphenol a glycerolate dimethacrylate, Sartomer SR 348 L are characterized and optimized with different additives. The adjustable refractive index of the material is achieved with a chemical doping by 9-vinylcarbazole. Titanium nanoparticles in the mixtures generate light scattering and increase the refractive index additionally. To prevent sedimentation and agglomeration of these nanoparticles, a stabilization agent [2-(2-methoxyethoxy)ethoxy]acetic acid is added to the mixture. Other ingredients are a UV-starter and thermal starter for the radical polymerization. A high power stirrer (ultraturrax) is used to mix and disperse all chemical substances together to a homogenous mixture. The viscosity behavior of the mixtures is an important property for the selection of the production method and gets characterized. After the mixing, the monomer mixture is applied on glass substrates by blade coating or screen printing. To initiate the chain growing (polymerization) the produced films are irradiated for 10 minutes long with UV light (UV LED Spot Hönle, 405 nm). After this step a final post bake from the layers in the oven (150°C, 30 min.) is operated. Light transmission measurements (UV-Vis) of the polymer matrix and roughness measurements complement the characterization.

Relationships between recent channel adjustments, present morphological state and river corridor vegetation in the Fortore River (southern Italy)

NASA Astrophysics Data System (ADS)

Rosskopf, Carmen Maria; Scorpio, Vittoria; Calabrese, Valentina; Frate, Ludovico; Loy, Anna; Stanisci, Angela

2017-04-01

The Fortore River, as many other rivers in Italy, has experienced huge channel adjustments during the last 60 years that were mainly caused by anthropic interventions, especially in-channel mining and the closure of the Occhito dam in 1966. Such changes deeply modified extension and morphological characteristics of the river corridor and, consequently, also its ecological features. The present study aims to better understand the relationships between channel adjustments and river corridor vegetation changes and those between morphological features and environmental quality of the present-day river corridor. The study has been carried out by means of a multi-temporal GIS analysis of topographic maps and aerial photographs integrated with topographic, geomorphological and ecological field surveys. Results highlight that channel adjustments occurred through two distinct phases. Most of the channel changes occurred from the 1950s until the end of the 1990s (phase 1) and led to an overall channel narrowing (from 81 to 96%) and channel bed lowering (1-4 m). These changes were accompanied by pattern shifts from multithread to single-thread configurations. The reaches located downstream of the Occhito dam were affected by more intense modifications, especially channel narrowing, with respect to upstream reaches. From 2000 to 2016 (phase 2), a trend inversion occurred. Downstream reaches remained essentially stable, while upstream reaches were affected even by some channel widening and bed aggradation and slight increase of the extension of floodplain areas giving more space to the potential development of the riparian vegetation. The evolution and the present geomorphological conditions of the river corridor are also reflected by the state of the riparian vegetation. Upstream reaches are characterized by a higher richness in riparian vegetation types and vegetation cover with respect to downstream reaches. Best conditions occur especially in the upper Fortore valley. In

Modelling spatial and temporal vegetation variability with the Climate Constrained Vegetation Index: evidence of CO2 fertilisation and of water stress in continental interiors

NASA Astrophysics Data System (ADS)

Los, S. O.

2015-06-01

A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen-Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 < r <0.87), seasonal variability (median r = 0.83) and interannual variability (median global r = 0.24) in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8 % for the 20th century). This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity.

Global trends in vegetation phenology from 32-year GEOV1 leaf area index time series

NASA Astrophysics Data System (ADS)

Verger, Aleixandre; Baret, Frédéric; Weiss, Marie; Filella, Iolanda; Peñuelas, Josep

2013-04-01

Phenology is a critical component in understanding ecosystem response to climate variability. Long term data records from global mapping satellite platforms are valuable tools for monitoring vegetation responses to climate change at the global scale. Phenology satellite products and trend detection from satellite time series are expected to contribute to improve our understanding of climate forcing on vegetation dynamics. The capacity of monitoring ecosystem responses to global climate change was evaluated in this study from the 32-year time series of global Leaf Area Index (LAI) which have been recently produced within the geoland2 project. The long term GEOV1 LAI products were derived from NOAA/AVHRR (1981 to 2000) and SPOT/VGT (1999 to the present) with specific emphasis on consistency and continuity. Since mid-November, GEOV1 LAI products are freely available to the scientific community at geoland2 portal (www.geoland2.eu/core-mapping-services/biopar.html). These products are distributed at a dekadal time step for the period 1981-2000 and 2000-2012 at 0.05° and 1/112°, respectively. The use of GEOV1 data covering a long time period and providing information at dense time steps are expected to increase the reliability of trend detection. In this study, GEOV1 LAI time series aggregated at 0.5° spatial resolution are used. The CACAO (Consistent Adjustment of the Climatology to Actual Observations) method (Verger et al, 2013) was applied to characterize seasonal anomalies as well as identify trends. For a given pixel, CACAO computes, for each season, the time shift and the amplitude difference between the current temporal profile and the climatology computed over the 32 years. These CACAO parameters allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. Interannual variations in the timing of the Start of Season and End of Season, Season Length and LAI level in the peak of the

Relation of raw and cooked vegetable consumption to blood pressure: the INTERMAP Study.

PubMed

Chan, Q; Stamler, J; Brown, I J; Daviglus, M L; Van Horn, L; Dyer, A R; Oude Griep, L M; Miura, K; Ueshima, H; Zhao, L; Nicholson, J K; Holmes, E; Elliott, P

2014-06-01

Inverse associations have been reported of overall vegetable intake to blood pressure (BP); whether such relations prevail for both raw and cooked vegetables has not been examined. Here we report cross-sectional associations of vegetable intakes with BP for 2195 Americans ages 40-59 in the International Study of Macro/Micronutrients and Blood Pressure (INTERMAP) using four standardized multi-pass 24-h dietary recalls and eight BP measurements. Relations to BP of raw and cooked vegetables consumption, and main individual constituents were assessed by multiple linear regression. Intakes of both total raw and total cooked vegetables considered separately were inversely related to BP in multivariate-adjusted models. Estimated average systolic BP differences associated with two s.d. differences in raw vegetable intake (68 g per 1000 kcal) and cooked vegetable intake (92 g per 1000 kcal) were -1.9 mm Hg (95% confidence interval (CI): -3.1, -0.8; P=0.001) and -1.3 mm Hg (95% CI: -2.5, -0.2; P=0.03) without body mass index (BMI) in the full model; -1.3 mm Hg (95% CI: -2.4, -0.2; P=0.02) and -0.9 mm Hg (95% CI: -2.0, 0.2; P=0.1) with additional adjustment for BMI. Among commonly consumed individual raw vegetables, tomatoes, carrots, and scallions related significantly inversely to BP. Among commonly eaten cooked vegetables, tomatoes, peas, celery, and scallions related significantly inversely to BP.

Analysis of the spatial-temporal change and impact factors of the vegetation index in Yulin of China: the effect of forest conservation and grain for green

NASA Astrophysics Data System (ADS)

Liu, D.; Luan, J.; Lin, M.; Huang, Q.

2017-12-01

Since 1999, China began the Grain for Green program to conserve the forest in the north of China. After 17 years, the vegetation in the north has changed. Vegetation index is an important method to study the regional vegetation change. This study is based on MODIS/Terra NDVI remote sensing data, and analyzes the spatial-temporal changes and the impact factors of the NDVI in August from 2000 to 2016 at pixel scale in Yulin City of Shaanxi Province in China. The results showed that, on about 96.44% of the region in the Yulin city, vegetation index increased, and the area with increasing NDVI between 0-0.02/a accounts for 93.63% of Yulin city. The area with significant increasing trend accounts for 80.72%. The complex linear regression analysis showed that, the meteorological factors play a positive role in the growth and evolution of vegetation, and human activities also make the vegetation index become more uniform. The area, where the human activities restrain the growth and evolution of the vegetation, is 45.04% of the Yulin area. It is mainly distributed in Fugu County which located in the north of Yulin, and most areas of southern and western parts of Yulin. The area where human activities promote the increase of the vegetation index, accounted for 54.96% of the Yulin area, which indicated that on more than half of the region, human activities have played a positive role in the growth of vegetation. In these areas, the effect of forest conservation, and grain for green (i.e. returning farmland to forests, and returning pasturage to natural grassland) is better.

Be aware of the Adjusted Treatment Index.

PubMed

Langford, Melvyn

2015-10-01

The authors of the interim report relating to the Review of Operational Productivity in NHS providers, published in June of this year, are, as many will know, developing a set of Adjusted Treatment Index (ATI) metrics, and are also to publish a model of their interpretation of what an estates department should look like in terms of its operational productivity and cost. This article argues that the underlying reason for the past failures was the creation of static 'point-value' metrics similar to the ATIs proposed, and that this can only be overcome by designing and populating a series of non-linear dynamic simulation models with feedback control of an organisation's estate in relation to its asset base and condition with respect to time, together with the resultant financial capital and revenue consequences. It concludes by calling on IHEEM's Council to urgently make representation to the authors of the June 2015 report, and suggests that the Institute's members be fully involved in the design, testing, and interpretation, of the estates model and ATIs. IHEEM's Technology Platforms are ideally placed to play a central role in this.

Use of Radar Vegetation Index (RVI) in Passive Microwave Algorithms for Soil Moisture Estimates

NASA Astrophysics Data System (ADS)

Rowlandson, T. L.; Berg, A. A.

2013-12-01

The Soil Moisture Active Passive (SMAP) satellite will provide a unique opportunity for the estimation of soil moisture by having simultaneous radar and radiometer measurements available. As with the Soil Moisture and Ocean Salinity (SMOS) satellite, the soil moisture algorithms will need to account for the contribution of vegetation to the brightness temperature. Global maps of vegetation volumetric water content (VWC) are difficult to obtain, and the SMOS mission has opted to estimate the optical depth of standing vegetation by using a relationship between the VWC and the leaf area index (LAI). LAI is estimated from optical remote sensing or through soil-vegetation-atmosphere transfer modeling. During the growing season, the VWC of agricultural crops can increase rapidly, and if cloud cover exists during an optical acquisition, the estimation of LAI may be delayed, resulting in an underestimation of the VWC and overestimation of the soil moisture. Alternatively, the radar vegetation index (RVI) has shown strong correlation and linear relationship with VWC for rice and soybeans. Using the SMAP radar to produce RVI values that are coincident to brightness temperature measurements may eliminate the need for LAI estimates. The SMAP Validation Experiment 2012 (SMAPVEX12) was a cal/val campaign for the SMAP mission held in Manitoba, Canada, during a 6-week period in June and July, 2012. During this campaign, soil moisture measurements were obtained for 55 fields with varying soil texture and vegetation cover. Vegetation was sampled from each field weekly to determine the VWC. Soil moisture measurements were taken coincident to overpasses by an aircraft carrying the Passive and Active L-band System (PALS) instrumentation. The aircraft flew flight lines at both high and low altitudes. The low altitude flight lines provided a footprint size approximately equivalent to the size of the SMAPVEX12 field sites. Of the 55 field sites, the low altitude flight lines provided

5 CFR 591.227 - What adjustment factors does OPM add to the price indexes?

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false What adjustment factors does OPM add to the price indexes? 591.227 Section 591.227 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS ALLOWANCES AND DIFFERENTIALS Cost-of-Living Allowance and Post Differential-Nonforeign Areas Cost-Of-Living Allowances §...

Addressing climate change in the Forest Vegetation Simulator to assess impacts on landscape forest dynamics

Treesearch

Nicholas L. Crookston; Gerald E. Rehfeldt; Gary E. Dixon; Aaron R. Weiskittel

2010-01-01

To simulate stand-level impacts of climate change, predictors in the widely used Forest Vegetation Simulator (FVS) were adjusted to account for expected climate effects. This was accomplished by: (1) adding functions that link mortality and regeneration of species to climate variables expressing climatic suitability, (2) constructing a function linking site index to...

Addressing climate change in the forest vegetation simulator to assess impacts on landscape forest dynamics

Treesearch

Nicholas L. Crookston; Gerald E. Rehfeldt; Gary E. Dixon; Aaron R. Weiskittel

2010-01-01

To simulate stand-level impacts of climate change, predictors in the widely used Forest Vegetation Simulator (FVS) were adjusted to account for expected climate effects. This was accomplished by: (1) adding functions that link mortality and regeneration of species to climate variables expressing climatic suitability, (2) constructing a function linking site index to...

Methods, systems and apparatus for adjusting modulation index to improve linearity of phase voltage commands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gallegos-Lopez, Gabriel; Perisic, Milun; Kinoshita, Michael H.

2017-03-14

Embodiments of the present invention relate to methods, systems and apparatus for controlling operation of a multi-phase machine in a motor drive system. The disclosed embodiments provide a mechanism for adjusting modulation index of voltage commands to improve linearity of the voltage commands.

Vegetation extraction from high-resolution satellite imagery using the Normalized Difference Vegetation Index (NDVI)

NASA Astrophysics Data System (ADS)

AlShamsi, Meera R.

2016-10-01

Over the past years, there has been various urban development all over the UAE. Dubai is one of the cities that experienced rapid growth in both development and population. That growth can have a negative effect on the surrounding environment. Hence, there has been a necessity to protect the environment from these fast pace changes. One of the major impacts this growth can have is on vegetation. As technology is evolving day by day, there is a possibility to monitor changes that are happening on different areas in the world using satellite imagery. The data from these imageries can be utilized to identify vegetation in different areas of an image through a process called vegetation detection. Being able to detect and monitor vegetation is very beneficial for municipal planning and management, and environment authorities. Through this, analysts can monitor vegetation growth in various areas and analyze these changes. By utilizing satellite imagery with the necessary data, different types of vegetation can be studied and analyzed, such as parks, farms, and artificial grass in sports fields. In this paper, vegetation features are detected and extracted through SAFIY system (i.e. the Smart Application for Feature extraction and 3D modeling using high resolution satellite ImagerY) by using high-resolution satellite imagery from DubaiSat-2 and DEIMOS-2 satellites, which provide panchromatic images of 1m resolution and spectral bands (red, green, blue and near infrared) of 4m resolution. SAFIY system is a joint collaboration between MBRSC and DEIMOS Space UK. It uses image-processing algorithms to extract different features (roads, water, vegetation, and buildings) to generate vector maps data. The process to extract green areas (vegetation) utilize spectral information (such as, the red and near infrared bands) from the satellite images. These detected vegetation features will be extracted as vector data in SAFIY system and can be updated and edited by end-users, such as

78 FR 8530 - Price Index Adjustments for Contribution and Expenditure Limitations and Lobbyist Bundling...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-06

...As mandated by provisions of the Federal Election Campaign Act of 1971, as amended (``FECA'' or ``the Act''), the Federal Election Commission (``FEC'' or ``the Commission'') is adjusting certain contribution and expenditure limitations and the lobbyist bundling disclosure threshold set forth in the Act, to index the amounts for inflation. Additional details appear in the supplemental information that follows.

77 FR 9925 - Price Index Adjustments for Expenditure Limitations and Lobbyist Bundling Disclosure Threshold

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-21

...As mandated by provisions of the Federal Election Campaign Act of 1971, as amended (``FECA'' or ``the Act''), the Federal Election Commission (``FEC'' or ``the Commission'') is adjusting certain expenditure limitations and the lobbyist bundling disclosure threshold set forth in the Act, to index the amounts for inflation. Additional details appear in the supplemental information that follows.

75 FR 8353 - Price Index Adjustments for Expenditure Limitations and Lobbyist Bundling Disclosure Threshold

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-24

...As mandated by provisions of the Federal Election Campaign Act of 1971, as amended (``FECA'' or ``the Act''), the Federal Election Commission (``FEC'' or ``the Commission'') is adjusting certain expenditure limitations and the lobbyist bundling disclosure threshold set forth in the Act, to index the amounts for inflation. Additional details appear in the supplemental information that follows.

Relation of raw and cooked vegetable consumption to blood pressure: the INTERMAP Study

PubMed Central

Chan, Q; Stamler, J; Brown, I J; Daviglus, M L; Van Horn, L; Dyer, A R; Oude Griep, L M; Miura, K; Ueshima, H; Zhao, L; Nicholson, J K; Holmes, E; Elliott, P

2014-01-01

Inverse associations have been reported of overall vegetable intake to blood pressure (BP); whether such relations prevail for both raw and cooked vegetables has not been examined. Here we report cross-sectional associations of vegetable intakes with BP for 2195 Americans ages 40–59 in the International Study of Macro/Micronutrients and Blood Pressure (INTERMAP) using four standardized multi-pass 24-h dietary recalls and eight BP measurements. Relations to BP of raw and cooked vegetables consumption, and main individual constituents were assessed by multiple linear regression. Intakes of both total raw and total cooked vegetables considered separately were inversely related to BP in multivariate-adjusted models. Estimated average systolic BP differences associated with two s.d. differences in raw vegetable intake (68 g per 1000 kcal) and cooked vegetable intake (92 g per 1000 kcal) were −1.9 mm Hg (95% confidence interval (CI): −3.1, −0.8; P=0.001) and −1.3 mm Hg (95% CI: −2.5, −0.2; P=0.03) without body mass index (BMI) in the full model; −1.3 mm Hg (95% CI: −2.4, −0.2; P=0.02) and −0.9 mm Hg (95% CI: −2.0, 0.2; P=0.1) with additional adjustment for BMI. Among commonly consumed individual raw vegetables, tomatoes, carrots, and scallions related significantly inversely to BP. Among commonly eaten cooked vegetables, tomatoes, peas, celery, and scallions related significantly inversely to BP. PMID:24257514

Inversion of Farmland Soil Moisture in Large Region Based on Modified Vegetation Index

NASA Astrophysics Data System (ADS)

Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.

2018-04-01

Soil moisture is an important parameter for agricultural production. Efficient and accurate monitoring of soil moisture is an important link to ensure the safety of agricultural production. Remote sensing technology has been widely used in agricultural moisture monitoring because of its timeliness, cyclicality, dynamic tracking of changes in things, easy access to data, and extensive monitoring. Vegetation index and surface temperature are important parameters for moisture monitoring. Based on NDVI, this paper introduces land surface temperature and average temperature for optimization. This article takes the soil moisture in winter wheat growing area in Henan Province as the research object, dividing Henan Province into three main regions producing winter wheat and dividing the growth period of winter wheat into the early, middle and late stages on the basis of phenological characteristics and regional characteristics. Introducing appropriate correction factor during the corresponding growth period of winter wheat, correcting the vegetation index in the corresponding area, this paper establishes regression models of soil moisture on NDVI and soil moisture on modified NDVI based on correlation analysis and compare models. It shows that modified NDVI is more suitable as a indicator of soil moisture because of the better correlation between soil moisture and modified NDVI and the higher prediction accuracy of the regression model of soil moisture on modified NDVI. The research in this paper has certain reference value for winter wheat farmland management and decision-making.

Nanomaterials for the cleaning and pH adjustment of vegetable-tanned leather

NASA Astrophysics Data System (ADS)

Baglioni, Michele; Bartoletti, Angelica; Bozec, Laurent; Chelazzi, David; Giorgi, Rodorico; Odlyha, Marianne; Pianorsi, Diletta; Poggi, Giovanna; Baglioni, Piero

2016-02-01

Leather artifacts in historical collections and archives are often contaminated by physical changes such as soiling, which alter their appearance and readability, and by chemical changes which occur on aging and give rise to excessive proportion of acids that promote hydrolysis of collagen, eventually leading to gelatinization and loss of mechanical properties. However, both cleaning and pH adjustment of vegetable-tanned leather pose a great challenge for conservators, owing to the sensitivity of these materials to the action of solvents, especially water-based formulations and alkaline chemicals. In this study, the cleaning of historical leather samples was optimized by confining an oil-in-water nanostructured fluid in a highly retentive chemical hydrogel, which allows the controlled release of the cleaning fluid on sensitive surfaces. The chemical gel exhibits optimal viscoelasticity, which facilitates its removal after the application without leaving residues on the object. Nanoparticles of calcium hydroxide and lactate, dispersed in 2-propanol, were used to adjust the pH up to the natural value of leather, preventing too high alkalinity which causes swelling of fibers and denaturation of the collagen. The treated samples were characterized using scanning electron microscopy, controlled environment dynamic mechanical analysis, and infrared spectroscopy. The analytical assessment validated the use of tools derived from colloid and materials science for the preservation of collagen-based artifacts.

The Oslo Health Study: a Dietary Index estimating high intake of soft drinks and low intake of fruits and vegetables was positively associated with components of the metabolic syndrome.

PubMed

Høstmark, Arne Torbjørn

2010-12-01

A previous finding that soft drink intake is associated with increased serum triglycerides and decreased high-density-lipoprotein (HDL) cholesterol, both components of the metabolic syndrome (MetS), raises the question of whether other aspects of an unhealthy diet might be associated with MetS. Main MetS requirements are central obesity and 2 of the following: increased triglycerides, low HDL, increased systolic or diastolic blood pressure, and elevated fasting blood glucose. Of the 18 770 participants in the Oslo Health Study, there were 13 170 respondents (5997 men and 7173 women) with data on MetS factors (except fasting glucose) and on the components used to determine the Dietary Index score (calculated as the intake estimate of soft drinks divided by the sum of intake estimates of fruits and vegetables). MetSRisk was calculated as the sum of arbitrarily weighted factors positively associated with MetS divided by HDL cholesterol. Using regression analyses, the association of the Dietary Index with MetSRisk, with the number of MetS requirements present, and with the complete MetS was studied. In young, middle-aged, and senior men and women, there was, in general, a positive association (p < 0.001) between the Dietary Index and the MetS estimates, which persisted in regression models adjusted for sex, age, time since the last meal, intake of cheese, intake of fatty fish, intake of coffee, intake of alcohol, smoking, physical activity, education, and birthplace. Thus, an index reflecting a high intake of soft drinks and a low intake of fruit and vegetables was positively and independently associated with aspects of MetS.

Testing the Potential of Vegetation Indices for Land Use/cover Classification Using High Resolution Data

NASA Astrophysics Data System (ADS)

Karakacan Kuzucu, A.; Bektas Balcik, F.

2017-11-01

Accurate and reliable land use/land cover (LULC) information obtained by remote sensing technology is necessary in many applications such as environmental monitoring, agricultural management, urban planning, hydrological applications, soil management, vegetation condition study and suitability analysis. But this information still remains a challenge especially in heterogeneous landscapes covering urban and rural areas due to spectrally similar LULC features. In parallel with technological developments, supplementary data such as satellite-derived spectral indices have begun to be used as additional bands in classification to produce data with high accuracy. The aim of this research is to test the potential of spectral vegetation indices combination with supervised classification methods and to extract reliable LULC information from SPOT 7 multispectral imagery. The Normalized Difference Vegetation Index (NDVI), the Ratio Vegetation Index (RATIO), the Soil Adjusted Vegetation Index (SAVI) were the three vegetation indices used in this study. The classical maximum likelihood classifier (MLC) and support vector machine (SVM) algorithm were applied to classify SPOT 7 image. Catalca is selected region located in the north west of the Istanbul in Turkey, which has complex landscape covering artificial surface, forest and natural area, agricultural field, quarry/mining area, pasture/scrubland and water body. Accuracy assessment of all classified images was performed through overall accuracy and kappa coefficient. The results indicated that the incorporation of these three different vegetation indices decrease the classification accuracy for the MLC and SVM classification. In addition, the maximum likelihood classification slightly outperformed the support vector machine classification approach in both overall accuracy and kappa statistics.

Estimation of vegetation parameters such as Leaf Area Index from polarimetric SAR data

NASA Astrophysics Data System (ADS)

Hetz, Marina; Blumberg, Dan G.; Rotman, Stanley R.

2010-05-01

This work presents the analysis of the capability to use the radar backscatter coefficient in semi-arid zones to estimate the vegetation crown in terms of Leaf Area Index (LAI). The research area is characterized by the presence of a pine forest with shrubs as an underlying vegetation layer (understory), olive trees, natural grove areas and eucalyptus trees. The research area was imaged by an airborne RADAR system in L-band during February 2009. The imagery includes multi-look radar images. All the images were fully polarized i.e., HH, VV, HV polarizations. For this research we used the central azimuth angle (113° ). We measured LAI using the ?T Sun Scan Canopy Analysis System. Verification was done by analytic calculations and digital methods for the leaf's and needle's surface area. In addition, we estimated the radar extinction coefficient of the vegetation volume by comparing point calibration targets (trihedral corner reflectors with 150cm side length) within and without the canopy. The radar extinction in co- polarized images was ~26dB and ~24dB for pines and olives respectively, compared to the same calibration target outside the vegetation. We used smaller trihedral corner reflectors (41cm side length) and covered them with vegetation to measure the correlation between vegetation density, LAI and radar backscatter coefficient for pines and olives under known conditions. An inverse correlation between the radar backscatter coefficient of the trihedral corner reflectors covered by olive branches and the LAI of those branches was observed. The correlation between LAI and the optical transmittance was derived using the Beer-Lambert law. In addition, comparing this law's principle to the principle of the radar backscatter coefficient production, we derived the equation that connects between the radar backscatter coefficient and LAI. After extracting the radar backscatter coefficient of forested areas, all the vegetation parameters were used as inputs for the

The relationship between fruit and vegetable intake with gastroesophageal reflux disease in Iranian adults

PubMed Central

Keshteli, Ammar Hassanzadeh; Shaabani, Pouria; Tabibian, Seyed-Reza; Saneei, Parvane; Esmaillzadeh, Ahmad; Adibi, Peyman

2017-01-01

Background: Findings from studies that investigated the relationship between fruit and vegetable intake with gastroesophageal reflux disease (GERD) were inconsistent. We aimed to assess the relationship between fruit and vegetable consumption and GERD among a large group of Iranian adults. Materials and Methods: In this cross-sectional study on 3979 adults, a validated food frequency questionnaire was used to assess usual dietary intakes including fruits and vegetables. The presence of heartburn sometimes or more during the past 3 months were considered as having GERD. Results: The prevalence of GERD among study population was 23.9%. After adjustment for potential confounding factors, those with the highest consumption of fruits had 25% lower risk for GERD, in comparison to those with the lowest intake (odds ratio [OR] = 0.75, 95% confidence interval [CI]: 0.59–0.97). Vegetable intake was not significantly related to the risk of GERD in crude or multivariable-adjusted models. However, participants with the highest intake of fruits and vegetables had 33% lower risk of GERD (OR = 0.67, 95% CI: 0.51–0.88), after adjustment for confounders. Women with the highest fruit and vegetable intake had 36% lower risk for GERD (OR = 0.64, 95% CI: 0.45–0.91). Overweight/obese participants in the last tertile of fruit consumption had 42% lower risk for GERD, in comparison to the first category (OR = 0.58, 95% CI: 0.42–0.83). Furthermore, participants with body mass index higher than 25 kg/m2 and higher intake of fruits and vegetables had 53% lower risk for GERD (OR = 0.47, 95% CI: 0.32-0.69). Conclusion: We found inverse associations between fruit intake as well as fruit and vegetable intake and risk of GERD among Iranian adults. PMID:29259636

The relationship between fruit and vegetable intake with gastroesophageal reflux disease in Iranian adults.

PubMed

Keshteli, Ammar Hassanzadeh; Shaabani, Pouria; Tabibian, Seyed-Reza; Saneei, Parvane; Esmaillzadeh, Ahmad; Adibi, Peyman

2017-01-01

Findings from studies that investigated the relationship between fruit and vegetable intake with gastroesophageal reflux disease (GERD) were inconsistent. We aimed to assess the relationship between fruit and vegetable consumption and GERD among a large group of Iranian adults. In this cross-sectional study on 3979 adults, a validated food frequency questionnaire was used to assess usual dietary intakes including fruits and vegetables. The presence of heartburn sometimes or more during the past 3 months were considered as having GERD. The prevalence of GERD among study population was 23.9%. After adjustment for potential confounding factors, those with the highest consumption of fruits had 25% lower risk for GERD, in comparison to those with the lowest intake (odds ratio [OR] = 0.75, 95% confidence interval [CI]: 0.59-0.97). Vegetable intake was not significantly related to the risk of GERD in crude or multivariable-adjusted models. However, participants with the highest intake of fruits and vegetables had 33% lower risk of GERD (OR = 0.67, 95% CI: 0.51-0.88), after adjustment for confounders. Women with the highest fruit and vegetable intake had 36% lower risk for GERD (OR = 0.64, 95% CI: 0.45-0.91). Overweight/obese participants in the last tertile of fruit consumption had 42% lower risk for GERD, in comparison to the first category (OR = 0.58, 95% CI: 0.42-0.83). Furthermore, participants with body mass index higher than 25 kg/m 2 and higher intake of fruits and vegetables had 53% lower risk for GERD (OR = 0.47, 95% CI: 0.32-0.69). We found inverse associations between fruit intake as well as fruit and vegetable intake and risk of GERD among Iranian adults.

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 2; Implementation, Analysis and Validation

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Samanta, Arindam; Schull, Mitchell A.; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramajrushna R,; Knyazikhin, Yuri; Myneni, Ranga B.

2008-01-01

The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the intercomparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.

Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland.

PubMed

Ren, Shilong; Chen, Xiaoqiu; An, Shuai

2017-04-01

Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland

NASA Astrophysics Data System (ADS)

Ren, Shilong; Chen, Xiaoqiu; An, Shuai

2017-04-01

Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

Estimating riparian and agricultural evapotranspiration by reference crop evapotranspiration and MODIS Enhanced Vegetation Index

USGS Publications Warehouse

Nagler, Pamela L.; Glenn, Edward P.; Nguyen, Uyen; Scott, Russell; Doody, Tania

2013-01-01

Dryland river basins frequently support both irrigated agriculture and riparian vegetation and remote sensing methods are needed to monitor water use by both crops and natural vegetation in irrigation districts. We developed an algorithm for estimating actual evapotranspiration (ETa) based on the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the EOS-1 Terra satellite and locally-derived measurements of reference crop ET (ETo). The algorithm was calibrated with five years of ETa data from three eddy covariance flux towers set in riparian plant associations on the upper San Pedro River, Arizona, supplemented with ETa data for alfalfa and cotton from the literature. The algorithm was based on an equation of the form ETa = ETo [a(1 − e−bEVI) − c], where the term (1 − e−bEVI) is derived from the Beer-Lambert Law to express light absorption by a canopy, with EVI replacing leaf area index as an estimate of the density of light-absorbing units. The resulting algorithm capably predicted ETa across riparian plants and crops (r2 = 0.73). It was then tested against water balance data for five irrigation districts and flux tower data for two riparian zones for which season-long or multi-year ETa data were available. Predictions were within 10% of measured results in each case, with a non-significant (P = 0.89) difference between mean measured and modeled ETa of 5.4% over all validation sites. Validation and calibration data sets were combined to present a final predictive equation for application across crops and riparian plant associations for monitoring individual irrigation districts or for conducting global water use assessments of mixed agricultural and riparian biomes.

Fruit and vegetable intake, body mass index and waist circumference among young female students in Isfahan.

PubMed

Ghalaeh, Reihaneh Seyed; Gholi, Zahra; Bank, Sahar Saraf; Azadbakht, Leila

2012-01-01

Obesity is growing rapidly in our country. Nutrition is an important issue of obesity. The aim of this study was to determine the association between fruit and vegetable intake with the waist circumference and the body mass index (BMI) among young female university students. This cross-sectional study was conducted on 236 healthy female university students aged between 18 and 30 years old, who were selected randomly from the students of Isfahan University of Medical Sciences, Iran. A previously validated semi-quantitative food frequency questionnaire was used to assess the entire dietary component intake. Physical activity was assessed by daily recording of the physical activities. The prevalence of obesity, central adiposity and overweight was 1.7, 0.9 and 8.1%, respectively. The mean value of BMI and the waist circumference was 21.54 kg/m(2) and 70.37 cm, respectively. There was an inverse correlation between the fruit and vegetable intake and body weight (r = -0.1, P = 0.03) as well as BMI (r = -0.1, P = 0.04) and also there was an inverse correlation between the fruit intake and body weight (r = -0.1, P = 0.01) and BMI (r = -0.1, P = 0.01). There was no significant correlation between fruit and vegetable as well as fruit or vegetable separately with the waist circumference. There were significant correlations between fruit and also fruit and vegetable and body weight and BMI among female university students. There was no significant correlation between fruit and vegetable as well as fruit or vegetable separately with waist circumference.

Validation of Vegetation Index Time Series from Suomi NPP Visible Infrared Imaging Radiometer Suite Using Tower Radiation Flux Measurements

NASA Astrophysics Data System (ADS)

Miura, T.; Kato, A.; Wang, J.; Vargas, M.; Lindquist, M.

2015-12-01

Satellite vegetation index (VI) time series data serve as an important means to monitor and characterize seasonal changes of terrestrial vegetation and their interannual variability. It is, therefore, critical to ensure quality of such VI products and one method of validating VI product quality is cross-comparison with in situ flux tower measurements. In this study, we evaluated the quality of VI time series derived from Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft by cross-comparison with in situ radiation flux measurements at select flux tower sites over North America and Europe. VIIRS is a new polar-orbiting satellite sensor series, slated to replace National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer in the afternoon overpass and to continue the highly-calibrated data streams initiated with Moderate Resolution Imaging Spectrometer of National Aeronautics and Space Administration's Earth Observing System. The selected sites covered a wide range of biomes, including croplands, grasslands, evergreen needle forest, woody savanna, and open shrublands. The two VIIRS indices of the Top-of-Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI) and the atmospherically-corrected, Top-of-Canopy (TOC) Enhanced Vegetation Index (EVI) (daily, 375 m spatial resolution) were compared against the TOC NDVI and a two-band version of EVI (EVI2) calculated from tower radiation flux measurements, respectively. VIIRS and Tower VI time series showed comparable seasonal profiles across biomes with statistically significant correlations (> 0.60; p-value < 0.01). "Start-of-season (SOS)" phenological metric values extracted from VIIRS and Tower VI time series were also highly compatible (R2 > 0.95), with mean differences of 2.3 days and 5.0 days for the NDVI and the EVI, respectively. These results indicate that VIIRS VI time series can capture seasonal evolution of

White vegetables: glycemia and satiety.

PubMed

Anderson, G Harvey; Soeandy, Chesarahmia Dojo; Smith, Christopher E

2013-05-01

The objective of this review is to discuss the effect of white vegetable consumption on glycemia, satiety, and food intake. White vegetables is a term used to refer to vegetables that are white or near white in color and include potatoes, cauliflowers, turnips, onions, parsnips, white corn, kohlrabi, and mushrooms (technically fungi but generally considered a vegetable). They vary greatly in their contribution to the energy and nutrient content of the diet and glycemia and satiety. As with other foods, the glycemic effect of many white vegetables has been measured. The results illustrate that interpretation of the semiquantitative comparative ratings of white vegetables as derived by the glycemic index must be context dependent. As illustrated by using the potato as an example, the glycemic index of white vegetables can be misleading if not interpreted in the context of the overall contribution that the white vegetable makes to the carbohydrate and nutrient composition of the diet and their functionality in satiety and metabolic control within usual meals. It is concluded that application of the glycemic index in isolation to judge the role of white vegetables in the diet and, specifically in the case of potato as consumed in ad libitum meals, has led to premature and possibly counterproductive dietary guidance.

Global-scale analysis of vegetation indices for moderate resolution monitoring of terrestrial vegetation

NASA Astrophysics Data System (ADS)

Huete, Alfredo R.; Didan, Kamel; van Leeuwen, Willem J. D.; Vermote, Eric F.

1999-12-01

Vegetation indices have emerged as important tools in the seasonal and inter-annual monitoring of the Earth's vegetation. They are radiometric measures of the amount and condition of vegetation. In this study, the Sea-viewing Wide Field-of-View sensor (SeaWiFS) is used to investigate coarse resolution monitoring of vegetation with multiple indices. A 30-day series of SeaWiFS data, corrected for molecular scattering and absorption, was composited to cloud-free, single channel reflectance images. The normalized difference vegetation index (NDVI) and an optimized index, the enhanced vegetation index (EVI), were computed over various 'continental' regions. The EVI had a normal distribution of values over the continental set of biomes while the NDVI was skewed toward higher values and saturated over forested regions. The NDVI resembled the skewed distributions found in the red band while the EVI resembled the normal distributions found in the NIR band. The EVI minimized smoke contamination over extensive portions of the tropics. As a result, major biome types with continental regions were discriminable in both the EVI imagery and histograms, whereas smoke and saturation considerably degraded the NDVI histogram structure preventing reliable discrimination of biome types.

Simulation of two-dimensional adjustable liquid gradient refractive index (L-GRIN) microlens

NASA Astrophysics Data System (ADS)

Le, Zichun; Wu, Xiang; Sun, Yunli; Du, Ying

2017-07-01

In this paper, a two-dimensional liquid gradient refractive index (L-GRIN) microlens is designed which can be used in adjusting focusing direction and focal spot of light beam. Finite element method (FEM) is used to simulate the convection diffusion process happening in core inlet flow and cladding inlet flow. And the ray tracing method shows us the light beam focusing effect including the extrapolation of focal length and output beam spot size. When the flow rates of the core and cladding fluids are held the same between the internal and external, left and right, and upper and lower inlets, the focal length varied from 313 μm to 53.3 μm while the flow rate of liquids ranges from 500 pL/s to 10,000 pL/s. While the core flow rate is bigger than the cladding inlet flow rate, the light beam will focus on a light spot with a tunable size. By adjusting the ratio of cladding inlet flow rate including Qright/Qleft and Qup/Qdown, we get the adjustable two-dimensional focus direction rather than the one-dimensional focusing. In summary, by adjusting the flow rate of core inlet and cladding inlet, the focal length, output beam spot and focusing direction of the input light beam can be manipulated. We suppose this kind of flexible microlens can be used in integrated optics and lab-on-a-chip system.

Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

NASA Technical Reports Server (NTRS)

Ulsig, Laura; Nichol, Caroline J.; Huemmrich, Karl F.; Landis, David R.; Middleton, Elizabeth M.; Lyapustin, Alexei I.; Mammarella, Ivan; Levula, Janne; Porcar-Castell, Albert

2017-01-01

Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS) were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction) processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R (sup 2) equals 0.36-0.8), which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R (sup 2) is greater than 0.6 in all cases). The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.

Analysis of smoke and cloud impact on seasonal and interannual variations in normalized difference vegetation index in Amazon

NASA Astrophysics Data System (ADS)

Kobayashi, H.; Dye, D. G.

2004-12-01

Normalized difference vegetation index (NDVI) derived from National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR) is a unique measurement of long-term variations in global vegetation dynamics. The NDVI data have been used for the detection of the seasonal and interannual variations in vegetation. However, as reported in several studies, NDVI decreases with the increase in clouds and/or smoke aerosol contaminated in the pixels. This study assesses the smoke and clouds effect on long-term Global Inventory Modeling and Mapping Studies (GIMMS) and Pathfinder AVHRR Land (PAL) NDVI data in Amazon. This knowledge will help developing the correction method in the tropics in the future. To assess the smoke and cloud effects on GIMMS and PAL, we used another satellite-derived data sets; NDVI derived from SPOT/VEGETATION (VGT) data and Aerosol Index (AI) derived from Total Ozone Mapping Spectrometer (TOMS). Since April 1998, VGT has measured the earth surface globally including in Amazon. The advantage of the VGT is that it has blue channel where the smoke and cloud can be easily detected. By analyzing the VGT NDVI and comparing with the AVHRR-based NDVI, we inferred smoke and cloud effect on the AVHRR-based NDVI. From the results of the VGT analysis, we found the large NDVI seasonality in South and Southeastern Amazon. In these areas, the NDVI gradually increased from April to July and decreased from August to October. However the sufficient NDVI data were not existed from August to November when the smoke and cloud pixels were masked using blue reflectance. Thus it is said that the smoke and clouds mainly cause the large decreases in NDVI between August and November and NDVI has little vegetation signature in these months. Also we examined the interannual variations in NDVI and smoke aerosol. Then the decrease in NDVI is well consistent with the increase in the increase in AI. Our results suggest that the months between April

Fruit and vegetable intake, body mass index and waist circumference among young female students in Isfahan

PubMed Central

Ghalaeh, Reihaneh Seyed; Gholi, Zahra; Bank, Sahar Saraf; Azadbakht, Leila

2012-01-01

Background: Obesity is growing rapidly in our country. Nutrition is an important issue of obesity. The aim of this study was to determine the association between fruit and vegetable intake with the waist circumference and the body mass index (BMI) among young female university students. Materials and Methods: This cross-sectional study was conducted on 236 healthy female university students aged between 18 and 30 years old, who were selected randomly from the students of Isfahan University of Medical Sciences, Iran. A previously validated semi-quantitative food frequency questionnaire was used to assess the entire dietary component intake. Physical activity was assessed by daily recording of the physical activities. Findings: The prevalence of obesity, central adiposity and overweight was 1.7, 0.9 and 8.1%, respectively. The mean value of BMI and the waist circumference was 21.54 kg/m2 and 70.37 cm, respectively. There was an inverse correlation between the fruit and vegetable intake and body weight (r = -0.1, P = 0.03) as well as BMI (r = -0.1, P = 0.04) and also there was an inverse correlation between the fruit intake and body weight (r = -0.1, P = 0.01) and BMI (r = -0.1, P = 0.01). There was no significant correlation between fruit and vegetable as well as fruit or vegetable separately with the waist circumference. Conclusion: There were significant correlations between fruit and also fruit and vegetable and body weight and BMI among female university students. There was no significant correlation between fruit and vegetable as well as fruit or vegetable separately with waist circumference. PMID:23555132

Soil moisture status estimation over Three Gorges area with Landsat TM data based on temperature vegetation dryness index

NASA Astrophysics Data System (ADS)

Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang

2011-12-01

Soil moisture is the important indicator of climate, hydrology, ecology, agriculture and other parameters of the land surface and atmospheric interface. Soil moisture plays an important role on the water and energy exchange at the land surface/atmosphere interface. Remote sensing can provide information on large area quickly and easily, so it is significant to do research on how to monitor soil moisture by remote sensing. This paper presents a method to assess soil moisture status using Landsat TM data over Three Gorges area in China based on TVDI. The potential of Temperature- Vegetation Dryness Index (TVDI) from Landsat TM data in assessing soil moisture was investigated in this region. After retrieving land surface temperature and vegetation index a TVDI model based on the features of Ts-NDVI space is established. And finally, soil moisture status is estimated according to TVDI. It shows that TVDI has the advantages of stability and high accuracy to estimating the soil moisture status.

Comparison of Vegetation Indices from Rpas and SENTINEL-2 Imagery for Detecting Permanent Pastures

NASA Astrophysics Data System (ADS)

Piragnolo, M.; Lusiani, G.; Pirotti, F.

