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Showing 41 to 50 of 50 (0.063 seconds)Spelling suggestions: "subject:"egetation fndices"" "subject:"egetation endices""
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Technological Innovations for Mid-Atlantic Cropping SystemsSwoish, Michael Joseph 05 February 2020 (has links)
Greater projected demand for food, fuel, and fiber will require substantial increases in global agricultural production over the next three decades. Climate change is also forecasted to make weather events more extreme and variable. Efficiency will become more important as demand for food products increases and the availability of fertilizer and land decreases. Technology may be of paramount importance for pushing the boundaries of production while remaining sustainable for generations to come. The first chapter of this dissertation investigated the importance of rate and timing of the plant growth regulator trinexapac-ethyl to malting barley in Virginia. Plant growth regulators can help plants remain upright during strong winds, thereby preserving grain quality and yield. However, this study demonstrated that risks of plant injury also exist. Application should be restricted to fields with greater risk of lodging and made only after the barley crop has broken dormancy and a substantial increase in air temperature is not forecasted in the week following application. Chapter two compared the efficacy of eight vegetation indices calculated from three satellites (Landsat 8, Sentinel 2, and Planet) for estimating cover crop biomass. Cover crops can have beneficial effects on agricultural land as well as groundwater and surface water, but only when adequate biomass is established to reduce erosion and nutrient leaching. Satellite imagery was able to estimate multi-species cover crop biomass more accurately than field-based sensors, although the most accurate vegetation index was dependent upon which satellite was being tested. Chapter three investigated the potential of Arabidopsis thaliana ipk1-, a loss-of-function mutant which exhibits decreased growth at elevated phosphorus concentration, for serving as in indicator of plant available phosphorus. An indicator crop could provide greater spatial resolution compared to soil testing, as well as represent plant available nutrients as opposed to chemically extracted nutrient estimations. Plant response exhibited a quadratic relationship with media P concentration in the range of fertilizer decision making for maize, providing valuable insight for potential yield response in agricultural fields below 'very high' phosphorus concentration. / Doctor of Philosophy / Climate change, increased demand for locally sourced ingredients, and elevated pressure for environmentally responsible practices will make meeting the growing demand for food difficult for farmers to achieve over the next few decades. Similar to many other industries, implementation of advanced technology may be necessary to keep up with agricultural demand. Plant growth regulators are one such technology which when applied to plants can cause them to remain short, decreasing the chance of blowing over during windstorms. However, chapter one of this dissertation concluded that risks of plant injury also exist when applying plant growth regulator on malting barley (for brewing or distilling). Application should be restricted to fields with greater risk of wind damage (e.g. taller barley) and made only after the barley crop begins spring growth and a decrease in air temperature is not forecasted in the week following application. Chapter two compared eight spectral vegetation indices across three satellites with different image resolution for their ability to estimate cover crop biomass. Cover crops protect groundwater and surface water quality, but only when adequate growth is achieved. Satellite imagery was able to estimate multi-species cover crop biomass more accurately than field-based sensors, although the most accurate vegetation index was dependent upon which satellite was being tested. Chapter three investigated the potential of Arabidopsis thaliana ipk1-, a loss-of-function mutant which exhibits decreased growth at elevated phosphorus concentration, as in indicator of plant available phosphorus in soil. An indicator crop could help determine which areas of a field are likely to have increased crop yield if fertilized and which are not. The mutant tested could be useful as an indicator crop given its response to phosphorus concentration, warranting further research with other plant species more appropriate for field use.
