Дисертації з теми "Plant reflectance spectra"
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Johansson, Peter. "Plant Condition Measurement from Spectral Reflectance Data." Thesis, Linköping University, Computer Vision, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-59286.
Повний текст джерелаThe thesis presents an investigation of the potential of measuring plant condition from hyperspectral reflectance data. To do this, some linear methods for embedding the high dimensional hyperspectral data and to perform regression to a plant condition space have been compared. A preprocessing step that aims at normalized illumination intensity in the hyperspectral images has been conducted and some different methods for this purpose have also been compared.A large scale experiment has been conducted where tobacco plants have been grown and treated differently with respect to watering and nutrition. The treatment of the plants has served as ground truth for the plant condition. Four sets of plants have been grown one week apart and the plants have been measured at different ages up to the age of about five weeks. The thesis concludes that there is a relationship between plant treatment and their leaves' spectral reflectance, but the treatment has to be somewhat extreme for enabling a useful treatment approximation from the spectrum. CCA has been the proposed method for calculation of the hyperspectral basis that is used to embed the hyperspectral data to the plant condition (treatment) space. A preprocessing method that uses a weighted normalization of the spectrums for illumination intensity normalization is concluded to be the most powerful of the compared methods.
Bidston, Caroline. "The effects of metal pollution on the spectral reflectance of plants." Thesis, University of Reading, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314319.
Повний текст джерелаHollberg, Jens Lothar [Verfasser]. "Detecting Plant Functional Traits of Grassland Vegetation Using Spectral Reflectance Measurements / Jens Lothar Hollberg." Bonn : Universitäts- und Landesbibliothek Bonn, 2018. http://d-nb.info/1160594171/34.
Повний текст джерелаSugianto, Biological Earth & Environmental Science UNSW. "Multi-angular hyperspectral data and its influences on soil and plant property measurements: spectral mapping and functional data analysis approach." Awarded by:University of New South Wales. Biological, Earth and Environmental Science, 2006. http://handle.unsw.edu.au/1959.4/25531.
Повний текст джерелаYang, Yang. "Non-contacting techniques for detecting plant drought stress in a closed environment." Connect to this title online, 2003. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1068499233.
Повний текст джерелаTitle from first page of PDF file. Document formatted into pages; contains xx, 245 p.; also includes graphics. Includes bibliographical references (p. 206-216).
Chen, Yaw-Nan, and 陳耀南. "The chlorophyll fluorescence and leaf reflectance spectra characteristics among different ecophysiological behavior plants." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/53928819798218020759.
Повний текст джерела國立中興大學
生命科學系
92
In order to understand the chlorophyll fluorescence and leaf reflectance spectral characteristics among species, 12 species with different elevation distribution and temperature adaptation were used. The experiments were made in the campus of National Chung Hsing University (78 m), Hui-Sun Forest Station (800 m), and Tatachia area (2600 m). The results indicated that the PSII efficiency estimated from chlorophyll fluorescence parameters of Pinus taiwanensis (conifer) was lesser influenced by the low temperature and high illumination than those of 2 Miscanthus (C4) species when they were measured in Tatachia. Among 2 Miscanthus species, low elevation origin M. floridulus was more influenced by low temperature than that of high elevation origin M. transomrrisonensis. In Tatachia, transplanted M. floridulus showed lower photochemical reflectance index (PRI) calculated from leaf reflectance spectra in the winter, indicating it required higher xanthophyll cycle to dissipate more excess absorbed energy due to PSII efficiency were more inhibited by low temperature. It also found that no difference of potential of PSII efficiency (Fv/Fm) between flatland and crest line grew P. taiwanensis in Hui-Sun Forest Station. However the PRI of crest line grew P. taiwanensis was lower than that of flatland grown in dry season, probably due to the difference of water condition between 2 habitats. It showed positive correlation between photosynthesis capacity (Pn) and electron transport rate (ETR) for C4 species. This regression coefficient was higher in the species with higher photosynthetic capacity, and no significant correlation could be found in Miscanthus, which showed the lowest Pn among 5 tested C4 species. When merged together of 5 C4 species to statistic analysis, the leaf with higher photosynthetic capacity showed higher portion of absorbed light energy for photochemical (P), and low portion for non-photochemical (D) dissipations. The slope between Pn and P, as well as Pn and D were decreasing with PAR increased. However, the portion of excess energy was not influenced by PAR. From November to December, which daily minimum temperature ranging from 11.6oC to 22.4oC, predawn Fv/Fm of mango (Mangifera indica, cv. Aiwen) and Podocarpus nagi decrease with low temperature, and mango was more influenced than P. nagi. On the contrary, predawn Fv/Fm of Taiwan alder (Alnus formosana) was lesser influenced by temperature. Nevertheless, predawn Fv/Fm showed a strong significant correlation with predawn PRI (PRIp) for statistical analysis when merged together of 3 species. Therefore PRIp could be used as an indicator to estimate the seasonal variation of the potential photochemical efficiency of PSII. Both Fv/Fm and Ф (actual PSII efficiency) showed significant curvilinear correlation with PRI (PRIn) when 3 species were merged together for statistical analysis which data measured at noon. However, more strong correlation between Fv/Fm and ΔPRI (PRIp - PRIn) as well as between Ф and ΔPRI were found. In addition, non photochemical quenching (NPQ) did not correlated with PRIn, but significant correlated with ΔPRI. Thus ΔPRI is suit to indicate the actual dissipation of the excess energy as well as PSII efficiency during illumination. As a conclusion, both chlorophyll fluorescence parameters and leaf reflectance spectra indexes are powerful tools for ecophysiological study.