2018-04-01

Permanent pastures (PP) are defined as grasslands, which are not subjected to any tillage, but only to natural growth. They are important for local economies in the production of fodder and pastures (Ali et al. 2016). Under these definitions, a pasture is permanent when it is not under any crop-rotation, and its production is related to only irrigation, fertilization and mowing. Subsidy payments to landowners require monitoring activities to determine which sites can be considered PP. These activities are mainly done with visual field surveys by experienced personnel or lately also using remote sensing techniques. The regional agency for SPS subsidies, the Agenzia Veneta per i Pagamenti in Agricoltura (AVEPA) takes care of monitoring and control on behalf of the Veneto Region using remote sensing techniques. The investigation integrate temporal series of Sentinel-2 imagery with RPAS. Indeed, the testing area is specific region were the agricultural land is intensively cultivated for production of hay harvesting four times every year between May and October. The study goal of this study is to monitor vegetation presence and amount using the Normalized Difference Vegetation Index (NDVI), the Soil-adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Built Index (NDBI). The overall objective is to define for each index a set of thresholds to define if a pasture can be classified as PP or not and recognize the mowing.

Evaluation of vegetation post-fire resilience in the Alpine region using descriptors derived from MODIS spectral index time series

NASA Astrophysics Data System (ADS)

Di Mauro, Biagio; Fava, Francesco; Busetto, Lorenzo; Crosta, Giovanni Franco; Colombo, Roberto

2013-04-01

In this study a method based on the analysis of MODerate-resolution Imaging Spectroradiometer (MODIS) time series is proposed to estimate the post-fire resilience of mountain vegetation (broadleaf forest and prairies) in the Italian Alps. Resilience is defined herewith as the ability of a dynamical system to counteract disturbances. It can be quantified by the amount of time the disturbed system takes to resume, in statistical terms, an ecological functionality comparable with its undisturbed behavior. Satellite images of the Normalized Difference Vegetation Index (NDVI) and of the Enhanced Vegetation Index (EVI) with spatial resolution of 250m and temporal resolution of 16 days in the 2000-2012 time period were used. Wildfire affected areas in the Lombardy region between the years 2000 and 2010 were analysed. Only large fires (affected area >40ha) were selected. For each burned area, an undisturbed adjacent control site was located. Data pre-processing consisted in the smoothing of MODIS time series for noise removal and then a double logistic function was fitted. Land surface phenology descriptors (proxies for growing season start/end/length and green biomass) were extracted in order to characterize the time evolution of the vegetation. Descriptors from a burned area were compared to those extracted from the respective control site by means of the one-way analysis of variance. According to the number of subsequent years which exhibit statistically meaningful difference between burned and control site, five classes of resilience were identified and a set of thematic maps was created for each descriptor. The same method was applied to all 84 aggregated events and to events aggregated by main land cover. EVI index results more sensitive to fire impact than NDVI index. Analysis shows that fire causes both a reduction of the biomass and a variation in the phenology of the Alpine vegetation. Results suggest an average ecosystem resilience of 6-7 years. Moreover

Multi-index time series monitoring of drought and fire effects on desert grasslands

USGS Publications Warehouse

Villarreal, Miguel; Norman, Laura M.; Buckley, Steven; Wallace, Cynthia S.A.; Coe, Michelle A.

2016-01-01

The Western United States is expected to undergo both extended periods of drought and longer wildfire seasons under forecasted global climate change and it is important to understand how these disturbances will interact and affect recovery and composition of plant communities in the future. In this research paper we describe the temporal response of grassland communities to drought and fire in southern Arizona, where land managers are using repeated, prescribed fire as a habitat restoration tool. Using a 25-year atlas of fire locations, we paired sites with multiple fires to unburned control areas and compare satellite and field-based estimates of vegetation cover over time. Two hundred and fifty Landsat TM images, dating from 1985–2011, were used to derive estimates of Total Vegetation Fractional Cover (TVFC) of live and senescent grass using the Soil-Adjusted Total Vegetation Index (SATVI) and post-fire vegetation greenness using the Normalized Difference Vegetation Index (NDVI). We also implemented a Greenness to Cover Index that is the difference of time-standardized SATVI-TVFC and NDVI values at a given time and location to identify post-fire shifts in native, non-native, and annual plant cover. The results highlight anomalous greening and browning during drought periods related to amounts of annual and non-native plant cover present. Results suggest that aggressive application of prescribed fire may encourage spread of non-native perennial grasses and annual plants, particularly during droughts.

76 FR 8368 - Price Index Adjustments for Contribution and Expenditure Limits and Lobbyist Bundling Disclosure...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-14

...As mandated by provisions of the Federal Election Campaign Act of 1971, as amended (``FECA'' or ``the Act''), the Federal Election Commission (``FEC'' or ``the Commission'') is adjusting certain contribution and expenditure limits and the lobbyist bundling disclosure threshold set forth in the Act, to index the amounts for inflation. Additional details appear in the supplemental information that follows.

How universal is the relationship between remotely sensed vegetation indices and crop leaf area index? A global assessment

USDA-ARS?s Scientific Manuscript database

This study aims to assess the relationship between Leaf Area Index (LAI) and remotely sensed Vegetation Indices (VIs) for major crops, based on a globally explicit dataset of in situ LAI measurements over a significant set of locations. We used a total of 1394 LAI measurements from 29 sites spannin...

Assessing Plant Senescence Reflectance Index retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland

NASA Astrophysics Data System (ADS)

Ren, S.; Chen, X.; An, S.

2016-12-01

Other than green vegetation indices, Plant Senescence Reflectance Index (PSRI) is sensitive to carotenoids/chlorophyll ratio in plant leaves, and shows a reversed bell curve during the growing season. Up to now, performances of PSRI in monitoring vegetation phenology are still unclear. Here, we used Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 to determine PSRI-derived start (SOS) and end (EOS) dates of the growing season in the Inner Mongolian Grassland, and validated the reliability of PSRI-derived SOS and EOS dates using Normalized Difference Vegetation Index (NDVI) derived SOS and EOS dates. Then, we conducted temporal and spatial correlation analyses between SOS/EOS date and climatic factors. Moreover, we revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

White Vegetables: Glycemia and Satiety12

PubMed Central

Anderson, G. Harvey; Soeandy, Chesarahmia Dojo; Smith, Christopher E.

2013-01-01

The objective of this review is to discuss the effect of white vegetable consumption on glycemia, satiety, and food intake. White vegetables is a term used to refer to vegetables that are white or near white in color and include potatoes, cauliflowers, turnips, onions, parsnips, white corn, kohlrabi, and mushrooms (technically fungi but generally considered a vegetable). They vary greatly in their contribution to the energy and nutrient content of the diet and glycemia and satiety. As with other foods, the glycemic effect of many white vegetables has been measured. The results illustrate that interpretation of the semiquantitative comparative ratings of white vegetables as derived by the glycemic index must be context dependent. As illustrated by using the potato as an example, the glycemic index of white vegetables can be misleading if not interpreted in the context of the overall contribution that the white vegetable makes to the carbohydrate and nutrient composition of the diet and their functionality in satiety and metabolic control within usual meals. It is concluded that application of the glycemic index in isolation to judge the role of white vegetables in the diet and, specifically in the case of potato as consumed in ad libitum meals, has led to premature and possibly counterproductive dietary guidance. PMID:23674805

Policy efficiency in the field of food sustainability. The adjusted food agriculture and nutrition index.

PubMed

Agovino, Massimiliano; Cerciello, Massimiliano; Gatto, Andrea

2018-07-15

This work introduces a revised version of the Food Sustainability Index, proposed by the Economist Intelligence Unit and the Barilla Center for Food and Nutrition in 2016. Our Adjusted Food Sustainability Index features two important advantages: 1) it employs the Mazziotta-Pareto method to compute weights, hence granting an objective aggregation criterion and 2) it does not take policy variables into account, thus focusing on the status quo. The policy variables are aggregated into the Policy Index, measuring the quality of the food sustainability policies. We compute the two indices for 25 countries worldwide, then we use the Data Envelopment Analysis to evaluate policy efficiency. Our results show that country-level variation in policy efficiency is wide and policies affect food sustainability significantly, especially when they target nutritional challenges. Copyright © 2018 Elsevier Ltd. All rights reserved.

Adjusting site index and age to account for genetic effects in yield equations for loblolly pine

Treesearch

Steven A. Knowe; G. Sam Foster

2010-01-01

Nine combinations of site index curves and age adjustments methods were evaluated for incorporating genetic effects for open-pollinated loblolly pine (Pinus taeda L.) families. An explicit yield system consisting of dominant height, basal area, and merchantable green weight functions was used to compare the accuracy of predictions associated with...

A Methodology for Surface Soil Moisture and Vegetation Optical Depth Retrieval Using the Microwave Polarization Difference Index

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Richard; Walker, Jeffrey; Zukor, Dorothy J. (Technical Monitor)

2001-01-01

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz brightness temperature observations from the Scanning Multichannel Microwave Radiometer over several test sites in Illinois. Results using only nighttime data are presented at this time, due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a non-linear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness. Surface temperature is derived by a procedure using high frequency vertically polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and is totally independent of wavelength. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors.

Waist Circumference Adjusted for Body Mass Index and Intra-Abdominal Fat Mass

PubMed Central

Berentzen, Tina Landsvig; Ängquist, Lars; Kotronen, Anna; Borra, Ronald; Yki-Järvinen, Hannele; Iozzo, Patricia; Parkkola, Riitta; Nuutila, Pirjo; Ross, Robert; Allison, David B.; Heymsfield, Steven B.; Overvad, Kim; Sørensen, Thorkild I. A.; Jakobsen, Marianne Uhre

2012-01-01

Background The association between waist circumference (WC) and mortality is particularly strong and direct when adjusted for body mass index (BMI). One conceivable explanation for this association is that WC adjusted for BMI is a better predictor of the presumably most harmful intra-abdominal fat mass (IAFM) than WC alone. We studied the prediction of abdominal subcutaneous fat mass (ASFM) and IAFM by WC alone and by addition of BMI as an explanatory factor. Methodology/Principal Findings WC, BMI and magnetic resonance imaging data from 742 men and women who participated in clinical studies in Canada and Finland were pooled. Total adjusted squared multiple correlation coefficients (R2) of ASFM and IAFM were calculated from multiple linear regression models with WC and BMI as explanatory variables. Mean BMI and WC of the participants in the pooled sample were 30 kg/m2 and 102 cm, respectively. WC explained 29% of the variance in ASFM and 51% of the variance in IAFM. Addition of BMI to WC added 28% to the variance explained in ASFM, but only 1% to the variance explained in IAFM. Results in subgroups stratified by study center, sex, age, obesity level and type 2 diabetes status were not systematically different. Conclusion/Significance The prediction of IAFM by WC is not improved by addition of BMI. PMID:22384179

Vegetative response to water availability on the San Carlos Apache Reservation

USGS Publications Warehouse

Petrakis, Roy; Wu, Zhuoting; McVay, Jason; Middleton, Barry R.; Dye, Dennis G.; Vogel, John M.

2016-01-01

On the San Carlos Apache Reservation in east-central Arizona, U.S.A., vegetation types such as ponderosa pine forests, pinyon-juniper woodlands, and grasslands have significant ecological, cultural, and economic value for the Tribe. This value extends beyond the tribal lands and across the Western United States. Vegetation across the Southwestern United States is susceptible to drought conditions and fluctuating water availability. Remotely sensed vegetation indices can be used to measure and monitor spatial and temporal vegetative response to fluctuating water availability conditions. We used the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Modified Soil Adjusted Vegetation Index II (MSAVI2) to measure the condition of three dominant vegetation types (ponderosa pine forest, woodland, and grassland) in response to two fluctuating environmental variables: precipitation and the Standardized Precipitation Evapotranspiration Index (SPEI). The study period covered 2002 through 2014 and focused on a region within the San Carlos Apache Reservation. We determined that grassland and woodland had a similar moderate to strong, year-round, positive relationship with precipitation as well as with summer SPEI. This suggests that these vegetation types respond negatively to drought conditions and are more susceptible to initial precipitation deficits. Ponderosa pine forest had a comparatively weaker relationship with monthly precipitation and summer SPEI, indicating that it is more buffered against short-term drought conditions. This research highlights the response of multiple, dominant vegetation types to seasonal and inter-annual water availability. This research demonstrates that multi-temporal remote sensing imagery can be an effective tool for the large scale detection of vegetation response to adverse impacts from climate change and support potential management practices such as increased monitoring and management of drought-affected areas. Different

Normalized difference vegetation index (ndvi) analysis for land cover types using landsat 8 oli in besitang watershed, Indonesia

NASA Astrophysics Data System (ADS)

Zaitunah, A.; Samsuri; Ahmad, A. G.; Safitri, R. A.

2018-03-01

Watershed is an ecosystem area confined by topography and has function as a catcher, storage, and supplier of water, sediments, pollutants and nutrients in the river system and exit through a single outlet. Various activities around watershed areas of Besitang have changed the land cover and vegetation index (NDVI) that exist in the region. In order to detect changes in land cover and NDVI quickly and accurately, we used remote sensing technology and geographic information systems (GIS). The study aimed to assess changes in land cover and vegetation density (NDVI) between 2005 and 2015, as well as obtaining the density of vegetation (NDVI) on each of the land cover of 2005 and 2015. The research showed the extensive of forest area of 949.65 Ha and a decline of mangrove forest area covering an area of 2,884.06 Ha. The highest vegetation density reduced 39,714.58 Ha, and rather dense increased 24,410.72 Ha between 2005 and 2015. The land cover that have the highest NDVI value range with very dense vegetation density class is the primary dry forest (0.804 to 0.876), followed by secondary dry forest (0.737 to 0.804) for 2015. In 2015 the land cover has NDVI value range the primary dry forest (0.513 to 0.57), then secondary dry forest (0.456 to 0.513) with dense vegetation density class

A MODIS-based vegetation index climatology

USDA-ARS?s Scientific Manuscript database

Our motivation here is to provide information for the NASA Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval algorithms (launch in 2014). Vegetation attenuates the signal and the algorithms must correct for this effect. One approach is to use data that describes the canopy water ...

White Light Emission from Vegetable Extracts

NASA Astrophysics Data System (ADS)

Singh, Vikram; Mishra, Ashok K.

2015-06-01

A mixture of extracts from two common vegetables, red pomegranate and turmeric, when photoexcited at 380 nm, produced almost pure white light emission (WLE) with Commission Internationale d’Eclairage (CIE) chromaticity index (0.35, 0.33) in acidic ethanol. It was also possible to obtain WLE in polyvinyl alcohol film (0.32, 0.25), and in gelatin gel (0.26, 0.33) using the same extract mixture. The colour temperature of the WLE was conveniently tunable by simply adjusting the concentrations of the component emitters. The primary emitting pigments responsible for contributing to WLE were polyphenols and anthocyanins from pomegranate, and curcumin from turmeric. It was observed that a cascade of Forster resonance energy transfer involving polyphenolics, curcumin and anthocyanins played a crucial role in obtaining a CIE index close to pure white light. The optimized methods of extraction of the two primary emitting pigments from their corresponding plant sources are simple, cheap and fairly green.

Vegetation Coverage Mapping and Soil Effect Correction in Estimating Vegetation Water Content and Dry Biomass from Satellites

NASA Astrophysics Data System (ADS)

Huang, J.; Chen, D.

2005-12-01

Vegetation water content (VWC) attracts great research interests in hydrology research in recent years. As an important parameter describing the horizontal expansion of vegetation, vegetation coverage is essential to implement soil effect correction for partially vegetated fields to estimate VWC accurately. Ground measurements of corn and soybeans in SMEX02 resulted in an identical expolinear relationship between vegetation coverage and leaf area index (LAI), which is used for vegetation coverage mapping. Results illustrated two parts of LAI growth quantitatively: the horizontal expansion of leaf coverage and the vertical accumulation of leaf layers. It is believed that the former part contributes significantly to LAI growth at initial vegetation growth stage and the latter is more dominant after vegetation coverage reaches a certain level. The Normalized Difference Water Index (NDWI) using short-wave infrared bands is convinced for its late saturation at high LAI values, in contrast to the Normalized Difference Vegetation Index (NDVI). NDWI is then utilized to estimate LAI, via another expolinear relationship, which is evidenced having vegetation species independency in study of corn and soybeans in SMEX02 sites. It is believed that the surface reflectance measured at satellites spectral bands are the mixed results of signals reflected from vegetation and bare soil, especially at partially vegetated fields. A simple linear mixture model utilizing vegetation coverage information is proposed to correct soil effect in such cases. Surface reflectance fractions for -rpure- vegetation are derived from the model. Comparing with ground measurements, empirical models using soil effect corrected vegetation indices to estimate VWC and dry biomass (DB) are generated. The study enhanced the in-depth understanding of the mechanisms how vegetation growth takes effect on satellites spectral reflectance with and without soil effect, which are particularly useful for modeling in

Multifractal Downscaling of Rainfall Using Normalized Difference Vegetation Index (NDVI) in the Andes Plateau.

PubMed

Duffaut Espinosa, L A; Posadas, A N; Carbajal, M; Quiroz, R

2017-01-01

In this paper, a multifractal downscaling technique is applied to adequately transformed and lag corrected normalized difference vegetation index (NDVI) in order to obtain daily estimates of rainfall in an area of the Peruvian Andean high plateau. This downscaling procedure is temporal in nature since the original NDVI information is provided at an irregular temporal sampling period between 8 and 11 days, and the desired final scale is 1 day. The spatial resolution of approximately 1 km remains the same throughout the downscaling process. The results were validated against on-site measurements of meteorological stations distributed in the area under study.

Multifractal Downscaling of Rainfall Using Normalized Difference Vegetation Index (NDVI) in the Andes Plateau

PubMed Central

Posadas, A. N.; Carbajal, M.; Quiroz, R.

2017-01-01

In this paper, a multifractal downscaling technique is applied to adequately transformed and lag corrected normalized difference vegetation index (NDVI) in order to obtain daily estimates of rainfall in an area of the Peruvian Andean high plateau. This downscaling procedure is temporal in nature since the original NDVI information is provided at an irregular temporal sampling period between 8 and 11 days, and the desired final scale is 1 day. The spatial resolution of approximately 1 km remains the same throughout the downscaling process. The results were validated against on-site measurements of meteorological stations distributed in the area under study. PMID:28125607

Vegetable behavioral tool demonstrates validity with MyPlate vegetable cups and carotenoid and inflammatory biomarkers.

PubMed

Townsend, Marilyn S; Shilts, Mical K; Styne, Dennis M; Drake, Christiana; Lanoue, Louise; Woodhouse, Leslie; Allen, Lindsay H

2016-12-01

Young children are not meeting recommendations for vegetable intake. Our objective is to provide evidence of validity and reliability for a pictorial vegetable behavioral assessment for use by federally funded community nutrition programs. Parent/child pairs (n=133) from Head Start and the Special Supplemental Nutrition Program for Women, Infants and Children [WIC] provided parent-administered vegetable tools, three child 24-hour diet recalls, child blood sample and measured heights/weights. The 10-item Focus on Veggies scale, with an alpha of .83 and a stability reliability coefficient of .74, was positively related to vegetables in cup equivalents [p≤.05]; dietary intakes of folate, vitamin C, β-carotene, potassium and magnesium [p≤.05-.01]; and soluble fiber [p≤.001]. The child vegetable scores were related to the parent's mediators [p≤.00001] and vegetable behaviors [p≤.00001]. Children's plasma inflammatory markers were negatively related to the 10 item scale [p≤.05] and are indicators of the child's health status. The positive relationship between the serum carotenoid index and a sub-scale of child vegetable behaviors offered additional support for criterion validity [p≤.05]. Finally, the inverse relationship of BMI-for-age percentile one year post baseline and a sub-scale of child vegetable behaviors supported the predictive validity [p≤.05]. Focus on Veggies, a simple assessment tool, can inform practitioners about the child's health status. A child with a high score, shows a healthful profile with a lower inflammation index, higher carotenoid index, lower BMI and higher vegetable intake. In conclusion, validity of Focus on Veggies has been demonstrated using vegetable cup equivalents and micronutrient intakes, anthropometry and blood biomarkers. Copyright © 2016 Elsevier Ltd. All rights reserved.

The potential of small-Unmanned Aircraft Systems for the rapid detection of threatened unimproved grassland communities using an Enhanced Normalized Difference Vegetation Index.

PubMed

Strong, Conor J; Burnside, Niall G; Llewellyn, Dan

2017-01-01

The loss of unimproved grassland has led to species decline in a wide range of taxonomic groups. Agricultural intensification has resulted in fragmented patches of remnant grassland habitat both across Europe and internationally. The monitoring of remnant patches of this habitat is critically important, however, traditional surveying of large, remote landscapes is a notoriously costly and difficult task. The emergence of small-Unmanned Aircraft Systems (sUAS) equipped with low-cost multi-spectral cameras offer an alternative to traditional grassland survey methods, and have the potential to progress and innovate the monitoring and future conservation of this habitat globally. The aim of this article is to investigate the potential of sUAS for rapid detection of threatened unimproved grassland and to test the use of an Enhanced Normalized Difference Vegetation Index (ENDVI). A sUAS aerial survey is undertaken at a site nationally recognised as an important location for fragmented unimproved mesotrophic grassland, within the south east of England, UK. A multispectral camera is used to capture imagery in the visible and near-infrared spectrums, and the ENDVI calculated and its discrimination performance compared to a range of more traditional vegetation indices. In order to validate the results of analysis, ground quadrat surveys were carried out to determine the grassland communities present. Quadrat surveys identified three community types within the site; unimproved grassland, improved grassland and rush pasture. All six vegetation indices tested were able to distinguish between the broad habitat types of grassland and rush pasture; whilst only three could differentiate vegetation at a community level. The Enhanced Normalized Difference Vegetation Index (ENDVI) was the most effective index when differentiating grasslands at the community level. The mechanisms behind the improved performance of the ENDVI are discussed and recommendations are made for areas of future

The potential of small-Unmanned Aircraft Systems for the rapid detection of threatened unimproved grassland communities using an Enhanced Normalized Difference Vegetation Index

PubMed Central

Strong, Conor J.; Llewellyn, Dan

2017-01-01

The loss of unimproved grassland has led to species decline in a wide range of taxonomic groups. Agricultural intensification has resulted in fragmented patches of remnant grassland habitat both across Europe and internationally. The monitoring of remnant patches of this habitat is critically important, however, traditional surveying of large, remote landscapes is a notoriously costly and difficult task. The emergence of small-Unmanned Aircraft Systems (sUAS) equipped with low-cost multi-spectral cameras offer an alternative to traditional grassland survey methods, and have the potential to progress and innovate the monitoring and future conservation of this habitat globally. The aim of this article is to investigate the potential of sUAS for rapid detection of threatened unimproved grassland and to test the use of an Enhanced Normalized Difference Vegetation Index (ENDVI). A sUAS aerial survey is undertaken at a site nationally recognised as an important location for fragmented unimproved mesotrophic grassland, within the south east of England, UK. A multispectral camera is used to capture imagery in the visible and near-infrared spectrums, and the ENDVI calculated and its discrimination performance compared to a range of more traditional vegetation indices. In order to validate the results of analysis, ground quadrat surveys were carried out to determine the grassland communities present. Quadrat surveys identified three community types within the site; unimproved grassland, improved grassland and rush pasture. All six vegetation indices tested were able to distinguish between the broad habitat types of grassland and rush pasture; whilst only three could differentiate vegetation at a community level. The Enhanced Normalized Difference Vegetation Index (ENDVI) was the most effective index when differentiating grasslands at the community level. The mechanisms behind the improved performance of the ENDVI are discussed and recommendations are made for areas of future

Investigating the utility of a GPA institutional adjustment index.

PubMed

Didier, Thomas; Kreiter, Clarence D; Buri, Russell; Solow, Catherine

2006-05-01

Grading standards vary widely across undergraduate institutions. If, during the medical school admissions process, GPA is considered without reference to the institution attended, it will disadvantage applicants from undergraduate institutions employing rigorous grading standards. A regression-based GPA institutional equating method using historical MCAT and GPA information is described. Classes selected from eight applicant pools demonstrate the impact of the GPA adjustment. The validity of the adjustment is examined by comparing adjusted and unadjusted GPAs' correlation with USMLE and medical college grades. The adjusted GPA demonstrated significantly improved congruence with MCAT estimates of applicant preparedness. The adjustment changed selection decisions for 21% of those admitted. The adjusted GPA enhanced prediction of USMLE and medical school grades only for students from institutions which required large adjustments. Unlike other indices, the adjustment described uses the same metric as GPA and is based only on an institution's history of preparing medical school applicants. The institutional adjustment is consequential in selection, significantly enhances congruence with a standardized measure of academic preparedness and may enhance the validity of the GPA.

Using remotely sensed vegetation indices to model ecological pasture conditions in Kara-Unkur watershed, Kyrgyzstan

NASA Astrophysics Data System (ADS)

Masselink, Loes; Baartman, Jantiene; Verbesselt, Jan; Borchardt, Peter

2017-04-01

Kyrgyzstan has a long history of nomadic lifestyle in which pastures play an important role. However, currently the pastures are subject to severe grazing-induced degradation. Deteriorating levels of biomass, palatability and biodiversity reduce the pastures' productivity. To counter this and introduce sustainable pasture management, up-to-date information regarding the ecological conditions of the pastures is essential. This research aimed to investigate the potential of a remote sensing-based methodology to detect changing ecological pasture conditions in the Kara-Unkur watershed, Kyrgyzstan. The relations between Vegetation Indices (VIs) from Landsat ETM+ images and biomass, palatability and species richness field data were investigated. Both simple and multiple linear regression (MLR) analyses, including terrain attributes, were applied. Subsequently, trends of these three pasture conditions were mapped using time series analysis. The results show that biomass is most accurately estimated by a model including the Modified Soil Adjusted Vegetation Index (MSAVI) and a slope factor (R2 = 0.65, F = 0.0006). Regarding palatability, a model including the Enhanced Vegetation Index (EVI), Northness Index, Near Infrared (NIR) and Red band was most accurate (R2 = 0.61, F = 0.0160). Species richness was most accurately estimated by a model including Topographic Wetness Index (TWI), Eastness Index and estimated biomass (R2 = 0.81, F = 0.0028). Subsequent trend analyses of all three estimated ecological pasture conditions presented very similar trend patterns. Despite the need for a more robust validation, this study confirms the high potential of a remote sensing based methodology to detect changing ecological pasture conditions.

Remote sensing of temperate coniferous forest lead area index - The influence of canopy closure, understory vegetation and background reflectance

NASA Technical Reports Server (NTRS)

Spanner, Michael A.; Pierce, Lars L.; Running, Steven W.; Peterson, David L.

1990-01-01

Consideration is given to the effects of canopy closure, understory vegetation, and background reflectance on the relationship between Landsat TM data and the leaf area index (LAI) of temperate coniferous forests in the western U.S. A methodology for correcting TM data for atmospheric conditions and sun-surface-sensor geometry is discussed. Strong inverse curvilinear relationships were found between coniferous forest LAI and TM bands 3 and 5. It is suggested that these inverse relationships are due to increased reflectance of understory vegetation and background in open stands of lower LAI and decreased reflectance of the overstory in closed canopy stands with higher LAI.

Detecting post-fire burn severity and vegetation recovery using multitemporal remote sensing spectral indices and field-collected composite burn index data in a ponderosa pine forest

USGS Publications Warehouse

Chen, Xuexia; Vogelmann, James E.; Rollins, Matt; Ohlen, Donald; Key, Carl H.; Yang, Limin; Huang, Chengquan; Shi, Hua

2011-01-01

It is challenging to detect burn severity and vegetation recovery because of the relatively long time period required to capture the ecosystem characteristics. Multitemporal remote sensing data can providemultitemporal observations before, during and after a wildfire, and can improve the change detection accuracy. The goal of this study is to examine the correlations between multitemporal spectral indices and field-observed burn severity, and to provide a practical method to estimate burn severity and vegetation recovery. The study site is the Jasper Fire area in the Black Hills National Forest, South Dakota, that burned during August and September 2000. Six multitemporal Landsat images acquired from 2000 (pre-fire), 2001 (post-fire), 2002, 2003, 2005 and 2007 were used to assess burn severity. The normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), normalized burn ratio (NBR), integrated forest index (IFI) and the differences of these indices between the pre-fire and post-fire years were computed and analysed with 66 field-based composite burn index (CBI) plots collected in 2002. Results showed that differences of NDVI and differences of EVI between the pre-fire year and the first two years post-fire were highly correlated with the CBI scores. The correlations were low beyond the second year post-fire. Differences of NBR had good correlation with CBI scores in all study years. Differences of IFI had low correlation with CBI in the first year post-fire and had good correlation in later years. A CBI map of the burnt area was produced using regression tree models and the multitemporal images. The dynamics of four spectral indices from 2000 to 2007 indicated that both NBR and IFI are valuable for monitoring long-term vegetation recovery. The high burn severity areas had a much slower recovery than the moderate and low burn areas.

[Differences of vegetation phenology monitoring by remote sensing based on different spectral vegetation indices.

PubMed

Zuo, Lu; Wang, Huan Jiong; Liu, Rong Gao; Liu, Yang; Shang, Rong

2018-02-01

Vegetation phenology is a comprehensive indictor for the responses of terrestrial ecosystem to climatic and environmental changes. Remote sensing spectrum has been widely used in the extraction of vegetation phenology information. However, there are many differences between phenology extracted by remote sensing and site observations, with their physical meaning remaining unclear. We selected one tile of MODIS data in northeastern China (2000-2014) to examine the SOS and EOS differences derived from the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (SR) based on both the red and near-infrared bands. The results showed that there were significant differences between NDVI-phenology and SR-phenology. SOS derived from NDVI averaged 18.9 days earlier than that from SR. EOS derived from NDVI averaged 19.0 days later than from SR. NDVI-phenology had a longer growing season. There were significant differences in the inter-annual variation of phenology from NDVI and SR. More than 20% of the pixel SOS and EOS derived from NDVI and SR showed the opposite temporal trend. These results caused by the seasonal curve characteristics and noise resistance differences of NDVI and SR. The observed data source of NDVI and SR were completely consistent, only the mathematical expressions were different, but phenology results were significantly different. Our results indicated that vegetation phenology monitoring by remote sensing is highly dependent on the mathematical expression of vegetation index. How to establish a reliable method for extracting vegetation phenology by remote sensing needs further research.

Estimating vegetation dryness to optimize fire risk assessment with spot vegetation satellite data in savanna ecosystems

NASA Astrophysics Data System (ADS)

Verbesselt, J.; Somers, B.; Lhermitte, S.; van Aardt, J.; Jonckheere, I.; Coppin, P.

2005-10-01

The lack of information on vegetation dryness prior to the use of fire as a management tool often leads to a significant deterioration of the savanna ecosystem. This paper therefore evaluated the capacity of SPOT VEGETATION time-series to monitor the vegetation dryness (i.e., vegetation moisture content per vegetation amount) in order to optimize fire risk assessment in the savanna ecosystem of Kruger National Park in South Africa. The integrated Relative Vegetation Index approach (iRVI) to quantify the amount of herbaceous biomass at the end of the rain season and the Accumulated Relative Normalized Difference vegetation index decrement (ARND) related to vegetation moisture content were selected. The iRVI and ARND related to vegetation amount and moisture content, respectively, were combined in order to monitor vegetation dryness and optimize fire risk assessment in the savanna ecosystems. In situ fire activity data was used to evaluate the significance of the iRVI and ARND to monitor vegetation dryness for fire risk assessment. Results from the binary logistic regression analysis confirmed that the assessment of fire risk was optimized by integration of both the vegetation quantity (iRVI) and vegetation moisture content (ARND) as statistically significant explanatory variables. Consequently, the integrated use of both iRVI and ARND to monitor vegetation dryness provides a more suitable tool for fire management and suppression compared to other traditional satellite-based fire risk assessment methods, only related to vegetation moisture content.

Fruit and Vegetable Intake During Infancy and Early Childhood

PubMed Central

Kim, Sonia A.; Yaroch, Amy L.; Scanlon, Kelley S.

2014-01-01

OBJECTIVES: To examine the association of timing of introduction and frequency of fruit and vegetable intake during infancy with frequency of fruit and vegetable intake at age 6 years in a cohort of US children. METHODS: We analyzed data on fruit and vegetable intake during late infancy, age of fruit and vegetable introduction, and frequency of fruit and vegetable intake at 6 years from the Infant Feeding Practices Study II and the Year 6 Follow-Up (Y6FU) Study. We determined the percent of 6-year-old children consuming fruits and vegetables less than once per day and examined associations with infant fruit and vegetable intake using logistic regression modeling, controlling for multiple covariates (n = 1078). RESULTS: Based on maternal report, 31.9% of 6-year-old children consumed fruit less than once daily and 19.0% consumed vegetables less than once daily. In adjusted analyses, children who consumed fruits and vegetables less than once daily during late infancy had increased odds of eating fruits and vegetables less than once daily at age 6 years (fruit, adjusted odds ratio: 2.48; vegetables, adjusted odds ratio: 2.40). Age of introduction of fruits and vegetables was not associated with intake at age 6 years. CONCLUSIONS: Our study suggests that infrequent intake of fruits and vegetables during late infancy is associated with infrequent intake of these foods at 6 years of age. These findings highlight the importance of infant feeding guidance that encourages intake of fruits and vegetables and the need to examine barriers to fruit and vegetable intake during infancy. PMID:25183758

A MODIS-based begetation index climatology

USDA-ARS?s Scientific Manuscript database

Passive microwave soil moisture algorithms must account for vegetation attenuation of the signal in the retrieval process. One approach to accounting for vegetation is to use vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to estimate the vegetation optical depth. The pa...

75 FR 49411 - Consumer Price Index Adjustments of Oil Pollution Act of 1990 Limits of Liability-Vessels and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-13

... collection OMB Control Number 1625-0046 entitled ``Financial Responsibility for Water Pollution (Vessels... Consumer Price Index Adjustments of Oil Pollution Act of 1990 Limits of Liability--Vessels and Deepwater..., the Coast Guard amended the Oil Pollution Act of 1990 limits of liability for vessels and deepwater...

Soil-vegetation correlations in the Connecticut River floodplain of Western Massachusetts

USGS Publications Warehouse

Veneman, Peter L.M.; Tiner, Ralph W.

1990-01-01

As part of a national study analyzing the relation between hydric soils and wetland vegetation, the vegetation associated with a series of known soils was sampled along the Connecticut River floodplain in Massachusetts. Weighted average and index average (presence/absence) values were calculated for vegetation using wetland ecological index values from the National List of Plant Species that Occur in Wetlands developed by the U.S. Fish and Wildlife Service and procedures developed by T. R. Wentworth and G. P. Johnson at North Carolina State University. Good correspondence between soils and vegetation was recorded with two exceptions. Two typically nonhydric soils were determined to be hydric based on vegetation analyses. Examination of the groundwater hydrology of these two soils confirmed their hydric nature. The authors suggested that one of these soils may need to be redefined and they also suggested that the assigned index values for a few species of vegetation should be reexamined. However, in general the index average values of vegetation based on published wetland index values corresponded with the hydric and nonhydric nature of soils.

Comparison of MODIS and AVHRR 16-day normalized difference vegetation index composite data

USGS Publications Warehouse

Gallo, Kevin P.; Ji, Lei; Reed, Bradley C.; Dwyer, John L.; Eidenshink, Jeffery C.

2004-01-01

Normalized difference vegetation index (NDVI) data derived from visible and near-infrared data acquired by the MODIS and AVHRR sensors were compared over the same time periods and a variety of land cover classes within the conterminous USA. The relationship between the AVHRR derived NDVI values and those of future sensors is critical to continued long term monitoring of land surface properties. The results indicate that the 16-day composite values are quite similar over the 23 intervals of 2001 that were analyzed, and a linear relationship exists between the NDVI values from the two sensors. The composite AVHRR NDVI data were associated with over 90% of the variation in the MODIS NDVI values. Copyright 2004 by the American Geophysical Union.

Trends in normalized difference vegetation index (NDVI) associated with urban development in northern West Siberia

NASA Astrophysics Data System (ADS)

Esau, Igor; Miles, Victoria V.; Davy, Richard; Miles, Martin W.; Kurchatova, Anna

2016-08-01

Exploration and exploitation of oil and gas reserves of northern West Siberia has promoted rapid industrialization and urban development in the region. This development leaves significant footprints on the sensitive northern environment, which is already stressed by the global warming. This study reports the region-wide changes in the vegetation cover as well as the corresponding changes in and around 28 selected urbanized areas. The study utilizes the normalized difference vegetation index (NDVI) from high-resolution (250 m) MODIS data acquired for summer months (June through August) over 15 years (2000-2014). The results reveal the increase of NDVI (or "greening") over the northern (tundra and tundra-forest) part of the region. Simultaneously, the southern, forested part shows the widespread decrease of NDVI (or "browning"). These region-wide patterns are, however, highly fragmented. The statistically significant NDVI trends occupy only a small fraction of the region. Urbanization destroys the vegetation cover within the developed areas and at about 5-10 km distance around them. The studied urbanized areas have the NDVI values by 15 to 45 % lower than the corresponding areas at 20-40 km distance. The largest NDVI reduction is typical for the newly developed areas, whereas the older areas show recovery of the vegetation cover. The study reveals a robust indication of the accelerated greening near the older urban areas. Many Siberian cities become greener even against the wider browning trends at their background. Literature discussion suggests that the observed urban greening could be associated not only with special tending of the within-city green areas but also with the urban heat islands and succession of more productive shrub and tree species growing on warmer sandy soils.

CRMS vegetation analytical team framework: Methods for collection, development, and use of vegetation response variables

USGS Publications Warehouse

Cretini, Kari F.; Visser, Jenneke M.; Krauss, Ken W.; Steyer, Gregory D.

2011-01-01

This document identifies the main objectives of the Coastwide Reference Monitoring System (CRMS) vegetation analytical team, which are to provide (1) collection and development methods for vegetation response variables and (2) the ways in which these response variables will be used to evaluate restoration project effectiveness. The vegetation parameters (that is, response variables) collected in CRMS and other coastal restoration projects funded under the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) are identified, and the field collection methods for these parameters are summarized. Existing knowledge on community and plant responses to changes in environmental drivers (for example, flooding and salinity) from published literature and from the CRMS and CWPPRA monitoring dataset are used to develop a suite of indices to assess wetland condition in coastal Louisiana. Two indices, the floristic quality index (FQI) and a productivity index, are described for herbaceous and forested vegetation. The FQI for herbaceous vegetation is tested with a long-term dataset from a CWPPRA marsh creation project. Example graphics for this index are provided and discussed. The other indices, an FQI for forest vegetation (that is, trees and shrubs) and productivity indices for herbaceous and forest vegetation, are proposed but not tested. New response variables may be added or current response variables removed as data become available and as our understanding of restoration success indicators develops. Once indices are fully developed, each will be used by the vegetation analytical team to assess and evaluate CRMS/CWPPRA project and program effectiveness. The vegetation analytical teams plan to summarize their results in the form of written reports and/or graphics and present these items to CRMS Federal and State sponsors, restoration project managers, landowners, and other data users for their input.

Forested floristic quality index: An assessment tool for forested wetland habitats using the quality and quantity of woody vegetation at Coastwide Reference Monitoring System (CRMS) vegetation monitoring stations

USGS Publications Warehouse

Wood, William B.; Shaffer, Gary P.; Visser, Jenneke M.; Krauss, Ken W.; Piazza, Sarai C.; Sharp, Leigh Anne; Cretini, Kari F.

2017-02-08

The U.S. Geological Survey, in cooperation with the Coastal Protection and Restoration Authority of Louisiana and the Coastal Wetlands Planning, Protection and Restoration Act, developed the Forested Floristic Quality Index (FFQI) for the Coastwide Reference Monitoring System (CRMS). The FFQI will help evaluate forested wetland sites on a continuum from severely degraded to healthy and will assist in defining areas where forested wetland restoration can be successful by projecting the trajectories of change. At each CRMS forested wetland site there are stations for quantifying the overstory, understory, and herbaceous vegetation layers. Rapidly responding overstory canopy cover and herbaceous layer composition are measured annually, while gradually changing overstory basal area and species composition are collected on a 3-year cycle.A CRMS analytical team has tailored these data into an index much like the Floristic Quality Index (FQI) currently used for herbaceous marsh and for the herbaceous layer of the swamp vegetation. The core of the FFQI uses basal area by species to assess the quality and quantity of the overstory at each of three stations within each CRMS forested wetland site. Trees that are considered by experts to be higher quality swamp species like Taxodium distichum (bald cypress) and Nyssa aquatica (water tupelo) are scored higher than tree species like Triadica sebifera (Chinese tallow) and Salix nigra (black willow) that are indicators of recent disturbance. This base FFQI is further enhanced by the percent canopy cover in the overstory and the presence of indicator species at the forest floor. This systemic approach attempts to differentiate between locations with similar basal areas that are on different ecosystem trajectories. Because of these varying states of habitat degradation, paired use of the FQI and the FFQI is useful to interpret the vegetative data in transitional locations. There is often an inverse relation between the health of the

Monitoring phenology of photosynthesis in temperate evergreen and mixed deciduous forests using the normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI) at leaf and canopy scales

NASA Astrophysics Data System (ADS)

Wong, C. Y.; Arain, M. A.; Ensminger, I.

2016-12-01

Evergreen conifers in boreal and temperate regions undergo strong seasonal changes in photoperiod and temperatures, which determines their phenology of high photosynthetic activity in the growing season and downregulation during the winter. Monitoring the timing of the transition between summer activity and winter downregulation in evergreens is difficult since this is a largely invisible process, unlike in deciduous trees that have a visible budding and a sequence of leaf unfolding in the spring and leaf abscission in the fall. The light-use efficiency (LUE) model estimates gross primary productivity (GPP) and may be parameterized using remotely sensed vegetation indices. Using spectral reflectance data, we derived the normalized difference vegetation index (NDVI), a measure of leaf "greenness", and the photochemical reflectance index (PRI), a proxy for chlorophyll:carotenoid ratios which is related to photosynthetic activity. To better understand the relationship between these vegetation indices and photosynthetic activity and to contrast this relationship between plant functional types, the phenology of NDVI, PRI and photosynthesis was monitored in an evergreen forest and a mixed deciduous forest at the leaf and canopy scale. Our data indicates that the LUE model can be parameterized by NDVI and PRI to track forest phenology. Differences in the sensitivity of PRI and NDVI will be discussed. These findings have implications to address the phenology of evergreen conifers by using PRI to complement NDVI in the LUE model, potentially improving model productivity estimates in northern hemisphere forests, that are dominated by conifers.