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Avaliação da cobertura florestal da sub-bacia hidrográfica do rio Alegre, Sul do estado do Espírito Santo, utilizando geotecnologias / Assessment of forest cover in the hydrographic subbasin of the Alegre river, southern Espirito Santo state, using geotechnologySilva, Kmila Gomes da 12 March 2013 (has links)
Made available in DSpace on 2016-12-23T13:51:55Z (GMT). No. of bitstreams: 1
kmila Gomes da Silva.pdf: 1840290 bytes, checksum: 71792d0ca0267bf6f9206f3a5d471245 (MD5)
Previous issue date: 2013-03-12 / The analysis of the plant covering behavior on a temporal scale addresses practices that make forest remnant sustainability possible. The present study seeks to analyze the dynamics of the forest fragments in the hydrographic subbasin of the Alegre river, Espirito Santo state, based on the alterations of the plant covering and the structure of the forest landscape on a space-time scale, through two chapters. The first is based on the hypothesis that vegetation indexes can express similar vegetative or differentiated vigor of canopies of a specific area. To test the hypothesis, the objective was to to compare three vegetation indexes: TVI (Transformed Vegetation Index), CTVI (Corrected Transformed Vegetation Index) and RATIO (Ratio Vegetation Index), in relation to the behavior of NDVI (Normalized Difference Vegetation Index), regarding the discrimination of the vegetative vigor, as well as the alterations in the forest cover between 1987 and 2010. Through the obtained results, it was verified that the vegetation indexes allowed to estimate the vegetative vigor of the plant covering. A 4.90% (NDVI) increase and one of 7.78% (TVI) of forest covering, a pasture reduction of 3.34% (NDVI) and 5.53% (TVI) and a reduction of nonvegetated areas of 5.93% (NDVI) and 3.35% (TVI), in the period between 1987 and 2010 were evidenced. The natural regeneration process might have been the decisive factor for the area increrease and the changes in the forest vegetation of the area. The second chapter was based on the hypotheses that:1) In the forest landscape the predominance of fragments of small area occured during the years studied (1975, 2002 and 2007); 2) there is a predominance of forest fragments with complex forms and with smaller central area; 3) The forest remnants are isolated and with a larger border area. Based on the above, the aim was to characterize the space and temporal evolution of the forest fragment structures using landscape ecology metrics applied in the years of 1975, 2002 and 2007; the structural analysis of the forest fragments was conducted contemplating area parameters, form, nucleus, border and proximity by size classes. Based on the obtained results, a 7% increase was verified in the total area of the forest covering with the appearance of 645 new fragments. The number of fragments increased and the area of contribution small, which implied in the high border/area ratio. The smallest fragments (< 1 ha.) presented simple geometric form in relation to the others. The largest forest fragments (> 20 ha.) were shown proximate, presenting a tendency towards reduction of the proximity measure values / A análise do comportamento da cobertura vegetal numa escala temporal direciona práticas que viabilizam a sustentabilidade dos remanescentes florestais. O presente estudo visa analisar a dinâmica dos fragmentos florestais na sub-bacia hidrográfica do rio Alegre-ES, com base nas alterações da cobertura vegetal e na estrutura da paisagem florestal em uma escala espaço temporal, por meio de dois capítulos. O primeiro deles com base na hipótese de que índices de vegetação podem expressar vigores vegetativos semelhantes ou diferenciados, de dosséis de uma determinada região. Para testar a hipótese, objetivou-se comparar três índices de vegetação: TVI (Transformed Vegetation Index), CTVI (Corrected Transformed Vegetation Index) e RATIO (Ratio Vegetation Index), em relação ao comportamento do NDVI (Normalized Difference Vegetation Índex), quanto à discriminação do vigor vegetativo, bem como as alterações na cobertura florestal entre 1987 e 2010. Por meio dos resultados obtidos, verificou-se que os índices de vegetação permitiram estimar o vigor vegetativo da cobertura vegetal. Evidenciou-se o aumento da cobertura florestal de 4,90% (NDVI) e 7,78% (TVI), redução de pastagens de 3,34% (NDVI) e 5,53% (TVI), e redução de áreas não vegetadas de 5,93% (NDVI) e 3,35% (TVI), entre o período de 1987 e 2010. O processo de regeneração natural pode ter sido o fator determinante para o incremento de área e as mudanças na vegetação florestal da região. Já o segundo capítulo, baseou-se nas hipóteses de que: 1) Na paisagem florestal ocorre a predominância de fragmentos de pequena área durante os anos estudados (1975, 2002 e 2007); 2) Há predominância de fragmentos florestais com formas complexas e com menor área central; 3) Os remanescentes florestais estão isolados e com maior área de borda. Diante disso, objetivou-se caracterizar a evolução espacial e temporal das estruturas dos fragmentos florestais, utilizando as métricas da ecologia da paisagem aplicadas nos anos de 1975, 2002 e 2007; a análise estrutural dos fragmentos florestais foi realizada contemplando parâmetros de área, forma, núcleo, borda e proximidade em classes de tamanho. Com base nos resultados obtidos, verificou-se um aumento de 7% na área total da cobertura florestal com o surgimento de 645 novos fragmentos. O número de fragmentos foi elevado e a área de contribuição pequena, o que implicou na alta relação de borda/área. Os menores fragmentos (< 1 ha) apresentaram forma geométrica simples, em relação aos demais. Os maiores fragmentos florestais ( > 20 ha) mostraram-se próximos, apresentando uma tendência de redução nos valores da métrica de proximidade
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Multispektrální analýza obrazových dat / Multispectral Analyse of Image DataNovotný, Jan January 2009 (has links)
The airborne hyperspectral remote sensing is used as an approach to monitor actual state of environmental components. This thesis covers priority treatment to analyse of hyperspectral data with the aim of a tree crowns delineation. Specific algorithm applying adaptive equalization and the Voronoi diagrams is designed to subdivide a forest area into individual trees. A computer program executes the algorithm and allows testing it on real data, checking and analyzing the results.