Pereira, Maria de Lamares da Piedade e. Teixeira. "Monitoring the impact of soil management on plant spectral reflectance and soil-borne disease resistance." Master's thesis, 2016. http://hdl.handle.net/10348/6801.
Повний текст джерелаO solo e a sua biodiversidade são o motor de todos os sistemas de produção terrestres e serviços de ecossistemas. A mudança na produção agrícola de extensiva para intensiva tem um efeito negativo profundo nos solos e na sua biodiversidade. A perda de biodiversidade resulta em comunidades do solo menos complexas. Com o aumento da procura dos serviços dos ecossistemas, como o solo, existe a necessidade da melhoria da gestão dos solos e das produções agrícolas. Esta melhoria pode trazer vantagens a nível do desenvolvimento de práticas mais sustentáveis que contribuem para um desenvolvimento económico sustentável. A gestão sustentável de qualquer ecossistema requer, entre outras informações, uma compreensão completa da interação solo-planta para tentar descrever padrões naturais. As plantas produzem substância orgânica através da fotossíntese. A fotosíntese depende da absorção de luz pelos pigmentos fotossintéticos presentes na folha. Portanto, as propriedades óticas da folha são influenciadas pela concentração dos pigmentos fotossintéticos e metabolitos, do seu teor em água e da estrutura e anatomia da folha. A reflectância hiperspectral tem ganho importância comercial e científica, contudo, permanece ainda subdesenvolvida apesar do seu potencial. A deteção remota da vegetação é uma boa ferramenta, pois pode extrapolar escalas de tempo, e é cada vez mais utilizada para perceber interações planta-solo. Sabe-se que o sinal de reflectância é sensível a mudanças abióticas e bióticas, mas ainda há um longo caminho a percorrer. Consequentemente, foi realizado durante nove semanas um bioensaio com duas culturas diferentes, a Beterraba (Beta vulgaris) e o Milho (Zea mays). Foram plantadas em três diferentes tipos de gestão do solo e aplicados seis tipos de tratamentos. Os tratamentos aplicados foram: o fungo Rhizoctonia solani, o nemátode Pratylenchus penetrans, a radiação gama, os nutrientes, e o fungo R. solani com nutrientes e um controlo. Os tipos de gestão que foram aplicados foram o solo Biológico, os fertilizantes artificiais e Fertelizantes orgânicos. No total foram consideradas 3650 plantas. Os dados da refletância espetral foram obtidos com um espectrómetro de campo ASD plant-probe e clip-foliar. Um objetivo deste estudo consistiu em monitorizar a refletância espetral das folhas das duas espécies durante o período experimental. Os dados espetrais foram analisados utilizando índices de vegetação. Os efeitos do biota do solo foram analizados numa análise multivariada ANOVA com os fatores, espécie de planta, tipos de solo e tratamentos. A biomassa total de patogénicos tende a aumentar quanto mais intensiva for a prática agricola. No solo Biológico observou-se uma intensificação da cor verde da planta nas duas espécies, com o aumento da disponibilidade de nutrientes. A adição de fertelizante pode ter influenciado a resistência das plantas às doenças do solo. A menor biomassa foi encontrada no tratamento com radiação gama (estéril), sugerindo que o biota do solo influenciou o desempenho da planta. O melhor tipo de gestão do solo teve um efeito positivo no crescimento das plantas. As melhores práticas agricolas permitem uma supressão das doenças inoculadas. Foi demonstrado que o espetro da planta difere quando é induzido stresse e também consoante o tipo de gestão do solo. A melhor gestão agrícola foi considerada a Biológica.