Leaf area index retrieval using Hyperion EO-1 data-based vegetation indices in Himalayan forest system

NASA Astrophysics Data System (ADS)

Singh, Dharmendra; Singh, Sarnam

2016-04-01

Present Study is being taken to retrieve Leaf Area Indexn(LAI) in Himalayan forest system using vegetation indices developed from Hyperion EO-1 hyperspectral data. Hemispherical photograph were captured in the month of March and April, 2012 at 40 locations, covering moist tropical Sal forest, subtropical Bauhinia and pine forest and temperate Oak forest and analysed using an open source GLA software. LAI in the study region was ranging in between 0.076 m2/m2 to 6.00 m2/m2. These LAI values were used to develop spectral models with the FLAASH corrected Hyperion measurements.Normalized difference vegetation index (NDVI) was used taking spectral reflectance values of all the possible combinations of 170 atmospherically corrected channels. The R2 was ranging from lowest 0.0 to highest 0.837 for the band combinations of spectral region 640 nm and 670 nm. The spectral model obtained was, spectral reflectance (y) = 0.02x LAI(x) - 0.0407.

Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index Composites

USGS Publications Warehouse

,

2005-01-01

The Advanced Very High Resolution Radiometer (AVHRR) is a broad-band scanner with four to six bands, depending on the model. The AVHRR senses in the visible, near-, middle-, and thermal- infrared portions of the electromagnetic spectrum. This sensor is carried on a series of National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellites (POES), beginning with the Television InfraRed Observation Satellite (TIROS-N) in 1978. Since 1989, the United States Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) has been mapping the vegetation condition of the United States and Alaska using satellite information from the AVHRR sensor. The vegetation condition composites, more commonly called greenness maps, are produced every week using the latest information on the growth and condition of the vegetation. One of the most important aspects of USGS greenness mapping is the historical archive of information dating back to 1989. This historical stretch of information has allowed the USGS to determine a 'normal' vegetation condition. As a result, it is possible to compare the current week's vegetation condition with normal vegetation conditions. An above normal condition could indicate wetter or warmer than normal conditions, while a below normal condition could indicate colder or dryer than normal conditions. The interpretation of departure from normal will depend on the season and geography of a region.

Usual Cruciferous Vegetable Consumption and Ovarian Cancer: A Case-Control Study.

PubMed

McManus, Hallie; Moysich, Kirsten B; Tang, Li; Joseph, Janine; McCann, Susan E

2018-01-01

Ovarian cancer is the fifth leading cause of cancer-related deaths among women, primarily due to diagnosis at late stages. Therefore, identification of modifiable risk factors for this disease is warranted. Using the Patient Epidemiology Data System (PEDS), collected from 1981 to 1998 at Roswell Park Cancer Institute, Buffalo, NY, we conducted a hospital-based, case-control analysis of self-reported cruciferous vegetable intake and ovarian cancer among 675 women with primary, incident ovarian cancer, and 1275 without cancer. Cruciferous vegetable intake was queried using a 44-item food frequency questionnaire (FFQ). Odds ratios (OR) and 95% confidence intervals (CI) were estimated with logistic regression, adjusting for age, body mass index (BMI), education, smoking status, parity, family history of ovarian cancer, total fruit consumption, total meat consumption, and total noncruciferous vegetable consumption. We observed a significant inverse association for women with highest vs. lowest intakes of total vegetables (OR = 0.65, 95% CI = 0.46-0.92), cooked cauliflower (OR = 0.82, 95% CI = 0.67-0.99), and cooked greens (OR = 0.63, 95% CI = 0.46-0.86) and an inverse, dose-dependent association between cooked cruciferous vegetables intake and ovarian cancer (for each additional ten servings per month, OR = 0.85, 95% CI = 0.76-0.96). These findings suggest that a diet that includes cruciferous vegetables could be an important modifiable risk factor for ovarian cancer.

Vegetation spatial variability and its effect on vegetation indices

NASA Technical Reports Server (NTRS)

Ormsby, J. P.; Choudhury, B. J.; Owe, M.

1987-01-01

Landsat MSS data were used to simulate low resolution satellite data, such as NOAA AVHRR, to quantify the fractional vegetation cover within a pixel and relate the fractional cover to the normalized difference vegetation index (NDVI) and the simple ratio (SR). The MSS data were converted to radiances from which the NDVI and SR values for the simulated pixels were determined. Each simulated pixel was divided into clusters using an unsupervised classification program. Spatial and spectral analysis provided a means of combining clusters representing similar surface characteristics into vegetated and non-vegetated areas. Analysis showed an average error of 12.7 per cent in determining these areas. NDVI values less than 0.3 represented fractional vegetated areas of 5 per cent or less, while a value of 0.7 or higher represented fractional vegetated areas greater than 80 per cent. Regression analysis showed a strong linear relation between fractional vegetation area and the NDVI and SR values; correlation values were 0.89 and 0.95 respectively. The range of NDVI values calculated from the MSS data agrees well with field studies.

Use of Normalized Difference Vegetation Index (NDVI) habitat models to predict breeding birds on the San Pedro River, Arizona

USGS Publications Warehouse

McFarland, Tiffany Marie; van Riper, Charles

2013-01-01

Successful management practices of avian populations depend on understanding relationships between birds and their habitat, especially in rare habitats, such as riparian areas of the desert Southwest. Remote-sensing technology has become popular in habitat modeling, but most of these models focus on single species, leaving their applicability to understanding broader community structure and function largely untested. We investigated the usefulness of two Normalized Difference Vegetation Index (NDVI) habitat models to model avian abundance and species richness on the upper San Pedro River in southeastern Arizona. Although NDVI was positively correlated with our bird metrics, the amount of explained variation was low. We then investigated the addition of vegetation metrics and other remote-sensing metrics to improve our models. Although both vegetation metrics and remotely sensed metrics increased the power of our models, the overall explained variation was still low, suggesting that general avian community structure may be too complex for NDVI models.

Comparing MODIS and near-surface vegetation indexes for monitoring tropical dry forest phenology along a successional gradient using optical phenology towers

NASA Astrophysics Data System (ADS)

Rankine, C.; Sánchez-Azofeifa, G. A.; Guzmán, J. Antonio; Espirito-Santo, M. M.; Sharp, Iain

2017-10-01

Tropical dry forests (TDFs) present strong seasonal greenness signals ideal for tracking phenology and primary productivity using remote sensing techniques. The tightly synchronized relationship these ecosystems have with water availability offer a valuable natural experiment for observing the complex interactions between the atmosphere and the biosphere in the tropics. To investigate how well the MODIS vegetation indices (normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI)) represented the phenology of different successional stages of naturally regenerating TDFs, within a widely conserved forest fragment in the semi-arid southeast of Brazil, we installed several canopy towers with radiometric sensors to produce high temporal resolution near-surface vegetation greenness indices. Direct comparison of several years of ground measurements with a combined Aqua/Terra 8 day satellite product showed similar broad temporal trends, but MODIS often suffered from cloud contamination during the onset of the growing season and occasionally during the peak growing season. The strength of the in-situ and MODIS linear relationship was greater for NDVI than for EVI across sites but varied with forest stand age. Furthermore, we describe the onset dates and duration of canopy development phases for three years of in-situ monitoring. A seasonality analysis revealed significant discrepancies between tower and MODIS phenology transitions dates, with up to five weeks differences in growing season length estimation. Our results indicate that 8 and 16 day MODIS satellite vegetation monitoring products are suitable for tracking general patterns of tropical dry forest phenology in this region but are not temporally sufficient to characterize inter-annual differences in phenology phase onset dates or changes in productivity due to mid-season droughts. Such rapid transitions in canopy greenness are important indicators of climate change sensitivity of these

Fruit and vegetable intake during infancy and early childhood.

PubMed

Grimm, Kirsten A; Kim, Sonia A; Yaroch, Amy L; Scanlon, Kelley S

2014-09-01

To examine the association of timing of introduction and frequency of fruit and vegetable intake during infancy with frequency of fruit and vegetable intake at age 6 years in a cohort of US children. We analyzed data on fruit and vegetable intake during late infancy, age of fruit and vegetable introduction, and frequency of fruit and vegetable intake at 6 years from the Infant Feeding Practices Study II and the Year 6 Follow-Up (Y6FU) Study. We determined the percent of 6-year-old children consuming fruits and vegetables less than once per day and examined associations with infant fruit and vegetable intake using logistic regression modeling, controlling for multiple covariates (n = 1078). Based on maternal report, 31.9% of 6-year-old children consumed fruit less than once daily and 19.0% consumed vegetables less than once daily. In adjusted analyses, children who consumed fruits and vegetables less than once daily during late infancy had increased odds of eating fruits and vegetables less than once daily at age 6 years (fruit, adjusted odds ratio: 2.48; vegetables, adjusted odds ratio: 2.40). Age of introduction of fruits and vegetables was not associated with intake at age 6 years. Our study suggests that infrequent intake of fruits and vegetables during late infancy is associated with infrequent intake of these foods at 6 years of age. These findings highlight the importance of infant feeding guidance that encourages intake of fruits and vegetables and the need to examine barriers to fruit and vegetable intake during infancy. Copyright © 2014 by the American Academy of Pediatrics.

Satellite Vegetation Index Data as a Tool to Forecast Population Dynamics of Medically Important Mosquitoes at Military Installations in the Continental United States

DTIC Science & Technology

2008-07-01

for the two installations. We obtained monthly North American normalized differ- ence vegetation index ( NDVI ) satellite climate data sets for 1981-2005...from the Goddard Space Flight Center."*-" The NDVI measures the greenness of the earth, capturing in one index the combined effects of temperature...humidity, insola- tion, elevation, soils, land use. and precipitation on vegeta- tion. There is an almost-linear relationship between NDVI values and

The Occupational Mix Adjustment to the Medicare Hospital Wage Index: Why the Rural Impact Is Less than Expected

ERIC Educational Resources Information Center

Reiter, Kristin L.; Slifkin, Rebecca; Holmes, George M.

2008-01-01

Context: Rural hospitals are heavily dependent on Medicare for their long-term financial solvency. A recent change to Medicare prospective payment system reimbursement--the occupational mix adjustment (OMA) to the wage index--has attracted a great deal of attention in rural policy circles. Purpose: This paper explores variation in the OMA across…

The assessment of anthropogenic impact on the environment in East Fennoscandia based on the Normalized Difference Vegetation Index data

NASA Astrophysics Data System (ADS)

Miulgauzen, Daria; Pankratova, Lubov

2017-04-01

Being a part of Eurasian "cold sector", ecosystems of East Fennoscandia may fit in the category of the most vulnerable to any external impact, including anthropogenic one. The productivity of plant communities can serve as an indicator representing the state of ecosystems, especially in disturbed areas. The present research is aimed at the environmental impact assessment caused by the Pechenganikel Mining and Metallurgical Plant based on the plant communities' productivity data on the example of ecosystems of East Fennoscandia. Vegetation productivity was assessed on the basis of the Normalized Difference Vegetation Index (NDVI) which is often used for screenings to quantify plant canopy. The essence of the method is that of the difference between the spectral reflectance of vegetation in red and near-infrared regions. The index was calculated on the satellite images of Landsat 8 in IDRISI Kilimanjaro (Clark Labs) according to the equation: N DV I = N-IR- RED-; N IR +RED NIR - spectral reflectance measurements in near-infrared region, RED - spectral reflectance measurements in red region. To compare the index calculations with the information on the state of plant communities, the field studies were carried out in the area of 380 km2 in the vicinity of the Pechenganikel Mining and Metallurgical Plant (Kola Peninsula, Nikel urban-type settlement). As a result, there was created a map in MapInfo Professional 12.5 (Pitney Bowes Software) that represents the vegetation damage at a scale of 1:100,000. The field research has revealed the morphogenetic discrepancy between the soil-plant cover of the area in question and the one of "zonal" ecosystems. Plant communities have been widely modified or destroyed because of air pollution and there are numerous disturbances in the soil profile structure. In terms of vegetation productivity, the analysis of the NDVI figures has shown that the closer the pollution source (Pechenganikel Plant) is, the more significant the

Preliminary Study on the Radar Vegetation Index (RVI) Application to Actual Paddy Fields by ALOS/PALSAR Full-polarimetry SAR Data

NASA Astrophysics Data System (ADS)

Yamada, Y.

2015-04-01

Kim and van Zyl (2001) proposed a kind of radar vegetation index (RVI). RVI = 4*min(λ1, λ2, λ3) / (λ1 + λ2 + λ3) They modified the equation as follows. (2009) RVI = 8 * σ0hv / (σ0hh + σ0vv +σ0hv ) by L-band full-polarimetric SAR data. They applied it into rice crop and soybean. (Y.Kim, T.Jackson et al., 2012) They compared RVI for L-, C- and X-bands to crop growth data, LAI and NDVI. They found L-band RVI was well correlated with Vegetation Water Content, LAI and NDVI. But the field data were collected by the multifrequency polarimetric scatterometer. The platform height was 4.16 meters from the ground. The author tried to apply the method to actual paddy fields near Tsukuba science city in Japan using ALOS/PALSAR, full-polarimetry L-band SAR data. The staple crop in Eastern Asia is rice and paddy fields are dominant land use. A rice-planting machine comes into wide use in this areas. The young rice plants were bedded regularly ridged line in the paddy fields by the machine. The space between two ridges of rice plants is about 30 cm and the wave length of PALSAR sensor is about 23 cm. Hence the Bragg scattering will appear depending upon the direction of the ridges of paddy fields. Once the Bragg scattering occurs, the backscattering values from the pixels should be very high comparing the surrounding region. Therefore the radar vegetation index (RVI) would be saturated. The RVI did not follow the increasing of vegetation anymore. Japan has launched ALOS-2 satellite and it has PALSAR-2, L-band SAR. Therefore RVI application product by PALSAR-2 will be watched with deep interest.

Monitoring Thermal Status of Ecosystems with MODIS Land-Surface Temperature and Vegetation Index Products

NASA Technical Reports Server (NTRS)

Wan, Zhengming

2002-01-01

The global land-surface temperature (LST) and normalized difference vegetation index (NDVI) products retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) data in 2001 were used in this study. The yearly peak values of NDVI data at 5km grids were used to define six NDVI peak zones from -0.2 to 1 in steps of 0.2, and the monthly NDVI values at each grid were sorted in decreasing order, resulting in 12 layers of NDVI images for each of the NDVI peak zones. The mean and standard deviation of daytime LSTs and day-night LST differences at the grids corresponding to the first layer of NDVI images characterize the thermal status of terrestrial ecosystems in the NDVI peak zones. For the ecosystems in the 0.8-1 NDVI peak zone, daytime LSTs distribute from 0-35 C and day-night LST differences distribute from -2 to 22 C. The daytime LSTs and day-night LST differences corresponding to the remaining layers of NDVI images show that the growth of vegetation is limited at low and high LSTs. LSTs and NDVI may be used to monitor photosynthetic activity and drought, as shown in their applications to a flood-irrigated grassland in California and an unirrigated grassland in Nevada.

Body mass index adjustments to increase the validity of body fatness assessment in UK Black African and South Asian children.

PubMed

Hudda, M T; Nightingale, C M; Donin, A S; Fewtrell, M S; Haroun, D; Lum, S; Williams, J E; Owen, C G; Rudnicka, A R; Wells, J C K; Cook, D G; Whincup, P H

2017-07-01

Body mass index (BMI) (weight per height 2 ) is the most widely used marker of childhood obesity and total body fatness (BF). However, its validity is limited, especially in children of South Asian and Black African origins. We aimed to quantify BMI adjustments needed for UK children of Black African and South Asian origins so that adjusted BMI related to BF in the same way as for White European children. We used data from four recent UK studies that made deuterium dilution BF measurements in UK children of White European, South Asian and Black African origins. A height-standardized fat mass index (FMI) was derived to represent BF. Linear regression models were then fitted, separately for boys and girls, to quantify ethnic differences in BMI-FMI relationships and to provide ethnic-specific BMI adjustments. We restricted analyses to 4-12 year olds, to whom a single consistent FMI (fat mass per height 5 ) could be applied. BMI consistently underestimated BF in South Asians, requiring positive BMI adjustments of +1.12 kg m - 2 (95% confidence interval (CI): 0.83, 1.41 kg m - 2 ; P<0.0001) for boys and +1.07 kg m - 2 (95% CI: 0.74, 1.39 kg m - 2 ; P<0.0001) for girls of all age groups and FMI levels. BMI overestimated BF in Black Africans, requiring negative BMI adjustments for Black African children. However, these were complex because there were statistically significant interactions between Black African ethnicity and FMI (P=0.004 boys; P=0.003 girls) and also between FMI and age group (P<0.0001 for boys and girls). BMI adjustments therefore varied by age group and FMI level (and indirectly BMI); the largest adjustments were in younger children with higher unadjusted BMI and the smallest in older children with lower unadjusted BMI. BMI underestimated BF in South Asians and overestimated BF in Black Africans. Ethnic-specific adjustments, increasing BMI in South Asians and reducing BMI in Black Africans, can improve the accuracy of BF assessment in

Spectral Reflectance and Vegetation Index Changes in Deciduous Forest Foliage Following Tree Removal: Potential for Deforestation Monitoring

NASA Astrophysics Data System (ADS)

Peng, D.; Hu, Y.; Li, Z.

2016-05-01

It is important to detect and quantify deforestation to guide strategic decisions regarding environment, socioeconomic development, and climate change. In the present study, we conducted a field experiment to examine spectral reflectance and vegetation index changes in poplar and locust tree foliage with different leaf area indices over the course of three sunny days, following tree removal from the canopy. The spectral reflectance of foliage from harvested trees was measured using an ASD FieldSpec Prospectroradiometer; synchronous meteorological data were also obtained. We found that reflectance in short-wave infrared and red-edge reflectance was more time sensitive after tree removal than reflectance in other spectral regions, and that the normalized difference water index (NDWI) and the red-edge chlorophyll index (CIRE) were the preferred indicators of these changes from several indices evaluated. Synthesized meteorological environments were found to influence water and chlorophyll contents after tree removal, and this subsequently changed the spectral canopy reflectance. Our results indicate the potential for such tree removal to be detected with NDWI or CIRE from the second day of a deforestation event.

Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data. [Normalized Difference Vegetation Index

NASA Technical Reports Server (NTRS)

Nemani, Ramakrishna R.; Running, Steven W.

1989-01-01

Infrared surface temperatures from satellite sensors have been used to infer evaporation and soil moisture distribution over large areas. However, surface energy partitioning to latent versus sensible heat changes with surface vegetation cover and water availability. The hypothesis that the relationship between surface temperature and canopy density is sensitivite to seasonal changes in canopy resistance of conifer forests is presently tested. Surface temperature and canopy density were computed for a 20 x 25 km forested region in Montana, from the NOAA/AVHRR for 8 days during the summer of 1985. A forest ecosystem model, FOREST-BGC, simulated canopy resistance for the same period. For all eight days, surface temperatures had high association with canopy density, measured as Normalized Difference Vegetation Index, implying that latent heat exchange is the major cause of spatial variations in surface radiant tmeperatures.

Integration of biomass data in the dynamic vegetation model ORCHIDEE

NASA Astrophysics Data System (ADS)

Delbart, N.; Viovy, N.; Ciais, P.; Le Toan, T.

2009-04-01

Dynamic vegetation models (DVMs) are aimed at estimating exchanges between the terrestrial vegetated surface and the atmosphere, and the spatial distribution of natural vegetation types. For this purpose, DVMs use the climatic data alone to feed the vegetation process equations. As dynamic models, they can also give predictions under the current and the future climatic conditions. However, they currently lack accuracy in locating carbon stocks, sinks and sources, and in getting the correct magnitude. Consequently they have been essentially used to compare the vegetation responses under different scenarii. The assimilation of external data such as remote sensing data has been shown to improve the simulations. For example, the land cover maps are used to force the correct distribution of plant functional types (PFTs), and the leaf area index data is used to force the photosynthesis processes. This study concerns the integration of biomass data within the DVM ORCHIDEE. The objective here is to have the living carbon stocks with the correct magnitude and the correct location. Carbon stocks depend on interplay of carbon assimilated by photosynthesis, and carbon lost by respiration, mortality and disturbance. Biomass data can therefore be used as one essential constraint on this interplay. In this study, we use a large database provided by in-situ measurements of carbon stocks and carbon fluxes of old growth forests to constraint this interplay. For each PFT, we first adjust the simulated photosynthesis by reducing the mean error with the in situ measurements. Then we proceed similarly to adjust the autotrophic respiration. We then compare the biomass measured, and adjust the mortality processes in the model. Second, when processes are adjusted for each PFT to minimize the mean error on the carbon stock, biomass measurements can be assimilated. This assimilation is based on the hypothesis that the main variable explaining the biomass level at a given location is the age

Frequency of Fruit and Vegetable Consumption and the Oral Health-Related Quality of Life among Japanese Elderly: A Cross-Sectional Study from the Kyoto-Kameoka Study

PubMed Central

Nanri, Hinako; Itoi, Aya; Yamagata, Emi; Watanabe, Yuya; Yoshida, Tsukasa; Miyake, Motoko; Date, Heiwa; Ishikawa-Takata, Kazuko; Yoshida, Mitsuyoshi; Kikutani, Takeshi; Kimura, Misaka

2017-01-01

Objective: Many previous studies have reported that fruit and vegetable consumption is associated with a reduced risk of various disease, but whether or not their consumption is associated with the oral health-related quality of life (OHRQoL) is unclear. The objective of this study was to examine the association between the frequency of fruit and vegetable consumption and the OHRQoL in elderly subjects by sex. Methods: We analyzed cross-sectional data from a population-based Kyoto-Kameoka Study in 2012 of 3112 men and 3439 women (age ≥ 65 years). The frequencies of fruit and vegetable consumption were assessed using a validated food frequency questionnaire. We evaluated the OHRQoL using the General Oral Health Assessment Index (GOHAI), a self-reported measure designed to assess the oral health problems in old adults. Results: After adjusting for age, body mass index, alcohol, smoking, education, socioeconomic status, history of disease, medication use, mobility disability, and total energy intake, a higher frequency of combined fruit and vegetable consumption showed a significant positive association with the GOHAI score in both men and women (p-trend < 0.001 in both sexes). These associations remained significant after adjustment for poor mastication and denture use (p-trend all < 0.05 in both sexes). We observed a significant positive association even when the frequencies of fruit or vegetable consumption were analyzed separately (all p-trend < 0.05 in both sexes). Conclusions: A higher frequency of fruit and/or vegetable consumption independently showed a strong positive association with the OHRQoL in both men and women. Further prospective studies are needed to confirm these findings. PMID:29244736

Allium Vegetables and Stomach Cancer Risk in China

PubMed Central

Setiawan, Veronica Wendy; Yu, Guo-Pei; Lu, Qing-Yi; Lu, Ming-Lan; Yu, Shun-Zhang; Mu, Lina; Zhang, Jian-Guo; Kurtz, Robert C; Cai, Lin; Hsieh, Chung-Cheng; Zhang, Zuo-Feng

2014-01-01

Although the incidence of stomach cancer has been declining, it remains the second leading cause of cancer death worldwide. Potential protective effects of allium vegetables against cancer have been reported by a few epidemiologic studies in Chinese populations, but the sample sizes of these studies were relatively small. We examined the associations between allium vegetable consumption and stomach cancer in a large population-based case-control study in Shanghai (750 cases and 750 age- and gender-matched controls) and Qingdao (128 cases and 128 age- and gender-matched controls). Epidemiological data were collected by a standard questionnaire, and odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using conditional logistic regression in SAS. After adjusting for matching variables, education, body mass index, pack-years of smoking, alcohol drinking, salt intake, and fruit and vegetable intake, inverse relationships with dose response pattern were observed between frequency of onion intake and stomach cancer in Qingdao (P for trend=0.02) and Shanghai (P for trend=0.04) populations. In Shanghai, negative dose-response relationships were observed between monthly intake of onions (P=0.03), monthly intake of garlic stalks (P=0.04) and distal cancer (but not with cardia cancer). Negative association was also noted between intake of garlic stalks (often vs. never) and risk of stomach cancer in Qingdao (OR=0.30; 95% CI: 0.12–0.77). Our results confirm the protective effect of allium vegetables (especially garlic and onions) against stomach cancer. PMID:16236005

Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops

NASA Astrophysics Data System (ADS)

Kross, Angela; McNairn, Heather; Lapen, David; Sunohara, Mark; Champagne, Catherine

2015-02-01

Leaf area index (LAI) and biomass are important indicators of crop development and the availability of this information during the growing season can support farmer decision making processes. This study demonstrates the applicability of RapidEye multi-spectral data for estimation of LAI and biomass of two crop types (corn and soybean) with different canopy structure, leaf structure and photosynthetic pathways. The advantages of Rapid Eye in terms of increased temporal resolution (∼daily), high spatial resolution (∼5 m) and enhanced spectral information (includes red-edge band) are explored as an individual sensor and as part of a multi-sensor constellation. Seven vegetation indices based on combinations of reflectance in green, red, red-edge and near infrared bands were derived from RapidEye imagery between 2011 and 2013. LAI and biomass data were collected during the same period for calibration and validation of the relationships between vegetation indices and LAI and dry above-ground biomass. Most indices showed sensitivity to LAI from emergence to 8 m2/m2. The normalized difference vegetation index (NDVI), the red-edge NDVI and the green NDVI were insensitive to crop type and had coefficients of variations (CV) ranging between 19 and 27%; and coefficients of determination ranging between 86 and 88%. The NDVI performed best for the estimation of dry leaf biomass (CV = 27% and r2 = 090) and was also insensitive to crop type. The red-edge indices did not show any significant improvement in LAI and biomass estimation over traditional multispectral indices. Cumulative vegetation indices showed strong performance for estimation of total dry above-ground biomass, especially for corn (CV ≤ 20%). This study demonstrated that continuous crop LAI monitoring over time and space at the field level can be achieved using a combination of RapidEye, Landsat and SPOT data and sensor-dependant best-fit functions. This approach eliminates/reduces the need for reflectance

High Vegetable Fats Intake Is Associated with High Resting Energy Expenditure in Vegetarians.

PubMed

Montalcini, Tiziana; De Bonis, Daniele; Ferro, Yvelise; Carè, Ilaria; Mazza, Elisa; Accattato, Francesca; Greco, Marta; Foti, Daniela; Romeo, Stefano; Gulletta, Elio; Pujia, Arturo

2015-07-17

It has been demonstrated that a vegetarian diet may be effective in reducing body weight, however, the underlying mechanisms are not entirely clear. We investigated whether there is a difference in resting energy expenditure between 26 vegetarians and 26 non-vegetarians and the correlation between some nutritional factors and inflammatory markers with resting energy expenditure. In this cross-sectional study, vegetarians and non-vegetarians were matched by age, body mass index and gender. All underwent instrumental examinations to assess the difference in body composition, nutrient intake and resting energy expenditure. Biochemical analyses and 12 different cytokines and growth factors were measured as an index of inflammatory state. A higher resting energy expenditure was found in vegetarians than in non-vegetarians (p = 0.008). Furthermore, a higher energy from diet, fibre, vegetable fats intake and interleukin-β (IL-1β) was found between the groups. In the univariate and multivariable analysis, resting energy expenditure was associated with vegetarian diet, free-fat mass and vegetable fats (p < 0.001; Slope in statistic (B) = 4.8; β = 0.42). After adjustment for cytokines, log10 interleukin-10 (IL-10) still correlated with resting energy expenditure (p = 0.02). Resting energy expenditure was positively correlated with a specific component of the vegetarian's diet, i.e., vegetable fats. Furthermore, we showed that IL-10 was positively associated with resting energy expenditure in this population.

Standard and Amputation-Adjusted Body Mass Index Measures: Comparison and Relevance to Functional Measures, Weight-Related Comorbidities, and Dieting.

PubMed

Wong, Christopher Kevin; Wong, Ryan J

2017-12-01

People with limb loss may misjudge weight-related health when not adjusting body mass index (BMI) for amputation level. This cross-sectional, community-based study compared BMI and amputation-adjusted BMI (A-BMI) and evaluated relationships among BMI categories, function, and dieting. Subjects provided self-reported demographic, functional, and medical/prosthetic data including height and weight and completed performance-based balance and gait measures. A Web-based A-BMI calculator adjusted for amputation levels. Results for 294 subjects from 11 states (68.4% men; 76.5% white; average age, 55.6 [15.1] y) were reported, with vascular (49.7%) and unilateral transtibial (40.8%) amputations as the most common. Body mass index and A-BMI were closely correlated (Pearson r = 0.99), but a BMI of 28.6 (6.7) was less than an A-BMI of 30.3 (6.2) (t test, P < 0.001). Agreement among Centers for Disease Control BMI categories was moderate (κ = 0.48); 39.7% of BMI categories were underestimated without adjusting for amputations. Functional measures did not differ among BMI/A-BMI categories (P > 0.05). A larger than random proportion categorized as overweight by BMI dieted (χ, P < 0.05), and people categorized as overweight by A-BMI did not (38.3% classified as normal BMI). Functional abilities did not differ among BMI categories (Kruskal-Wallis and analysis of variance, P > 0.05). People with limb loss using BMI may underestimate weight-related health; a Web-based A-BMI calculator may help monitor weight to make dieting decisions.

Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2003-01-01

The Normalized Difference Vegetation Index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) has been widely used to monitor moisture-related vegetation condition. The relationship between vegetation vigor and moisture availability, however, is complex and has not been adequately studied with satellite sensor data. To better understand this relationship, an analysis was conducted on time series of monthly NDVI (1989–2000) during the growing season in the north and central U.S. Great Plains. The NDVI was correlated to the Standardized Precipitation Index (SPI), a multiple-time scale meteorological-drought index based on precipitation. The 3-month SPI was found to have the best correlation with the NDVI, indicating lag and cumulative effects of precipitation on vegetation, but the correlation between NDVI and SPI varies significantly between months. The highest correlations occurred during the middle of the growing season, and lower correlations were noted at the beginning and end of the growing season in most of the area. A regression model with seasonal dummy variables reveals that the relationship between the NDVI and SPI is significant in both grasslands and croplands, if this seasonal effect is taken into account. Spatially, the best NDVI–SPI relationship occurred in areas with low soil water-holding capacity. Our most important finding is that NDVI is an effective indicator of vegetation-moisture condition, but seasonal timing should be taken into consideration when monitoring drought with the NDVI.

An approach to compute the C factor for universal soil loss equation using EOS-MODIS vegetation index (VI)

NASA Astrophysics Data System (ADS)

Li, Hui; He, Huizhong; Chen, Xiaoling; Zhang, Lihua

2008-12-01

C factor, known as cover and management factor in USLE, is one of the most important factors since it represents the combined effects of plant, soil cover and management on erosion, whereas it also most easily changed variables by men for it itself is time-variant and the uncertainty nature. So it's vital to compute C factor properly in order to model erosion effectively. In this paper we attempt to present a new method for calculating C value using Vegetation Index (VI) derived from multi-temporal MODIS imagery, which can estimate C factor in a more scientific way. Based on the theory that C factor is strongly correlated with VI, the average annual C value is estimated by adding the VI value of three growth phases within a year with different weights. Modified Fournier Index (MFI) is employed to determine the weight of each growth phase for the vegetation growth and agricultural activities are significantly influenced by precipitation. The C values generated by the proposed method were compared with that of other method, and the results showed that the results of our method is highly correlated with the others. This study is helpful to extract C value from satellite data in a scientific and efficient way, which in turn could be used to facilitate the prediction of erosion.

Study of Wetland Ecosystem Vegetation Using Satellite Data

NASA Astrophysics Data System (ADS)

Dyukarev, E. A.; Alekseeva, M. N.; Golovatskaya, E. A.

2017-12-01

The normalized difference vegetation index (NDVI) is used to estimate the aboveground net production (ANP) of wetland ecosystems for the key area at the South Taiga zone of West Siberia. The vegetation index and aboveground production are related by linear dependence and are specific for each wetland ecosystem. The NDVI grows with an increase in the ANP at wooded oligotrophic ecosystems. Open oligotrophic bogs and eutrophic wetlands are characterized by an opposite relation. Maps of aboveground production for wetland ecosystems are constructed for each study year and for the whole period of studies. The average aboveground production for all wetland ecosystems of the key area, which was estimated with consideration for the area they occupy and using the data of satellite measurements of the vegetation index, is 305 g C/m2/yr. The total annual carbon accumulation in aboveground wetland vegetation in the key area is 794600 t.

Study of atmospheric and bidirectional effects on surface reflectance and vegetation index time series: Application to NOAA AVHRR and preparation for future space missions

NASA Technical Reports Server (NTRS)

Frouin, Robert

1993-01-01

The objectives of the investigation, namely 'to characterize the atmospheric and directional effects on surface reflectance and vegetation index using the First International Satellite Cloud Climatology Project (ISLCSP) Field Experiment (FIFE) data set, develop new algorithms to obtain better Advanced Very High Resolution Radiometer (AVHRR) indices, and define possible improvements for future satellite missions', were addressed in three separate, yet complementary studies. First, it was shown, from theoretical calculations, that visible and near infrared reflectances combined linearly at optimum (one or two) viewing angles relate linearly to the fraction of photosynthetically available radiation absorbed by plants, f(sub par), can be used independently of the type of foliage and substrate, eliminate the effects of sub-pixel spatial heterogeneity, and improve the accuracy of the f(sub par) estimates when compared to the Normalized Difference Vegetation Index, NDVI. Second, it was demonstrated that NDVI, even though it is not a linear combination of radiances or reflectances, can be spatially integrated without significant loss of information from scales of 300 to 1000 m. Third, AVHRR visible and near-infrared reflectances over the FIFE site, separating temporal and bidirectional components and determining the model parameters through an original iterative scheme was successfully modeled. It appears that NDVI generated from the top-of-atmosphere reflectances normalized by the bidirectional effects (as determined in the scheme) is a better vegetation index than maximum NDVI. Details about the three studies are presented.

On the relationship between thermal emissivity and the Normalized Difference Vegetation Index for natural surfaces

NASA Technical Reports Server (NTRS)

Van De Griend, A. A.; Owe, M.

1993-01-01

The spatial variation of both the thermal emissivity (8-14 microns) and Normalized Difference Vegetation Index (NDVI) was measured for a series of natural surfaces within a savanna environment in Botswana. The measurements were performed with an emissivity-box and with a combined red and near-IR radiometer, with spectral bands corresponding to NOAA/AVHRR. It was found that thermal emissivity was highly correlated with NDVI after logarithmic transformation, with a correlation coefficient of R = 0.94. This empirical relationship is of potential use for energy balance studies using thermal IR remote sensing. The relationship was used in combination with AVHRR (GAC), AVHRR (LAC), and Landsat (TM) data to demonstrate and compare the spatial variability of various spatial scales.

Marsh collapse thresholds for coastal Louisiana estimated using elevation and vegetation index data

USGS Publications Warehouse

Couvillion, Brady R.; Beck, Holly

2013-01-01

Forecasting marsh collapse in coastal Louisiana as a result of changes in sea-level rise, subsidence, and accretion deficits necessitates an understanding of thresholds beyond which inundation stress impedes marsh survival. The variability in thresholds at which different marsh types cease to occur (i.e., marsh collapse) is not well understood. We utilized remotely sensed imagery, field data, and elevation data to help gain insight into the relationships between vegetation health and inundation. A Normalized Difference Vegetation Index (NDVI) dataset was calculated using remotely sensed data at peak biomass (August) and used as a proxy for vegetation health and productivity. Statistics were calculated for NDVI values by marsh type for intermediate, brackish, and saline marsh in coastal Louisiana. Marsh-type specific NDVI values of 1.5 and 2 standard deviations below the mean were used as upper and lower limits to identify conditions indicative of collapse. As marshes seldom occur beyond these values, they are believed to represent a range within which marsh collapse is likely to occur. Inundation depth was selected as the primary candidate for evaluation of marsh collapse thresholds. Elevation relative to mean water level (MWL) was calculated by subtracting MWL from an elevation dataset compiled from multiple data types including light detection and ranging (lidar) and bathymetry. A polynomial cubic regression was used to examine a random subset of pixels to determine the relationship between elevation (relative to MWL) and NDVI. The marsh collapse uncertainty range values were found by locating the intercept of the regression line with the 1.5 and 2 standard deviations below the mean NDVI value for each marsh type. Results indicate marsh collapse uncertainty ranges of 30.7–35.8 cm below MWL for intermediate marsh, 20–25.6 cm below MWL for brackish marsh, and 16.9–23.5 cm below MWL for saline marsh. These values are thought to represent the ranges of

[Responses of normalized difference vegetation index (NDVI) to precipitation changes on the grassland of Tibetan Plateau from 2000 to 2015.

PubMed

Wang, Zhi Peng; Zhang, Xian Zhou; He, Yong Tao; Li, Meng; Shi, Pei Li; Zu, Jia Xing; Niu, Ben

2018-01-01

Precipitation change is an important factor in the inter-annual variation of grassland growth on the Tibetan Plateau. The total amount, distribution pattern and concentration time are three basic characteristics of precipitation change. The temporal and spatial characteristics of precipitation change were analyzed based on climate data of 145 meteorological stations on the Tibetan Plateau and nearby areas from 2000 to 2015. The total precipitation amount was characterized by annual precipitation, distribution pattern of precipitation during the year was characterized by improved precipitation concentration index (PCI), and precipitation centroid (PC) was defined to indicate the change in precipitation concentrated time. To better illustrate the response of grassland to precipitation change, vegetation growth status was characterized by the maximum value of normalized difference vegetation index (NDVI max ). Results indicated that the annual precipitation and PCI had an apparent gradient across the whole plateau and the latest PC occurred in the southern plateau. NDVI max of alpine shrub grassland was significantly correlated with the change of PCI,increased with even distribution of precipitation during growth period, and limited by the total annual precipitation. Alpine meadow did not show significantly correlations with these three indices. The inter-annual variability of NDVI max of steppe was controlled by both PCI and PC. NDVI max of alpine desert grassland was mainly controlled by annual precipitation. In addition to annual total amount of precipitation, the distribution characteristics of precipitation should be further considered when the influence of precipitation change on different types of vegetation on the Qinghai Tibet Plateau was studied.

Fresh Fruit and Vegetable Program and Requests for Fruits and Vegetables Outside School Settings.

PubMed

Ohri-Vachaspati, Punam; Dachenhaus, Elizabeth; Gruner, Jessie; Mollner, Kristina; Hekler, Eric B; Todd, Michael

2018-01-08

Consumption of fruits and vegetables (F/V) among elementary school-aged children remains inadequate, especially among low-income children. The US Department of Agriculture's Fresh Fruit and Vegetable Program (FFVP) provides F/V as snacks to children during the school day, outside of school meals. School-based initiatives are successful in changing behaviors in school settings; however, their influence on behaviors outside of schools needs investigation. To examine whether FFVP participation is associated with F/V requests at stores, self-efficacy to ask for and choose F/V at home, and F/V consumption. Cross-sectional study. Fourth graders in six classrooms (n=296) from three urban, low-income school districts in Phoenix, AZ, were surveyed during 2015; one FFVP and one non-FFVP school from each district that were similar in school size, percent free/reduced-price meal eligibility, and race/ethnicity of enrolled students were selected. Children's self-reported F/V requests during shopping, their self-efficacy to ask for and choose F/V at home, and F/V consumption on the previous day (non-FFVP school day) were measured using questions adapted from validated surveys. Multivariable mixed-effect regression models, adjusting for clustering of students within classes and classes within schools were explored. In models adjusting for individual-level factors (ie, age and sex) only, several significant positive associations were observed between school FFVP participation and healthier F/V outcomes. After additionally adjusting for school-level factors (ie, total enrollment and % Hispanic/Latino students) significant associations were observed between school FFVP participation and more requests for vegetables during shopping (P<0.001), higher scores on self-efficacy to choose vegetables at home (P=0.004), stronger preferences for vegetables (P<0.001), and more frequent consumption of fruit (P=0.006). School FFVP participation was associated with more requests for vegetables

Integrating multiple vegetation indices via an artificial neural network model for estimating the leaf chlorophyll content of Spartina alterniflora under interspecies competition.

PubMed

Liu, Pudong; Shi, Runhe; Zhang, Chao; Zeng, Yuyan; Wang, Jiapeng; Tao, Zhu; Gao, Wei

2017-10-31

The invasive species Spartina alterniflora and native species Phragmites australis display a significant co-occurrence zonation pattern and this co-exist region exerts most competitive situations between these two species, competing for the limited space, directly influencing the co-exist distribution in the future. However, these two species have different growth ratios in this area, which increase the difficulty to detect the distribution situation directly by remote sensing. As chlorophyll content is a key indicator of plant growth and physiological status, the objective of this study was to reduce the effect of interspecies competition when estimating Cab content; we evaluated 79 published representative indices to determine the optimal indices for estimating the chlorophyll a and b (Cab) content. After performing a sensitivity analysis for all 79 spectral indices, five spectral indices were selected and integrated using an artificial neural network (ANN) to estimate the Cab content of different competition ratios: the Gitelson ratio green index, the transformed chlorophyll absorption ratio index/optimized soil-adjusted vegetation index, the modified normalized difference vegetation index, the chlorophyll fluorescence index, and the Vogelmann chlorophyll index. The ANN method yielded better results (R 2  = 0.7110 and RMSE = 8.3829 μg cm -2 ) on average than the best single spectral index (R 2  = 0.6319 and RMSE = 9.3535 μg cm -2 ), representing an increase of 10.78% in R 2 and a decrease of 10.38% in RMSE. Our results indicated that integrating multiple vegetation indices with an ANN can alleviate the impact of interspecies competition and achieve higher estimation accuracy than the traditional approach using a single index.

[Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

PubMed

Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

2016-01-01

With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote

Body mass index adjustments to increase the validity of body fatness assessment in UK Black African and South Asian children

PubMed Central

Hudda, M T; Nightingale, C M; Donin, A S; Fewtrell, M S; Haroun, D; Lum, S; Williams, J E; Owen, C G; Rudnicka, A R; Wells, J C K; Cook, D G; Whincup, P H

2017-01-01

Background/Objectives: Body mass index (BMI) (weight per height2) is the most widely used marker of childhood obesity and total body fatness (BF). However, its validity is limited, especially in children of South Asian and Black African origins. We aimed to quantify BMI adjustments needed for UK children of Black African and South Asian origins so that adjusted BMI related to BF in the same way as for White European children. Methods: We used data from four recent UK studies that made deuterium dilution BF measurements in UK children of White European, South Asian and Black African origins. A height-standardized fat mass index (FMI) was derived to represent BF. Linear regression models were then fitted, separately for boys and girls, to quantify ethnic differences in BMI–FMI relationships and to provide ethnic-specific BMI adjustments. Results: We restricted analyses to 4–12 year olds, to whom a single consistent FMI (fat mass per height5) could be applied. BMI consistently underestimated BF in South Asians, requiring positive BMI adjustments of +1.12 kg m−2 (95% confidence interval (CI): 0.83, 1.41 kg m−2; P<0.0001) for boys and +1.07 kg m−2 (95% CI: 0.74, 1.39 kg m−2; P<0.0001) for girls of all age groups and FMI levels. BMI overestimated BF in Black Africans, requiring negative BMI adjustments for Black African children. However, these were complex because there were statistically significant interactions between Black African ethnicity and FMI (P=0.004 boys; P=0.003 girls) and also between FMI and age group (P<0.0001 for boys and girls). BMI adjustments therefore varied by age group and FMI level (and indirectly BMI); the largest adjustments were in younger children with higher unadjusted BMI and the smallest in older children with lower unadjusted BMI. Conclusions: BMI underestimated BF in South Asians and overestimated BF in Black Africans. Ethnic-specific adjustments, increasing BMI in South Asians and reducing BMI in Black

Study of vegetation cover distribution using DVI, PVI, WDVI indices with 2D-space plot

NASA Astrophysics Data System (ADS)

Naji, Taghreed A. H.

2018-05-01

The present work aims to study the effect of using vegetation indices technique on image segmentation for subdividing an image into the homogeneous regions. Three of these vegetation indices technique has been adopted (i.e. Difference Vegetation-Index (DVI), Perpendicular Vegetation Index (PVI) and Weighted Difference Vegetation Index (WDVI)) for detecting and monitoring vegetation distribution and healthiness. Image binarization method being followed the implementation of the indices to isolating the vegetation areas from the image background. The separated agriculture regions from other land use regions and their percentages are presented for two years (2001 and 2002) of the (ETM+) scenes. The counted areas resulted from 2D-space plot technique and the separated vegetated areas resulted from the using of the vegetation indices are also presented. The separated agriculture regions from the implementation of the DVI-index have proved better than other used indices. Because it showed better coincident approximately with 2D-space plot segmentation.

NDVI (Normalized Difference Vegetation Index) signatures of transient ecohydrological systems: The case of post-mining landscapes

NASA Astrophysics Data System (ADS)

Brück, Yasemine; Schulte Overberg, Philipp; Pohle, Ina; Hinz, Christoph

2017-04-01

Assessing ecohydrological systems that undergo state transitions due to environmental change is becoming increasingly important. One system that can be used to study severe disturbances are post-mining landscapes as they usually are associated with complete removal of vegetation and afterwards subsequent ecosystem restoration or spontaneous rehabilitation in line with natural succession. Within this context it is of interest, whether and how (fast) the land cover in these areas returns to conditions comparable to those in the undisturbed surrounding or those prior mining. Many aspects of mine site rehabilitation depend on climatic, geomorphic and ecological settings, which determine at which rate vegetation may be re-established. In order to identify general patterns of vegetation establishment, we propose to use NDVI (Normalized Difference Vegetation Index) time series for mine affected land to estimate rate of recovery across climate regions and ecoregions. In this study we analysed the MODIS Terra Satellite 8 day-composite NDVI for areas influenced by surface mining in different climates from 2001 to 2015. The locations have been chosen based on their extent and the data availability of mining and rehabilitation activities. We selected coal extraction as a case study as strip mining generates well-defined chronosequences of disturbance. The selected mining areas are located in equatorial, arid, warm temperate or snow climates with different precipitation and temperature conditions according to the Köppen-Geiger classification. We analysed the NDVI time series regarding significant characteristics of the re-vegetation phase. We applied hierarchical cluster analysis to capture the spatial heterogeneity between different pixels (ca. 250 * 250 m2 each) in and around each open cast mine. We disentangled seasonality, trend and residual components in the NDVI time series by Seasonal and Trend decomposition using LOESS. As expected the time of the removal of vegetation

Antireflective coatings with adjustable refractive index and porosity synthesized by micelle-templated deposition of MgF2 sol particles.

PubMed

Bernsmeier, Denis; Polte, Jörg; Ortel, Erik; Krahl, Thoralf; Kemnitz, Erhard; Kraehnert, Ralph

2014-11-26

Minimizing efficiency losses caused by unwanted light reflection at the interface between lenses, optical instruments and solar cells with the surrounding medium requires antireflective coatings with adequate refractive index and coating thickness. We describe a new type of antireflective coating material with easily and independently tailorable refractive index and coating thickness based on the deposition of colloidal MgF2 nanoparticles. The material synthesis employs micelles of amphiphilic block copolymers as structure directing agent to introduce controlled mesoporosity into MgF2 film. The coatings thickness can be easily adjusted by the applied coating conditions. The coatings refractive index is determined by the materials porosity, which is controlled by the amount of employed pore template. The refractive index can be precisely tuned between 1.23 and 1.11, i.e., in a range that is not accessible to nonporous inorganic materials. Hence, zero reflectance conditions can be established for a wide range of substrate materials.

Previous Gardening Experience and Gardening Enjoyment Is Related to Vegetable Preferences and Consumption Among Low-Income Elementary School Children.

PubMed

Evans, Alexandra; Ranjit, Nalini; Fair, Cori N; Jennings, Rose; Warren, Judith L

2016-10-01

To examine if gardening experience and enjoyment are associated with vegetable exposure, preferences, and consumption of vegetables among low-income third-grade children. Cross-sectional study design, using baseline data from the Texas! Grow! Eat! Go! Twenty-eight Title I elementary schools located in different counties in Texas. Third-grade students (n = 1,326, 42% Hispanic) MAIN OUTCOME MEASURES: Gardening experience, gardening enjoyment, vegetable exposure, preference, and consumption. Random-effects regression models, adjusted for age, sex, ethnicity, and body mass index percentile of child, estimated means and standard errors of vegetable consumption, exposure, and preference by levels of gardening experience and enjoyment. Wald χ 2 tests evaluated the significance of differences in means of outcomes across levels of gardening experience and enjoyment. Children with more gardening experience had greater vegetable exposure and higher vegetable preference and consumed more vegetables compared with children who reported less gardening experience. Those who reported that they enjoyed gardening had the highest levels of vegetable exposure, preference, and consumption. Garden-based interventions can have an important and positive effect on children's vegetable consumption by increasing exposure to fun gardening experiences. Copyright © 2016 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States

DOE PAGES

Robinson, Nathaniel; Allred, Brady; Jones, Matthew; ...

2017-08-21

Satellite derived vegetation indices (VIs) are broadly used in ecological research, ecosystem modeling, and land surface monitoring. The Normalized Difference Vegetation Index (NDVI), perhaps the most utilized VI, has countless applications across ecology, forestry, agriculture, wildlife, biodiversity, and other disciplines. Calculating satellite derived NDVI is not always straight-forward, however, as satellite remote sensing datasets are inherently noisy due to cloud and atmospheric contamination, data processing failures, and instrument malfunction. Readily available NDVI products that account for these complexities are generally at coarse resolution; high resolution NDVI datasets are not conveniently accessible and developing them often presents numerous technical and methodologicalmore » challenges. Here, we address this deficiency by producing a Landsat derived, high resolution (30 m), long-term (30+ years) NDVI dataset for the conterminous United States. We use Google Earth Engine, a planetary-scale cloud-based geospatial analysis platform, for processing the Landsat data and distributing the final dataset. We use a climatology driven approach to fill missing data and validate the dataset with established remote sensing products at multiple scales. We provide access to the composites through a simple web application, allowing users to customize key parameters appropriate for their application, question, and region of interest.« less

A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robinson, Nathaniel; Allred, Brady; Jones, Matthew

Satellite derived vegetation indices (VIs) are broadly used in ecological research, ecosystem modeling, and land surface monitoring. The Normalized Difference Vegetation Index (NDVI), perhaps the most utilized VI, has countless applications across ecology, forestry, agriculture, wildlife, biodiversity, and other disciplines. Calculating satellite derived NDVI is not always straight-forward, however, as satellite remote sensing datasets are inherently noisy due to cloud and atmospheric contamination, data processing failures, and instrument malfunction. Readily available NDVI products that account for these complexities are generally at coarse resolution; high resolution NDVI datasets are not conveniently accessible and developing them often presents numerous technical and methodologicalmore » challenges. Here, we address this deficiency by producing a Landsat derived, high resolution (30 m), long-term (30+ years) NDVI dataset for the conterminous United States. We use Google Earth Engine, a planetary-scale cloud-based geospatial analysis platform, for processing the Landsat data and distributing the final dataset. We use a climatology driven approach to fill missing data and validate the dataset with established remote sensing products at multiple scales. We provide access to the composites through a simple web application, allowing users to customize key parameters appropriate for their application, question, and region of interest.« less

Occupational adjustment of the prospective payment system wage index

PubMed Central

Pope, Gregory C.

1989-01-01

In this article, the bias in the Medicare prospective payment system (PPS) hospital wage index that results from its failure to hold hospital occupation mix constant is examined. On average, the difference between the current PPS wage index and a fixed-occupation-mix Laspeyres index is small, approximately 2 percent. However, occupation-mix distortions are substantially larger for a small proportion of labor market areas, especially some in the South. Biases in the wage index resulting from its failure to appropriately account for labor substitution and intra-occupational worker characteristics are also analyzed but are not found to be significant. PMID:10313354

Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices

NASA Astrophysics Data System (ADS)

Hamzeh, S.; Naseri, A. A.; AlaviPanah, S. K.; Mojaradi, B.; Bartholomeus, H. M.; Clevers, J. G. P. W.; Behzad, M.

2013-04-01

The presence of salt in the soil profile negatively affects the growth and development of vegetation. As a result, the spectral reflectance of vegetation canopies varies for different salinity levels. This research was conducted to (1) investigate the capability of satellite-based hyperspectral vegetation indices (VIs) for estimating soil salinity in agricultural fields, (2) evaluate the performance of 21 existing VIs and (3) develop new VIs based on a combination of wavelengths sensitive for multiple stresses and find the best one for estimating soil salinity. For this purpose a Hyperion image of September 2, 2010, and data on soil salinity at 108 locations in sugarcane (Saccharum officina L.) fields were used. Results show that soil salinity could well be estimated by some of these VIs. Indices related to chlorophyll absorption bands or based on a combination of chlorophyll and water absorption bands had the highest correlation with soil salinity. In contrast, indices that are only based on water absorption bands had low to medium correlations, while indices that use only visible bands did not perform well. From the investigated indices the optimized soil-adjusted vegetation index (OSAVI) had the strongest relationship (R2 = 0.69) with soil salinity for the training data, but it did not perform well in the validation phase. The validation procedure showed that the new salinity and water stress indices (SWSI) implemented in this study (SWSI-1, SWSI-2, SWSI-3) and the Vogelmann red edge index yielded the best results for estimating soil salinity for independent fields with root mean square errors of 1.14, 1.15, 1.17 and 1.15 dS/m, respectively. Our results show that soil salinity could be estimated by satellite-based hyperspectral VIs, but validation of obtained models for independent data is essential for selecting the best model.

Integrated study of biomass index in La Herreria (Sierra de Guadarrama)

NASA Astrophysics Data System (ADS)

Hernandez Díaz-Ambrona, Carlos G.

2016-04-01

Drought severity has many implications for society, including its impacts on the water supply, water pollution, reservoir management and ecosystem. There have been many attempts to characterize its severity, resulting in the numerous drought indices that have been developed (Niemeyer 2008). The'biomass index', based on satellite image derived Normalized Difference Vegetation Index (NDVI) has been used in several countries for pasture and forage crops for some years (Rao, 2010; Escribano-Rodriguez et al., 2014). NDVI generally provides a broad overview of the vegetation condition and spatial vegetation distribution in a region. Vegetative drought is closely related with weather impacts. However, in NDVI, the weather component gets subdued by the strong ecological component. Another vegetation index is Vegetation Condition Index (VCI) that separates the short-term weather-related NDVI fluctuations from the long-term ecosystem changes (Kogan, 1990). Therefore, while NDVI shows seasonal vegetation dynamics, VCI rescales vegetation dynamics between 0 and 100 to reflect relative changes in the vegetation condition from extremely bad to optimal (Kogan et al., 2003). In this work a pasture area at La Herreria (Sierra de Guadarrama, Spain) has been delimited. Then, NDVI historical data are reconstructed based on remote sensing imaging MODIS, with 500x500m2 resolution. From the closest meteorological station (Santolaria-Canales, 2015) records of weekly precipitation, temperature and evapotranspiration from 2001 till 2012 were obtained. Standard Precipitation Index (SPI), Crop Moisture Index (CMI) (Palmer, 1968) and Evapotranspiration-Precipitation Ratio (EPR) are calculated in an attempt to relate them to several vegetation indexes: NDVI, VCI and NDVI Change Ratio to Median (RMNDVI). The results are discussed in the context of pasture index insurance. References Escribano Rodriguez, J.Agustín, Carlos Gregorio Hernández Díaz-Ambrona and Ana María Tarquis Alfonso

Assessing the vegetation condition impacts of the 2011 drought across the U.S. southern Great Plains using the vegetation drought response index (VegDRI)

USGS Publications Warehouse

Tadesse, Tsegaye; Wardlow, Brian D.; Brown, Jesslyn F.; Svoboda, Mark; Hayes, Michael; Fuchs, Brian; Gutzmer, Denise

2015-01-01

The vegetation drought response index (VegDRI), which combines traditional climate- and satellite-based approaches for assessing vegetation conditions, offers new insights into assessing the impacts of drought from local to regional scales. In 2011, the U.S. southern Great Plains, which includes Texas, Oklahoma, and New Mexico, was plagued by moderate to extreme drought that was intensified by an extended period of record-breaking heat. The 2011 drought presented an ideal case study to evaluate the performance of VegDRI in characterizing developing drought conditions. Assessment of the spatiotemporal drought patterns represented in the VegDRI maps showed that the severity and patterns of the drought across the region corresponded well to the record warm temperatures and much-below-normal precipitation reported by the National Climatic Data Center and the sectoral drought impacts documented by the Drought Impact Reporter (DIR). VegDRI values and maps also showed the evolution of the drought signal before the Las Conchas Fire (the largest fire in New Mexico’s history). Reports in the DIR indicated that the 2011 drought had major adverse impacts on most rangeland and pastures in Texas and Oklahoma, resulting in total direct losses of more than $12 billion associated with crop, livestock, and timber production. These severe impacts on vegetation were depicted by the VegDRI at subcounty, state, and regional levels. This study indicates that the VegDRI maps can be used with traditional drought indicators and other in situ measures to help producers and government officials with various management decisions, such as justifying disaster assistance, assessing fire risk, and identifying locations to move livestock for grazing.

Analysis of Leaf Area Index and Fraction of PAR Absorbed by Vegetation Products from the Terra MODIS Sensor: 2000-2005

NASA Technical Reports Server (NTRS)

Yang, Wenze; Huang, Dong; Tan, Bin; Stroeve, Julienne C.; Shabanov, Nikolay V.; Knyazikhin, Yuri; Nemani, Ramakrishna R.; Myneni, Ranga B.

2006-01-01

The analysis of two years of Collection 3 and five years of Collection 4 Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) data sets is presented in this article with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus backup), snow (snow-free versus snow on the ground), and cloud (cloud-free versus cloudy) conditions. Retrievals from the main radiative transfer algorithm increased from 55% in Collection 3 to 67% in Collection 4 due to algorithm refinements and improved inputs. Anomalously high LAI/FPAR values observed in Collection 3 product in some vegetation types were corrected in Collection 4. The problem of reflectance saturation and too few main algorithm retrievals in broadleaf forests persisted in Collection 4. The spurious seasonality in needleleaf LAI/FPAR fields was traced to fewer reliable input data and retrievals during the boreal winter period. About 97% of the snow covered pixels were processed by the backup Normalized Difference Vegetation Index-based algorithm. Similarly, a majority of retrievals under cloudy conditions were obtained from the backup algorithm. For these reasons, the users are advised to consult the quality flags accompanying the LAI and FPAR product.

Generating Stock Trading Rules Using Genetic Network Programming with Flag Nodes and Adjustment of Importance Indexes

NASA Astrophysics Data System (ADS)

Mabu, Shingo; Chen, Yan; Hirasawa, Kotaro

Genetic Network Programming (GNP) is an evolutionary algorithm which represents its solutions using graph structures. Since GNP can create quite compact programs and has an implicit memory function, GNP works well especially in dynamic environments. In addition, a study on creating trading rules on stock markets using GNP with Importance Index (GNP-IMX) has been done. IMX is one of the criterions for decision making. However, the values of IMXs must be deteminined by our experience/knowledge. Therefore in this paper, IMXs are adjusted appropriately during the stock trading in order to predict the rise and fall of the stocks. Moreover, newly defined flag nodes are introduced to GNP, which can appropriately judge the current situation of the stock prices, and also contributes to the use of many kinds of nodes in GNP program. In the simulation, programs are evolved using the stock prices of 20 companies. Then the generalization ability is tested and compared with GNP without flag nodes, GNP without IMX adjustment and Buy&Hold.

High Vegetable Fats Intake Is Associated with High Resting Energy Expenditure in Vegetarians

PubMed Central

Montalcini, Tiziana; De Bonis, Daniele; Ferro, Yvelise; Carè, Ilaria; Mazza, Elisa; Accattato, Francesca; Greco, Marta; Foti, Daniela; Romeo, Stefano; Gulletta, Elio; Pujia, Arturo

2015-01-01

It has been demonstrated that a vegetarian diet may be effective in reducing body weight, however, the underlying mechanisms are not entirely clear. We investigated whether there is a difference in resting energy expenditure between 26 vegetarians and 26 non-vegetarians and the correlation between some nutritional factors and inflammatory markers with resting energy expenditure. In this cross-sectional study, vegetarians and non-vegetarians were matched by age, body mass index and gender. All underwent instrumental examinations to assess the difference in body composition, nutrient intake and resting energy expenditure. Biochemical analyses and 12 different cytokines and growth factors were measured as an index of inflammatory state. A higher resting energy expenditure was found in vegetarians than in non-vegetarians (p = 0.008). Furthermore, a higher energy from diet, fibre, vegetable fats intake and interleukin-β (IL-1β) was found between the groups. In the univariate and multivariable analysis, resting energy expenditure was associated with vegetarian diet, free-fat mass and vegetable fats (p < 0.001; Slope in statistic (B) = 4.8; β = 0.42). After adjustment for cytokines, log10 interleukin-10 (IL-10) still correlated with resting energy expenditure (p = 0.02). Resting energy expenditure was positively correlated with a specific component of the vegetarian’s diet, i.e., vegetable fats. Furthermore, we showed that IL-10 was positively associated with resting energy expenditure in this population. PMID:26193314

Effects of experimental protocol on global vegetation model accuracy: a comparison of simulated and observed vegetation patterns for Asia

USGS Publications Warehouse

Tang, Guoping; Shafer, Sarah L.; Barlein, Patrick J.; Holman, Justin O.

2009-01-01

Prognostic vegetation models have been widely used to study the interactions between environmental change and biological systems. This study examines the sensitivity of vegetation model simulations to: (i) the selection of input climatologies representing different time periods and their associated atmospheric CO2 concentrations, (ii) the choice of observed vegetation data for evaluating the model results, and (iii) the methods used to compare simulated and observed vegetation. We use vegetation simulated for Asia by the equilibrium vegetation model BIOME4 as a typical example of vegetation model output. BIOME4 was run using 19 different climatologies and their associated atmospheric CO2 concentrations. The Kappa statistic, Fuzzy Kappa statistic and a newly developed map-comparison method, the Nomad index, were used to quantify the agreement between the biomes simulated under each scenario and the observed vegetation from three different global land- and tree-cover data sets: the global Potential Natural Vegetation data set (PNV), the Global Land Cover Characteristics data set (GLCC), and the Global Land Cover Facility data set (GLCF). The results indicate that the 30-year mean climatology (and its associated atmospheric CO2 concentration) for the time period immediately preceding the collection date of the observed vegetation data produce the most accurate vegetation simulations when compared with all three observed vegetation data sets. The study also indicates that the BIOME4-simulated vegetation for Asia more closely matches the PNV data than the other two observed vegetation data sets. Given the same observed data, the accuracy assessments of the BIOME4 simulations made using the Kappa, Fuzzy Kappa and Nomad index map-comparison methods agree well when the compared vegetation types consist of a large number of spatially continuous grid cells. The results of this analysis can assist model users in designing experimental protocols for simulating vegetation.

Evaluation of Radar Vegetation Indices for Vegetation Water Content Estimation Using Data from a Ground-Based SMAP Simulator

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; O'Neill, Peggy; Cosh, Michael; Lang, Roger; Joseph, Alicia

2015-01-01

Vegetation water content (VWC) is an important component of microwave soil moisture retrieval algorithms. This paper aims to estimate VWC using L band active and passive radar/radiometer datasets obtained from a NASA ground-based Soil Moisture Active Passive (SMAP) simulator known as ComRAD (Combined Radar/Radiometer). Several approaches to derive vegetation information from radar and radiometer data such as HH, HV, VV, Microwave Polarization Difference Index (MPDI), HH/VV ratio, HV/(HH+VV), HV/(HH+HV+VV) and Radar Vegetation Index (RVI) are tested for VWC estimation through a generalized linear model (GLM). The overall analysis indicates that HV radar backscattering could be used for VWC content estimation with highest performance followed by HH, VV, MPDI, RVI, and other ratios.

Drought index driven by L-band microwave soil moisture data

NASA Astrophysics Data System (ADS)

Bitar, Ahmad Al; Kerr, Yann; Merlin, Olivier; Cabot, François; Choné, Audrey; Wigneron, Jean-Pierre

2014-05-01

Drought is considered in many areas across the globe as one of the major extreme events. Studies do not all agree on the increase of the frequency of drought events over the past 60 years [1], but they all agree that the impact of droughts has increased and the need for efficient global monitoring tools has become most than ever urgent. Droughts are monitored through drought indexes, many of which are based on precipitation (Palmer index(s), PDI…), on vegetation status (VDI) or on surface temperatures. They can also be derived from climate prediction models outputs. The GMO has selected the (SPI) Standardized Precipitation Index as the reference index for the monitoring of drought at global scale. The drawback of this index is that it is directly dependent on global precipitation products that are not accurate over global scale. On the other hand, Vegetation based indexes show the a posteriori effect of drought, since they are based on NDVI. In this study, we choose to combine the surface soil moisture from microwave sensor with climate data to access a drought index. The microwave data are considered from the SMOS (Soil Moisture and Ocean Salinity) mission at L-Band (1.4 Ghz) interferometric radiometer from ESA (European Space Agency) [2]. Global surface soil moisture maps with 3 days coverage for ascending 6AM and descending 6PM orbits SMOS have been delivered since January 2010 at a 40 km nominal resolution. We use in this study the daily L3 global soil moisture maps from CATDS (Centre Aval de Traitement des Données SMOS) [3,4]. We present a drought index computed by a double bucket hydrological model driven by operational remote sensing data and ancillary datasets. The SPI is also compared to other drought indicators like vegetation indexes and Palmer drought index. Comparison of drought index to vegetation indexes from AVHRR and MODIS over continental United States show that the drought index can be used as an early warning system for drought monitoring as

NOAA-AVHRR image mosaics applied to vegetation identification

NASA Astrophysics Data System (ADS)

de Almeida, Maria d. G.; Ruddorff, Bernardo F.; Shimabukuro, Yosio E.

2001-06-01

In this paper, the maximum-value composite of images procedure from Normalized Difference Vegetation Index is used to get a cloud free image mosaic. The image mosaic is used to identify vegetation targets such as tropical forest, savanna and caatinga as well to make the vegetation cover mapping of Minas Gerais state, Brazil.

Suppression of vegetation in LANDSAT ETM+ remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Le; Porwal, Alok; Holden, Eun-Jung; Dentith, Michael

2010-05-01

Vegetation cover is an impediment to the interpretation of multispectral remote sensing images for geological applications, especially in densely vegetated terrains. In order to enhance the underlying geological information in such terrains, it is desirable to suppress the reflectance component of vegetation. One form of spectral unmixing that has been successfully used for vegetation reflectance suppression in multispectral images is called "forced invariance". It is based on segregating components of the reflectance spectrum that are invariant with respect to a specific spectral index such as the NDVI. The forced invariance method uses algorithms such as software defoliation. However, the outputs of software defoliation are single channel data, which are not amenable to geological interpretations. Crippen and Blom (2001) proposed a new forced invariance algorithm that utilizes band statistics, rather than band ratios. The authors demonstrated the effectiveness of their algorithms on a LANDSAT TM scene from Nevada, USA, especially in open canopy areas in mixed and semi-arid terrains. In this presentation, we report the results of our experimentation with this algorithm on a densely to sparsely vegetated Landsat ETM+ scene. We selected a scene (Path 119, Row 39) acquired on 18th July, 2004. Two study areas located around the city of Hangzhou, eastern China were tested. One of them covers uninhabited hilly terrain characterized by low rugged topography, parts of the hills are densely vegetated; another one covers both inhabited urban areas and uninhabited hilly terrain, which is densely vegetated. Crippen and Blom's algorithm is implemented in the following sequential steps: (1) dark pixel correction; (2) vegetation index calculation; (3) estimation of statistical relationship between vegetation index and digital number (DN) values for each band; (4) calculation of a smooth best-fit curve for the above relationships; and finally, (5) selection of a target average DN

Vegetables, but not pickled vegetables, are negatively associated with the risk of breast cancer.

PubMed

Yu, Hyejin; Hwang, Ji-Yun; Ro, Jungsil; Kim, Jeongseon; Chang, Namsoo

2010-01-01

This study investigated the association between pickled vegetable consumption and the risk of breast cancer using a validated food frequency questionnaire. A total of 358 patients with breast cancer who were matched to 360 healthy controls by age (using a 5-yr age distribution) were recruited from the National Cancer Center in South Korea. After adjusting for nondietary risk factors, total vegetable intake was inversely associated with risk of breast cancer. However, unlike nonpickled vegetables, pickled vegetable intake and its proportion relative to total vegetables were positively associated with the risk of breast cancer, and this association was more profound and consistent when pickled vegetable intake was considered as a proportion relative to total vegetables (odds ratio [OR] = 6.24, 95% confidence interval [CI] = 3.55-10.97; P for trend <0.001 for highest vs. lowest quartiles of intake) than as the absolute consumed amount (OR = 2.47, 95% CI = 1.45-4.21; P for trend = 0.015 for highest vs. lowest quartiles of intake). These results suggest that not only the amount of total vegetable intake but also the amounts of different types of vegetable (i.e., pickled or nonpickled) and their proportions relative to total vegetables are significantly associated with the risk of breast cancer.

VIP Data Explorer: A Tool for Exploring 30 years of Vegetation Index and Phenology Observations

NASA Astrophysics Data System (ADS)

Barreto-munoz, A.; Didan, K.; Rivera-Camacho, J.; Yitayew, M.; Miura, T.; Tsend-Ayush, J.

2011-12-01

Continuous acquisition of global satellite imagery over the years has contributed to the creation of long term data records from AVHRR, MODIS, TM, SPOT-VGT and other sensors. These records account for 30+ years, as these archives grow, they become invaluable tools for environmental, resources management, and climate studies dealing with trends and changes from local, regional to global scale. In this project, the Vegetation Index and Phenology Lab (VIPLab) is processing 30 years of daily global surface reflectance data into an Earth Science Data Record of Vegetation Index and Phenology metrics. Data from AVHRR (N07,N09,N11 and N14) and MODIS (AQUA and TERRA collection 5) for the periods 1981-1999 and 2000-2010, at CMG resolution were processed into one seamless and sensor independent data record using various filtering, continuity and gap filling techniques (Tsend-Ayush et al., AGU 2011, Rivera-Camacho et al, AGU 2011). An interactive online tool (VIP Data Explorer) was developed to support the visualization, qualitative and quantitative exploration, distribution, and documentation of these records using a simple web 2.0 interface. The VIP Data explorer (http://vip.arizona.edu/viplab_data_explorer) can display any combination of multi temporal and multi source data, enable the quickly exploration and cross comparison of the various levels of processing of this data. It uses the Google Earth (GE) model and was developed using the GE API for images rendering, manipulation and geolocation. These ESDRs records can be quickly animated in this environment and explored for visual trends and anomalies detection. Additionally the tool enables extracting and visualizing any land pixel time series while showing the different levels of processing it went through. User can explore this ESDR database within this data explorer GUI environment, and any desired data can be placed into a dynamic "cart" to be ordered and downloaded later. More functionalities are planned and will be

Vegetation shifts observed in arctic tundra 17 years after fire

USGS Publications Warehouse

Barrett, Kirsten; Rocha, Adrian V.; van de Weg, Martine Janet; Shaver, Gaius

2012-01-01

With anticipated climate change, tundra fires are expected to occur more frequently in the future, but data on the long-term effects of fire on tundra vegetation composition are scarce. This study addresses changes in vegetation structure that have persisted for 17 years after a tundra fire on the North Slope of Alaska. Fire-related shifts in vegetation composition were assessed from remote-sensing imagery and ground observations of the burn scar and an adjacent control site. Early-season remotely sensed imagery from the burn scar exhibits a low vegetation index compared with the control site, whereas the late-season signal is slightly higher. The range and maximum vegetation index are greater in the burn scar, although the mean annual values do not differ among the sites. Ground observations revealed a greater abundance of moss in the unburned site, which may account for the high early growing season normalized difference vegetation index (NDVI) anomaly relative to the burn. The abundance of graminoid species and an absence of Betula nana in the post-fire tundra sites may also be responsible for the spectral differences observed in the remotely sensed imagery. The partial replacement of tundra by graminoid-dominated ecosystems has been predicted by the ALFRESCO model of disturbance, climate and vegetation succession.

Evaluation of a native vegetation masking technique

NASA Technical Reports Server (NTRS)

Kinsler, M. C.

1984-01-01

A crop masking technique based on Ashburn's vegetative index (AVI) was used to evaluate native vegetation as an indicator of crop moisture condition. A mask of the range areas (native vegetation) was generated for each of thirteen Great Plains LANDSAT MSS sample segments. These masks were compared to the digitized ground truth and accuracies were computed. An analysis of the types of errors indicates a consistency in errors among the segments. The mask represents a simple quick-look technique for evaluating vegetative cover.

Estimating wheat growth with radar vegetation indices

USDA-ARS?s Scientific Manuscript database

In this study, we computed the Radar Vegetation Index (RVI) using observations made with a ground based multi-frequency polarimetric scatterometer system over an entire wheat growth period. The temporal variations of the backscattering coefficients for L-, C-, and X-band, RVI, vegetation water conte...

Association between Frequency of Consumption of Fruit, Vegetables, Nuts and Pulses and BMI: Analyses of the International Study of Asthma and Allergies in Childhood (ISAAC).

PubMed

Wall, Clare R; Stewart, Alistair W; Hancox, Robert J; Murphy, Rinki; Braithwaite, Irene; Beasley, Richard; Mitchell, Edwin A

2018-03-07

Diets which emphasize intakes of plant-based foods are recommended to reduce disease risk and for promoting healthy weight. The aim of this study was to examine the association between fruit, vegetables, pulses and nut intake and body mass index (BMI) across countries in adolescents (13-14 years) and children (6-7 years). Data from the International Study of Asthma and Allergies in Childhood; 77,243 children's parents and 201,871 adolescents was used to examine the association between dietary intake (Food Frequency Questionnaire) and BMI using general linear models, adjusting for country gross national index. Adolescents who consumed fruit, vegetables, pulses and nuts three or more times a week had a lower BMI than the never or occasional group; eating nuts three or more times a week, was associated with a BMI value of 0.274 kg/m² lower than the never group ( p < 0.001). Compared to children who never or occasionally reported eating vegetables, those reporting that they ate vegetables three or more times per week had a lower BMI of -0.079 kg/m². In this large global study, an inverse association was observed between BMI and the reported increasing intake of vegetables in 6-7 years old and fruit, vegetables, pulses and nuts in adolescents. This study supports current dietary recommendations which emphasize the consumption of vegetables, nut and pulses, although the effect sizes were small.

The effect of water vapour on the normalized difference vegetation index derived for the Sahelian region from NOAA AVHRR data

NASA Technical Reports Server (NTRS)

Justice, Christopher O.; Eck, T. F.; Tanre, Didier; Holben, B. N.

1991-01-01

The near-infrared channel of the NOAA advanced very high resolution radiometer (AVHRR) contains a water vapor absorption band that affects the determination of the normalized difference vegetation index (NDVI). Daily and seasonal variations in atmospheric water vapor within the Sahel are shown to affect the use of the NDVI for the estimation of primary production. This water vapor effect is quantified for the Sahel by radiative transfer modeling and empirically using observations made in Mali in 1986.

Sixteen years of agricultural drought assessment of the BioBío region in Chile using a 250 m resolution Vegetation Condition Index (VCI)

NASA Astrophysics Data System (ADS)

Zambrano, Francisco; Lillo-Saavedra, Mario; Verbist, Koen; Lagos, Octavio

2016-10-01

Drought is one of the most complex natural hazards because of its slow onset and long-term impact; it has the potential to negatively affect many people. There are several advantages to using remote sensing to monitor drought, especially in developing countries with limited historical meteorological records and a low weather station density. In the present study, we assessed agricultural drought in the croplands of the BioBio Region in Chile. The vegetation condition index (VCI) allows identifying the temporal and spatial variations of vegetation conditions associated with stress because of rainfall deficit. The VCI was derived at a 250m spatial resolution for the 2000-2015 period with the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 product. We evaluated VCI for cropland areas using the land cover MCD12Q1 version 5.1 product and compared it to the in situ Standardized Precipitation Index (SPI) for six-time scales (1-6 months) from 26 weather stations. Results showed that the 3-month SPI (SPI-3), calculated for the modified growing season (Nov-Apr) instead of the regular growing season (Sept-Apr), has the best Pearson correlation with VCI values with an overall correlation of 0.63 and between 0.40 and 0.78 for the administrative units. These results show a very short-term vegetation response to rainfall deficit in September, which is reflected in the vegetation in November, and also explains to a large degree the variation in vegetation stress. It is shown that for the last 16 years in the BioBio Region we could identify the 2007/2008, 2008/2009, and 2014/2015 seasons as the three most important drought events; this is reflected in both the overall regional and administrative unit analyses. These results concur with drought emergencies declared by the regional government. Future studies are needed to associate the remote sensing values observed at high resolution (250m) with the measured crop yield to identify more detailed individual crop

Monitoring vegetation greenness with satellite data

Treesearch

Robert E. Burgan; Roberta A. Hartford

1993-01-01

Vegetation greenness can be monitored at 1-km resolution for the conterminous United States through data obtained from the Advanced Very High Resolution Radiometer on the NOAA-11 weather satellites. The data are used to calculate biweekly composites of the Normalized Difference Vegetation Index. The resulting composite images are updated weekly and made available to...

Comparison of the New LEAF Area INDEX (LAI 3G) with the Kazahstan-Wide LEAF Area INDEX DATA SET (GGRS-LAI) over Central ASIA

NASA Astrophysics Data System (ADS)

Kappas, M.; Propastin, P.; Degener, J.; Renchin, T.

2014-12-01

Long-term global data sets of Leaf Area Index (LAI) are important for monitoring global vegetation dynamics. LAI indicating phenological development of vegetation is an important state variable for modeling land surface processes. The comparison of long-term data sets is based on two recently available data sets both derived from AVHRR time series. The LAI 3g data set introduced by Zaichun Zhu et al. (2013) is developed from the new improved third generation Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) and best-quality MODIS LAI data. The second long-term data set is based on the 8 km spatial resolution GIMMS-AVHRR data (GGRS-data set by Propastin et al. 2012). The GGRS-LAI product uses a three-dimensional physical radiative transfer model which establishes relationship between LAI, vegetation fractional cover and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation. The model incorporates a number of site/region specific parameters, including the vegetation architecture variables such as leaf angle distribution, clumping index, and light extinction coefficient. For the application of the model to Kazakhstan, the vegetation architecture variables were computed at the local (pixel) level based on extensive field surveys of the biophysical properties of vegetation in representative grassland areas of Kazakhstan. The comparison of both long-term data sets will be used to interpret their quality for scientific research in other disciplines. References:Propastin, P., Kappas, M. (2012). Retrieval of coarse-resolution leaf area index over the Republic of Kazakhstan using NOAA AVHRR satellite data and ground measurements," Remote Sensing, vol. 4, no. 1, pp. 220-246. Zaichun Zhu, Jian Bi, Yaozhong Pan, Sangram Ganguly, Alessandro Anav, Liang Xu, Arindam Samanta, Shilong Piao, Ramakrishna R. Nemani and Ranga B. Myneni (2013). Global Data Sets of Vegetation Leaf Area

Estimates of phytomass and net primary productivity in terrestrial ecosystems of the former Soviet Union identified by classified Global Vegetation Index

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaston, G.G.; Kolchugina, T.P.

1995-12-01

Forty-two regions with similar vegetation and landcover were identified in the former Soviet Union (FSU) by classifying Global Vegetation Index (GVI) images. Image classes were described in terms of vegetation and landcover. Image classes appear to provide more accurate and precise descriptions for most ecosystems when compared to general thematic maps. The area of forest lands were estimated at 1,330 Mha and the actual area of forest ecosystems at 875 Mha. Arable lands were estimated to be 211 Mha. The area of the tundra biome was estimated at 261 Mha. The areas of the forest-tundra/dwarf forest, taiga, mixed-deciduous forest andmore » forest-steppe biomes were estimated t 153, 882, 196, and 144 Mha, respectively. The areas of desert-semidesert biome and arable land with irrigated land and meadows, were estimated at 126 and 237 Mha, respectively. Vegetation and landcover types were associated with the Bazilevich database of phytomass and NPP for vegetation in the FSU. The phytomass in the FSU was estimated at 97.1 Gt C, with 86.8 in forest vegetation, 9.7 in natural non-forest and 0.6 Gt C in arable lands. The NPP was estimated at 8.6 Gt C/yr, with 3.2, 4.8, and 0.6 Gt C/yr of forest, natural non-forest, and arable ecosystems, respectively. The phytomass estimates for forests were greater than previous assessments which considered the age-class distribution of forest stands in the FSU. The NPP of natural ecosystems estimated in this study was 23% greater than previous estimates which used thematic maps to identify ecosystems. 47 refs., 4 figs., 2 tabs.« less

An Assessment of Normalized Difference Skin Index Robustness in Aquatic Environments

DTIC Science & Technology

2014-03-27

Index NDSI Normalized Difference Skin Index NDVI Normalized Difference Vegetation Index NIR Near-Infrared SAR Search and Rescue SERG Sensors... Vegetation and water-bearing objects with high scatter tend to have NDSI values similar to human skin , potentially causing false positives in certain...AN ASSESSMENT OF NORMALIZED DIFFERENCE SKIN INDEX ROBUSTNESS IN AQUATIC ENVIRONMENTS THESIS Alice W. Chan, First Lieutenant, USAF AFIT-ENG-14-M-17

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fanwei; Collatz, George James; Pinzon, Jorge E.; Ivanoff, Alvaro

2013-01-01

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

Advanced Very High Resolution Radiometer (AVHRR) data evaluation for use in monitoring vegetation. Volume 1: Channels 1 and 2

NASA Technical Reports Server (NTRS)

Horvath, N. C.; Gray, T. I.; Mccrary, D. G. (Principal Investigator)

1982-01-01

Data from the National Oceanic and Atmospheric Administration satellite system (NOAA-6 satellite) were analyzed to study their nonmeteorological uses. A file of charts, graphs, and tables was created form the products generated. It was found that the most useful data lie between pixel numbers 400 and 2000 on a given scan line. The analysis of the generated products indicates that the Gray-McCrary Index can discern vegetation and associated daily and seasonal changes. The solar zenith-angle correction used in previous studies was found to be a useful adjustment to the index. The METSAT system seems best suited for providing large-area analyses of surface features on a daily basis.

A Wetness Index Using Terrain-Corrected Surface Temperature and Normalized Difference Vegetation Index Derived from Standard MODIS Products: An Evaluation of Its Use in a Humid Forest-Dominated Region of Eastern Canada

PubMed Central

Hassan, Quazi K.; Bourque, Charles P.-A.; Meng, Fan-Rui; Cox, Roger M.

2007-01-01

In this paper we develop a method to estimate land-surface water content in a mostly forest-dominated (humid) and topographically-varied region of eastern Canada. The approach is centered on a temperature-vegetation wetness index (TVWI) that uses standard 8-day MODIS-based image composites of land surface temperature (TS) and surface reflectance as primary input. In an attempt to improve estimates of TVWI in high elevation areas, terrain-induced variations in TS are removed by applying grid, digital elevation model-based calculations of vertical atmospheric pressure to calculations of surface potential temperature (θS). Here, θS corrects TS to the temperature value to what it would be at mean sea level (i.e., ∼101.3 kPa) in a neutral atmosphere. The vegetation component of the TVWI uses 8-day composites of surface reflectance in the calculation of normalized difference vegetation index (NDVI) values. TVWI and corresponding wet and dry edges are based on an interpretation of scatterplots generated by plotting θS as a function of NDVI. A comparison of spatially-averaged field measurements of volumetric soil water content (VSWC) and TVWI for the 2003-2005 period revealed that variation with time to both was similar in magnitudes. Growing season, point mean measurements of VSWC and TVWI were 31.0% and 28.8% for 2003, 28.6% and 29.4% for 2004, and 40.0% and 38.4% for 2005, respectively. An evaluation of the long-term spatial distribution of land-surface wetness generated with the new θS-NDVI function and a process-based model of soil water content showed a strong relationship (i.e., r2 = 95.7%). PMID:28903212

Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS.