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[pt] ESTIMADOR INTELIGENTE DE BIOMASSA EM PASTOS USANDO ÍNDICES DE VEGETAÇÃO A PARTIR DE IMAGENS CAPTURADAS POR VANTS / [en] INTELLIGENT BIOMASS ESTIMATION IN PASTURES USING RGB-BASED VEGETATION INDICES FROM UAV IMAGERYLUCIANA DOS SANTOS NETTO DOS REYS 11 August 2022 (has links)
[pt] O gerenciamento correto das pastagens em regiões agropecuárias tem
papel fundamental na própria produção, na prevenção ao desperdício da
biomassa vegetal e a liberação de gases de efeito estufa (GEE). Além disso,
é necessário evitar o movimento inapropriado do rebanho entre pastos, pois
este é um processo demorado e pode ser estressante para o animal. O sucesso
desta gestão requer uma avaliação eficiente dos recursos da plantação. Os
estudos desenvolvidos com esta finalidade tem relação direta com a estimativa
da quantidade de biomassa em uma região específica da pastagem, pois, na
prática, ela não é realizada de forma precisa, devido à dificuldade de medição
em toda a área delimitada. Este trabalho tem como objetivo desenvolver
uma metodologia de estimativa de biomassa de baixo custo, baseada em
modelos de regressão que correlacionem os atributos de entrada mais relevantes
para a aplicação com o real peso da plantação, medido em g/m2
. Para os
atributos, foi medida a altura da grama forrageira e calculados os índices
de vegetação baseados em RGB a partir de imagens de veículos aéreos não
tripulados (VANTs). Como metodologia, utilizou-se regressões lineares, não
lineares, redes neurais artificiais baseados em perceptrons de múltiplas camadas
e a combinação de todos os modelos gerados (stacking ensemble). Foram
alcançados resultados satisfatórios utilizando modelos de redes neurais com
ainda duas camadas e com a metodologia de empilhamento de modelos,
alcançando um RMSE de 31.76 g/m2
, MAPE de 13.35 por cento e R
2 de 0.9. Portanto,
a metodologia proposta pode se tornar uma solução promissora e acessível para
a estimativa de biomassa vegetal para uma gestão eficiente e sustentável do
rebanho. / [en] The correct management of pastures in agricultural regions plays a
fundamental role in the production itself, in the prevention of plant biomass
waste and the release of greenhouse gases (GHG). In addition, it is necessary
to avoid inappropriate movement of the herd between pastures, as this is a
time-consuming process and can be stressful for the animal. The success of this
management requires an efficient assessment of the plant resources. The studies
developed for this purpose are directly related to the amount estimation of
biomass in a specific region of the pasture, because, in practice, it is not carried
out accurately, due to the difficulty of measurement throughout the field.
This work aims to develop a low-cost biomass estimation methodology, based
on regression models that correlate the most relevant input features for the
application with the actual density of the plantation, measured in g/m2
. For the
features, the height of the forage grass was measured and the vegetation indexes
based on RGB were calculated from images of unmanned aerial vehicles (UAV).
Linear, nonlinear regression (MNLR), artificial neural networks (ANN) based
on multi-layer perceptron (MLP) and the combination of all models generated
(stacking ensemble) were the methodologies tested in order to achieve the
best correlation. Satisfactory results were achieved using models of neural
networks with two layers and using stacking ensemble methodology, reaching a
RMSE of 31.76 g/m2
, MAPE of 13.35 percent and R-Squared of 0.9. Therefore, the
proposed methodology may become a promising and affordable solution for
plant biomass estimation toward efficient and sustainable herd management.