Soil and soil biodiversity are the driving force of all the terrestrial production systems and ecosystem services. The intensification of agriculture production and shifts from extensive crop rotation have, regularly, a profound negative effect on soils and their biodiversity. Biodiversity losses result in less complex soil communities. The increasing demand of soil ecosystem implies the improvement of soil and crop management, and it’s a key opportunity for supporting sustainable economic development. The sustainable management of any ecosystem requires, amongst other information, a thorough understanding of plant-soil feedback attempting to describe natural patterns and relations between the plants and their environment. Plants produce organic substances by photosynthesis. Photosynthesis depends upon the absorption of light by pigments, as chlorophyll-a among other accessory pigments, in the leaves of the plants. Therefore, leaf optical properties are influenced by the concentration of the photosynthetic pigments, metabolites, water content, leaf structure and leaf anatomy. Hyperspectral reflectance in remote sensing has gained scientific and commercial importance but still remains underdeveloped despite its potential. Vegetation remote sensing is a great tool, as it can extrapolate to synoptic scales and time sequences can be acquired. It is increasingly used for measurements of agricultural crop condition and also for plant-soil interactions. It is known that reflectance signal is sensitive to abiotic changes, but concerning biotic changes, there are still several limitations. Therefore, was conducted a 9 weeks greenhouse bioassay with two different crops, Sugar beet (Beta vulgaris) and Corn (Zea mays), three different types of soil management and six different treatments were applied. The treatments applied were: the fungus Rhizoctonia solani, the nematode Pratylenchus penetrans, the Gamma radiation, the nutrients, the R. solani with nutrients and a control treatment. The types of management were the Biologic, the Artificial Fertilizer and the Manure. In total were 3650 plants. Spectral reflectance data were collected with an ASD Fieldspec 3 spectrometer with an ASD plant-probe and leaf-clip device attached. One of the objectives of the measurement was to monitor the differences between leaf reflectance over time. The spectral data was analyzed using vegetation indices. The effects of soil biota were analyzed in a multivariate ANOVA analysis with plant species, soil regime and soil treatment. The total biomass of the pathogens increase with a more intensive agriculture and shoot biomass in both plant species increased with disposal of the nutrient supply in the Biologic soil. The application of manure compost that is rich in nitrogen may have reduced soil-borne diseases. The lowest biomass was found in the sterilized treatments suggesting that the soil biota has influenced the plant performance. The best soil management had positive effect in growth of the plants. Disease suppression can be influenced by management practices. It was demonstrated that plant spectral signatures changes due induced stress and soil type. The best soil regime overall in this study case was considered the Biologic type.
Prasad, Bishwajit. "The potential for using canopy spectral reflectance as an indirect selection tool for yield improvement in winter wheat." 2006. http://digital.library.okstate.edu/etd/umi-okstate-1915.pdf.
Повний текст джерелаHwang, Mon-Yuan, and 黃盟元. "Studies on reflectance spectra of plants leaves and the related physiological characters in different ecological habitats and seasons." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/80327596581588152296.
Повний текст джерелаAxness, Daniel S. "Estimating ground cover via spectral data." Thesis, 1991. http://hdl.handle.net/1957/36337.
Повний текст джерелаGraduation date: 1992
Garcia, Richard L. "Spectral reflectance estimates of light interception and photochemical efficiency in wheat under different nitrogen regimes." 1986. http://hdl.handle.net/2097/22061.
Повний текст джерелаGutierrez-Rodriguez, Mario. "Spectral reflectance indices for estimating yield and water content in spring wheat genotypes under well irrigated, water stress, and high temperature conditions." 2009. http://digital.library.okstate.edu/etd/GutierrezRodriguez_okstate_0664D_10347.pdf.
Повний текст джерела"Field spectroscopy of plant water content in Eucalyptus grandis forest stands in KwaZulu-Natal, South Africa." Thesis, 2008. http://hdl.handle.net/10413/263.
Повний текст джерелаThesis (M.Sc.) - University of KwaZulu-Natal, Pietermaritzburg, 2008.
Govender, Marilyn. "Assessing groundwater access by trees growing above contaminated groundwater plumes originating from gold tailings storage facilities." Thesis, 2012. http://hdl.handle.net/10539/11221.