PubMed

Bajgain, Rajen; Xiao, Xiangming; Basara, Jeffrey; Wagle, Pradeep; Zhou, Yuting; Zhang, Yao; Mahan, Hayden

2017-02-01

Agricultural drought, a common phenomenon in most parts of the world, is one of the most challenging natural hazards to monitor effectively. Land surface water index (LSWI), calculated as a normalized ratio between near infrared (NIR) and short-wave infrared (SWIR), is sensitive to vegetation and soil water content. This study examined the potential of a LSWI-based, drought-monitoring algorithm to assess summer drought over 113 Oklahoma Mesonet stations comprising various land cover and soil types in Oklahoma. Drought duration in a year was determined by the number of days with LSWI <0 (DNLSWI) during summer months (June-August). Summer rainfall anomalies and LSWI anomalies followed a similar seasonal dynamics and showed strong correlations (r 2  = 0.62-0.73) during drought years (2001, 2006, 2011, and 2012). The DNLSWI tracked the east-west gradient of summer rainfall in Oklahoma. Drought intensity increased with increasing duration of DNLSWI, and the intensity increased rapidly when DNLSWI was more than 48 days. The comparison between LSWI and the US Drought Monitor (USDM) showed a strong linear negative relationship; i.e., higher drought intensity tends to have lower LSWI values and vice versa. However, the agreement between LSWI-based algorithm and USDM indicators varied substantially from 32 % (D 2 class, moderate drought) to 77 % (0 and D 0 class, no drought) for different drought intensity classes and varied from ∼30 % (western Oklahoma) to >80 % (eastern Oklahoma) across regions. Our results illustrated that drought intensity thresholds can be established by counting DNLSWI (in days) and used as a simple complementary tool in several drought applications for semi-arid and semi-humid regions of Oklahoma. However, larger discrepancies between USDM and the LSWI-based algorithm in arid regions of western Oklahoma suggest the requirement of further adjustment in the algorithm for its application in arid regions.

Effects of Telecoupling on Global Vegetation Dynamics

NASA Astrophysics Data System (ADS)

Viña, A.; Liu, J.

2016-12-01

With the ever increasing trend in telecoupling processes, such as international trade, all countries around the world are becoming more interdependent. However, the effects of this growing interdependence on vegetation (e.g., shifts in the geographic extent and distribution) remain unknown even though vegetation dynamics are crucially important for food production, carbon sequestration, provision of other ecosystem services, and biodiversity conservation. In this study we evaluate the effects of international trade on the spatio-temporal trajectories of vegetation at national and global scales, using vegetation index imagery collected over more than three decades by the Advanced Very High Resolution Radiometer (AVHRR) satellite sensor series together with concurrent national and international data on international trade (and its associated movement of people, goods, services and information). The spatio-temporal trajectories of vegetation are obtained using the scale of fluctuation technique, which is based on the decomposition of the AVHRR image time series to obtain information on its spatial dependence structure over time. Similar to the correlation length, the scale of fluctuation corresponds to the range over which fluctuations in the vegetation index are spatially correlated. Results indicate that global vegetation has changed drastically over the last three decades. These changes are not uniform across space, with hotspots in active trading countries. This study not only has direct implications for understanding global vegetation dynamics, but also sheds important insights on the complexity of human-nature interactions across telecoupled systems.

Using normalized difference vegetation index to estimate carbon fluxes from small rotationally grazed pastures

USGS Publications Warehouse

Skinner, R.H.; Wylie, B.K.; Gilmanov, T.G.

2011-01-01

Satellite-based normalized difference vegetation index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. However, the usefulness of satellite-based images for monitoring rotationally-grazed pastures in the northeastern United States might be limited because paddock size is often smaller than the resolution limits of the satellite image. This research compared NDVI data from satellites with data obtained using a ground-based system capable of fine-scale (submeter) NDVI measurements. Gross primary productivity was measured by eddy covariance on two pastures in central Pennsylvania from 2003 to 2008. Weekly 250-m resolution satellite NDVI estimates were also obtained for each pasture from the moderate resolution imaging spectroradiometer (MODIS) sensor. Ground-based NDVI data were periodically collected in 2006, 2007, and 2008 from one of the two pastures. Multiple-regression and regression-tree estimates of GPP, based primarily on MODIS 7-d NDVI and on-site measurements of photosynthetically active radiation (PAR), were generally able to predict growing-season GPP to within an average of 3% of measured values. The exception was drought years when estimated and measured GPP differed from each other by 11 to 13%. Ground-based measurements improved the ability of vegetation indices to capture short-term grazing management effects on GPP. However, the eMODIS product appeared to be adequate for regional GPP estimates where total growing-season GPP across a wide area would be of greater interest than short-term management-induced changes in GPP at individual sites.

Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave Data

NASA Technical Reports Server (NTRS)

Bolten, John D.; Mladenova, Iliana E.; Crow, Wade; De Jeu, Richard

2016-01-01

A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.

42 CFR 412.316 - Geographic adjustment factors.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Geographic adjustment factors. 412.316 Section 412... Costs § 412.316 Geographic adjustment factors. (a) Local cost variation. CMS adjusts for local cost... part. The adjustment factor equals the hospital wage index value applicable to the hospital raised to...

Vegetation monitoring and classification using NOAA/AVHRR satellite data

NASA Technical Reports Server (NTRS)

Greegor, D. H., Jr.; Norwine, J. R.

1983-01-01

A vegetation gradient model, based on a new surface hydrologic index and NOAA/AVHRR meteorological satellite data, has been analyzed along a 1300 km east-west transect across the state of Texas. The model was developed to test the potential usefulness of such low-resolution data for vegetation stratification and monitoring. Normalized Difference values (ratio of AVHRR bands 1 and 2, considered to be an index of greenness) were determined and evaluated against climatological and vegetation characteristics at 50 sample locations (regular intervals of 0.25 deg longitude) along the transect on five days in 1980. Statistical treatment of the data indicate that a multivariate model incorporating satellite-measured spectral greenness values and a surface hydrologic factor offer promise as a new technique for regional-scale vegetation stratification and monitoring.

[Kriging analysis of vegetation index depression in peak cluster karst area].

PubMed

Yang, Qi-Yong; Jiang, Zhong-Cheng; Ma, Zu-Lu; Cao, Jian-Hua; Luo, Wei-Qun; Li, Wen-Jun; Duan, Xiao-Fang

2012-04-01

In order to master the spatial variability of the normal different vegetation index (NDVI) of the peak cluster karst area, taking into account the problem of the mountain shadow "missing" information of remote sensing images existing in the karst area, NDVI of the non-shaded area were extracted in Guohua Ecological Experimental Area, in Pingguo County, Guangxi applying image processing software, ENVI. The spatial variability of NDVI was analyzed applying geostatistical method, and the NDVI of the mountain shadow areas was predicted and validated. The results indicated that the NDVI of the study area showed strong spatial variability and spatial autocorrelation resulting from the impact of intrinsic factors, and the range was 300 m. The spatial distribution maps of the NDVI interpolated by Kriging interpolation method showed that the mean of NDVI was 0.196, apparently strip and block. The higher NDVI values distributed in the area where the slope was greater than 25 degrees of the peak cluster area, while the lower values distributed in the area such as foot of the peak cluster and depression, where slope was less than 25 degrees. Kriging method validation results show that interpolation has a very high prediction accuracy and could predict the NDVI of the shadow area, which provides a new idea and method for monitoring and evaluation of the karst rocky desertification.

Consumption of raw cruciferous vegetables is inversely associated with bladder cancer risk.

PubMed

Tang, Li; Zirpoli, Gary R; Guru, Khurshid; Moysich, Kirsten B; Zhang, Yuesheng; Ambrosone, Christine B; McCann, Susan E

2008-04-01

Cruciferous vegetables contain isothiocyanates, which show potent chemopreventive activity against bladder cancer in both in vitro and in vivo studies. However, previous epidemiologic studies investigating cruciferous vegetable intake and bladder cancer risk have been inconsistent. Cooking can substantially reduce or destroy isothiocyanates, and could account for study inconsistencies. In this hospital-based case-control study involving 275 individuals with incident, primary bladder cancer and 825 individuals without cancer, we examined the usual prediagnostic intake of raw and cooked cruciferous vegetables in relation to bladder cancer risk. Odds ratios (OR) and 95% confidence intervals (CI) were estimated with unconditional logistic regression, adjusting for smoking and other bladder cancer risk factors. We observed a strong and statistically significant inverse association between bladder cancer risk and raw cruciferous vegetable intake (adjusted OR for highest versus lowest category = 0.64; 95% CI, 0.42-0.97), with a significant trend (P = 0.003); there were no significant associations for fruit, total vegetables, or total cruciferous vegetables. The associations observed for total raw crucifers were also observed for individual raw crucifers. The inverse association remained significant among current and heavy smokers with three or more servings per month of raw cruciferous vegetables (adjusted ORs, 0.46 and 0.60; 95% CI, 0.23-0.93 and 0.38-0.93, respectively). These data suggest that cruciferous vegetables, when consumed raw, may reduce the risk of bladder cancer, an effect consistent with the role of dietary isothiocyanates as chemopreventive agents against bladder cancer.

Monitoring vegetation phenology using MODIS

USGS Publications Warehouse

Zhang, Xiayong; Friedl, Mark A.; Schaaf, Crystal B.; Strahler, Alan H.; Hodges, John C.F.; Gao, Feng; Reed, Bradley C.; Huete, Alfredo

2003-01-01

Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate–biosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success.

[Estimation and Visualization of Nitrogen Content in Citrus Canopy Based on Two Band Vegetation Index (TBVI)].

PubMed

Wang, Qiao-nan; Ye, Xu-jun; Li, Jin-meng; Xiao, Yu-zhao; He, Yong

2015-03-01

Nitrogen is a necessary and important element for the growth and development of fruit orchards. Timely, accurate and nondestructive monitoring of nitrogen status in fruit orchards would help maintain the fruit quality and efficient production of the orchard, and mitigate the pollution of water resources caused by excessive nitrogen fertilization. This study investigated the capability of hyperspectral imagery for estimating and visualizing the nitrogen content in citrus canopy. Hyperspectral images were obtained for leaf samples in laboratory as well as for the whole canopy in the field with ImSpector V10E (Spectral Imaging Ltd., Oulu, Finland). The spectral datas for each leaf sample were represented by the average spectral data extracted from the selected region of interest (ROI) in the hyperspectral images with the aid of ENVI software. The nitrogen content in each leaf sample was measured by the Dumas combustion method with the rapid N cube (Elementar Analytical, Germany). Simple correlation analysis and the two band vegetation index (TBVI) were then used to develop the spectra data-based nitrogen content prediction models. Results obtained through the formula calculation indicated that the model with the two band vegetation index (TBVI) based on the wavelengths 811 and 856 nm achieved the optimal estimation of nitrogen content in citrus leaves (R2 = 0.607 1). Furthermore, the canopy image for the identified TBVI was calculated, and the nitrogen content of the canopy was visualized by incorporating the model into the TBVI image. The tender leaves, middle-aged leaves and elder leaves showed distinct nitrogen status from highto low-levels in the canopy image. The results suggested the potential of hyperspectral imagery for the nondestructive detection and diagnosis of nitrogen status in citrus canopy in real time. Different from previous studies focused on nitrogen content prediction at leaf level, this study succeeded in predicting and visualizing the nutrient

Vegetable and fruit intakes and risk of Barrett's esophagus in men and women123

PubMed Central

Thompson, Olivia M; Beresford, Shirley AA; Kirk, Elizabeth A; Vaughan, Thomas L

2009-01-01

Background: Barrett's esophagus (BE) is a risk factor for esophageal adenocarcinoma. Modifiable risk factors for BE are largely unknown. Objective: The purpose of this study was to determine whether vegetable and fruit intakes are associated with BE risk. Design: In a case-control study based in western Washington State, we compared the vegetable and fruit intakes of 170 patients with newly diagnosed BE with those of 182 controls from the general population. Relations between vegetable and fruit intakes and BE were examined by using unconditional logistic regression to compute odds ratios (ORs) and corresponding 95% CIs. Results: Participants in the second (adjusted OR: 0.40; 95% CI: 0.23, 0.71) and third (adjusted OR: 0.33; 95% CI: 0.17, 0.63) tertiles of vegetable intake appeared to have a lower risk of BE (P for trend = 0.048) than did participants in the first tertile of vegetable intake. Similarly, participants in the second (adjusted OR: 0.49; 95% CI: 0.28, 0.86) and third (adjusted OR: 0.39; 95% CI: 0.21, 0.75) tertiles of combined vegetable and fruit intakes had a lower risk of BE (P for trend = 0.047) than did participants in the first tertile of vegetable and fruit intakes. Similar results were obtained in subanalyses limited to patients with visible and with long-segment BE. Conclusions: The results support previous findings that increased intakes of vegetables and of vegetables and fruit are associated with a lower risk of BE in men and women. Prospective data that examine relations between diet and BE are needed. PMID:19144726

Post-fire vegetation recovery in Portugal based on spot/vegetation data

NASA Astrophysics Data System (ADS)

Gouveia, C.; Dacamara, C. C.; Trigo, R. M.

2010-04-01

A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI), with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation indices.

Sensitivity of the normalized difference vegetation index to subpixel canopy cover, soil albedo, and pixel scale

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.

1990-01-01

An analytical framework is provided for examining the physically based behavior of the normalized difference vegetation index (NDVI) in terms of the variability in bulk subpixel landscape components and with respect to variations in pixel scales, within the context of the stochastic-geometric canopy reflectance model. Analysis focuses on regional scale variability in horizontal plant density and soil background reflectance distribution. Modeling is generalized to different plant geometries and solar angles through the use of the nondimensional solar-geometric similarity parameter. Results demonstrate that, for Poisson-distributed plants and for one deterministic distribution, NDVI increases with increasing subpixel fractional canopy amount, decreasing soil background reflectance, and increasing shadows, at least within the limitations of the geometric reflectance model. The NDVI of a pecan orchard and a juniper landscape is presented and discussed.

[Progress in inversion of vegetation nitrogen concentration by hyperspectral remote sensing].

PubMed

Wang, Li-Wen; Wei, Ya-Xing

2013-10-01

Nitrogen is the necessary element in life activity of vegetation, which takes important function in biosynthesis of protein, nucleic acid, chlorophyll, and enzyme etc, and plays a key role in vegetation photosynthesis. The technology about inversion of vegetation nitrogen concentration by hyperspectral remote sensing has been the research hotspot since the 70s of last century. With the development of hyperspectral remote sensing technology in recent years, the advantage of spectral bands subdivision in a certain spectral region provides the powerful technology measure for correlative spectral characteristic research on vegetation nitrogen. In the present paper, combined with the newest research production about monitoring vegetation nitrogen concentration by hyperspectral remote sensing published in main geography science literature in recent several years, the principle and correlated problem about monitoring vegetation nitrogen concentration by hyperspectral remote sensing were introduced. From four aspects including vegetation nitrogen spectral index, vegetation nitrogen content inversion based on chlorophyll index, regression model, and eliminating influence factors to inversion of vegetation nitrogen concentration, main technology methods about inversion of vegetation nitrogen concentration by hyperspectral remote sensing were detailedly introduced. Correlative research conclusions were summarized and analyzed, and research development trend was discussed.

Reliability and validity of the Turkish version of the situational self-efficacy scale for fruit and vegetable consumption in adolescents.

PubMed

Kadioglu, Hasibe; Erol, Saime; Ergun, Ayse

2015-01-01

The purpose of this research was to examine the psychometric properties of the Turkish version of the situational self-efficacy scale for vegetable and fruit consumption in adolescents. This was a methodological study. The study was conducted in four public secondary schools in Istanbul, Turkey. Subjects were 1586 adolescents. Content and construct validity were assessed to test the validity of the scale. The reliability was assessed in terms of internal consistency and test-retest reliability. For confirmatory factor analysis, χ(2) statistics plus other fit indices were used, including the goodness-of-fit index, the adjusted goodness-of-fit index, the nonnormed fit index, the comparative fit index, the standardized root mean residual, and the root mean square error of approximation. Pearson's correlation was used for test-retest reliability and item total correlation. The internal consistency was assessed by using Cronbach α. Confirmatory factor analysis strongly supported the three-component structure representing positive social situations (α = .81), negative effect situations (α = .93), and difficult situations (α = .78). Psychometric analyses of the Turkish version of the situational self-efficacy scale indicate high reliability and good content and construct validity. Researchers and health professionals will find it useful to employ the Turkish situational self-efficacy scale in evaluating situational self-efficacy for fruit and vegetable consumption in Turkish adolescents.

Lifting the Green Veil: A Fresh Look at Synoptic Vegetation Dynamics

NASA Astrophysics Data System (ADS)

Henebry, G. M.; Vina, A.; Gitelson, A. A.

2003-12-01

Observing the dynamics of the vegetated land surface synoptically from spaceborne sensors plays a key role in understanding the global water, carbon, and nitrogen cycles, land cover and land use change, and biodiversity mapping. For the past three decades the study of global and regional vegetation dynamics has relied on satellite observations of the distinctive spectral contrast between red and near infrared reflectance exhibited by photosynthetically active green vegetation. It has long been recognized, however, that the spectral vegetation index with the widest currency-the Normalized Difference Vegetation Index (NDVI)-suffers a rapid decrease of sensitivity even at moderate Leaf Area Index (LAI) values of 2 to 4, as are commonly encountered in croplands and woodlands. This decrease in NDVI sensitivity casts a green veil over the land surface that obscures vegetation dynamics across vast areas during much of the growing season. This veil has important consequences for monitoring vegetation dynamics, developing land surface climatologies, and detecting significant changes. A straightforward modification of the NDVI, developed to increase its sensitivity under higher green biomass conditions, was applied to a standard, widely available AVHRR NDVI dataset for the conterminous US. The new Wide Dynamic Range Vegetation Index (WDRVI) exhibited increases in sensitivity between 30%-50% for Omernik Level III ecoregions dominated by woodlands, croplands, and grasslands. Ecoregions with lower aboveground net primary production, such as aridlands and semi-arid grasslands, showed no increase in sensitivity of the WDRVI over the NDVI. This powerful, new but simple approach creates an opportunity for a fresh look at the satellite data record. Further, it offers the possibility for significant improvements in the retrievals of canopy variables for carbon and nitrogen models, more accurate land surface characterizations for numerical weather prediction models, more sensitive

Computing Robust, Bootstrap-Adjusted Fit Indices for Use with Nonnormal Data

ERIC Educational Resources Information Center

Walker, David A.; Smith, Thomas J.

2017-01-01

Nonnormality of data presents unique challenges for researchers who wish to carry out structural equation modeling. The subsequent SPSS syntax program computes bootstrap-adjusted fit indices (comparative fit index, Tucker-Lewis index, incremental fit index, and root mean square error of approximation) that adjust for nonnormality, along with the…

Potential for early warning of maalria in India using NOAA-AVHRR based vegetation health indices

NASA Astrophysics Data System (ADS)

Dhiman, R. C.; Kogan, Felix; Singh, Neeru; Singh, R. P.; Dash, A. P.

Malaria is still a major public health problem in India with about 1 82 million cases annually and 1000 deaths As per World Health Organization WHO estimates about 1 3 million Disability Adjusted Life Years DALYs are lost annually due to malaria in India Central peninsular region of India is prone to malaria outbreaks Meteorological parameters changes in ecological conditions development of resistance in mosquito vectors development of resistance in Plasmodium falciparum parasite and lack of surveillance are the likely reasons of outbreaks Based on satellite data and climatic factors efforts have been made to develop Early Warning System EWS in Africa but there is no headway in this regard in India In order to find out the potential of NOAA satellite AVHRR derived Vegetation Condition Index VCI Temperature Condition Index TCI and a cumulative indicator Vegetation Health Index VHI were attempted to find out their potential for development of EWS Studies were initiated by analysing epidemiological data of malaria vis-a-vis VCI TCI and VHI from Bikaner and Jaisalmer districts of Rajasthan and Tumkur and Raichur districts of Karnataka Correlation coefficients between VCI and monthly malaria cases for epidemic years were computed Positive correlation 0 67 has been found with one-month lag between VCI and malaria incidence in respect of Tumkur while a negative correlation with TCI -0 45 is observed In Bikaner VCI is found to be negatively related -0 71 with malaria cases in epidemic year of 1994 Weekly

Consumption of vegetables and their relation with ultra-processed foods in Brazil

PubMed Central

Canella, Daniela Silva; Louzada, Maria Laura da Costa; Claro, Rafael Moreira; Costa, Janaina Calu; Bandoni, Daniel Henrique; Levy, Renata Bertazzi; Martins, Ana Paula Bortoletto

2018-01-01

ABSTRACT OBJECTIVE To characterize the household purchase and the individual consumption of vegetables in Brazil and to analyze their relation with the consumption of ultra-processed foods. METHODS We have used data on the purchase of food for household consumption and individual consumption from the 2008–2009 Brazilian Household Budget Survey. The Brazilian Household Budget Survey studied the purchase of food of 55,970 households and the food consumption of 34,003 individuals aged 10 years and over. The foods of interest in this study were vegetables (excluding roots and tubers) and ultra-processed foods. We have described the amount of vegetables (grams) purchased and consumed by all Brazilians and according to the quintiles of caloric intake of ultra-processed food. To this end, we have calculated the crude and predicted values obtained by regression models adjusted for sociodemographic variables. We have analyzed the most commonly purchased types of vegetables (% in the total amount) and, in relation to individual food consumption, the variety of vegetables consumed (absolute number), the participation (%) of the types of culinary preparations based on vegetables, and the time of consumption. RESULTS The adjusted mean household purchase of vegetables was 42.9 g/per capita/day. The adjusted mean individual consumption was 46.1 g. There was an inverse relation between household purchase and individual consumption of vegetables and ultra-processed foods. Ten types of vegetables account for more than 80% of the total amount usually purchased. The variety consumed was, on average, 1.08 type/per capita/day. Approximately 60% of the vegetables were eaten raw, and the amount consumed at lunch was twice that consumed at dinner; individuals with higher consumption of ultra-processed foods tended to consume even less vegetables at dinner. CONCLUSIONS The consumption of vegetables in Brazil is insufficient, and this is worse among individuals with higher consumption of

On the relationship between some production parameters and a vegetation index in viticulture

NASA Astrophysics Data System (ADS)

Santangelo, Tanino; Di Lorenzo, R.; La Loggia, G.; Maltese, A.

2013-10-01

The use and timing of many agronomical practices such as the scheduling of irrigation and harvesting are dependent on accurate vineyard sampling of qualitative and productive parameters. Crop forecasting also depends on the representativeness of vineyard samples during the whole phenological period. This manuscript summarizes the last two years of precision viticulture in Sicily (Italy); agronomic campaigns were carried out in 2012 and 2013 within the "Tenute Rapitalà" and "Donnafugata" farms. Normalized Difference Vegetation Index derived from satellite images (RapidEye) acquired at berry set, pre-veraison and ripening phenological stages (occurred at June, July and August respectively) have been related to production parameters (sugar and anthocyanins contents) at harvesting of a selected red autochthonous cultivar (Nero D'Avola). The research aims to assess how robust are prediction models based on simple linear regression analysis, in particular: 1) whether there is a suitable period for acquiring the remote sensing image to evaluate these parameters at harvesting, when their knowledge is required; 2) if these relationships are consistent between years or need to be re-calibrated; 3) the models transferability to other vineyard of the same cultivar.

Developing Remote Sensing Methodology to Characterize Savanna Vegetation Structure and Composition for Rangeland Monitoring and Conservation Applications

NASA Astrophysics Data System (ADS)

Tsalyuk, M.; Kelly, M.; Getz, W.

2012-12-01

identify additional six sub-classes based on the dominant species in each class: Colophospermum mopane woodland, Colophospermum mopane shrubland, Cataphractes alexandri woodland, Acacia nebrownii shrubland, mixed Combretum species woodland and Terminalia prunioides woodland. Second, we used quantitative methods to relate satellite-based vegetation indices to the biometric properties measured on the ground. We found a correlation among measured height, diameter and canopy cover of woody vegetation and used this to improve the correlation between cover and Normalized Difference Vegetation Index (NDVI). We showed that the Soil Adjusted Total Vegetation Index (SATVI) and Normalized Difference Water Index (NDWI) were related to both greenness and density at a site. In order to measure grass biomass in the field, we calibrated Disc Pasture Mater by clipping, weighing and drying grass in 1m^2 plots, in the dry and wet seasons, with resulting R^2 of 0.87 and 0.83, respectively. MODIS-derived leaf area index (LAI) data was best correlated with dry grass biomass. We used these correlations to produce detailed maps of each vegetation parameter for the whole park. These maps will provide a baseline to employ historical imagery to better understand the effects of the park's management and changing grazing pressure on vegetation structure.

Vegetation Interaction Enhances Interdecadal Climate Variability in the Sahel

NASA Technical Reports Server (NTRS)

Zeng, Ning; Neelin, J. David; Lau, William K.-M.

1999-01-01

The role of naturally varying vegetation in influencing the climate variability in the Sahel is explored in a coupled atmosphere-land-vegetation model. The Sahel rainfall variability is influenced by sea surface temperature (SST) variations in the oceans. Land-surface feedback is found to increase this variability both on interannual and interdecadal time scales. Interactive vegetation enhances the interdecadal variation significantly, but can reduce year to year variability due to a phase lag introduced by the relatively slow vegetation adjustment time. Variations in vegetation accompany the changes in rainfall, in particular, the multi-decadal drying trend from the 1950s to the 80s.

Vegetative resistance to flow in South Florida; summary of vegetation sampling at sites NESRS3 and P33, Shark River slough, April 1996

USGS Publications Warehouse

Carter, Virginia; Ruhl, H.; Rybicki, N.B.; Reel, J.T.; Gammon, P.T.

1999-01-01

The U.S. Geological Survey is one of many agencies participating in the effort to restore the south Florida Everglades. We are sampling and characterizing the vegetation at selected sites in the Everglades as part of a study to quantify vegetative flow resistance. The objectives of the vegetative sampling are (1) to provide detailed information on species composition, vegetative characteristics, vegetative structure, and biomass for quantification of vegetative resistance to flow, and (2) to use this information to classify the vegetation and to improve existing vegetation maps for use with numerical models of surface-water flow. Vegetative sampling was conducted in the Shark River Slough in April, 1996. The data collected and presented here include live, dead, and periphyton biomass, vegetation characteristics and structure, and leaf area index.

Future vegetation ecosystem response to warming climate over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Bao, Y.; Gao, Y.; Wang, Y.

2017-12-01

The amplified vegetation response to climate variability has been found over the Tibetan Plateau (TP) in recent decades. In this study, the potential impacts of 21st century climate change on the vegetation ecosystem over the TP are assessed based on the dynamic vegetation outputs of models from Coupled Model Intercomparison Project Phase 5 (CMIP5), and the sensitivity of the TP vegetation in response to warming climate was investigated. Models project a continuous and accelerating greening in future, especially in the eastern TP, which closely associates with the plant type upgrade due to the pronouncing warming in growing season.Vegetation leaf area index (LAI) increase well follows the global warming, suggesting the warming climate instead of co2 fertilization controlls the future TP plant growth. The warming spring may advance the start of green-up day and extend the growing season length. More carbon accumulation in vegetation and soil will intensify the TP carbon cycle and will keep it as a carbon sink in future. Keywords: Leaf Area Index (LAI), Climate Change, Global Dynamic Vegetation Models (DGVMs), CMIP5, Tibetan Plateau (TP)

The stochastic Beer-Lambert-Bouguer law for discontinuous vegetation canopies

NASA Astrophysics Data System (ADS)

Shabanov, N.; Gastellu-Etchegorry, J.-P.

2018-07-01

The 3D distribution of canopy foliage affects the radiation regime and retrievals of canopy biophysical parameters. The gap fraction is one primary indicator of a canopy structure. Historically the Beer-Lambert-Bouguer law and the linear mixture model have served as a basis for multiple technologies for retrievals of the gap (or vegetation) fraction and Leaf Area Index (LAI). The Beer-Lambert-Bouguer law is a form of the Radiative Transfer (RT) equation for homogeneous canopies, which was later adjusted for a correlation between fitoelements using concept of the clumping index. The Stochastic Radiative Transfer (SRT) approach has been developed specifically for heterogeneous canopies, however the approach lacks a proper model of the vegetation fraction. This study is focused on the implementation of the stochastic version of the Beer-Lambert-Bouguer law for heterogeneous canopies, featuring the following principles: 1) two mechanisms perform photon transport- transmission through the turbid medium of foliage crowns and direct streaming through canopy gaps, 2) the radiation field is influenced by a canopy structure (quantified by the statistical moments of a canopy structure) and a foliage density (quantified by the gap fraction as a function of LAI), 3) the notions of canopy transmittance and gap fraction are distinct. The derived stochastic Beer-Lambert-Bouguer law is consistent with the Geometrical Optical and Radiative Transfer (GORT) derivations. Analytical and numerical analysis of the stochastic Beer-Lambert-Bouguer law presented in this study provides the basis to reformulate widely used technologies for retrievals of the gap fraction and LAI from ground and satellite radiation measurements.

Analysis of relationships between land surface temperature and land use changes in the Yellow River Delta

NASA Astrophysics Data System (ADS)

Ning, Jicai; Gao, Zhiqiang; Meng, Ran; Xu, Fuxiang; Gao, Meng

2018-06-01

This study analyzed land use and land cover changes and their impact on land surface temperature using Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager and Thermal Infrared Sensor imagery of the Yellow River Delta. Six Landsat images comprising two time series were used to calculate the land surface temperature and correlated vegetation indices. The Yellow River Delta area has expanded substantially because of the deposited sediment carried from upstream reaches of the river. Between 1986 and 2015, approximately 35% of the land use area of the Yellow River Delta has been transformed into salterns and aquaculture ponds. Overall, land use conversion has occurred primarily from poorly utilized land into highly utilized land. To analyze the variation of land surface temperature, a mono-window algorithm was applied to retrieve the regional land surface temperature. The results showed bilinear correlation between land surface temperature and the vegetation indices (i.e., Normalized Difference Vegetation Index, Adjusted-Normalized Vegetation Index, Soil-Adjusted Vegetation Index, and Modified Soil-Adjusted Vegetation Index). Generally, values of the vegetation indices greater than the inflection point mean the land surface temperature and the vegetation indices are correlated negatively, and vice versa. Land surface temperature in coastal areas is affected considerably by local seawater temperature and weather conditions.

On the use of satellite VEGETATION time series for monitoring post fire vegetation recovery

NASA Astrophysics Data System (ADS)

de Santis, F.; Didonna, I.

2009-04-01

Fire is one of the most critical factors of disturbance in worldwide ecosystems. The effects of fires on soil, plants, landscape and ecosystems depend on many factors, among them fire frequency, fire severity and plant resistance. The characterization of vegetation post-fire behaviour is a fundamental issue to model and evaluate the fire resilience, which the ability of vegetation to recover after fire. Recent changes in fire regime, due to abandonment of local land use practice and climate change, can induce significant variations in vegetation fire resilience. In the Mediterranean-type communities, post fire vegetation trends have been analysed in a wide range of habitats, although pre- and post-fire investigation has been widely performed at stand level. But, factors controlling regeneration at the landscape scale are less well known. In this study, a time series of normalized difference vegetation index (NDVI) data derived from SPOT-VEGETATION was used to examine the recovery characteristics of fire affected vegetation in some test areas of the Mediterranean ecosystems of Southern Italy. The vegetation indices operate by contrasting intense chlorophyll pigment absorption in the red against the high reflectance of leaf mesophyll in the near infrared. SPOT-VEGETATION Normalized Difference Vegetation Index (NDVI) data from 1998 to 2005 were analyzed in order to evaluate the resilient effects in a some significant test sites of southern Italy. In particular, we considered: (i) one stable area site, one site affected by one fire during the investigated time window, (iii) one site affected by two consecutive fires during the investigated time window. In order to eliminate the phenological fluctuations, for each decadal composition of each pixel, we focused on the departure NDVId = [NDVI - ]/, where is the decadal mean and  is the decadal standard deviation. The decadal mean and the standard deviation were calculated for each decade, e.g. 1st

Climatic factors driving vegetation declines in the 2005 and 2010 Amazon droughts

PubMed Central

Zhao, Wenqian; Zhao, Xiang; Zhou, Tao; Wu, Donghai; Tang, Bijian; Wei, Hong

2017-01-01

Along with global climate change, the occurrence of extreme droughts in recent years has had a serious impact on the Amazon region. Current studies on the driving factors of the 2005 and 2010 Amazon droughts has focused on the influence of precipitation, whereas the impacts of temperature and radiation have received less attention. This study aims to explore the climate-driven factors of Amazonian vegetation decline during the extreme droughts using vegetation index, precipitation, temperature and radiation datasets. First, time-lag effects of Amazonian vegetation responses to precipitation, radiation and temperature were analyzed. Then, a multiple linear regression model was established to estimate the contributions of climatic factors to vegetation greenness, from which the dominant climate-driving factors were determined. Finally, the climate-driven factors of Amazonian vegetation greenness decline during the 2005 and 2010 extreme droughts were explored. The results showed that (i) in the Amazon vegetation greenness responded to precipitation, radiation and temperature, with apparent time lags for most averaging interval periods associated with vegetation index responses of 0–4, 0–9 and 0–6 months, respectively; (ii) on average, the three climatic factors without time lags explained 27.28±21.73% (mean±1 SD) of vegetation index variation in the Amazon basin, and this value increased by 12.22% and reached 39.50±27.85% when time lags were considered; (iii) vegetation greenness in this region in non-drought years was primarily affected by precipitation and shortwave radiation, and these two factors altogether accounted for 93.47% of the total explanation; and (iv) in the common epicenter of the two droughts, pixels with a significant variation in precipitation, radiation and temperature accounted for 36.68%, 40.07% and 10.40%, respectively, of all pixels showing a significant decrease in vegetation index in 2005, and 15.69%, 2.01% and 45.25% in 2010

Climatic factors driving vegetation declines in the 2005 and 2010 Amazon droughts.

PubMed

Zhao, Wenqian; Zhao, Xiang; Zhou, Tao; Wu, Donghai; Tang, Bijian; Wei, Hong

2017-01-01

Along with global climate change, the occurrence of extreme droughts in recent years has had a serious impact on the Amazon region. Current studies on the driving factors of the 2005 and 2010 Amazon droughts has focused on the influence of precipitation, whereas the impacts of temperature and radiation have received less attention. This study aims to explore the climate-driven factors of Amazonian vegetation decline during the extreme droughts using vegetation index, precipitation, temperature and radiation datasets. First, time-lag effects of Amazonian vegetation responses to precipitation, radiation and temperature were analyzed. Then, a multiple linear regression model was established to estimate the contributions of climatic factors to vegetation greenness, from which the dominant climate-driving factors were determined. Finally, the climate-driven factors of Amazonian vegetation greenness decline during the 2005 and 2010 extreme droughts were explored. The results showed that (i) in the Amazon vegetation greenness responded to precipitation, radiation and temperature, with apparent time lags for most averaging interval periods associated with vegetation index responses of 0-4, 0-9 and 0-6 months, respectively; (ii) on average, the three climatic factors without time lags explained 27.28±21.73% (mean±1 SD) of vegetation index variation in the Amazon basin, and this value increased by 12.22% and reached 39.50±27.85% when time lags were considered; (iii) vegetation greenness in this region in non-drought years was primarily affected by precipitation and shortwave radiation, and these two factors altogether accounted for 93.47% of the total explanation; and (iv) in the common epicenter of the two droughts, pixels with a significant variation in precipitation, radiation and temperature accounted for 36.68%, 40.07% and 10.40%, respectively, of all pixels showing a significant decrease in vegetation index in 2005, and 15.69%, 2.01% and 45.25% in 2010, respectively

Fruit and vegetable intake and smoking cessation.

PubMed

Poisson, T; Dallongeville, J; Evans, A; Ducimetierre, P; Amouyel, P; Yarnell, J; Bingham, A; Kee, F; Dauchet, L

2012-11-01

In cohort studies, fruit and vegetable (F&V) intake is associated with lower cardiovascular diseases (CVDs). Former smokers often have a higher F&V intake than current smokers. If a high intake of F&V precedes smoking cessation, the latter may explain the favorable association between F&V intake and CVD among smokers. The objective was to assess whether higher F&V intake precedes smoking cessation. The study population comprised 1056 male smokers from Lille (France) and Belfast (Northern Ireland) aged 50-59 years on inclusion in 1991. At baseline, participants completed self-administered questionnaires related to smoking habits, demographic, socioeconomic factors and diet. At the 10-year follow-up, smoking habits were assessed by mailed questionnaire. After 10 years, 590 out of 1056 smokers had quit smoking (70.7% of smoker in Lille and 37.8% in Belfast). After adjusting for center, consumption of F&V was associated with quitting (odds ratio (OR) for high versus low F&V intake: 1.73; 95% confidence interval (CI): (1.22-2.45); P-trend=0.002). After further adjustment for sociodemographic factors, body mass index and medical diet, the association was still statistically significant (OR: 1.59; 95% CI (1.12-2.27); P-trend = 0.01). In a model fully adjusted for age, smoking intensity, alcohol consumption and physical activity, the association was no longer significant (P = 0.14). Higher F&V intake precedes smoking cessation. Hence, smoking cessation could affect the causal interpretation of the association between F&V and CVD in smokers.

Spatiotemporal changes of normalized difference vegetation index (NDVI) and response to climate extremes and ecological restoration in the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Zhao, Anzhou; Zhang, Anbing; Liu, Xianfeng; Cao, Sen

2018-04-01

Extreme drought, precipitation, and other extreme climatic events often have impacts on vegetation. Based on meteorological data from 52 stations in the Loess Plateau (LP) and a satellite-derived normalized difference vegetation index (NDVI) from the third-generation Global Inventory Modeling and Mapping Studies (GIMMS3g) dataset, this study investigated the relationship between vegetation change and climatic extremes from 1982 to 2013. Our results showed that the vegetation coverage increased significantly, with a linear rate of 0.025/10a ( P < 0.001) from 1982 to 2013. As for the spatial distribution, NDVI revealed an increasing trend from the northwest to the southeast, with about 61.79% of the LP exhibiting a significant increasing trend ( P < 0.05). Some temperature extreme indices, including TMAXmean, TMINmean, TN90p, TNx, TX90p, and TXx, increased significantly at rates of 0.77 mm/10a, 0.52 °C/10a, 0.62 °C/10a, 0.80 °C/10a, 5.16 days/10a, and 0.65 °C/10a, respectively. On the other hand, other extreme temperature indices including TX10p and TN10p decreased significantly at rates of -2.77 days/10a and 4.57 days/10a ( P < 0.01), respectively. Correlation analysis showed that only TMINmean had a significant relationship with NDVI at the yearly time scale ( P < 0.05). At the monthly time scale, vegetation coverage and different vegetation types responded significantly positively to precipitation and temperature extremes (TMAXmean, TMINmean, TNx, TNn, TXn, and TXx) ( P < 0.01). All of the precipitation extremes and temperature extremes exhibited significant positive relationships with NDVI during the spring and autumn ( P < 0.01). However, the relationship between NDVI and RX1day, TMAXmean, TXn, and TXx was insignificant in summer. Vegetation exhibited a significant negative relationship with precipitation extremes in winter ( P < 0.05). In terms of human activity, our results indicate a strong correlation between the cumulative afforestation area and NDVI in

Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia

NASA Astrophysics Data System (ADS)

Poveda, GermáN.; Jaramillo, Alvaro; Gil, Marta MaríA.; Quiceno, Natalia; Mantilla, Ricardo I.

2001-08-01

An analysis of hydrologic variability in Colombia shows different seasonal effects associated with El Niño/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong El Niño and La Niña events. Soil moisture exhibited greater negative anomalies during 1997-1998 El Niño, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Niña 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during El Niños, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and El Niño has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin.

Normalized difference vegetation index as an estimator for abundance and quality of avian herbivore forage in arctic Alaska

USGS Publications Warehouse

Hogrefe, Kyle R.; Patil, Vijay; Ruthrauff, Daniel R.; Meixell, Brandt W.; Budde, Michael E.; Hupp, Jerry W.; Ward, David H.

2017-01-01

Tools that can monitor biomass and nutritional quality of forage plants are needed to understand how arctic herbivores may respond to the rapidly changing environment at high latitudes. The Normalized Difference Vegetation Index (NDVI) has been widely used to assess changes in abundance and distribution of terrestrial vegetative communities. However, the efficacy of NDVI to measure seasonal changes in biomass and nutritional quality of forage plants in the Arctic remains largely un-evaluated at landscape and fine-scale levels. We modeled the relationships between NDVI and seasonal changes in aboveground biomass and nitrogen concentration in halophytic graminoids, a key food source for arctic-nesting geese. The model was calibrated based on data collected at one site and validated using data from another site. Effects of spatial scale on model accuracy were determined by comparing model predictions between NDVI derived from moderate resolution (250 × 250 m pixels) satellite data and high resolution (20 cm diameter area) handheld spectrometer data. NDVI derived from the handheld spectrometer was a superior estimator (R2 ≥ 0.67) of seasonal changes in aboveground biomass compared to satellite-derived NDVI (R2 ≤ 0.40). The addition of temperature and precipitation variables to the model for biomass improved fit, but provided minor gains in predictive power beyond that of the NDVI-only model. This model, however, was only a moderately accurate estimator of biomass in an ecologically-similar halophytic graminoid wetland located 100 km away, indicating the necessity for site-specific validation. In contrast to assessments of biomass, satellite-derived NDVI was a better estimator for the timing of peak percent of nitrogen than NDVI derived from the handheld spectrometer. We confirmed that the date when NDVI reached 50% of its seasonal maximum was a reasonable approximation of the period of peak spring vegetative green-up and peak percent nitrogen. This study

Foliar anthocyanin content - Sensitivity of vegetation indices using green reflectance

NASA Astrophysics Data System (ADS)

Vina, A.; Gitelson, A. A.

2009-12-01

The amount and composition of photosynthetic and non-photosynthetic foliar pigments varies primarily as a function of species, developmental and phenological stages, and environmental stresses. Information on the absolute and relative amounts of these pigments thus provides insights onto the physiological conditions of plants and their responses to stress, and has the potential to be used for evaluating plant species composition and diversity across broad geographic regions. Anthocyanins in particular, are non-photosynthetic pigments associated with the resistance of plants to environmental stresses (e.g., drought, low soil nutrients, high radiation, herbivores, and pathogens). As they absorb radiation primarily in the green region of the electromagnetic spectrum (around 540-560 nm), broad-band vegetation indices that use this region in their formulation will respond to their presence. We evaluated the sensitivity of three vegetation indices using reflectance in the green spectral region (the green Normalized Difference Vegetation Index, gNDVI, the green Chlorophyll Index, CIg, and the Visible Atmospherically Resistant Vegetation Index, VARI) to foliar anthocyanins in five different species. For comparison purposes the widely used Normalized Difference Vegetation Index, NDVI was also evaluated. Among the four indices tested, the VARI, which uses only spectral bands in the visible region of the electromagnetic spectrum, was found to be inversely and linearly related to the relative amount of foliar anthocyanins. While this result was obtained at leaf level, it opens new possibilities for analyzing anthocyanin content across multiple scales, by means of currently operational aircraft- and spacecraft-mounted broad-band sensor systems. Further studies that evaluate the sensitivity of the VARI to the relative content of anthocyanins across space (e.g., at canopy and regional scales) and time, and its relationship with plant biodiversity and vegetation stresses, are

[Remote sensing detection of vegetation health status after ecological restoration in soil and water loss region].