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A CHARACTERIZATION OF CEREAL RYE COVER CROP PERFORMANCE, NITROGEN CYCLING, AND ASSOCIATED ECONOMIC RISK WITHIN REGENERATIVE CROPPING SYSTEMSRichard T Roth (11206164) 30 July 2021 (has links)
<p>Cereal rye (<i>Secale cereale</i>, L., CR) is the most commonly utilized cover crop
species within the United States. Yet, the total land area planted to CR on an
annual basis remains relatively low despite its numerous proven environmental
benefits. The relatively low rates of CR adoption could be due to a dearth of
knowledge surrounding certain agronomic and economic components of CR adoption.
Currently, there exists knowledge gaps within the scientific literature
regarding CR performance, N cycling, and associated economic risk. <a>Thus, to address the above-mentioned knowledge gaps, three
individual studies were developed to: i) investigate the fate of scavenged CR
nitrogen (N) amongst soil N pools, ii) assess the suitability of
visible-spectrum vegetation indices (VIs) to predict CR biomass and nutrient
accumulation (BiNA), and iii) characterize the economic risk of CR adoption at
a regional scale over time.</a></p>
<p>In the first
study, <sup>15</sup>N, a stable isotope of N, was used in an aerobic incubation
to track the fate of CR root and shoot N among the soil microbial biomass,
inorganic, and organic N pools, as well as explore CR N bioavailability over a
simulated corn growing season. In this study, the C:N ratio of the shoot
residues was 16:1 and the roots was 31:1 and differences in residue quality affected the dynamics of CR N
release from each residue type. On average, 14% of whole plant CR N was
recovered in the soil inorganic N pool at the final sample date.
Correspondingly, at the final sampling date 53%, 33%, and less than 1% of whole plant CR N was
recovered as soil organic N, undecomposed residue, and as microbial biomass N,
respectively. Most CR N remained unavailable to plants during the first cash
crop growing season subsequent to termination. This knowledge could support the
advancement of N fertilizer management strategies for cropping systems
containing cereal rye.</p>
<p>In the second
study, a commercially available unmanned aerial vehicle (UAV) outfitted with a
standard RGB sensor was used to collect aerial imagery of growing CR from which
visible-spectrum VIs were computed. Computed VIs were then coupled with weather
and geographic data using linear multiple regression to produce prediction
models for CR biomass, carbon (C), N, phosphorus (P), potassium (K), and sulfur
(S). Five visible-spectrum VIs (Visible Atmospherically Resistant Index (VARI),
Green Leaf Index (GLI), Modified Green Red Vegetation Index (MGRVI), Red Green
Blue Vegetation Index (RGBVI), and Excess of Green (ExG)) were evaluated and
the results determined that MGRVI was the best predictor for CR biomass, C, K,
and S and that RGBVI was the best predictor for CR N and P. Furthermore, the
final prediction models for the VIs selected as the best predictors developed
in this study performed satisfactorily in the prediction of CR biomass, C, N,
P, K, and S producing adjusted R<sup>2</sup> values of 0.79, 0.79, 0.75, 0.81,
0.81, and 0.78, respectively. The results of this study have the potential to
aid producers in making informed decisions regarding CR and fertility
management. </p>
<p>In the final
study, agronomic data for corn and soybean cropping systems with and without CR
was collected from six states (Illinois, Indiana, Iowa, Minnesota, Missouri,
and Wisconsin) and used within a Monte-Carlo stochastic simulation to
characterize the economic risk of adopting CR at a regional scale over time.