PubMed

Hu, Xiu Juan; Xu, Han Qiu; Guo, Yan Bin; Zhang, Bo Bo

2017-01-01

This paper proposed a vegetation health index (VHI) to rapidly monitor and assess vegetation health status in soil and water loss region based on remote sensing techniques and WorldView-2 imagery. VHI was constructed by three factors, i.e., the normalized mountain vegetation index, the nitrogen reflectance index and the reflectance of the yellow band, through the principal component transformation, in order to avoid the deviation induced by subjective method of weighted summation. The Hetian Basin of Changting County in Fujian Province, China, was taken as a test area to assess the vegetation health status in soil and water loss region using VHI. The results showed that the VHI could detect vegetation health status with a total accuracy of 91%. The vegetation of Hetian Basin in good, moderate and poor health status accounted for 10.1%, 49.2% and 40.7%, respectively. The vegetation of the study area was still under an unhealthy status because the soil was poor and the growth of newly planted vegetation was not good in the soil and water loss region.

Highly Transparent w/o Pickering Emulsions without Adjusting the Refractive Index of the Stabilizing Particles.

PubMed

Sihler, Susanne; Lindén, Mika; Ziener, Ulrich

2017-10-03

Pickering emulsions with a remarkable transmittance of up to 86% across the visible spectrum have been prepared without adjusting the refractive index (RI) of the stabilizing particles to those of the aqueous and oil phases. Commercially available hydrophilic silica particles with a diameter of 20 nm, which are hydrophobized partially in situ, were used to stabilize water droplets with diameters below 400 nm in IsoparM. In this system, the stabilizing particles and the emulsion droplets act as one single scattering object, which renders RI-matching of the particles unnecessary. By either evaporation of some water from the droplets or addition of an appropriate organic liquid to the oil phase, it is possible to match the RI of the droplets (aqueous phase + particles) with that of the continuous phase, which minimizes scattering and results in highly transparent emulsions.

Dietary antioxidants, fruits and vegetables, and the risk of Barrett’s esophagus

PubMed Central

Kubo, Ai; Levin, T.R.; Block, Gladys; Rumore, Gregory J.; Quesenberry, Charles P.; Buffler, Patricia; Corley, Douglas A.

2009-01-01

OBJECTIVE The present study evaluated the associations between antioxidants, fruit and vegetable intakes and the risk of Barrett’s esophagus, a potential precursor to esophageal adenocarcinoma. METHODS We conducted a case-control study within the Kaiser Permanente Northern California population. Incident Barrett’s esophagus cases (n=296) were matched to persons with gastroesophageal reflux disease (GERD) (GERD controls, n=308) and to population controls (n=309). Nutrient intake was measured using a validated 110-item food frequency questionnaire. The antioxidant results were stratified by dietary vs. total intake of antioxidants. RESULTS Comparing cases to population controls, dietary intake of vitamin C and beta-carotene were inversely associated with the risk of Barrett’s esophagus [4th vs. 1st quartile, adjusted odds ratio [OR]=0.48 95% confidence interval [CI] (0.26–0.90); OR=0.56 95%CI(0.32–0.99), respectively], and the inverse association was strongest for vitamin E [OR=0.25 95%CI (0.11–0.59)]. The inverse trends for antioxidant index (total and dietary) and fruit and vegetable intake were statistically significant, while most total intakes were not associated with reduced risk. The use of antioxidant supplements did not influence the risk of Barrett’s esophagus, and antioxidants and fruits and vegetables were inversely associated with a GERD diagnosis. CONCLUSION Dietary antioxidants, fruit and vegetable are inversely associated with the risk of Barrett’s esophagus, while no association was observed for supplement intake. Our results suggest that fruits and vegetables themselves or associated undetected confounders may influence early events in the carcinogenesis of esophageal adenocarcinoma. PMID:18494834

78 FR 59093 - Quarterly Rail Cost Adjustment Factor

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-25

...)] Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board, DOT ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board has approved the fourth quarter 2013 rail cost adjustment factor (RCAF) and cost index filed by the Association of American Railroads. The fourth quarter 2013 RCAF...

Reduced risk of pre-eclampsia with organic vegetable consumption: results from the prospective Norwegian Mother and Child Cohort Study.

PubMed

Torjusen, Hanne; Brantsæter, Anne Lise; Haugen, Margaretha; Alexander, Jan; Bakketeig, Leiv S; Lieblein, Geir; Stigum, Hein; Næs, Tormod; Swartz, Jackie; Holmboe-Ottesen, Gerd; Roos, Gun; Meltzer, Helle Margrete

2014-09-10

Little is known about the potential health effects of eating organic food either in the general population or during pregnancy. The aim of this study was to examine associations between organic food consumption during pregnancy and the risk of pre-eclampsia among nulliparous Norwegian women. Prospective cohort study. Norway, years 2002-2008. 28 192 pregnant women (nulliparous, answered food frequency questionnaire and general health questionnaire in mid-pregnancy and no missing information on height, body weight or gestational weight gain). Relative risk was estimated as ORs by performing binary logistic regression with pre-eclampsia as the outcome and organic food consumption as the exposure. The prevalence of pre-eclampsia in the study sample was 5.3% (n=1491). Women who reported to have eaten organic vegetables 'often' or 'mostly' (n=2493, 8.8%) had lower risk of pre-eclampsia than those who reported 'never/rarely' or 'sometimes' (crude OR=0.76, 95% CI 0.61 to 0.96; adjusted OR=0.79, 95% CI 0.62 to 0.99). The lower risk associated with high organic vegetable consumption was evident also when adjusting for overall dietary quality, assessed as scores on a healthy food pattern derived by principal component analysis. No associations with pre-eclampsia were found for high intake of organic fruit, cereals, eggs or milk, or a combined index reflecting organic consumption. These results show that choosing organically grown vegetables during pregnancy was associated with reduced risk of pre-eclampsia. Possible explanations for an association between pre-eclampsia and use of organic vegetables could be that organic vegetables may change the exposure to pesticides, secondary plant metabolites and/or influence the composition of the gut microbiota. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Reduced risk of pre-eclampsia with organic vegetable consumption: results from the prospective Norwegian Mother and Child Cohort Study

PubMed Central

Torjusen, Hanne; Brantsæter, Anne Lise; Haugen, Margaretha; Alexander, Jan; Bakketeig, Leiv S; Lieblein, Geir; Stigum, Hein; Næs, Tormod; Swartz, Jackie; Holmboe-Ottesen, Gerd; Roos, Gun; Meltzer, Helle Margrete

2014-01-01

Objective Little is known about the potential health effects of eating organic food either in the general population or during pregnancy. The aim of this study was to examine associations between organic food consumption during pregnancy and the risk of pre-eclampsia among nulliparous Norwegian women. Design Prospective cohort study. Setting Norway, years 2002–2008. Participants 28 192 pregnant women (nulliparous, answered food frequency questionnaire and general health questionnaire in mid-pregnancy and no missing information on height, body weight or gestational weight gain). Main outcome measure Relative risk was estimated as ORs by performing binary logistic regression with pre-eclampsia as the outcome and organic food consumption as the exposure. Results The prevalence of pre-eclampsia in the study sample was 5.3% (n=1491). Women who reported to have eaten organic vegetables ‘often’ or ‘mostly’ (n=2493, 8.8%) had lower risk of pre-eclampsia than those who reported ‘never/rarely’ or ‘sometimes’ (crude OR=0.76, 95% CI 0.61 to 0.96; adjusted OR=0.79, 95% CI 0.62 to 0.99). The lower risk associated with high organic vegetable consumption was evident also when adjusting for overall dietary quality, assessed as scores on a healthy food pattern derived by principal component analysis. No associations with pre-eclampsia were found for high intake of organic fruit, cereals, eggs or milk, or a combined index reflecting organic consumption. Conclusions These results show that choosing organically grown vegetables during pregnancy was associated with reduced risk of pre-eclampsia. Possible explanations for an association between pre-eclampsia and use of organic vegetables could be that organic vegetables may change the exposure to pesticides, secondary plant metabolites and/or influence the composition of the gut microbiota. PMID:25208850

Vegetative resistance to flow in south Florida; summary of vegetation sampling at sites NESRS3 and P33, Shark River slough, November, 1996

USGS Publications Warehouse

Carter, Virginia; Reel, J.T.; Rybicki, N.B.; Ruhl, H.; Gammon, P.T.; Lee, J.K.

1999-01-01

The U.S. Geological Survey is one of many agencies participating in the effort to restore the South Florida Everglades. We are sampling and characterizing the vegetation at selected sites in the Everglades as part of a study to quantify vegetative flow resistance. The objectives of the vegetation sampling are (1) to provide detailed information on species composition, vegetation characteristics, vegetation structure, and biomass for quantification of vegetative resistance to flow, and (2) to use this information to classify the vegetation and to improve existing vegetation maps for use with numerical models of surface-water flow. Vegetation was sampled at two sites in the Shark River Slough in November, 1996. The data collected and presented here include those for live and dead standing sawgrass, other dead material, periphyton biomass, vegetation characteristics and structure, and leaf area index.

Reconstructed high-resolution scatterometer data: a comparison with AVHRR vegetation index images for regional-scale monitoring of tropical rain forests

NASA Astrophysics Data System (ADS)

Hardin, Perry J.; Long, David G.

1993-08-01

There is considerable interest in utilizing microwave and visible spectrum imagery for the assessment of tropical rain forests. Because rain forest spans large sub-continental areas, medium resolution (1 - 16 km) imagery will play an important role in providing a global perspective of any forest removal or change. Since 1978, AVHRR imagery from NOAA polar orbiters has provided coverage of tropical regions at this desirable resolution, but much of the imagery is plagued with heavy cloud cover typical of equatorial regions. In contrast, no historical source of active microwave imagery at native 1 - 16 km resolution exists for all the global rain forest regions. In this paper, the authors compare the utility of Seasat scatterometer (SASS) ku-band microwave data to early-date AVHRR vegetation index products for discrimination of tropical vegetation formations. When considered separately, both the AVHRR imagery and the SASS imagery could be used to distinguish between broad categories of equatorial land cover, but the AVHRR imagery was slightly superior. When combined, the two data sets provided discrimination capability superior than could be obtained by using either set alone.

Providing a Spatial Context for Crop Insurance in Ethiopia: Multiscale Comparisons of Vegetation Metrics in Tigray

NASA Astrophysics Data System (ADS)

Mann, B. F.; Small, C.

2014-12-01

Weather-based index insurance projects are rapidly expanding across the developing world. Many of these projects use satellite-based observations to detect extreme weather events, which inform and trigger payouts to smallholder farmers. While most index insurance programs use precipitation measurements to determine payouts, the use of remotely sensed observations of vegetation is currently being explored. In order to use vegetation indices as a basis for payouts, it is necessary to establish a consistent relationship between the vegetation index and the health and abundance of agriculture on the ground. The accuracy with which remotely sensed vegetation indices can detect changes in agriculture depends on both the spatial scale of the agriculture and the spatial resolution of the sensor. This study analyzes the relationship between meter and decameter scale vegetation fraction estimates derived from linear spectral mixture models with a more commonly used vegetation index (NDVI, EVI) at hectometer spatial scales. In addition, the analysis incorporates land cover/land use field observations collected in Tigray Ethiopia in July 2013. . It also tests the flexibility and utility of a standardized spectral mixture model in which land cover is represented as continuous fields of rock and soil substrate (S), vegetation (V) and dark surfaces (D; water, shadow). This analysis found strong linear relationships with vegetation metrics at 1.6-meter, 30-meter and 250-meter resolutions across spectrally diverse subsets of Tigray, Ethiopia and significantly correlated relationships using the Spearman's rho statistic. The observed linear scaling has positive implications for future use of moderate resolution vegetation indices in similar landscapes; especially index insurance projects that are scaling up across the developing world using remotely-sensed environmental information.

Earth Observation and Science: Monitoring Vegetation Dynamics from Deep Space Gateway

NASA Astrophysics Data System (ADS)

Knyazikhin, Y.; Park, T.; Hu, B.

2018-02-01

Retrieving diurnal courses of sunlit (SLAI) and shaded (ShLAI) leaf area indices, fraction of photosynthetically active radiation (PAR) absorbed by vegetation (FPAR), and Normalized Difference Vegetation Index (NDVI) from Deep Space Gateway data.

Retrieval of wheat growth parameters with radar vegetation indices

USDA-ARS?s Scientific Manuscript database

The Radar Vegetation Index (RVI) has a low sensitivity to changes in environmental conditions and has the potential as a tool to monitor the vegetation growth. In this study, we expand on previous research by investigating the radar response over a wheat canopy. RVI was computed using observations m...

Analysis of vegetation changes in Cidanau watershed, Indonesia

NASA Astrophysics Data System (ADS)

Khairiah, R. N.; Kunihiko, Y.; Prasetyo, L. B.; Setiawan, Y.

2018-05-01

Vegetation change detection is needed for conserve of quality and water cycle in Cidanau watershed. The NDVI was applied to quantify the vegetation changes of Cidanau watershed for three different years 1989, 2001, and 2015. Using NDVI we mapped the reflectance from chlorophyll and distinguished varying amounts of vegetation at the pixel level by index. In the present study, as a preliminary study, we proposed a vegetation change detection analysis based on the NDVI from 1989 through 2015. Multi-temporal satellite data i.e. Landsat imagery with 30 m spatial resolution are used in the present study. It is reported that agroforestry land exhibited the greatest reductions in highly dense vegetation class in 1989-2001 and also moderate vegetation class in 2001-2015. It’s mean that amount of vegetation present in agroforestry land is getting lower year by year.

An evaluation of hyperspectral vegetation indices for detecting soil salinity in sugarcane fields using EO-1 Hyperion Data

NASA Astrophysics Data System (ADS)

Hamzeh, S.; Naseri, A. A.; Alavi Panah, S. K.; Bartholomeus, H.; Mojaradi, B.; Clevers, J.; Behzad, M.

2012-04-01

Sugarcane is the major agricultural crops in the Khuzestan province, in the southwest of Iran. But soil salinity is a major problem affecting the sugarcane yield, and therefore, monitoring and assessment of soil salinity is necessary. This research was carried out to investigate the performance of several hyperspectral vegetation indices to assess salinity stress in sugarcane fields and to determine the suitable indicators and statistical models for detecting various soil salinity levels. For this purpose one Hyperion image was acquired on Sept 2, 2010 and soil salinity was measured in 108 points 5 to 15 days from this date. 60 Samples were used for modeling and 48 samples were used for validation. Values of the soil salinity were linked with the corresponding pixel at the satellite imagery and 16 (hyperspectral) spectral indices were calculated. Then, the potential of these indices for estimating the soil salinity were analyzed and results show that soil salinity can well be estimated by vegetation indices derived from Hyperion data. Indices that are based on the chlorophyll and water absorption bands have medium to high relationship with soil salinity, while indices that only use visible bands or combination of visible and NIR bands don't perform well. From the investigated indices the Optimized Soil-Adjusted Vegetation Index (OSAVI) has the strongest relationship (R2 = 0.69) with soil salinity, because this index minimizes the variations in reflectance characteristics of soil background.

Cost Indexing and Unit Price Adjustments for Construction Materials

DOT National Transportation Integrated Search

2012-10-30

This project was focused on the assimilation of information regarding unit price adjustment clauses, or PACs, : that are offered for construction materials at the state Departments of Transportation (DOTs). It is intended to : provide the South Carol...

Predicting Southern Appalachian overstory vegetation with digital terrain data

Treesearch

Paul V. Bolstad; Wayne Swank; James Vose

1998-01-01

Vegetation in mountainous regions responds to small-scale variation in terrain, largely due to effects on both temperature and soil moisture. However, there are few studies of quantitative, terrain-based methods for predicting vegetation composition. This study investigated relationships between forest composition, elevation, and a derived index of terrain shape, and...

Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

USGS Publications Warehouse

Gu, Yingxin; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, Jesslyn F.; Verdin, J.P.

2008-01-01

The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.

Monitoring global vegetation using Nimbus-7 37 GHz data - Some empirical relations

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Tucker, C. J.

1987-01-01

The difference of the vertically and horizontally polarized brightness temperatures observed by the 37 GHz channel of the SMMR on board the Nimbus-7 satellite are correlated temporally with three indicators of vegetation density, namely the temporal variation of the atmospheric CO2 concentration at Mauna Loa (Hawaii), rainfall over the Sahel and the normalized difference vegetation index derived from the AVHRR on board the NOAA-7 satellite. SMMR 37 GHz and AVHRR provide complementary data sets for monitoring global vegetation, the 37 GHz data being more suitable for arid and semiarid regions as these data are more sensitive to changes in sparse vegetation. The 37-GHz data might be useful for understanding desertification and indexing Co2 exchange between the biosphere and the atmosphere.

Estimation of Leaf Area Index and Plant Area Index of a Submerged Macrophyte Canopy Using Digital Photography

PubMed Central

Zhao, Dehua; Xie, Dong; Zhou, Hengjie; Jiang, Hao; An, Shuqing

2012-01-01

Non-destructive estimation using digital cameras is a common approach for estimating leaf area index (LAI) of terrestrial vegetation. However, no attempt has been made so far to develop non-destructive approaches to LAI estimation for aquatic vegetation. Using the submerged plant species Potamogeton malainus, the objective of this study was to determine whether the gap fraction derived from vertical photographs could be used to estimate LAI of aquatic vegetation. Our results suggested that upward-oriented photographs taken from beneath the water surface were more suitable for distinguishing vegetation from other objects than were downward-oriented photographs taken from above the water surface. Exposure settings had a substantial influence on the identification of vegetation in upward-oriented photographs. Automatic exposure performed nearly as well as the optimal trial exposure, making it a good choice for operational convenience. Similar to terrestrial vegetation, our results suggested that photographs taken for the purpose of distinguishing gap fraction in aquatic vegetation should be taken under diffuse light conditions. Significant logarithmic relationships were observed between the vertical gap fraction derived from upward-oriented photographs and plant area index (PAI) and LAI derived from destructive harvesting. The model we developed to depict the relationship between PAI and gap fraction was similar to the modified theoretical Poisson model, with coefficients of 1.82 and 1.90 for our model and the theoretical model, respectively. This suggests that vertical upward-oriented photographs taken from below the water surface are a feasible alternative to destructive harvesting for estimating PAI and LAI for the submerged aquatic plant Potamogeton malainus. PMID:23226557

Possible causes of Arctic Tundra Vegetation Productivity Declines

NASA Astrophysics Data System (ADS)

Bhatt, U. S.; Walker, D. A.; Raynolds, M. K.; Bieniek, P.; Epstein, H. E.; Comiso, J. C.; Pinzon, J. E.; Tucker, C. J.

2017-12-01

Three decades of remotely sensed Normalized Difference Vegetation Index (NDVI) data document an overall increase in Arctic tundra vegetation greenness but the trends display considerable spatial variability. Pan-Arctic tundra vegetation greening is associated with increases in summer warmth that are, in large-part, driven by summer sea-ice retreat along Arctic coasts. Trends covering the period 1982-2016 are overall positive for summer open water, Summer Warmth Index (SWI, the sum of the degree months above zero from May-August), MaxNDVI (peak NDVI) and time integrated NDVI (TI-NDVI, sum of biweekly NDVI above 0.05 from May-September). Upon closer examination, it is clear that not all regions have positive trends, for example, there is an area of cooling in western Eurasia, which is broadly co-located with maxNDVI and TI-NDVI declines. While sea ice decline has continued over the satellite record, summer landsurface temperatures and vegetation productivity measures have not simply increased. Regional differences between warming and greening trends suggest that it is likely that multiple processes influence vegetation productivity beyond secular greening with increased summer warmth. This paper will present Pan-Arctic and regional analyses of the NDVI data in the context of climate drivers. Other possible drivers of vegetation productivity decline will be discussed such as increased standing water, delayed spring snow-melt, and winter thaw events. The status and limitations of data sets and modeling needed to advance our understanding of tundra vegetation productivity will be summarized and will serve as a starting point for planning the next steps in this topic. Methodical multi-disciplinary synthesis research that jointly considers vegetation type, permafrost conditions, altitude, as well as climate factors such as temperature, heat and moisture transport, and timing of snowfall and spring snowmelt is needed to better understand recent tundra vegetation

Consumption Frequency of Foods Away from Home Linked with Higher Body Mass Index and Lower Fruit and Vegetable Intake among Adults: A Cross-Sectional Study

PubMed Central

Seguin, Rebecca A.; Aggarwal, Anju; Vermeylen, Francoise; Drewnowski, Adam

2016-01-01

Introduction. Consumption of foods prepared away from home (FAFH) has grown steadily since the 1970s. We examined the relationship between FAFH and body mass index (BMI) and fruit and vegetable (FV) consumption. Methods. Frequency of FAFH, daily FV intake, height and weight, and sociodemographic data were collected using a telephone survey in 2008-2009. Participants included a representative sample of 2,001 adult men and women (mean age 54 ± 15 years) residing in King County, WA, with an analytical sample of 1,570. Frequency of FAFH was categorized as 0-1, 2–4, or 5+ times per week. BMI was calculated from self-reported height and weight. We examined the relationship between FAFH with FV consumption and BMI using multivariate models. Results. Higher frequency of FAFH was associated with higher BMI, after adjusting for age, income, education, race, smoking, marital status, and physical activity (women: p = 0.001; men: p = 0.003). There was a negative association between frequency of FAFH and FV consumption. FAFH frequency was significantly (p < 0.001) higher among males than females (43.1% versus 54.0% eating out 0-1 meal per week, resp.). Females reported eating significantly (p < 0.001) more FV than males. Conclusion. Among adults, higher frequency of FAFH was related to higher BMI and less FV consumption. PMID:26925111

Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements

PubMed Central

Fontana, Fabio; Rixen, Christian; Jonas, Tobias; Aberegg, Gabriel; Wunderle, Stefan

2008-01-01

This study evaluates the ability to track grassland growth phenology in the Swiss Alps with NOAA-16 Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) time series. Three growth parameters from 15 alpine and subalpine grassland sites were investigated between 2001 and 2005: Melt-Out (MO), Start Of Growth (SOG), and End Of Growth (EOG). We tried to estimate these phenological dates from yearly NDVI time series by identifying dates, where certain fractions (thresholds) of the maximum annual NDVI amplitude were crossed for the first time. For this purpose, the NDVI time series were smoothed using two commonly used approaches (Fourier adjustment or alternatively Savitzky-Golay filtering). Moreover, AVHRR NDVI time series were compared against data from the newer generation sensors SPOT VEGETATION and TERRA MODIS. All remote sensing NDVI time series were highly correlated with single point ground measurements and therefore accurately represented growth dynamics of alpine grassland. The newer generation sensors VGT and MODIS performed better than AVHRR, however, differences were minor. Thresholds for the determination of MO, SOG, and EOG were similar across sensors and smoothing methods, which demonstrated the robustness of the results. For our purpose, the Fourier adjustment algorithm created better NDVI time series than the Savitzky-Golay filter, since latter appeared to be more sensitive to noisy NDVI time series. Findings show that the application of various thresholds to NDVI time series allows the observation of the temporal progression of vegetation growth at the selected sites with high consistency. Hence, we believe that our study helps to better understand large-scale vegetation growth dynamics above the tree line in the European Alps. PMID:27879852

Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements.

PubMed

Fontana, Fabio; Rixen, Christian; Jonas, Tobias; Aberegg, Gabriel; Wunderle, Stefan

2008-04-23

This study evaluates the ability to track grassland growth phenology in the Swiss Alps with NOAA-16 Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) time series. Three growth parameters from 15 alpine and subalpine grassland sites were investigated between 2001 and 2005: Melt-Out (MO), Start Of Growth (SOG), and End Of Growth (EOG).We tried to estimate these phenological dates from yearly NDVI time series by identifying dates, where certain fractions (thresholds) of the maximum annual NDVI amplitude were crossed for the first time. For this purpose, the NDVI time series were smoothed using two commonly used approaches (Fourier adjustment or alternatively Savitzky-Golay filtering). Moreover, AVHRR NDVI time series were compared against data from the newer generation sensors SPOT VEGETATION and TERRA MODIS. All remote sensing NDVI time series were highly correlated with single point ground measurements and therefore accurately represented growth dynamics of alpine grassland. The newer generation sensors VGT and MODIS performed better than AVHRR, however, differences were minor. Thresholds for the determination of MO, SOG, and EOG were similar across sensors and smoothing methods, which demonstrated the robustness of the results. For our purpose, the Fourier adjustment algorithm created better NDVI time series than the Savitzky-Golay filter, since latter appeared to be more sensitive to noisy NDVI time series. Findings show that the application of various thresholds to NDVI time series allows the observation of the temporal progression of vegetation growth at the selected sites with high consistency. Hence, we believe that our study helps to better understand largescale vegetation growth dynamics above the tree line in the European Alps.

[Effects of green space vegetation canopy pattern on the microclimate in residential quarters of Shenzhen City].

PubMed

Li, Ying-Han; Wang, Jun-Jian; Chen, Xue; Sun, Jian-Lin; Zeng, Hui

2011-02-01

Based on field survey and landscape pattern analysis, this paper studied the effects of green space vegetation canopy on the microclimate in three typical residential quarters in Shenzhen City. In each of the residential quarters, 22-26 points were chosen for meteorological observation; and around each of the observation points, a 20 m x 20 m quadrat was installed, with each quadrat divided into two different patches, one covered by vegetation canopy and the another no-covered. The patch density index (D(p)) and contagion index (CONTAG) in each quadrat were calculated to analyze the relationships between vegetation canopy pattern index and microclimate in each point. The results showed that the green space vegetation canopy pattern in Shenzhen had significant regulation effect on temperature and humidity. The cooling effect was mainly from the shading effect of vegetation, and also, correlated with vegetation quantity. The increase in the CONTAG of bare surface had obvious negative effects on the regulation effect of vegetation on microclimate. The regulation capability of green space vegetation on the temperature and humidity in residential quarters mainly came from tall arbor species.

High-resolution IKONOS satellite imagery for normalized difference vegetative index-related assessment applied to land clearance studies

NASA Astrophysics Data System (ADS)

Lavers, Chris R.; Mason, Travis

2017-07-01

High-resolution satellite imagery permits verification of human rights land clearance violations across international borders as a result of unstable regimes or socio-economic upheaval. Without direct access to these areas to validate allegations of human rights abuse, the use of remote sensing tools, techniques, and data is extremely important. Humanitarian assessment can benefit from software-based solutions, involving radiometrically calibrated normalized difference vegetation index and temporal change imagery. We discuss the introduction of a matrix filter approach for change detection studies to help assist rapid building detection over large search areas against a bright background to evaluate internally displaced people in the 2005 Porta Farm Zimbabwe clearances. Future wide-scale near real-time space-based monitoring with a range of digital filters would be of great benefit to international human rights observers and human rights networks.

Misperception of self-reported adherence to the fruit, vegetable and fish guidelines in older Dutch adults.

PubMed

Dijkstra, S C; Neter, J E; Brouwer, I A; Huisman, M; Visser, M

2014-11-01

In this study we investigated (the degree of) misperception of adherence to the fruit, vegetable and fish guidelines in older Dutch adults and examined to what extent misperception is associated with socio-economic position (SEP) and other demographic, lifestyle and nutrition-related characteristics. The sample included 1057 community dwelling adults, aged 55-85 years, who participated in the Longitudinal Aging Study Amsterdam. Respondents completed a lifestyle questionnaire which included a food frequency questionnaire to calculate fruit, vegetable and fish intake. After current dietary guidelines were explained, respondents were asked to indicate whether they believed they adhered to the fruit, vegetable and fish guidelines. Characteristics potentially associated with misperception included level of income and education, lifestyle factors, nutritional knowledge, as well as attitude, social support and self-efficacy toward healthy eating. In the total sample, 69.1% of the older adults reported to adhere to the fruit guideline, 77.5% to the vegetable guideline, and 36.4% to the fish guideline. Based on the calculated intake data, 82.6% adhered to the fruit guideline, 65.5% to the vegetable guideline and 33.8% to the fish guideline. Overestimation of adherence was most common for the vegetable guideline (18.7%). Multivariate analysis, adjusted for level of income as well as for attitude and self-efficacy toward healthy eating, showed that lower educated respondents were more likely to overestimate their adherence to the vegetable guideline (relative index of inequality (RII): 2.97 (95% CI: 1.47-6.01)). Overestimation rates for fish (3.4%) and fruit (2.3%) were lower and not associated with any of the characteristics. This study showed that overestimation in older adults was common for adherence to the vegetable guideline and especially in those with a lower education level, but not for adherence to the fruit and fish guideline. Copyright © 2014 Elsevier Ltd. All

Extracting Vegetation Coverage in Dry-hot Valley Regions Based on Alternating Angle Minimum Algorithm

NASA Astrophysics Data System (ADS)

Y Yang, M.; Wang, J.; Zhang, Q.

2017-07-01

Vegetation coverage is one of the most important indicators for ecological environment change, and is also an effective index for the assessment of land degradation and desertification. The dry-hot valley regions have sparse surface vegetation, and the spectral information about the vegetation in such regions usually has a weak representation in remote sensing, so there are considerable limitations for applying the commonly-used vegetation index method to calculate the vegetation coverage in the dry-hot valley regions. Therefore, in this paper, Alternating Angle Minimum (AAM) algorithm of deterministic model is adopted for selective endmember for pixel unmixing of MODIS image in order to extract the vegetation coverage, and accuracy test is carried out by the use of the Landsat TM image over the same period. As shown by the results, in the dry-hot valley regions with sparse vegetation, AAM model has a high unmixing accuracy, and the extracted vegetation coverage is close to the actual situation, so it is promising to apply the AAM model to the extraction of vegetation coverage in the dry-hot valley regions.

Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development.

PubMed

Breunig, Fábio M; Galvão, Lênio S; Formaggio, Antônio R; Epiphanio, José C N

2012-06-01

Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS). In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI(1640) and NDWI(2120)) with the soybean development in two growing seasons (2004-2005 and 2005-2006). To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.

Vegetation diversity protects against childhood asthma: results from a large New Zealand birth cohort

Treesearch

Geoffrey H. Donovan; Demetrios Gatziolis; Ian Longley; Jeroen Douwes

2018-01-01

We assessed the association between the natural environment and asthma in 49,956 New Zealand children born in 1998 and followed up until 2016 using routinely collected data. Children who lived in greener areas, as measured by the normalized difference vegetation index, were less likely to be asthmatic: a 1 s.d. increase in normalized difference vegetation index was...

Adjusting Health Expenditures for Inflation: A Review of Measures for Health Services Research in the United States.

PubMed

Dunn, Abe; Grosse, Scott D; Zuvekas, Samuel H

2018-02-01

To provide guidance on selecting the most appropriate price index for adjusting health expenditures or costs for inflation. Major price index series produced by federal statistical agencies. We compare the key characteristics of each index and develop suggestions on specific indexes to use in many common situations and general guidance in others. Price series and methodological documentation were downloaded from federal websites and supplemented with literature scans. The gross domestic product implicit price deflator or the overall Personal Consumption Expenditures (PCE) index is preferable to the Consumer Price Index (CPI-U) to adjust for general inflation, in most cases. The Personal Health Care (PHC) index or the PCE health-by-function index is generally preferred to adjust total medical expenditures for inflation. The CPI medical care index is preferred for the adjustment of consumer out-of-pocket expenditures for inflation. A new, experimental disease-specific Medical Care Expenditure Index is now available to adjust payments for disease treatment episodes. There is no single gold standard for adjusting health expenditures for inflation. Our discussion of best practices can help researchers select the index best suited to their study. © Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Dietary intake of fiber, fruit and vegetables decreases the risk of incident kidney stones in women: a Women's Health Initiative report.

PubMed

Sorensen, Mathew D; Hsi, Ryan S; Chi, Thomas; Shara, Nawar; Wactawski-Wende, Jean; Kahn, Arnold J; Wang, Hong; Hou, Lifang; Stoller, Marshall L

2014-12-01

We evaluated the relationship between dietary fiber, fruit and vegetable intake, and the risk of kidney stone formation. Overall 83,922 postmenopausal women from the Women's Health Initiative observational study were included in the analysis and followed prospectively. Cox proportional hazards regression analyses were used to evaluate the associations between total dietary fiber, fruit and vegetable intake, and the risk of incident kidney stone formation, adjusting for nephrolithiasis risk factors (age, race/ethnicity, geographic region, diabetes mellitus, calcium supplementation, hormone therapy use, body mass index and calibrated caloric intake; and dietary water, sodium, animal protein and calcium intake). Women with a history of kidney stones (3,471) were analyzed separately. Mean age of the women was 64±7 years, 85% were white and 2,937 (3.5%) experienced a kidney stone in a median followup of 8 years. In women with no history of kidney stones higher total dietary fiber (6% to 26% decreased risk, p <0.001), greater fruit intake (12% to 25% decreased risk, p <0.001) and greater vegetable intake (9% to 22% decreased risk, p=0.002) were associated with a decreased risk of incident kidney stone formation in separate adjusted models. In women with a history of stones there were no significant protective effects of fiber, fruit or vegetable intake on the risk of kidney stone recurrence. Greater dietary intake of fiber, fruits and vegetables was associated with a reduced risk of incident kidney stones in postmenopausal women. The protective effects were independent of other known risk factors for kidney stones. In contrast, there was no reduction in risk in women with a history of stones. Copyright © 2014 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Performance of different vegetation indices in assessing degradation of community grazing lands in Indian arid zone

NASA Astrophysics Data System (ADS)

Kumar, Suresh; Bastin, Gary; Friedel, Margaret; Narain, Pratap; Saha, D. K.; Ahuja, U. R.; Mathur, B. K.

2006-12-01

Vegetation in arid community grazinglands shows monsoonal growth. Its matching phenology with crops makes its detection difficult during July to September. While crops are harvested during September-October, using satellite data thereafter for the natural vegetation seems most appropriate but by then it turns dry. An index capable of sensing dry vegetation was needed since conventional NDVI is sensitive to greenness of vegetation. Performance of NDVI vis-à-vis another index, PD54, based on cover was therefore compared in assessing degradation of grazinglands. The PD54 was used to isolate anthropogenic impacts from environmental induced degradation by analyzing satellite images from dry and wet seasons. Substantial absence of appreciable vegetation response indicated poor resilience and severe degradation. Five grazinglands in Shergarh tehsil of Jodhpur district in Rajasthan were studied following above approach. Ground radiometric observations were recorded. Satellite data of IRS 1C/1D/P6 with LISS 3 sensor for both pre and post monsoon season were acquired for three contrasting wet-dry season events. These were geometrically registered and radiometrically calibrated to calculate an index of vegetation cover PD54 as well as NDVI. PD54 is a perpendicular vegetation index based on the green and red spectral band width. The PD54 and NDVI calculated from spectro-radiometer were related to vegetation cover measured on ground in permanent plots. This confirmed that PD54 was superior index for estimating cover in arid dry grasslands. These ground vegetation trends in a good rainfall year (2001) with drought year (2002) were related with satellite data for a protected and four unprotected grazinglands. NDVI failed to detect any vegetation in protected areas supporting excellent grass cover which was succinctly brought out by PD54. Successful validation of PD54 in detecting degradation of 13 additional sites confirmed its efficacy. These findings have implication in forage

Climatic drivers of vegetation based on wavelet analysis

NASA Astrophysics Data System (ADS)

Claessen, Jeroen; Martens, Brecht; Verhoest, Niko E. C.; Molini, Annalisa; Miralles, Diego

2017-04-01

Vegetation dynamics are driven by climate, and at the same time they play a key role in forcing the different bio-geochemical cycles. As climate change leads to an increase in frequency and intensity of hydro-meteorological extremes, vegetation is expected to respond to these changes, and subsequently feed back on their occurrence. This response can be analysed using time series of different vegetation diagnostics observed from space, in the optical (e.g. Normalised Difference Vegetation Index (NDVI), Solar Induced Fluorescence (SIF)) and microwave (Vegetation Optical Depth (VOD)) domains. In this contribution, we compare the climatic drivers of different vegetation diagnostics, based on a monthly global data-cube of 24 years at a 0.25° resolution. To do so, we calculate the wavelet coherence between each vegetation-related observation and observations of air temperature, precipitation and incoming radiation. The use of wavelet coherence allows unveiling the scale-by-scale response and sensitivity of the diverse vegetation indices to their climatic drivers. Our preliminary results show that the wavelet-based statistics prove to be a suitable tool for extracting information from different vegetation indices. Going beyond traditional methods based on linear correlations, the application of wavelet coherence provides information about: (a) the specific periods at which the correspondence between climate and vegetation dynamics is larger, (b) the frequencies at which this correspondence occurs (e.g. monthly or seasonal scales), and (c) the time lag in the response of vegetation to their climate drivers, and vice versa. As expected, areas of high rainfall volumes are characterised by a strong control of radiation and temperature over vegetation. Furthermore, precipitation is the most important driver of vegetation variability over short terms in most regions of the world - which can be explained by the rapid response of leaf development towards available water content

Trends in the normalized difference vegetation index (NDVI) associated with urban development in arctic and subarctic Western Siberia

NASA Astrophysics Data System (ADS)

Outten, S.; Miles, V.; Ezau, I.

2015-12-01

Changes in normalized difference vegetation index (NDVI) in the high Arctic have been reliably documented, with widespread "greening" (increase in NDVI), specifically along the northern rim of Eurasia and Alaska. Whereas in West Siberia south of 65N, widespread "browning" (decrease in NDVI) has been noted, although the causes remain largely unclear. In this study we report results of statistical analysis of the spatial and temporal changes in NDVI around 28 major urban areas in the arctic and subarctic Western Siberia. Exploration and exploitation of oil and gas reserves has led to rapid industrialization and urban development in the region. This development has significant impact on the environment and particularly in the vegetation cover in and around the urbanized areas. The analysis is based on 15 years (2000-2014) of high-resolution (250 m) Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired for summer months (June through August) over the entire arctic and subarctic Western Siberian region. The analysis shows that the NDVI background trends are generally in agreement with the trends reported in previous coarse-resolution NDVI studies. Our study reveals greening over the arctic (tundra and tundra-forest) part of the region. Simultaneously, the southern (boreal taiga forest) part is browning, with the more densely vegetation areas or areas with highest NDVI, particularly along Ob River showing strong negative trend. The unexpected and interesting finding of the study is statistically robust indication of the accelerated increase of NDVI ("greening") in the older urban areas. Many Siberian cities become greener even against the decrease in the NDVI background. Moreover, interannual variations of urban NDVI are not coherent with the NDVI background variability. We also find that in tundra zones, NDVI values are higher in a 5-10 km buffer zone around the city edge than in rural areas (40 km distance from the city edge), and in taiga in a 5-10 km

Satellite assessment of early-season forecasts for vegetation conditions of grazing allotments in Nevada, United States

USDA-ARS?s Scientific Manuscript database

Fifteen years of enhanced vegetation index data from the MODIS sensor are examined in conjunction with precipitation and the Palmer drought severity index to assess how well growing season conditions for vegetation within grazing allotments of Nevada can be predicted at different times of the year. ...

Soil moisture and vegetation patterns in northern California forests

Treesearch

James R. Griffin

1967-01-01

Twenty-nine soil-vegetation plots were studied in a broad transect across the southern Cascade Range. Variations in soil moisture patterns during the growing season and in soil moisture tension values are discussed. Plot soil moisture values for 40- and 80-cm. depths in August and September are integrated into a soil drought index. Vegetation patterns are described in...

Gully evolution and geomorphic adjustments of badlands to recent afforestation

NASA Astrophysics Data System (ADS)

Ballesteros-Cánovas, Juan Antonio; Stoffel, Markus; Francisco Martín-Duque, Jose; Corona, Christophe; Lucia, Ana; María Bodoque, Jose

2016-04-01

Badlands and gullied areas are among the geomorphic environments with the highest erosion rates worldwide, however records on their evolution are very scarce and often limited to presumed initial conditions and the known present state. In this communication, we present a unique and very dense and annual record and outstanding example of erosion processes in a Mediterranean environment in Central Spain, where badland and gullying processes on sandy slopes of a set of mesas have been presumably triggered by quarrying activities since Medieval times. The gully channel evolution here analyzed provides an exceptional example of a larger setting of geomorphic. Besides the analysis of geomorphic adjustments to historical land-use changes induced by historical quarrying and gullying dynamics, we also quantified the impact of current geomorphic adjustments to 20th century afforestation by combining multiproxy such as aerial photography, historical archives, and large dataset of exposed roots to date, quantify, and reconstruct the morphology of a rapidly evolving channel in a gullied catchment. In this analysis, more than 150 exposed roots were analyzed to quantify and report channel incision; widening and gully retreatment rates during the last decades, as well as to quantify sheet erosion on different soil units. Our results suggest that, rather than stabilizing gully evolution, the afforestation carried out during 1960s has played an important role in water-sediment balance and connectivity and would have triggered the initiation of channel incision processes in the 1980s. Therefore, we observe that the channel incision match with a significant increase of the vegetation cover, which leads a significant decrease in sheet erosion rates. Based on our long-term annual gully reconstruction, we observed that sediment delivery does not correlate with the estimated intensity of precipitation (Fourier index). Instead, we observe abrupt morphological changes in the gully are

Vegetation burn severity mapping using Landsat-8 and WorldView-2

USGS Publications Warehouse

Wu, Zhuoting; Middleton, Barry R.; Hetzler, Robert; Vogel, John M.; Dye, Dennis G.

2015-01-01

We used remotely sensed data from the Landsat-8 and WorldView-2 satellites to estimate vegetation burn severity of the Creek Fire on the San Carlos Apache Reservation, where wildfire occurrences affect the Tribe's crucial livestock and logging industries. Accurate pre- and post-fire canopy maps at high (0.5-meter) resolution were created from World- View-2 data to generate canopy loss maps, and multiple indices from pre- and post-fire Landsat-8 images were used to evaluate vegetation burn severity. Normalized difference vegetation index based vegetation burn severity map had the highest correlation coefficients with canopy loss map from WorldView-2. Two distinct approaches - canopy loss mapping from WorldView-2 and spectral index differencing from Landsat-8 - agreed well with the field-based burn severity estimates and are both effective for vegetation burn severity mapping. Canopy loss maps created with WorldView-2 imagery add to a short list of accurate vegetation burn severity mapping techniques that can help guide effective management of forest resources on the San Carlos Apache Reservation, and the broader fire-prone regions of the Southwest.

[Effects of re-vegetation on soil microbial functional diversity in purple soils at different re-vegetation stages on sloping-land in Hengyang, Hunan Province, China.

PubMed

Wen, Dong Xin; Yang, Ning; Yang, Man Yuan

2016-08-01

The aim of the study was to explore the effects of re-vegetation on soil microbial functio-nal diversity in purple soils at different re-vegetation stages on sloping-land in Hengyang, Hunan Province, China. By using the spatial series to replace time series, four typical sampling plots, grass (Setaria viridi, GS), frutex and grass (Lagerstroemia indica-Setaria viridi, FG), frutex (Vitex negundo var. cannabifolia+Robinia pseudoacacia, FX), as well as arbor and frutex (Liquidamdar formosana+Melia azedarach-Vitex negundo var. cannabifolia, AF) community were selected to study the soil microbial functional diversity by using the Biolog-ECO micro-plate technique. The four communities in purple soils on sloping-land were similar and denoted four different re-vegetation stages. The results showed that the soil microbial metabolic activity increased after re-vegetation significantly, and the average well color development (AWCD) which represented soil microbial activity and functional diversity followed the order of AF community＞FX community＞FG community＞GS community at different re-vegetation stages, and followed the order of 0-10 cm ＞10-20 cm in different soil layers. Principal component analysis (PCA) identified that FG and FX community had similar C sources utilization mode and metabolic function, and GS and AF community were diffe-rent. The carbohydrates, amino acids, intermediate metabolites, and secondary metabolites were the main carbon sources separating the two principal component factors. The Shannon species richness index (H), Shannon evenness index (E), Simpson dominance index (D), McIntosh index (U) at four re-vegetation stages were the highest in AF community, the second in FG and FX community, and the lowest in GS community. The results of correlation analysis indicated that the content of soil water content (SWC), soil total organic carbon (STOC), total nitrogen (TN), total phospho-rus (TP) and available phosphorus (AP) had important influence on

Prognostic validation of the body mass index, airflow obstruction, dyspnea, and exercise capacity (BODE) index in inoperable non-small-cell lung cancer.

PubMed

Denehy, Linda; Hornsby, Whitney E; Herndon, James E; Thomas, Samantha; Ready, Neal E; Granger, Catherine L; Valera, Lauren; Kenjale, Aarti A; Eves, Neil D; Jones, Lee W

2013-12-01

To investigate the prognostic utility of the body mass index, severity of airflow obstruction, measures of exertional dyspnea, and exercise capacity (BODE) index in patients with inoperable non-small-cell lung cancer (NSCLC). One hundred consecutive patients with inoperable NSCLC and performance status 0 to 3 completed pulmonary function testing, the modified Medical Research Council dyspnea scale, a 6-minute walk test, and body mass index-the multidimensional 10-point BODE index. Cox proportional models were used to estimate the risk of all-cause mortality according to the BODE index with or without adjustment for traditional prognostic factors. Median follow-up was 31.5 months; 61 deaths (61%) were reported during this period. There was a significant univariate association between the BODE index score and mortality (adjusted p(trend) = 0.027). Compared with patients with a BODE index of 0, the adjusted hazard ratio for risk of death was 1.37 (95% confidence interval [CI], 0.74-2.55) for a BODE index of 1, 1.22 (95% CI, 0.45-3.25) for a BODE index of 2, and 2.44 (95% CI, 1.19-4.99) for a BODE index more than 2. The BODE index provided incremental prognostic information beyond that provided traditional markers of prognosis (adjusted p(trend) = 0.051). Every one-point increase in the BODE index, the risk of death increased by 25% (hazard ratio = 1.25; 95% CI, 1.27-4.64). The BODE index is a strong independent predictor of survival in inoperable NSCLC beyond traditional risk factors. Use of this multidimensional tool may improve risk stratification and prognostication in NSCLC.

Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; Russell, Jeffrey; Ryan, Robert E.

2006-01-01

The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion

Climate Change Implications to Vegetation Production in Alaska

NASA Technical Reports Server (NTRS)

Neigh, Christopher S.R.

2008-01-01

Investigation of long-term meteorological satellite data revealed statistically significant vegetation response to climate drivers of temperature, precipitation and solar radiation with exclusion of fire disturbance in Alaska. Abiotic trends were correlated to satellite remote sensing observations of normalized difference vegetation index to understand biophysical processes that could impact ecosystem carbon storage. Warming resulted in disparate trajectories for vegetation growth due to precipitation and photosynthetically active radiation variation. Interior spruce forest low lands in late summer through winter had precipitation deficit which resulted in extensive fire disturbance and browning of undisturbed vegetation with reduced post-fire recovery while Northern slope moist alpine tundra had increased production due to warmer-wetter conditions during the late 1990s and early 2000s. Coupled investigation of Alaska s vegetation response to warming climate found spatially dynamic abiotic processes with vegetation browning not a result from increased fire disturbance.

Estimation of Anticipated Performance Index and Air Pollution Tolerance Index and of vegetation around the marble industrial areas of Potwar region: bioindicators of plant pollution response.

PubMed

Noor, Mehwish Jamil; Sultana, Shazia; Fatima, Sonia; Ahmad, Mushtaq; Zafar, Muhammad; Sarfraz, Maliha; Balkhyour, Masour A; Safi, Sher Zaman; Ashraf, Muhammad Aqeel

2015-06-01

Mitigating industrial air pollution is a big challenge, in such scenario screening of plants as a bio monitor is extremely significant. It requires proper selection and screening of sensitive and tolerant plant species which are bio indicator and sink for air pollution. The present study was designed to evaluate the Air Pollution Tolerance Index (APTI) and Anticipated Performance Index (API) of the common flora. Fifteen common plant species from among trees, herb and shrubs i.e. Chenopodium album (Chenopodiaceae), Parthenium hysterophorus (Asteraceae), Amaranthus viridis (Amaranthaceae), Lantana camara (Verbenaceaea), Ziziphus nummulari (Rhamnaceae), Silibum merianum (Asteraceae), Cannabis sativa (Cannabinaceae), Calatropis procera (Asclepediaceae), Ricinus communis (Euphorbiaceae), Melia azadirachta (Meliaceae), Psidium guajava (Myrtaceae), Eucalyptus globules (Myrtaceae), Broussonetia papyrifera (Moraceae), Withania somnifera (Solanaceae) and Sapium sabiferum (Euphorbiaceae) were selected growing frequently in vicinity of Marble industries in Potwar region. APTI and API of selected plant species were analyzed by determining important biochemical parameter i.e. total chlorophyll, ascorbic acid, relative water content and pH etc. Furthermore the selected vegetation was studied for physiological, economic, morphological and biological characteristics. The soil of studied sites was analyzed. It was found that most the selected plant species are sensitive to air pollution. However B. papyrifera, E. globulus and R. communis shows the highest API and therefore recommended for plantation in marble dust pollution stress area.

The heat rate index indicator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lasasso, M.; Runyan, B.; Napoli, J.

1995-06-01

This paper describes a method of tracking unit performance through the use of a reference number called the Heat Rate Index Indicator. The ABB Power Plant Controls OTIS performance monitor is used to determine when steady load conditions exist and then to collect controllable and equipment loss data which significantly impact thermal efficiency. By comparing these loss parameters to those found during the previous heat balance, it is possible to develop a new adjusted heat rate curve. These impacts on heat rate are used to changes the shape of the tested heat rate curve by the appropriate percentages over amore » specified load range. Mathcad is used to determine the Heat Rate Index by integrating for the areas beneath the adjusted heat rate curve and a heat rate curve that represents the unit`s ideal heat rate curve is the Heat Rate Index. An index of 1.0 indicates that the unit is operating at an ideal efficiency, while an index of less than 1.0 indicates that the unit is operating at less than ideal conditions. A one per cent change in the Heat Rate Index is equivalent to a one percent change in heat rate. The new shape of the adjusted heat rate curve and the individual curves generated from the controllable and equipment loss parameters are useful for determining performance problems in specific load ranges.« less

Greenup and evapotranspiration following the Minute 319 pulse flow to Mexico: An analysis using Landsat 8 Normalized Difference Vegetation Index (NDVI) data

USGS Publications Warehouse

Jarchow, Christopher J.; Nagler, Pamela L.; Glenn, Edward P.

2017-01-01

In the southwestern U.S., many riparian ecosystems have been altered by dams, water diversions, and other anthropogenic activities. This is particularly true of the Colorado River, where numerous dams and agricultural diversions have affected this water course, especially south of the U.S.–Mexico border. In the spring of 2014, 130 million cubic meters of water was released to the lower Colorado River Delta in Mexico. To understand the impact of this pulse flow release on vegetation in the delta’s riparian corridor, we analyzed a modified form of Landsat 8 Operational Land Imager (OLI) Normalized Difference Vegetation Index (NDVI*) data. We assessed greenup during the growing period and estimated actual evapotranspiration (ETa) for the period prior to (yr. 2013) and following (i.e., yr. 2014 and 2015) the pulse flow. We found a significant increase in NDVI* from 2013 to 2014 (P < 0.05) and a decrease from 2014 to 2015; however, 2015 levels were still significantly higher than in 2013. ETa was also higher in 2014 vs. 2013, with an estimated 74.5 million cubic meters in 2013 and 88.9 in 2014. The most intense greening occurred in the zone of inundation but also extended into the non-flooded part of the riparian zone, indicating replenishment of groundwater. These findings suggest the peak response by vegetation to the flow lasted about one year, followed by a decrease in NDVI*. As a long term solution to the declining condition of vegetation, additional pulse releases are likely needed for restoration and survival of riparian plant communities in the Colorado River Delta.

Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

NASA Astrophysics Data System (ADS)

Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

2018-04-01

Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted

The Relationship between Number of Fruits, Vegetables, and Noncore Foods Tried at Age 14 Months and Food Preferences, Dietary Intake Patterns, Fussy Eating Behavior, and Weight Status at Age 3.7 Years.

PubMed

Mallan, Kimberley M; Fildes, Alison; Magarey, Anthea M; Daniels, Lynne A

2016-04-01

We examined whether exposure to a greater number of fruits, vegetables, and noncore foods (ie, nutrient poor and high in saturated fats, added sugars, or added salt) at age 14 months was related to children's preference for and intake of these foods as well as maternal-reported food fussiness and measured child weight status at age 3.7 years. This study reports secondary analyses of longitudinal data from mothers and children (n=340) participating in the NOURISH randomized controlled trial. Exposure was quantified as the number of food items (n=55) tried by a child from specified lists at age 14 months. At age 3.7 years, food preferences, intake patterns, and fussiness (also at age 14 months) were assessed using maternal-completed, established questionnaires. Child weight and length/height were measured by study staff at both age points. Multivariable linear regression models were tested to predict food preferences, intake patterns, fussy eating, and body mass index z score at age 3.7 years adjusting for a range of maternal and child covariates. Having tried a greater number of vegetables, fruits, and noncore foods at age 14 months predicted corresponding preferences and higher intakes at age 3.7 years but did not predict child body mass index z score. Adjusting for fussiness at age 14 months, having tried more vegetables at age 14 months was associated with lower fussiness at age 3.7 years. These prospective analyses support the hypothesis that early taste and texture experiences influence subsequent food preferences and acceptance. These findings indicate introduction to a variety of fruits and vegetables and limited noncore food exposure from an early age are important strategies to improve later diet quality. Copyright © 2016 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Fruit and vegetables and cancer risk.

PubMed

Key, T J

2011-01-04

The possibility that fruit and vegetables may help to reduce the risk of cancer has been studied for over 30 years, but no protective effects have been firmly established. For cancers of the upper gastrointestinal tract, epidemiological studies have generally observed that people with a relatively high intake of fruit and vegetables have a moderately reduced risk, but these observations must be interpreted cautiously because of potential confounding by smoking and alcohol. For lung cancer, recent large prospective analyses with detailed adjustment for smoking have not shown a convincing association between fruit and vegetable intake and reduced risk. For other common cancers, including colorectal, breast and prostate cancer, epidemiological studies suggest little or no association between total fruit and vegetable consumption and risk. It is still possible that there are benefits to be identified: there could be benefits in populations with low average intakes of fruit and vegetables, such that those eating moderate amounts have a lower cancer risk than those eating very low amounts, and there could also be effects of particular nutrients in certain fruits and vegetables, as fruit and vegetables have very varied composition. Nutritional principles indicate that healthy diets should include at least moderate amounts of fruit and vegetables, but the available data suggest that general increases in fruit and vegetable intake would not have much effect on cancer rates, at least in well-nourished populations. Current advice in relation to diet and cancer should include the recommendation to consume adequate amounts of fruit and vegetables, but should put most emphasis on the well-established adverse effects of obesity and high alcohol intakes.

Fruit and vegetables and cancer risk

PubMed Central

Key, T J

2011-01-01

The possibility that fruit and vegetables may help to reduce the risk of cancer has been studied for over 30 years, but no protective effects have been firmly established. For cancers of the upper gastrointestinal tract, epidemiological studies have generally observed that people with a relatively high intake of fruit and vegetables have a moderately reduced risk, but these observations must be interpreted cautiously because of potential confounding by smoking and alcohol. For lung cancer, recent large prospective analyses with detailed adjustment for smoking have not shown a convincing association between fruit and vegetable intake and reduced risk. For other common cancers, including colorectal, breast and prostate cancer, epidemiological studies suggest little or no association between total fruit and vegetable consumption and risk. It is still possible that there are benefits to be identified: there could be benefits in populations with low average intakes of fruit and vegetables, such that those eating moderate amounts have a lower cancer risk than those eating very low amounts, and there could also be effects of particular nutrients in certain fruits and vegetables, as fruit and vegetables have very varied composition. Nutritional principles indicate that healthy diets should include at least moderate amounts of fruit and vegetables, but the available data suggest that general increases in fruit and vegetable intake would not have much effect on cancer rates, at least in well-nourished populations. Current advice in relation to diet and cancer should include the recommendation to consume adequate amounts of fruit and vegetables, but should put most emphasis on the well-established adverse effects of obesity and high alcohol intakes. PMID:21119663

Development and Analysis of Global, High-Resolution Diagnostic Metrics for Vegetation Monitoring, Yield Estimation and Famine Mitigation

NASA Astrophysics Data System (ADS)

Anderson, B. T.; Zhang, P.; Myneni, R.

2008-12-01

Drought, through its impact on food scarcity and crop prices, can have significant economic, social, and environmental impacts - presently, up to 36 countries and 73 million people are facing food crises around the globe. Because of these adverse affects, there has been a drive to develop drought and vegetation- monitoring metrics that can quantify and predict human vulnerability/susceptibility to drought at high- resolution spatial scales over the entire globe. Here we introduce a new vegetation-monitoring index utilizing data derived from satellite-based instruments (the Moderate Resolution Imaging Spectroradiometer - MODIS) designed to identify the vulnerability of vegetation in a particular region to climate variability during the growing season. In addition, the index can quantify the percentage of annual grid-point vegetation production either gained or lost due to climatic variability in a given month. When integrated over the growing season, this index is shown to be better correlated with end-of-season crop yields than traditional remotely-sensed or meteorological indices. In addition, in-season estimates of the index, which are available in near real-time, provide yield forecasts comparable to concurrent in situ objective yield surveys, which are only available in limited regions of the world. Overall, the cost effectiveness and repetitive, near-global view of earth's surface provided by this satellite-based vegetation monitoring index can potentially improve our ability to mitigate human vulnerability/susceptibility to drought and its impacts upon vegetation and agriculture.

Relationship between tourism development and vegetated landscapes in Luya Mountain Nature Reserve, Shanxi, China.

PubMed

Cheng, Zhan-Hong; Zhang, Jin-Tun

2005-09-01

The relationship between tourism development and vegetated landscapes is analyzed for the Luya Mountain Nature Reserve (LMNR), Shanxi, China, in this study. Indices such as Sensitive Level (SL), Landscape Importance Value (LIV), information index of biodiversity (H'), Shade-tolerant Species Proportion (SSP), and Tourism Influencing Index (TII) are used to characterize vegetated landscapes, the impact of tourism, and their relationship. Their relationship is studied by Two-Way Indicator Species Analysis (TWINSPAN) and Detrended Correspondence Analysis (DCA). TWINSPAN gives correct and rapid partition to the classification, and DCA ordination shows the changing tendency of all vegetation types based on tourism development. These results reflect the ecological relationship between tourism development and vegetated landscapes. In Luya Mountain Nature Reserve, most plant communities are in good or medium condition, which shows that these vegetated landscapes can support more tourism. However, the occurrence of the bad condition shows that there is a severe contradiction between tourism development and vegetated landscapes.

Retrieving pace in vegetation growth using precipitation and soil moisture

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, D. C.; Singh, V. P.

2013-12-01

The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and

Verification of watershed vegetation restoration policies, arid China

NASA Astrophysics Data System (ADS)

Zhang, Chengqi; Li, Yu

2016-07-01

Verification of restoration policies that have been implemented is of significance to simultaneously reduce global environmental risks while also meeting economic development goals. This paper proposed a novel method according to the idea of multiple time scales to verify ecological restoration policies in the Shiyang River drainage basin, arid China. We integrated modern pollen transport characteristics of the entire basin and pollen records from 8 Holocene sedimentary sections, and quantitatively reconstructed the millennial-scale changes of watershed vegetation zones by defining a new pollen-precipitation index. Meanwhile, Empirical Orthogonal Function method was used to quantitatively analyze spatial and temporal variations of Normalized Difference Vegetation Index in summer (June to August) of 2000-2014. By contrasting the vegetation changes that mainly controlled by millennial-scale natural ecological evolution with that under conditions of modern ecological restoration measures, we found that vegetation changes of the entire Shiyang River drainage basin are synchronous in both two time scales, and the current ecological restoration policies met the requirements of long-term restoration objectives and showed promising early results on ecological environmental restoration. Our findings present an innovative method to verify river ecological restoration policies, and also provide the scientific basis to propose future emphasizes of ecological restoration strategies.

Verification of watershed vegetation restoration policies, arid China

PubMed Central

Zhang, Chengqi; Li, Yu

2016-01-01

Verification of restoration policies that have been implemented is of significance to simultaneously reduce global environmental risks while also meeting economic development goals. This paper proposed a novel method according to the idea of multiple time scales to verify ecological restoration policies in the Shiyang River drainage basin, arid China. We integrated modern pollen transport characteristics of the entire basin and pollen records from 8 Holocene sedimentary sections, and quantitatively reconstructed the millennial-scale changes of watershed vegetation zones by defining a new pollen-precipitation index. Meanwhile, Empirical Orthogonal Function method was used to quantitatively analyze spatial and temporal variations of Normalized Difference Vegetation Index in summer (June to August) of 2000–2014. By contrasting the vegetation changes that mainly controlled by millennial-scale natural ecological evolution with that under conditions of modern ecological restoration measures, we found that vegetation changes of the entire Shiyang River drainage basin are synchronous in both two time scales, and the current ecological restoration policies met the requirements of long-term restoration objectives and showed promising early results on ecological environmental restoration. Our findings present an innovative method to verify river ecological restoration policies, and also provide the scientific basis to propose future emphasizes of ecological restoration strategies. PMID:27470948

The environmental vegetation index: A tool potentially useful for arid land management. [Texas and Mexico, plant growth stress due to water deficits

NASA Technical Reports Server (NTRS)

Gray, T. I., Jr.; Mccrary, D. G. (Principal Investigator)

1981-01-01

The NOAA-6 AVHRR data sets acquired over South Texas and Mexico during the spring of 1980 and after Hurricane Allen passed inland are analyzed. These data were processed to produce the Gray-McCrary Index (GMI's) for each pixel location over the selected area, which area contained rangeland and cropland, both irrigated and nonirrigated. The variations in the GMI's appear to reflect well the availability of water for vegetation. The GMI area maps are shown to delineate and to aid in defining the duration of drought; suggesting the possibility that time changes over a selected area could be useful for irrigation management.

Estimating sugarcane yield potential using an in-season determination of normalized difference vegetative index.

PubMed

Lofton, Josh; Tubana, Brenda S; Kanke, Yumiko; Teboh, Jasper; Viator, Howard; Dalen, Marilyn

2012-01-01

Estimating crop yield using remote sensing techniques has proven to be successful. However, sugarcane possesses unique characteristics; such as, a multi-year cropping cycle and plant height-limiting for midseason fertilizer application timing. Our study objective was to determine if sugarcane yield potential could be estimated using an in-season estimation of normalized difference vegetative index (NDVI). Sensor readings were taken using the GreenSeeker® handheld sensor from 2008 to 2011 in St. Gabriel and Jeanerette, LA, USA. In-season estimates of yield (INSEY) values were calculated by dividing NDVI by thermal variables. Optimum timing for estimating sugarcane yield was between 601-750 GDD. In-season estimated yield values improved the yield potential (YP) model compared to using NDVI. Generally, INSEY value showed a positive exponential relationship with yield (r(2) values 0.48 and 0.42 for cane tonnage and sugar yield, respectively). When models were separated based on canopy structure there was an increase the strength of the relationship for the erectophile varieties (r(2) 0.53 and 0.47 for cane tonnage and sugar yield, respectively); however, the model for planophile varieties weakened slightly. Results of this study indicate using an INSEY value for predicting sugarcane yield shows potential of being a valuable management tool for sugarcane producers in Louisiana.

Coupled topographic and vegetation patterns in coastal dunes: Remote sensing observations and ecomorphodynamic implications

NASA Astrophysics Data System (ADS)

Yousefi Lalimi, F.; Silvestri, S.; Moore, L. J.; Marani, M.

2017-01-01

Vegetation plays a key role in stabilizing coastal dunes and barrier islands by mediating sand transport, deposition, and erosion. Dune topography, in turn, affects vegetation growth, by determining local environmental conditions. However, our understanding of vegetation and dune topography as coupled and spatially extensive dynamical systems is limited. Here we develop and use remote sensing analyses to quantitatively characterize coastal dune ecotopographic patterns by simultaneously identifying the spatial distribution of topographic elevation and vegetation biomass. Lidar-derived leaf area index and hyperspectral-derived normalized difference vegetation index patterns yield vegetation distributions at the whole-system scale which are in agreement with each other and with field observations. Lidar-derived concurrent quantifications of biomass and topography show that plants more favorably develop on the landward side of the foredune crest and that the foredune crestline marks the position of an ecotone, which is interpreted as the result of a sheltering effect sharply changing local environmental conditions. We conclude that the position of the foredune crestline is a chief ecomorphodynamic feature resulting from the two-way interaction between vegetation and topography.

[Cross comparison of ASTER and Landsat ETM+ multispectral measurements for NDVI and SAVI vegetation indices].

PubMed

Xu, Han-qiu; Zhang, Tie-jun

2011-07-01

The present paper investigates the quantitative relationship between the NDVI and SAVI vegetation indices of Landsat and ASTER sensors based on three tandem image pairs. The study examines how well ASTER sensor vegetation observations replicate ETM+ vegetation observations, and more importantly, the difference in the vegetation observations between the two sensors. The DN values of the three image pairs were first converted to at-sensor reflectance to reduce radiometric differences between two sensors, images. The NDVI and SAVI vegetation indices of the two sensors were then calculated using the converted reflectance. The quantitative relationship was revealed through regression analysis on the scatter plots of the vegetation index values of the two sensors. The models for the conversion between the two sensors, vegetation indices were also obtained from the regression. The results show that the difference does exist between the two sensors, vegetation indices though they have a very strong positive linear relationship. The study found that the red and near infrared measurements differ between the two sensors, with ASTER generally producing higher reflectance in the red band and lower reflectance in the near infrared band than the ETM+ sensor. This results in the ASTER sensor producing lower spectral vegetation index measurements, for the same target, than ETM+. The relative spectral response function differences in the red and near infrared bands between the two sensors are believed to be the main factor contributing to their differences in vegetation index measurements, because the red and near infrared relative spectral response features of the ASTER sensor overlap the vegetation "red edge" spectral region. The obtained conversion models have high accuracy with a RMSE less than 0.04 for both sensors' inter-conversion between corresponding vegetation indices.

Vegetation Changes in the Permafrost Regions of the Qinghai-Tibetan Plateau from 1982-2012: Different Responses Related to Geographical Locations and Vegetation Types in High-Altitude Areas.

PubMed

Wang, Zhiwei; Wang, Qian; Wu, Xiaodong; Zhao, Lin; Yue, Guangyang; Nan, Zhuotong; Wang, Puchang; Yi, Shuhua; Zou, Defu; Qin, Yu; Wu, Tonghua; Shi, Jianzong

2017-01-01

The Qinghai-Tibetan Plateau (QTP) contains the largest permafrost area in a high-altitude region in the world, and the unique hydrothermal environments of the active layers in this region have an important impact on vegetation growth. Geographical locations present different climatic conditions, and in combination with the permafrost environments, these conditions comprehensively affect the local vegetation activity. Therefore, the responses of vegetation to climate change in the permafrost region of the QTP may be varied differently by geographical location and vegetation condition. In this study, using the latest Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) product based on turning points (TPs), which were calculated using a piecewise linear model, 9 areas within the permafrost region of the QTP were selected to investigate the effect of geographical location and vegetation type on vegetation growth from 1982 to 2012. The following 4 vegetation types were observed in the 9 selected study areas: alpine swamp meadow, alpine meadow, alpine steppe and alpine desert. The research results show that, in these study areas, TPs mainly appeared in 2000 and 2001, and almost 55.1% and 35.0% of the TPs were located in 2000 and 2001. The global standardized precipitation evapotranspiration index (SPEI) and 7 meteorological variables were selected to analyze their correlations with NDVI. We found that the main correlative variables to vegetation productivity in study areas from 1982 to 2012 were precipitation, surface downward long-wave radiation and temperature. Furthermore, NDVI changes exhibited by different vegetation types within the same study area followed similar trends. The results show that regional effects rather than vegetation type had a larger impact on changes in vegetation growth in the permafrost regions of the QTP, indicating that climatic factors had a larger impact in the permafrost regions than the

Vegetation Changes in the Permafrost Regions of the Qinghai-Tibetan Plateau from 1982-2012: Different Responses Related to Geographical Locations and Vegetation Types in High-Altitude Areas

PubMed Central

Wu, Xiaodong; Zhao, Lin; Yue, Guangyang; Nan, Zhuotong; Wang, Puchang; Yi, Shuhua; Zou, Defu; Qin, Yu; Wu, Tonghua; Shi, Jianzong

2017-01-01

The Qinghai-Tibetan Plateau (QTP) contains the largest permafrost area in a high-altitude region in the world, and the unique hydrothermal environments of the active layers in this region have an important impact on vegetation growth. Geographical locations present different climatic conditions, and in combination with the permafrost environments, these conditions comprehensively affect the local vegetation activity. Therefore, the responses of vegetation to climate change in the permafrost region of the QTP may be varied differently by geographical location and vegetation condition. In this study, using the latest Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) product based on turning points (TPs), which were calculated using a piecewise linear model, 9 areas within the permafrost region of the QTP were selected to investigate the effect of geographical location and vegetation type on vegetation growth from 1982 to 2012. The following 4 vegetation types were observed in the 9 selected study areas: alpine swamp meadow, alpine meadow, alpine steppe and alpine desert. The research results show that, in these study areas, TPs mainly appeared in 2000 and 2001, and almost 55.1% and 35.0% of the TPs were located in 2000 and 2001. The global standardized precipitation evapotranspiration index (SPEI) and 7 meteorological variables were selected to analyze their correlations with NDVI. We found that the main correlative variables to vegetation productivity in study areas from 1982 to 2012 were precipitation, surface downward long-wave radiation and temperature. Furthermore, NDVI changes exhibited by different vegetation types within the same study area followed similar trends. The results show that regional effects rather than vegetation type had a larger impact on changes in vegetation growth in the permafrost regions of the QTP, indicating that climatic factors had a larger impact in the permafrost regions than the

Vegetation Cover based on Eagleson's Ecohydrological Optimality in Northeast China Transect (NECT)

NASA Astrophysics Data System (ADS)

Cong, Z.; Mo, K.; Qinshu, L.; Zhang, L.

2016-12-01

Vegetation is considered as the indicator of climate, thus the study of vegetation growth and distribution is of great importance to cognize the ecosystem construction and functions. Vegetation cover is used as an important index to describe vegetation conditions. In Eagleson's ecohydrological optimality, the theoretical optimal vegetation cover M* can be estimated by solving water balance equations. In this study, the theory is applied in the Northeast China Transect (NECT), one of International Geosphere-Biosphere Programs (IGBP) terrestrial transects. The spatial distribution of actual vegetation cover M, which is derived from Normalized Vegetation Index (NDVI) from Moderate-resolution Imaging Spectroradiometer (MODIS), shows that there is a significant gradient ranging from 1 in the east forests to 0 in the west desert. The result indicates that the theoretical M* fits the actual M well (for forest, M* = 0.822 while M = 0.826; for grassland, M* = 0.353 while M = 0.352; the correlation coefficient between M and M* is 0.81). The reasonable calculated proportion of water balance components further demonstrates the applicability of the ecohydrological optimality theory. M* increases with the increase of LAI, leaf angle, stem fraction and temperature, and decreases with the increase of precipitation amount. This method offers the possibility to analyze the impacts of climate change to vegetation cover quantitatively, thus providing advices for eco-restoration projects.

Seasonal vegetation differences from ERTS imagery

NASA Technical Reports Server (NTRS)

Ashley, M. D.; Rea, J.

1975-01-01

Knowledge of the times when crop and forest vegetation experience seasonally related changes in development is important in understanding growth and yield relationships. This article describes how densitometry of earth resources technology satellite (ERTS-1) multispectral scanner (MSS) imagery can be used to identify such phenological events. Adjustments for instrument calibration, aperture size, gray-scale differences between overpasses, and normalization of changing solar elevation are considered in detail. Seasonal vegetation differences can be identified by densitometry of band 5 (0.6-0.7 microns) and band 7 (0.8-1.1 microns) MSS imagery. Band-to-band ratios of the densities depicted the changes more graphically than the individual band readings.

Prevalent vegetation growth enhancement in urban environment.

PubMed

Zhao, Shuqing; Liu, Shuguang; Zhou, Decheng

2016-05-31

Urbanization, a dominant global demographic trend, leads to various changes in environments (e.g., atmospheric CO2 increase, urban heat island). Cities experience global change decades ahead of other systems so that they are natural laboratories for studying responses of other nonurban biological ecosystems to future global change. However, the impacts of urbanization on vegetation growth are not well understood. Here, we developed a general conceptual framework for quantifying the impacts of urbanization on vegetation growth and applied it in 32 Chinese cities. Results indicated that vegetation growth, as surrogated by satellite-observed vegetation index, decreased along urban intensity across all cities. At the same time, vegetation growth was enhanced at 85% of the places along the intensity gradient, and the relative enhancement increased with urban intensity. This growth enhancement offset about 40% of direct loss of vegetation productivity caused by replacing productive vegetated surfaces with nonproductive impervious surfaces. In light of current and previous field studies, we conclude that vegetation growth enhancement is prevalent in urban settings. Urban environments do provide ideal natural laboratories to observe biological responses to environmental changes that are difficult to mimic in manipulative experiments. However, one should be careful in extrapolating the finding to nonurban environments because urban vegetation is usually intensively managed, and attribution of the responses to diverse driving forces will be challenging but must be pursued.

Prevalent vegetation growth enhancement in urban environment

PubMed Central

Zhao, Shuqing; Liu, Shuguang; Zhou, Decheng

2016-01-01

Urbanization, a dominant global demographic trend, leads to various changes in environments (e.g., atmospheric CO2 increase, urban heat island). Cities experience global change decades ahead of other systems so that they are natural laboratories for studying responses of other nonurban biological ecosystems to future global change. However, the impacts of urbanization on vegetation growth are not well understood. Here, we developed a general conceptual framework for quantifying the impacts of urbanization on vegetation growth and applied it in 32 Chinese cities. Results indicated that vegetation growth, as surrogated by satellite-observed vegetation index, decreased along urban intensity across all cities. At the same time, vegetation growth was enhanced at 85% of the places along the intensity gradient, and the relative enhancement increased with urban intensity. This growth enhancement offset about 40% of direct loss of vegetation productivity caused by replacing productive vegetated surfaces with nonproductive impervious surfaces. In light of current and previous field studies, we conclude that vegetation growth enhancement is prevalent in urban settings. Urban environments do provide ideal natural laboratories to observe biological responses to environmental changes that are difficult to mimic in manipulative experiments. However, one should be careful in extrapolating the finding to nonurban environments because urban vegetation is usually intensively managed, and attribution of the responses to diverse driving forces will be challenging but must be pursued. PMID:27185955

Index to Estimate the Efficiency of an Ophthalmic Practice.

PubMed

Chen, Andrew; Kim, Eun Ah; Aigner, Dennis J; Afifi, Abdelmonem; Caprioli, Joseph

2015-08-01

A metric of efficiency, a function of the ratio of quality to cost per patient, will allow the health care system to better measure the impact of specific reforms and compare the effectiveness of each. To develop and evaluate an efficiency index that estimates the performance of an ophthalmologist's practice as a function of cost, number of patients receiving care, and quality of care. Retrospective review of 36 ophthalmology subspecialty practices from October 2011 to September 2012 at a university-based eye institute. The efficiency index (E) was defined as a function of adjusted number of patients (N(a)), total practice adjusted costs (C(a)), and a preliminary measure of quality (Q). Constant b limits E between 0 and 1. Constant y modifies the influence of Q on E. Relative value units and geographic cost indices determined by the Centers for Medicare and Medicaid for 2012 were used to calculate adjusted costs. The efficiency index is expressed as the following: E = b(N(a)/C(a))Q(y). Independent, masked auditors reviewed 20 random patient medical records for each practice and filled out 3 questionnaires to obtain a process-based quality measure. The adjusted number of patients, adjusted costs, quality, and efficiency index were calculated for 36 ophthalmology subspecialties. The median adjusted number of patients was 5516 (interquartile range, 3450-11,863), the median adjusted cost was 1.34 (interquartile range, 0.99-1.96), the median quality was 0.89 (interquartile range, 0.79-0.91), and the median value of the efficiency index was 0.26 (interquartile range, 0.08-0.42). The described efficiency index is a metric that provides a broad overview of performance for a variety of ophthalmology specialties as estimated by resources used and a preliminary measure of quality of care provided. The results of the efficiency index could be used in future investigations to determine its sensitivity to detect the impact of interventions on a practice such as training

On Budyko curve as a consequence of climate-soil-vegetation equilibrium hypothesis

NASA Astrophysics Data System (ADS)

Pande, S.

2012-04-01

A hypothesis that Budyko curve is a consequence of stable equilibriums of climate-soil-vegetation co-evolution is tested at biome scale. We assume that i) distribution of vegetation, soil and climate within a biome is a distribution of equilibriums of similar soil-vegetation dynamics and that this dynamics is different across different biomes and ii) soil and vegetation are in dynamic equilibrium with climate while in static equilibrium with each other. In order to test the hypothesis, a two stage regression is considered using MOPEX/Hydrologic Synthesis Project dataset for basins in eastern United States. In the first stage, multivariate regression (Seemingly Unrelated Regression) is performed for each biome with soil (estimated porosity and slope of soil water retention curve) and vegetation characteristics (5-week NDVI gradient) as dependent variables and aridity index, vegetation and soil characteristics as independent variables for respective dependent variables. The regression residuals of the first stage along with aridity index then serve as second stage independent variables while actual vaporization to precipitation ratio (vapor index) serving as dependent variable. Insignificance, if revealed, of a first stage parameter allows us to reject the role of corresponding soil or vegetation characteristics in the co-evolution hypothesis. Meanwhile the significance of second stage regression parameter corresponding to a first stage residual allow us to reject the hypothesis that Budyko curve is a locus "solely" of climate-soil-vegetation co-evolution equilibrium points. Results suggest lack of evidence for soil-vegetation co-evolution in Prairies and Mixed/SouthEast Forests (unlike in Deciduous Forests) though climate plays a dominant role in explaining within biome soil and vegetation characteristics across all the biomes. Preliminary results indicate absence of effects beyond climate-soil-vegetation co-evolution in explaining the ratio of annual total minimum

Observational intensity bias associated with illness adjustment: cross sectional analysis of insurance claims

PubMed Central

Staiger, Douglas O; Sharp, Sandra M; Gottlieb, Daniel J; Bevan, Gwyn; McPherson, Klim; Welch, H Gilbert

2013-01-01

Objective To determine the bias associated with frequency of visits by physicians in adjusting for illness, using diagnoses recorded in administrative databases. Setting Claims data from the US Medicare program for services provided in 2007 among 306 US hospital referral regions. Design Cross sectional analysis. Participants 20% sample of fee for service Medicare beneficiaries residing in the United States in 2007 (n=5 153 877). Main outcome measures The effect of illness adjustment on regional mortality and spending rates using standard and visit corrected illness methods for adjustment. The standard method adjusts using comorbidity measures based on diagnoses listed in administrative databases; the modified method corrects these measures for the frequency of visits by physicians. Three conventions for measuring comorbidity are used: the Charlson comorbidity index, Iezzoni chronic conditions, and hierarchical condition categories risk scores. Results The visit corrected Charlson comorbidity index explained more of the variation in age, sex, and race mortality across the 306 hospital referral regions than did the standard index (R2=0.21 v 0.11, P<0.001) and, compared with sex and race adjusted mortality, reduced regional variation, whereas adjustment using the standard Charlson comorbidity index increased it. Although visit corrected and age, sex, and race adjusted mortality rates were similar in hospital referral regions with the highest and lowest fifths of visits, adjustment using the standard index resulted in a rate that was 18% lower in the highest fifth (46.4 v 56.3 deaths per 1000, P<0.001). Age, sex, and race adjusted spending as well as visit corrected spending was more than 30% greater in the highest fifth of visits than in the lowest fifth, but only 12% greater after adjustment using the standard index. Similar results were obtained using the Iezzoni and the hierarchical condition categories conventions for measuring comorbidity. Conclusion The

North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer. [North America

NASA Technical Reports Server (NTRS)

Goward, S. N.; Tucker, C. J.; Dye, D. G.

1985-01-01

Spectral vegetation index measurements derived from remotely sensed observations show great promise as a means to improve knowledge of land vegetation patterns. The daily, global observations acquired by the advanced very high resolution radiometer, a sensor on the current series of U.S. National Oceanic and Atmospheric Administration meteorological satellites, may be particularly well suited for global studies of vegetation. Preliminary results from analysis of North American observations, extending from April to November 1982, show that the vegetation index patterns observed correspond to the known seasonality of North American natural and cultivated vegetation. Integration of the observations over the growing season produced measurements that are related to net primary productivity patterns of the major North American natural vegetation formations. Regions of intense cultivation were observed as anomalous areas in the integrated growing season measurements. Significant information on seasonality, annual extent and interannual variability of vegetation photosynthetic activity at continental and global scales can be derived from these satellite observations.

Soil, water, and vegetation conditions in south Texas

NASA Technical Reports Server (NTRS)

Wiegand, C. L.; Gausman, H. W.; Leamer, R. W.; Richardson, A. J.; Everitt, J. H.; Gerbermann, A. H. (Principal Investigator)

1977-01-01

The author has identified the following significant results. The best wavelengths in the 0.4 to 2.5 micron interval were determined for detecting lead toxicity and ozone damage, distinguishing succulent from woody species, and detecting silverleaf sunflower. A perpendicular vegetation index, a measure of the distance from the soil background line, in MSS 5 and MSS 7 data space, of pixels containing vegetation was developed and tested as an indicator of vegetation development and crop vigor. A table lookup procedure was devised that permits rapid identification of soil background and green biomass or phenological development in LANDSAT scenes without the need for training data.

Objective and Subjective Attractiveness and Early Adolescent Adjustment.

ERIC Educational Resources Information Center

Jovanovic, Jasna; And Others

1989-01-01

Used data from Pennsylvania Early Adolescent Transitions Study to assess how objective physical attractiveness (PA), indexed by appraisals from others, and subjective PA, indexed by self-appraisals, related to each other and to early adolescent adjustment. Findings indicated low relationship between objective and subjective PA; only subjective PA…

Soil Erosion Risk Map based on irregularity of the vegetative activity

NASA Astrophysics Data System (ADS)

Saa-Requejo, Antonio; Tarquis, Ana Maria; Martín-Sotoca, Juan J.; Valencia, Jose L.; Gobin, Anne; Rodriguez-Sinobas, Leonor

2016-04-01

Because of the difficulties to build on both daily rainfall and base shorter time, we explored the possibilities of building indexes based on land cover, which also provide us the opportunity to evaluate their evolution over time. We consider the Fournier index (Fournier, 1960) which is used to assess the rainfall erosivity based on monthly rainfall, alternatively to use of the rainfall intensity in time bases under one hour (eg., van der Knijff et al., 1999; Shamshad et al, 2008). This index can also be interpreted as an index of irregularity and representing a ratio between maximum monthly precipitation and annual rainfall. We propose to calculate this irregularity in terms of irregularity of the vegetative activity. This activity is related to precipitation, but also with the availability of water in the soil reservoir and land use. Therefore, we propose a kind of Fournier index on the effective use of water, which is also closely related to variations in infiltration. Higher is the presence of vegetation higher is the effective use of water. For this "modified Fourier index" we used the NDVI (Normalized Difference Vegetation Index) as index of available vegetative activity, which is widely reported in the literature (Jensen, 2000). Initial calculations have been done with MODIS 500 x 500 m satellite data. The selected area was Cega-Eresma-Adaja subbasin during the period from 2009 to 2012. We selected 8 days composite images product. The calculation of the valid values to eliminate areas with clouds or snow is performed according to the criteria of Martinez Sotoca (2014), ie with a Saturation (based on HSL color model) greater or equal to 0.15. Then, an average of these values was estimated to represent each month of the year. The results are very interesting when we compare Modified Fournier Index on NDVIs with the map of potential soil loss. We have found surprisingly similar patterns and practical equivalence between several classes. Therefore, the Modified

Interannual Variations and Trends in Global Land Surface Phenology Derived from Enhanced Vegetation Index During 1982-2010

NASA Technical Reports Server (NTRS)

Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

2014-01-01

Land swiace phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstmted to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This srudy detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examIned across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and OSL varied considerably during 1982-2010 across the globe. Generally, the interarmual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative OSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

2014-05-01

Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

Assessment of soil-vegetation cover condition in river basins applying remote sensing data

NASA Astrophysics Data System (ADS)

Mishchenko, Natalia; Petrosian, Janna; Shirkin, Leonid; Repkin, Roman

2017-04-01

Constant observation of vegetation and soil cover is one of the key issues of river basins ecologic monitoring. Lately remotely determining vegetation indices have been used for this purpose alongside with terrestrial data. It is necessary to consider that observation objects have been continuously changing and these changes are comprehensive and depend on temporal and dimensional parameters. Remote sensing data, embracing vast areas and reflecting various interrelations, allow excluding accidental and short-term changes though concentrating on the transformation of the observed river basin ecosystem environmental condition. The research objective is to assess spatial - temporal peculiarities and the dynamics of soil-vegetation condition of the Klyazma basin as whole and minor river basins within the area. Research objects are located in the centre of European Russia. Data used in our research include both statistic and published data, characterizing soil-vegetation cover of the area, space images («Landsat» ETM+ etc.) Research methods. 1. Dynamics analysis NDVI (Normalized difference vegetation index) 2. Remote data have been correlated to terrestrial measurement results of phytomass reserve, phytoproductivity, soil fertility characteristics, crop capacity (http://biodat.ru) 3. For the digital processing of space images software Erdas Imagine has been used, GIS analysis has been carried out applying Arc GIS. NDVI computation for each image pixel helped to map general condition of the Klyazma vegetation cover and to determine geographic ranges without vegetation or with depressed vegetation. For instance high vegetation index geographic range has been defined which corresponded to Vladimir Opolye characterized with the most fertile grey forest soil in the region. Comparative assessment of soil vegetation cover of minor river basins within the Klyazma basin, judging by the terrestrial data, revealed its better condition in the Koloksha basin which is also located

Bacterial community dynamics and product distribution during pH-adjusted fermentation of vegetable wastes.