The results of this study indicate that average net returns to CR are always
negative regardless of CR tenure primarily due to added costs and increased
variability in cash crop grain yields associated with CR adoption. Further, the
results demonstrate that the additional risk assumed by adopting CR is not adequately
compensated for with current CR adoption incentive programs and that the risk
premium necessary can be 1.7 to 15 times greater than existing incentive
payments. Knowledge gained from this study could be used to reimagine current
incentive programs to further promote adoption of CR.</p>
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Remote sensing of leaf area index in Savannah grass using inversion of radiative transfer model on Landsat 8 imagery: case study Mpumalanga, South AfricaMasemola, Cecilia Ramakgahlele 03 1900 (has links)
Savannahs regulate an agro-ecosystem crucial for the production of domestic livestock, one of the main sources of income worldwide as well as in South African rural communities. Nevertheless, globally these ecosystem functions are threatened by intense human exploitation, inappropriate land use and environmental changes. Leaf area index (LAI) defined as one half the total green leaf area per unit ground surface area, is an inventory of the plant green leaves that defines the actual size of the interface between the vegetation and the atmosphere. Thus, LAI spatial data could serve as an indicator of rangeland productivity. Consequently, the accurate and rapid estimation of LAI is a key requirement for farmers and policy makers to devise sustainable management strategies for rangeland resources.
In this study, the main focus was to assess the utility and the accuracy of the PROSAILH radiative transfer model (RTM) to estimate LAI in the South African rangeland on the recently launched Landsat 8 sensor data. The Landsat 8 sensor has been a promising sensor for estimating grassland LAI as compared to its predecessors Landsat 5 to 7 sensors because of its increased radiometric resolution. For this purpose, two PROSAIL inversion methods and semi- empirical methods such as Normalized difference vegetation index (NDVI) were utilized to estimate LAI. The results showed that physically based approaches surpassed empirical approach with highest accuracy yielded by artificial neural network (ANN) inversion approach (RMSE=0.138), in contrast to the Look-Up Table (LUT) approach (RMSE=0.265). In conclusion, the results of this study proved that PROSAIL RTM approach on Landsat 8 data could be utilized to accurately estimate LAI at regional scale which could aid in rapid assessment and monitoring of the rangeland resources. / Environmental Sciences / M. Sc. (Environmental Science)
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Remote sensing of leaf area index in Savannah grass using inversion of radiative transfer model on Landsat 8 imagery : case study Mpumalanga, South AfricaMasemola, Cecilia Ramakgahlele 03 1900 (has links)
Savannahs regulate an agro-ecosystem crucial for the production of domestic livestock, one of the main sources of income worldwide as well as in South African rural communities. Nevertheless, globally these ecosystem functions are threatened by intense human exploitation, inappropriate land use and environmental changes. Leaf area index (LAI) defined as one half the total green leaf area per unit ground surface area, is an inventory of the plant green leaves that defines the actual size of the interface between the vegetation and the atmosphere. Thus, LAI spatial data could serve as an indicator of rangeland productivity. Consequently, the accurate and rapid estimation of LAI is a key requirement for farmers and policy makers to devise sustainable management strategies for rangeland resources.
In this study, the main focus was to assess the utility and the accuracy of the PROSAILH radiative transfer model (RTM) to estimate LAI in the South African rangeland on the recently launched Landsat 8 sensor data. The Landsat 8 sensor has been a promising sensor for estimating grassland LAI as compared to its predecessors Landsat 5 to 7 sensors because of its increased radiometric resolution. For this purpose, two PROSAIL inversion methods and semi- empirical methods such as Normalized difference vegetation index (NDVI) were utilized to estimate LAI. The results showed that physically based approaches surpassed empirical approach with highest accuracy yielded by artificial neural network (ANN) inversion approach (RMSE=0.138), in contrast to the Look-Up Table (LUT) approach (RMSE=0.265). In conclusion, the results of this study proved that PROSAIL RTM approach on Landsat 8 data could be utilized to accurately estimate LAI at regional scale which could aid in rapid assessment and monitoring of the rangeland resources. / Environmental Sciences / M. Sc. (Environmental Science)
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Využití laboratorní a obrazové spektroskopie pro hodnocení odolnosti borovice lesní vůči suchu a rozlišení jejich ekotypů / Use of laboratory and image spectroscopy to evaluate drought resistance of Scots pine and to distinguish its ecotypesRaasch, Filip January 2021 (has links)
The aim of this study was to propose a non-destructive method for measuring Pinus sylvestris seedlings, to determine whether water stress would be evident in laboratory spectra of pines, to compare whether the response of pines would differ by ecotype, and to investigate whether two ecotypes of Pinus sylvestris could be distinguished using laboratory and image spectroscopy. For these purposes, hyperspectral images of seed orchards from August 2020 were processed and a three-month laboratory experiment was conducted, in which stress from water deficit was induced in two-year-old pine seedlings from the upland and hilly ecotypes. Spectral data were analysed using mixed statistical models, analysis of variance, principal component analysis, training of supervised pixel classifiers, vegetation indices, and linear regression. Based on the analyses, it was found that water stress can be detected in severely stressed Pinus sylvestris seedlings. The most sensitive spectral bands to water content were observed in the region between 1000-2500 nm. The initial response to water stress did not differ by ecotype, but a faster recovery was observed at the upland ecotype after the period of draught. The two Pinus sylvestris ecotypes were distinguished with high accuracy from both laboratory and image spectral...