PubMed

Ye, N-F; Lü, F; Shao, L-M; Godon, J-J; He, P-J

2007-10-01

To estimate the effect of pH on the structures of bacterial community during fermentation of vegetable wastes and to investigate the relationship between bacterial community dynamics and product distribution. The bacterial communities in five batch tests controlled at different pH values [uncontrolled (about pH 4), 5, 6, 7 and 8] were monitored by denaturing gradient gel electrophoresis (DGGE) and single-strand conformation polymorphism (SSCP). The two fingerprinting methods provided consistent results and principal component analysis indicated a close similarity of bacterial community at pH 7 and 8 in addition to those at pH 4-6. This clustering also corresponded to dominant metabolic pathway. Thus, pH 7-8 shifted from alcohol-forming to acid-forming, especially butyric acid, whereas both alcohol-forming and acid-forming dominated at pH 5-6, and at pH 4, fermentation was inhibited. Shannon-weaver index was calculated to analyse the DGGE profiles, which revealed that the bacterial diversities at pH 7 and 8 were the highest while those at pH 5 and 4 (uncontrolled) were the lowest. According to sequencing results of the bands excised from DGGE gels, lactic acid bacteria and Clostridium sp. were predominant at all pH values, but varieties in species were observed as pH changed and time prolonged. The bacterial community during fermentation was materially influenced by pH and the diverse product distribution was related to the shift of different bacterial population. The study reveals that the impact of pH on fermentation product distribution is implemented primarily by changes of bacterial community. It also provides information about the comparison of two fingerprinting methods, DGGE and SSCP.

Monitoring vegetation response to episodic disturbance events by using multitemporal vegetation indices

USGS Publications Warehouse

Steyer, Gregory D.; Couvillion, Brady R.; Barras, John A.

2013-01-01

Normalized Difference Vegetation Index (NDVI) derived from MODerate-resolution Imaging Spectroradiometer (MODIS) satellite imagery and land/water assessments from Landsat Thematic Mapper (TM) imagery were used to quantify the extent and severity of damage and subsequent recovery after Hurricanes Katrina and Rita of 2005 within the vegetation communities of Louisiana's coastal wetlands. Field data on species composition and total live cover were collected from 232 unique plots during multiple time periods to corroborate changes in NDVI values over time. Aprehurricane 5-year baseline time series clearly identified NDVI values by habitat type, suggesting the sensitivity of NDVI to assess and monitor phenological changes in coastal wetland habitats. Monthly data from March 2005 to November 2006 were compared to the baseline average to create a departure from average statistic. Departures suggest that over 33% (4,714 km2) of the prestorm, coastal wetlands experienced a substantial decline in the density and vigor of vegetation by October 2005 (poststorm), mostly in the east and west regions, where landfalls of Hurricanes Katrina and Rita occurred. The percentage of area of persistent vegetation damage due to long-lasting formation of new open water was 91.8% in the east and 81.0% and 29.0% in the central and west regions, respectively. Although below average NDVI values were observed in most marsh communities through November 2006, recovery of vegetation was evident. Results indicated that impacts and recovery from large episodic disturbance events that influence multiple habitat types can be accurately determined using NDVI, especially when integrated with assessments of physical landscape changes and field verifications.

Vegetation study in support of the design and optimization of vegetative soil covers, Sandia National Laboratories, Albuquerque, New Mexico.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peace, Gerald; Goering, Timothy James; Knight, Paul J.

A vegetation study was conducted in Technical Area 3 at Sandia National Laboratories, Albuquerque, New Mexico in 2003 to assist in the design and optimization of vegetative soil covers for hazardous, radioactive, and mixed waste landfills at Sandia National Laboratories/New Mexico and Kirtland Air Force Base. The objective of the study was to obtain site-specific, vegetative input parameters for the one-dimensional code UNSAT-H and to identify suitable, diverse native plant species for use on vegetative soil covers that will persist indefinitely as a climax ecological community with little or no maintenance. The identification and selection of appropriate native plant speciesmore » is critical to the proper design and long-term performance of vegetative soil covers. Major emphasis was placed on the acquisition of representative, site-specific vegetation data. Vegetative input parameters measured in the field during this study include root depth, root length density, and percent bare area. Site-specific leaf area index was not obtained in the area because there was no suitable platform to measure leaf area during the 2003 growing season due to severe drought that has persisted in New Mexico since 1999. Regional LAI data was obtained from two unique desert biomes in New Mexico, Sevilletta Wildlife Refuge and Jornada Research Station.« less

Osmotic adjustment and the growth response of seven vegetable crops following water-deficit stress. [Phaseolus vulgaris L. ; Beta vulgaris L. ; Abelmoschus esculentus; Pisum sativum L. ; Capsicum annuum L. ; Spinacia oleracea L. ; Lycopersicon esculentum Mill

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wullschleger, S.D.; Oosterhuis, D.M.

Growth-chamber studies were conducted to examine the ability of seven vegetable crops- Blue Lake beam (Phaseolus vulgaris L.) Detroit Dark Red beet (Beta vulgaris L.) Burgundy okra (Abelmoschus esculentus) (Moench), Little Marvel pea (Pisum sativum L), California Wonder bell pepper (Capsicum annuum L), New Zealand spinach (Spinacia oleracea L), and Beefsteak tomato (Lycopersicon esculentum Mill.) - to adjust osmotically in response to water-deficit stress. Water stress was imposed by withholding water for 3 days, and the adjustment of leaf and root osmotic potentials upon relief of the stress and rehydration were monitored with thermocouple psychrometers. Despite similar reductions in leafmore » water potential and stomatal conductance among the species studied reductions in lead water potential an stomatal conductance among the species, crop-specific differences were observed in leak and root osmotic adjustment. Leaf osmotic adjustment was observed for bean, pepper, and tomato following water-deficit stress. Root osmotic adjustment was significant in bean, okra, pea and tomato. Furthermore, differences in leaf and root osmotic adjustment were also observed among five tomato cultivars. Leaf osmotic adjustment was not associated with the maintenance of leaf growth following water-deficit stress, since leaf expansion of water-stressed bean and pepper, two species capable of osmotic adjustment, was similar to that of spinach, which exhibited no leaf osmotic adjustment.« less

78 FR 78508 - Quarterly Rail Cost Adjustment Factor

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-26

... Procedures--Productivity Adjustment, 5 I.C.C.2d 434 (1989), aff'd sub nom. Edison Electric Institute v. ICC... quarterly index for a measure of productivity. The provisions of 49 U.S.C. 10708 direct the Surface Transportation Board (Board) to continue to publish both an unadjusted RCAF and a productivity-adjusted RCAF. In...

Monitoring vegetation cover in the postfire in Tavira - São Brás de Alportel (southern Portugal)

NASA Astrophysics Data System (ADS)

Ramos-Simões, Nuno A.; Granja-Martins, Fernando M.; Neto-Paixão, Helena M.; Jordán, Antonio; Zavala, Lorena M.

2014-05-01

1. INTRODUCTION Often, restoration of areas affected by fire faces lack of knowledge of how ecosystems respond to the action of fire. Depending on environmental conditions, structure and diversity of the vegetation or the severity of the fire, burnt systems can provide responses ranging from spontaneous recovery in a relatively short time to onset of severe degradation processes. For this reason, it is necessary to monitor the evolution of post-burned in the fire, in order to plan effective strategies for restoring systems and soil erosion control. In order to assess soil erosion risk, this research aims to is to analyse the evolution of vegetation cover in a Mediterranean burnt forest soil, using vegetation indexes derived from Landsat-7 (Thematic Mapper sensor-TM) and Landsat-8 (Operation Land Imager sensor, OLI). 2. METHODS This study was carried out in a forest area affected by a wildfire by 18-22 July 2012. The study area is located within the coordinates 37o 9' - 37o 21' N and 7o 40' - 7o 53' W, including part of the municipalities of Tavira and São Brás de Alportel (southern Portugal). The relief in the studied area has an irregular topography. Soils are shallow and develop mainly metamorphic rocks (as slates or quartzite) and igneous rocks, which produce acidic and nutrient-poor soils, poorly developed in depth. The wildfire was one of the most important fires in Portugal during the recent years, and affected more than 24000 ha. Vegetation is dominated by cork oak (Quercus suber) ,holm oaks (Quercus ilex), strawberry tree (Arbutus unedo) and sclerophyllous vegetation (mostly formed by Quercus coccifera and Rosmarinus officinalis). These species are adapted to acidic-poor soils and show a great capability of resprouting and germination after fire. The study area is poorly developed, with cork and timber harvesting and other forest products or tourism as main economic activities. The area shows a highly fragmented urban fabric with the sparse

Evaluation of the photochemical reflectance index in AVIRIS imagery

NASA Technical Reports Server (NTRS)

Gamon, John A.; Roberts, Dar A.; Green, Robert O.

1995-01-01

In this paper, we evaluate the potential for extracting the 'photochemical reflectance index' (PRI; previously called the 'physiological reflectance index') from AVIRIS data. This index, which is derived from narrow-band reflectance at 531 and 570 nm, has proven to be a useful indicator of photosynthetic function at the leaf and canopy scales. At the leaf level, PRI varies with photosynthetic capacity, radiation-use efficiency, and vegetation type (unpublished data). This finding is consistent with the hypothesis that vegetation types exhibiting chronically reduced photosynthesis during periods of stress (e.g. drought-tolerant evergreens) invest proportionally more in photoprotective processes than vegetation with high photosynthetic capacity (e.g. crops or deciduous perennials). Vertical transects in tropical and boreal forest canopies have indicated declines in PRI associated with downregulation of photosynthesis at the canopy tops under sunny, dry midday conditions (unpublished data). This reduced PRI in upper canopy levels provides a further basis for examining this signal with the 'view from above' afforded by aircraft overflights. Although many factors could confound interpretation of a subtle physiological signal at the landscape scale, we conducted a preliminary examination of PRI extracted from existing, AVIRIS imagery of Stanford University's Jasper Ridge Biological Preserve obtained on the June 2nd, 1992, overflight. The goal was to use the hyperspectral capabilities of AVIRIS to evaluate the potential of this index for obtaining useful physiological data at the landscape scale. The expectation based on leaf- and canopy-level studies was that regions containing vegetation of reduced photosynthetic capacity (e.g. chaparral or evergreen woodland) would exhibit lower PRI values than regions of high capacity (e.g. deciduous woodland).

Modeling Vegetation Growth Impact on Groundwater Recharge

NASA Astrophysics Data System (ADS)

Anurag, H.; Ng, G. H. C.; Tipping, R.

2017-12-01

Vegetation growth is affected by variability in climate and land-cover / land-use over a range of temporal and spatial scales. Vegetation also modifies water budget through interception and evapotranspiration and thus has a significant impact on groundwater recharge. Most groundwater recharge assessments represent vegetation using specified, static parameter, such as for leaf-area-index, but this neglects the effect of vegetation dynamics on recharge estimates. Our study addresses this gap by including vegetation growth in model simulations of recharge. We use NCAR's Community Land Model v4.5 with its BGC module (BGC is the new CLM4.5 biogeochemistry). It integrates prognostic vegetation growth with land-surface and subsurface hydrological processes and can thus capture the effect of vegetation on groundwater. A challenge, however, is the need to resolve uncertainties in model inputs ranging from vegetation growth parameters all the way down to the water table. We have compiled diverse data spanning meteorological inputs to subsurface geology and use these to implement ensemble model simulations to evaluate the possible effects of dynamic vegetation growth (versus specified, static vegetation parameterizations) on estimating groundwater recharge. We present preliminary results for select data-intensive test locations throughout the state of Minnesota (USA), which has a sharp east-west precipitation gradient that makes it an apt testbed for examining ecohydrologic relationships across different temperate climatic settings and ecosystems. Using the ensemble simulations, we examine the effect of seasonal to interannual variability of vegetation growth on recharge and water table depths, which has implications for predicting the combined impact of climate, vegetation, and geology on groundwater resources. Future work will include distributed model simulations over the entire state, as well as conditioning uncertain vegetation and subsurface parameters on remote sensing

[Evaluation of the adjusted amino acid score by digestibility for estimating the protein quality and protein available in food and diets].

PubMed

Pak, N; Vera, G; Araya, H

1985-03-01

The purpose of the present study was to evaluate the amino acid score adjusted by digestibility to estimate protein quality and utilizable protein in foods and diets, considering net protein utilization (NPU) as a biological reference method. Ten foods of vegetable origin and ten of animal origin, as well as eight mixtures of foods of vegetable and animal origin were studied. When all the foods were considered, a positive (r = 0.83) and highly significant correlation (p less than 0.001) between NPU and the amino acid score adjusted by digestibility was found. When the foods were separated according to their origin, this correlation was positive only for the foods of vegetable origin (r = 0.93) and statistically significant (p less than 0.001). Also, only in those foods were similar values found between NPU and amino acid score adjusted by digestibility, as well as in utilizable protein estimated considering both methods. Caution is required to interpret protein quality and utilizable protein values of foods of animal origin and mixtures of foods of vegetable and animal origin when the amino acid score method adjusted by digestibility, or NPU, are utilized.

a Framework of Change Detection Based on Combined Morphologica Features and Multi-Index Classification

NASA Astrophysics Data System (ADS)

Li, S.; Zhang, S.; Yang, D.

2017-09-01

Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

Advances in Remote Sensing for Vegetation Dynamics and Agricultural Management

NASA Technical Reports Server (NTRS)

Tucker, Compton; Puma, Michael

2015-01-01

Spaceborne remote sensing has led to great advances in the global monitoring of vegetation. For example, the NASA Global Inventory Modeling and Mapping Studies (GIMMS) group has developed widely used datasets from the Advanced Very High Resolution Radiometer (AVHRR) sensors as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) map imagery and normalized difference vegetation index datasets. These data are valuable for analyzing vegetation trends and variability at the regional and global levels. Numerous studies have investigated such trends and variability for both natural vegetation (e.g., re-greening of the Sahel, shifts in the Eurasian boreal forest, Amazonian drought sensitivity) and crops (e.g., impacts of extremes on agricultural production). Here, a critical overview is presented on recent developments and opportunities in the use of remote sensing for monitoring vegetation and crop dynamics.

Consistency of vegetation index seasonality across the Amazon rainforest

NASA Astrophysics Data System (ADS)

Maeda, Eduardo Eiji; Moura, Yhasmin Mendes; Wagner, Fabien; Hilker, Thomas; Lyapustin, Alexei I.; Wang, Yujie; Chave, Jérôme; Mõttus, Matti; Aragão, Luiz E. O. C.; Shimabukuro, Yosio

2016-10-01

Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

Consistency of Vegetation Index Seasonality Across the Amazon Rainforest

NASA Technical Reports Server (NTRS)

Maeda, Eduardo Eiji; Moura, Yhasmin Mendes; Wagner, Fabien; Hilker, Thomas; Lyapustin, Alexei I.; Wang, Yujie; Chave, Jerome; Mottus, Matti; Aragao, Luiz E.O.C.; Shimabukuro, Yosio

2016-01-01

Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening?

Treesearch

Yulong Zhang; Conghe Song; Lawrence E. Band; Ge Sun; Junxiang Li

2017-01-01

Accurately monitoring global vegetation dynamics with modern remote sensing is critical for understanding the functions and processes of the biosphere and its interactions with the planetary climate. The MODerate resolution Imaging Spectroradiometer (MODIS) vegetation index (VI) product has been a primary data source for this purpose. To date, theMODIS teamhad released...

The Dutch Healthy Diet index (DHD-index): an instrument to measure adherence to the Dutch Guidelines for a Healthy Diet.

PubMed

van Lee, Linde; Geelen, Anouk; van Huysduynen, Eveline J C Hooft; de Vries, Jeanne H M; van't Veer, Pieter; Feskens, Edith J M

2012-07-20

The objective was to develop an index based on the Dutch Guidelines for a healthy Diet of 2006 that reflects dietary quality and to apply it to the Dutch National Food Consumption Survey (DNFCS) to examine the associations with micronutrient intakes. A total of 749 men and women, aged 19-30 years, contributed two 24-hour recalls and additional questionnaires in the DNFCS of 2003. The Dutch Healthy Diet index (DHD-index) includes ten components representing the ten Dutch Guidelines for a Healthy Diet. Per component the score ranges between zero and ten, resulting in a total score between zero (no adherence) and 100 (complete adherence). The mean ± SD of the DHD-index was 60.4 ± 11.5 for women and 57.8 ± 10.8 for men (P for difference = 0.002). Each component score increased across the sex-specific quintiles of the DHD-index. An inverse association was observed between the sex-specific quintiles of the DHD-index and total energy intake. Calcium, riboflavin, and vitamin E intake decreased with increasing DHD-index, an inverse association which disappeared after energy adjustment. Vitamin C showed a positive association across quintiles, also when adjusted for energy. For folate, iron, magnesium, potassium, thiamin, and vitamin B6 a positive association emerged after adjustment for energy. The DHD-index is capable of ranking participants according to their adherence to the Dutch Guidelines for a Healthy Diet by reflecting variation in nine out of ten components that constitute the index when based on two 24-hour recalls. Furthermore, the index showed to be a good measure of nutrient density of diets.

Metric Similarity in Vegetation-Based Wetland Assessment Methods

EPA Science Inventory

Wetland vegetation is a recognized indicator group for wetland assessments, but until recently few published protocols used plant-based indicators. To examine the proliferation of such protocols since 1999, this report reviewed 20 published index of biotic integrity (IBI) type p...

Improved biobased lubricants from chemically modified vegetable oils

USDA-ARS?s Scientific Manuscript database

Vegetable oils possess a number of desirable properties for lubricant application such as excellent boundary properties, high viscosity index, low volatility, low traction coefficient, renewability, and biodegradability. Unfortunately, they also have a number of weaknesses that make them less desira...

A population health approach to reducing observational intensity bias in health risk adjustment: cross sectional analysis of insurance claims

PubMed Central

Sharp, Sandra M; Bevan, Gwyn; Skinner, Jonathan S; Gottlieb, Daniel J

2014-01-01

Objective To compare the performance of two new approaches to risk adjustment that are free of the influence of observational intensity with methods that depend on diagnoses listed in administrative databases. Setting Administrative data from the US Medicare program for services provided in 2007 among 306 US hospital referral regions. Design Cross sectional analysis. Participants 20% sample of fee for service Medicare beneficiaries residing in one of 306 hospital referral regions in the United States in 2007 (n=5 153 877). Main outcome measures The effect of health risk adjustment on age, sex, and race adjusted mortality and spending rates among hospital referral regions using four indices: the standard Centers for Medicare and Medicaid Services—Hierarchical Condition Categories (HCC) index used by the US Medicare program (calculated from diagnoses listed in Medicare’s administrative database); a visit corrected HCC index (to reduce the effects of observational intensity on frequency of diagnoses); a poverty index (based on US census); and a population health index (calculated using data on incidence of hip fractures and strokes, and responses from a population based annual survey of health from the Centers for Disease Control and Prevention). Results Estimated variation in age, sex, and race adjusted mortality rates across hospital referral regions was reduced using the indices based on population health, poverty, and visit corrected HCC, but increased using the standard HCC index. Most of the residual variation in age, sex, and race adjusted mortality was explained (in terms of weighted R2) by the population health index: R2=0.65. The other indices explained less: R2=0.20 for the visit corrected HCC index; 0.19 for the poverty index, and 0.02 for the standard HCC index. The residual variation in age, sex, race, and price adjusted spending per capita across the 306 hospital referral regions explained by the indices (in terms of weighted R2) were 0.50 for

A population health approach to reducing observational intensity bias in health risk adjustment: cross sectional analysis of insurance claims.

PubMed

Wennberg, David E; Sharp, Sandra M; Bevan, Gwyn; Skinner, Jonathan S; Gottlieb, Daniel J; Wennberg, John E

2014-04-10

To compare the performance of two new approaches to risk adjustment that are free of the influence of observational intensity with methods that depend on diagnoses listed in administrative databases. Administrative data from the US Medicare program for services provided in 2007 among 306 US hospital referral regions. Cross sectional analysis. 20% sample of fee for service Medicare beneficiaries residing in one of 306 hospital referral regions in the United States in 2007 (n = 5,153,877). The effect of health risk adjustment on age, sex, and race adjusted mortality and spending rates among hospital referral regions using four indices: the standard Centers for Medicare and Medicaid Services--Hierarchical Condition Categories (HCC) index used by the US Medicare program (calculated from diagnoses listed in Medicare's administrative database); a visit corrected HCC index (to reduce the effects of observational intensity on frequency of diagnoses); a poverty index (based on US census); and a population health index (calculated using data on incidence of hip fractures and strokes, and responses from a population based annual survey of health from the Centers for Disease Control and Prevention). Estimated variation in age, sex, and race adjusted mortality rates across hospital referral regions was reduced using the indices based on population health, poverty, and visit corrected HCC, but increased using the standard HCC index. Most of the residual variation in age, sex, and race adjusted mortality was explained (in terms of weighted R2) by the population health index: R2=0.65. The other indices explained less: R2=0.20 for the visit corrected HCC index; 0.19 for the poverty index, and 0.02 for the standard HCC index. The residual variation in age, sex, race, and price adjusted spending per capita across the 306 hospital referral regions explained by the indices (in terms of weighted R2) were 0.50 for the standard HCC index, 0.21 for the population health index, 0.12 for the

The potential of climate change adjustment in crops: A synthesis

USDA-ARS?s Scientific Manuscript database

This chapter covers a study on various field crops like cereals, legumes, oil seeds, vegetables, cash crops, underutilized crops, and energy crops and their genetic adjustment to changing climates. More than 30 major field crops have been covered in different chapters of this book, which highlight h...

An enhanced TIMESAT algorithm for estimating vegetation phenology metrics from MODIS data

USGS Publications Warehouse

Tan, B.; Morisette, J.T.; Wolfe, R.E.; Gao, F.; Ederer, G.A.; Nightingale, J.; Pedelty, J.A.

2011-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates. ?? 2010 IEEE.

Seasonal Biophysical Dynamics of the Amazon from Space Using MODIS Vegetation Indices

NASA Astrophysics Data System (ADS)

Huete, A. R.; Didan, K.; Ratana, P.; Ferreira, L.

2002-12-01

We utilized the Terra- Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Index (VI) products to analyze the seasonal and spatial patterns of photosynthetic vegetation activity over the Amazon Basin and surrounding regions of Brazil. The seasonal patterns of vegetation activity were studied along two, eco-climatic transects extending from (1) the cerrado region (Brasilia National Park) to the seasonal tropical forest (Tapajos National Forest) and (2) the caatinga biome to the seasonal and per-humid tropical forests. In addition to the climatic transects, we also investigated the seasonal dynamics of altered, land conversion areas associated with pastures and clearcutting land use activities. Both the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) at 250-m, 500-m, and 1-km were used to extract seasonal profile curves. The quality assurance (QA) information of the output products was used in noise removal and data filtering prior to the generation of the seasonal profiles. Histogram analyses were also performed at coarse (biome) scale and fine, site intensive (flux towers) scale. The seasonal patterns of the cerrado and caatinga were very pronounced with distinct dry and wet seasonal trends. We observed decreasing dry-wet seasonal patterns in the transitional areas near Araguaia National Park. In contrast, the seasonal behavior of the tropical forests were much harder to assess, but indicated slight seasonal trends that ran counter to rainfall activity. This may be attributed to new leaf growth in the dry season. We further found MODIS VI seasonal patterns to vary significantly in land converted and land degraded areas.

An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

NASA Technical Reports Server (NTRS)

Tan, Bin; Morisette, Jeffrey T.; Wolfe, Robert E.; Gao, Feng; Ederer, Gregory A.; Nightingale, Joanne; Pedelty, Jeffrey A.

2012-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

Monitoring vegetation response to episodic disturbance events by using multi-temporal vegetation indices

USGS Publications Warehouse

Steyer, Gregory D.; Couvillion, Brady R.; Barras, John A.

2013-01-01

Normalized Difference Vegetation Index (NDVI) derived from MODerate-resolution Imaging Spectroradiometer (MODIS) satellite imagery and land/water assessments from Landsat Thematic Mapper (TM) imagery were used to quantify the extent and severity of damage and subsequent recovery after Hurricanes Katrina and Rita of 2005 within the vegetation communities of Louisiana's coastal wetlands. Field data on species composition and total live cover were collected from 232 unique plots during multiple time periods to corroborate changes in NDVI values over time. Aprehurricane 5-year baseline time series clearly identified NDVI values by habitat type, suggesting the sensitivity of NDVI to assess and monitor phenological changes in coastal wetland habitats. Monthly data from March 2005 to November 2006 were compared to the baseline average to create a departure from average statistic. Departures suggest that over 33% (4,714 km2) of the prestorm, coastal wetlands experienced a substantial decline in the density and vigor of vegetation by October 2005 (poststorm), mostly in the east and west regions, where landfalls of Hurricanes Katrina and Rita occurred. The percentage of area of persistent vegetation damage due to long-lasting formation of new open water was 91.8% in the east and 81.0% and 29.0% in the central and west regions, respectively. Although below average NDVI values were observed in most marsh communities through November 2006, recovery of vegetation was evident. Results indicated that impacts and recovery from large episodic disturbance events that influence multiple habitat types can be accurately determined using NDVI, especially when integrated with assessments of physical landscape changes and field verifications.

Point-of-purchase health information encourages customers to purchase vegetables: objective analysis by using a point-of-sales system.

PubMed

Ogawa, Yoshiko; Tanabe, Naohito; Honda, Akiko; Azuma, Tomoko; Seki, Nao; Suzuki, Tsubasa; Suzuki, Hiroshi

2011-07-01

Point-of-purchase (POP) information at food stores could help promote healthy dietary habits. However, it has been difficult to evaluate the effects of such intervention on customers' behavior. We objectively evaluated the usefulness of POP health information for vegetables in the modification of customers' purchasing behavior by using the database of a point-of-sales (POS) system. Two supermarket stores belonging to the same chain were assigned as the intervention store (store I) and control store (store C). POP health information for vegetables was presented in store I for 60 days. The percent increase in daily sales of vegetables over the sales on the same date of the previous year was compared between the stores by using the database of the POS system, adjusting for the change in monthly visitors from the previous year (adjusted ∆sales). The adjusted ∆sales significantly increased during the intervention period (Spearman's ρ = 0.258, P for trend = 0.006) at store I but did not increase at store C (ρ = -0.037, P for trend = 0.728). The growth of the mean adjusted ∆sales of total vegetables from 30 days before the intervention period through the latter half of the intervention period was estimated to be greater at store I than at store C by 18.7 percentage points (95% confidence interval 1.6-35.9). Health-related POP information for vegetables in supermarkets can encourage customers to purchase and, probably, consume vegetables.

Severity of climate change dictates the direction of biophysical feedbacks of vegetation change to Arctic climate

NASA Astrophysics Data System (ADS)

Zhang, Wenxin; Jansson, Christer; Miller, Paul; Smith, Ben; Samuelsson, Patrick

2014-05-01

Vegetation-climate feedbacks induced by vegetation dynamics under climate change alter biophysical properties of the land surface that regulate energy and water exchange with the atmosphere. Simulations with Earth System Models applied at global scale suggest that the current warming in the Arctic has been amplified, with large contributions from positive feedbacks, dominated by the effect of reduced surface albedo as an increased distribution, cover and taller stature of trees and shrubs mask underlying snow, darkening the surface. However, these models generally employ simplified representation of vegetation dynamics and structure and a coarse grid resolution, overlooking local or regional scale details determined by diverse vegetation composition and landscape heterogeneity. In this study, we perform simulations using an advanced regional coupled vegetation-climate model (RCA-GUESS) applied at high resolution (0.44×0.44° ) over the Arctic Coordinated Regional Climate Downscaling Experiment (CORDEX-Arctic) domain. The climate component (RCA4) is forced with lateral boundary conditions from EC-EARTH CMIP5 simulations for three representative concentration pathways (RCP 2.6, 4.5, 8.5). Vegetation-climate response is simulated by the individual-based dynamic vegetation model (LPJ-GUESS), accounting for phenology, physiology, demography and resource competition of individual-based vegetation, and feeding variations of leaf area index and vegetative cover fraction back to the climate component, thereby adjusting surface properties and surface energy fluxes. The simulated 2m air temperature, precipitation, vegetation distribution and carbon budget for the present period has been evaluated in another paper. The purpose of this study is to elucidate the spatial and temporal characteristics of the biophysical feedbacks arising from vegetation shifts in response to different CO2 concentration pathways and their associated climate change. Our results indicate that the

Characterization of Landsat-7 to Landsat-8 Reflective Wavelength and Normalized Difference Vegetation Index Continuity

NASA Technical Reports Server (NTRS)

Roy, D. P.; Kovalskyy, V.; Zhang, H. K.; Vermote, E. F.; Yan, L.; Kumar, S. S.; Egorov, A.

2016-01-01

At over 40 years, the Landsat satellites provide the longest temporal record of space-based land surface observations, and the successful 2013 launch of the Landsat-8 is continuing this legacy. Ideally, the Landsat data record should be consistent over the Landsat sensor series. The Landsat-8 Operational Land Imager (OLI) has improved calibration, signal to noise characteristics, higher 12-bit radiometric resolution, and spectrally narrower wavebands than the previous Landsat-7 Enhanced Thematic Mapper (ETM+). Reflective wavelength differences between the two Landsat sensors depend also on the surface reflectance and atmospheric state which are difficult to model comprehensively. The orbit and sensing geometries of the Landsat- 8 OLI and Landsat-7 ETM+ provide swath edge overlapping paths sensed only one day apart. The overlap regions are sensed in alternating backscatter and forward scattering orientations so Landsat bi-directional reflectance effects are evident but approximately balanced between the two sensors when large amounts of time series data are considered. Taking advantage of this configuration a total of 59 million 30m corresponding sensor observations extracted from 6,317 Landsat-7 ETM+ and Landsat-8 OLI images acquired over three winter and three summer months for all the conterminous United States (CONUS) are compared. Results considering different stages of cloud and saturation filtering, and filtering to reduce one day surface state differences, demonstrate the importance of appropriate per-pixel data screening. Top of atmosphere (TOA) and atmospherically corrected surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared bands, and derived normalized difference vegetation index (NDVI), are compared and their differences quantified. On average the OLI TOA reflectance is greater than the ETM+ TOA reflectance for all bands, with greatest differences in the near-infrared (NIR) and the shortwave infrared bands

[Simulation of vegetation indices optimizing under retrieval of vegetation biochemical parameters based on PROSPECT + SAIL model].

PubMed

Wu, Ling; Liu, Xiang-Nan; Zhou, Bo-Tian; Liu, Chuan-Hao; Li, Lu-Feng

2012-12-01

This study analyzed the sensitivities of three vegetation biochemical parameters [chlorophyll content (Cab), leaf water content (Cw), and leaf area index (LAI)] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT + SAIL model. The results showed that retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients (R2) between the measured and estimated values of Cab, Cw, and LAI were 90.8%, 95.7%, and 99.7%, and the root mean square errors of Cab, Cw, and LAI were 4.73 microg x cm(-2), 0.001 g x cm(-2), and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT + SAIL model.

Riparian vegetation as an indicator of riparian condition: Detecting departures from historic condition across the North American West.

PubMed

Macfarlane, William W; Gilbert, Jordan T; Jensen, Martha L; Gilbert, Joshua D; Hough-Snee, Nate; McHugh, Peter A; Wheaton, Joseph M; Bennett, Stephen N

2017-11-01

Floodplain riparian ecosystems support unique vegetation communities and high biodiversity relative to terrestrial landscapes. Accordingly, estimating riparian ecosystem health across landscapes is critical for sustainable river management. However, methods that identify local riparian vegetation condition, an effective proxy for riparian health, have not been applied across broad, regional extents. Here we present an index to assess reach-scale (500 m segment) riparian vegetation condition across entire drainage networks within large, physiographically-diverse regions. We estimated riparian vegetation condition for 53,250 km of perennial streams and rivers, 25,685 km in Utah, and 27,565 km in twelve watersheds of the interior Columbia River Basin (CRB), USA. We used nationally available, existing land cover classification derived from 30 m Landsat imagery (LANDFIRE EVT) and a modeled estimate of pre-European settlement land cover (LANDFIRE BpS). The index characterizes riparian vegetation condition as the ratio of existing native riparian vegetation cover to pre-European settlement riparian vegetation cover at a given reach. Roughly 62% of Utah and 48% of CRB watersheds showed significant (>33%) to large (>66%) departure from historic condition. Riparian vegetation change was predominantly caused by human land-use impacts (development and agriculture), or vegetation change (native riparian to invasive or upland vegetation types) that likely resulted from flow and disturbance regime alteration. Through comparisons to ground-based classification results, we estimate the existing vegetation component of the index to be 85% accurate. Our assessments yielded riparian condition maps that will help resource managers better prioritize sites and treatments for reach-scale conservation and restoration activities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Regional assessment of trends in vegetation change dynamics using principal component analysis

NASA Astrophysics Data System (ADS)

Osunmadewa, B. A.; Csaplovics, E.; R. A., Majdaldin; Adeofun, C. O.; Aralova, D.

2016-10-01

Vegetation forms the basis for the existence of animal and human. Due to changes in climate and human perturbation, most of the natural vegetation of the world has undergone some form of transformation both in composition and structure. Increased anthropogenic activities over the last decades had pose serious threat on the natural vegetation in Nigeria, many vegetated areas are either transformed to other land use such as deforestation for agricultural purpose or completely lost due to indiscriminate removal of trees for charcoal, fuelwood and timber production. This study therefore aims at examining the rate of change in vegetation cover, the degree of change and the application of Principal Component Analysis (PCA) in the dry sub-humid region of Nigeria using Normalized Difference Vegetation Index (NDVI) data spanning from 1983-2011. The method used for the analysis is the T-mode orientation approach also known as standardized PCA, while trends are examined using ordinary least square, median trend (Theil-Sen) and monotonic trend. The result of the trend analysis shows both positive and negative trend in vegetation change dynamics over the 29 years period examined. Five components were used for the Principal Component Analysis. The results of the first component explains about 98 % of the total variance of the vegetation (NDVI) while components 2-5 have lower variance percentage (< 1%). Two ancillary land use land cover data of 2000 and 2009 from European Space Agency (ESA) were used to further explain changes observed in the Normalized Difference Vegetation Index. The result of the land use data shows changes in land use pattern which can be attributed to anthropogenic activities such as cutting of trees for charcoal production, fuelwood and agricultural practices. The result of this study shows the ability of remote sensing data for monitoring vegetation change in the dry-sub humid region of Nigeria.

Childhood intermittent and persistent rhinitis prevalence and climate and vegetation: a global ecologic analysis.

PubMed

Fuertes, Elaine; Butland, Barbara K; Ross Anderson, H; Carlsten, Chris; Strachan, David P; Brauer, Michael

2014-10-01

The effect of climate change and its effects on vegetation growth, and consequently on rhinitis, are uncertain. To examine between- and within-country associations of climate measures and the normalized difference vegetation index with intermittent and persistent rhinitis symptoms in a global context. Questionnaire data from 6- to 7-year-olds and 13- to 14-year-olds were collected in phase 3 of the International Study of Asthma and Allergies in Childhood. Associations of intermittent (>1 symptom report but not for 2 consecutive months) and persistent (symptoms for ≥2 consecutive months) rhinitis symptom prevalences with temperature, precipitation, vapor pressure, and the normalized difference vegetation index were assessed in linear mixed-effects regression models adjusted for gross national income and population density. The mean difference in prevalence per 100 children (with 95% confidence intervals [CIs]) per interquartile range increase of exposure is reported. The country-level intermittent symptom prevalence was associated with several country-level climatic measures, including the country-level mean monthly temperature (6.09 °C; 95% CI, 2.06-10.11°C per 10.4 °C), precipitation (3.10 mm; 95% CI, 0.46-5.73 mm; per 67.0 mm), and vapor pressure (6.21 hPa; 95% CI, 2.17-10.24 hPa; per 10.4 hPa) among 13- to 14-year-olds (222 center in 94 countries). The center-level persistent symptom prevalence was positively associated with several center-level climatic measures. Associations with climate were also found for the 6- to 7-year-olds (132 center in 57 countries). Several between- and within-country spatial associations between climatic factors and intermittent and persistent rhinitis symptom prevalences were observed. These results provide suggestive evidence that climate (and future changes in climate) may influence rhinitis symptom prevalence. Copyright © 2014 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

24 CFR 203.49 - Eligibility of adjustable rate mortgages.

Code of Federal Regulations, 2010 CFR

2010-04-01

... corresponding to changes in the interest rate index. (d) Frequency of interest rate changes. (1) The interest...) Interest-rate index. Changes in the interest rate charged on an adjustable rate mortgage must correspond either to changes in the one-year London Interbank Offered Rate (LIBOR) or to changes in the weekly...

Exploring the control of land-atmospheric oscillations over terrestrial vegetation productivity

NASA Astrophysics Data System (ADS)

Depoorter, Mathieu; Green, Julia; Gentine, Pierre; Liu, Yi; van Eck, Christel; Regnier, Pierre; Dorigo, Wouter; Verhoest, Niko; Miralles, Diego

2015-04-01

Vegetation dynamics play an important role in the climate system due to their control on the carbon, energy and water cycles. The spatiotemporal variability of vegetation is regulated by internal climate variability as well as natural and anthropogenic forcing mechanisms, including fires, land use, volcano eruptions or greenhouse gas emissions. Ocean-atmospheric oscillations, affect the fluxes of heat and water over continents, leading to anomalies in radiation, precipitation or temperature at widely separated locations (i.e. teleconnections); an effect of ocean-atmospheric oscillations on terrestrial primary productivity can therefore be expected. While different studies have shown the general importance of internal climate variability for global vegetation dynamics, the control by particular teleconnections over the regional growth and decay of vegetation is still poorly understood. At continental to global scales, satellite remote sensing offers a feasible approach to enhance our understanding of the main drivers of vegetation variability. Traditional studies of the multi-decadal variability of global vegetation have been usually based on the normalized difference vegetation index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR), which extends back to the early '80s. There are, however, some limitations to NDVI observations; arguably the most important of these limitations is that from the plant physiology perspective the index does not have a well-defined meaning, appearing poorly correlated to vegetation productivity. On the other hand, recently developed records from other remotely-sensed properties of vegetation, like fluorescence or microwave vegetation optical depth, have proven a significantly better correspondence to above-ground biomass. To enhance our understanding of the controls of ocean-atmosphere oscillations over vegetation, we propose to explore the link between climate oscillation extremes and net primary productivity

Use of vegetation health data for estimation of aus rice yield in bangladesh.

PubMed

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991-2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8-13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

PubMed Central

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y.; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991–2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March–April (weeks 8–13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost. PMID:22574057

[Correlationships between the coverage of vegetation and the quality of groundwater in the lower reaches of the Tarim River].

PubMed

Chen, Yong-jin; Chen, Ya-ning; Liu, Jia-zhen

2010-03-01

The variations vegetation coverage is the result of conjunct effects of inner and outer energy of the earth, however, the human activity always makes the coverage of vegetation change a lot. Based on the monitoring data of chemistry of groundwater and the coverage of vegetation from 2002 to 2007 in the lower reaches of Tarim River, relations between vegetation coverage and groundwater chemistry were studied. It is found that vegetation coverage at Sector A was more than 80%, and decreased from sector to sector, the coverage of Sector I was less than 10%. At the same sector, samples near to water source owned high coverage index, and samples far away from the river had low coverage index. The variations of pH in groundwater expressed similar regulation to vegetation coverage, that is, Sectors near the water source had higher pH index comparing than those far away. Regression between groundwater quality and vegetation coverage disclosed that the coverage of Populus euphratica climbed up along with increase of pH in groundwater, change of Tamarix ramosissima coverage expressed an opposite trend to the Populus euphratica with the same environmental factors. This phenomenon can interpret spatial distribution of Populus euphratica and Tamarix ramosissima in lower reaches of the Tarim River.

An Analytical Study on an Orthodontic Index: Index of Complexity, Outcome and Need (ICON)

PubMed Central

Torkan, Sepide; Pakshir, Hamid Reza; Fattahi, Hamid Reza; Oshagh, Morteza; Momeni Danaei, Shahla; Salehi, Parisa; Hedayati, Zohreh

2015-01-01

Statement of the Problem The validity of the Index of Complexity, Outcome and Need (ICON) which is an orthodontic index developed and introduced in 2000 should be studied in different ethnic groups. Purpose The aim of this study was to perform an analysis on the ICON and to verify whether this index is valid for assessing both the need and complexity of orthodontic treatment in Iran. Materials and Method Five orthodontists were asked to score pre-treatment diagnostic records of 100 patients with a uniform distribution of different types of malocclusions determined by Dental Health Component of the Index of Treatment Need. A calibrated examiner also assessed the need for orthodontic treatment and complexity of the cases based on the ICON index as well as the Index of Orthodontic Treatment Need (IOTN). 10 days later, 25% of the cases were re-scored by the panel of experts and the calibrated orthodontist. Results The weighted kappa revealed the inter-examiner reliability of the experts to be 0.63 and 0.51 for the need and complexity components, respectively. ROC curve was used to assess the validity of the index. A new cut-off point was adjusted at 35 in lieu of 43 as the suggested cut-off point. This cut-off point showed the highest level of sensitivity and specificity in our society for orthodontic treatment need (0.77 and 0.78, respectively), but it failed to define definite ranges for the complexity of treatment. Conclusion ICON is a valid index in assessing the need for treatment in Iran when the cut-off point is adjusted to 35. As for complexity of treatment, the index is not validated for our society. It seems that ICON is a well-suited substitute for the IOTN index. PMID:26331142