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An Analysis of Grain Corn Nutritional Supplements and Relative Maturity in MississippiWhittenton, Joseph Bryan 04 May 2018 (has links)
A review of available corn relative maturity groups in Mississippi shows a limited range of maturity groups in use. Research focusing on expanding the range of maturity groups was conducted in MS in 2015 and 2016. Along with expanded maturity groups, treatments of fertilizer (10-34-0), foliar zinc, and a plant hormone blend were studied to shorten the growing season. Four site years in MS were studied to determine optimal plant maturity group and treatment for length of season. The results showed decreased yield of 0.09-0.15 Mg ha-1 (1.5-2.3 bu ac-1) for each day of decreasing relative maturity in three of four site years. The addition of starter fertilizer increased vegetative growth stage, plant height V5 and V7, SPAD values at V5, and significantly decreases days to tassel and silking reproductive growth stages but did not affect yield.
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Multispectral imaging of Sphagnum canopies: measuring the spectral response of three indicator species to a fluctuating water table at Burns BogElves, Andrew 02 May 2022 (has links)
Northern Canadian peatlands contain vast deposits of carbon. It is with growing urgency that we seek a better understanding of their assimilative capacity. Assimilative capacity and peat accumulation in raised bogs are linked to primary productivity of resident Sphagnum species. Understanding moisture-mediated photosynthesis of Sphagnum spp. is central to understanding peat production rates. The relationship between depth to water table fluctuation and spectral reflectance of Sphagnum moss was investigated using multispectral imaging at a recovering raised bog on the southwest coast of British Columbia, Canada. Burns Bog is a temperate oceanic ombrotrophic bog. Three ecohydrological indicator species of moss were chosen for monitoring: S. capillifolium, S. papillosum, and S. cuspidatum. Three spectral vegetation indices (SVIs) were used to characterize Sphagnum productivity: the normalized difference vegetation index 660, the chlorophyll index, and the photochemical reflectance index.
In terms of spectral sensitivity and the appropriateness of SVIs to species and field setting, we found better performance for the normalized difference vegetation index 660 in the discrimination of moisture mediated species-specific reflectance signals. The role that spatiotemporal scale and spectral mixing can have on reflectance signal fidelity was tested. We were specifically interested in the relationship between changes in the local water table and Sphagnum reflectance response, and whether shifting between close spatial scales can affect the statistical strength of this relationship. We found a loss of statistical significance when shifting from the species-specific cm2 scale to the spectrally mixed dm2 scale. This spatiospectral uncoupling of the moisture mediated reflectance signal has implications for the accuracy and reliability of upscaling from plot based measurements. In terms of species-specific moisture mediated reflectance signals, we were able to effectively discriminate between the three indicator species of Sphagnum along the hummock-to-hollow gradient. We were also able to confirm Sphagnum productivity and growth outside of the vascular growing season, establishing clear patterns of reflectance correlated with changes in the local moisture regime. The strongest relationships for moisture mediated Sphagnum productivity were found in the hummock forming species S. capillifolium. Each indicator Sphagnum spp. of peat has distinct functional traits adapted to its preferred position along the ecohydrological gradient. We also discovered moisture mediated and species-specific reflectance phenologies. These phenospectral characteristics of Sphagnum can inform future monitoring work, including the creation of a regionally specific phenospectral library. It’s recommended that further close scale multispectral monitoring be carried out incorporating more species of moss, as well as invasive and upland species of concern. Pervasive vascular reflectance bias in remote sensing products has implications for the reliability of peatland modelling. Avoiding vascular bias, targeted spectral monitoring of Sphagnum indicator species provides a more reliable measure for the modelling of peatland productivity and carbon assimilation estimates. / Graduate
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