Повний текст джерелаDeep-level gold mining in the Witwatersrand Basin Goldfields (WBG) of central South Africa is characterised by the production of extensive unlined tailings storage facilities (TSFs) comprising large quantities of pulverised rock and water contaminated with salts and a wide range of other inorganic pollutants (Weiersbye et al., 2006). There are more than 200 such TSFs covering a total area of more than 400 km2 (Rosner et al., 2001), and significant contaminated “footprint” areas occur after removal and reprocessing of the original TSFs (Chevrel et al., 2003). It is estimated that the Witwatersrand Basin contains six billion tons of gold and uranium tailings (Chevrel et al., 2003), 430 000 tons of uranium (Council of Geoscience, 1998; Winde, 2004a; b; c) and approximately 30 million tons of sulphur (Witkowski and Weiersbye, 1998a). An estimated 105 million tons of waste per annum is generated by the gold mining industry within the WBG (Department of Tourism, Economic and Environmental Affairs, 2002; Chamber of Mines of South Africa, 2004). A major environmental problem resulting from deep level mining in the WBG is the contaminated water that seeps from TSFs into adjacent lands and groundwater. Van As (1992) reported on the significant environmental hazards resulting from the storage of highly pulverised pyrite rock waste in TSFs (Straker et al., 2007). Adjacent lands become polluted through near-surface seepage, and this is enhanced by the movement of polluted groundwater in shallow aquifers that are commonly 1-30 m below ground (Funke, 1990; Hodgson et al., 2001; Rosner et al., 2001; Naicker et al., 2003). The impact of the mines and the TSFs extends far beyond their localities (Cogho et al., 1990). The Vaal River catchment receives a large proportion of the pollutants from WBG mining activities, with consequent acidification and salinisation of surface and ground waters. Salt discharges to the Vaal River were estimated to be 170 000 t/annum (Best, 1985), whereas discharges from the Free State gold mines south of the Vaal catchment were estimated at 350 000 t/annum of salts (Cogho et al., 1990). Concern also exists over the spread of dangerous contaminants such as uranium, chromium and mercury (Coetzee et al., 2006; Winde, 2009). Engineering solutions to these problems are hindered by the large sizes and great extent of TSFs, the high and indefinite costs involved, and the typically low hydraulic conductivity in affected aquifers, which makes the “pump and treat” option impractical. An alternative phytoremediation strategy is to establish belts or blocks of trees in strategic areas surrounding the TSFs in order to reduce the seepage of contaminated water into adjacent lands and groundwater bodies. The major reasons why trees are likely to have a greater impact on seepage water than the existing grasslands that characterise the area around most TSFs in the WBG, are that some tree species have the potential to develop very deep root systems and to continue transpiring water throughout the year. This is in contrast to seasonally dormant grasslands. In addition, some tree species are known to be tolerant to salts and other pollutants. Trees are thus potentially able to reach deep water tables, take up large quantities of water, and remove some of the pollutants in this water. It is crucial for a successful implementation of this strategy to know on what sites trees are able to access mine seepage water, and consequently maintain a high year-round rate of water use. If this access is limited, then growth and water use will be curtailed during the long winter dry season, and control of seepage will be considerably below potential. A primary aim of this study was to develop methodologies to discriminate between water-stressed and non-water-stressed trees currently growing in three gold mining districts (Welkom, Vaal River, West Wits) within the WBG. This information was required to assess what site types are likely to support adequate tree growth and permit high rates of water use and seepage control. The tree species selected were those most widely occurring in these areas, and include the non-native species Eucalyptus sideroxylon A. Cunningham ex Woolls and Eucalyptus camaldulensis Dehnhardt, as well as the indigenous species Searsia lancea L.f. Various remote sensing technologies including leaf-level spectroscopy, satellite and airborne remote sensing images were evaluated for their usefulness in detecting levels of winter-time water stress. Four commonly used ground-truthing techniques (predawn leaf water potential, leaf chlorophyll fluorescence, leaf chlorophyll and carotenoid pigment content, and leaf water content) were used for localised measurements of plant water stress and for ground-truthing of remotely sensed data on 75 sample sites and 15 sample sites. This study provided a unique opportunity to test and compare the use of stress reflectance models derived from different remote sensing data acquired at different spatial and spectral resolutions (i.e. multispectral and hyperspectral) for the same geographical location. The use of remote sensing to examine the spectral responses of vegetation to plant stress has been widely described in the scientific literature. A collation of published spectral reflectance indices provided the basis for investigating the use of hand-held remote sensing technology to detect plant water stress, and was used as a stepping stone to further develop spectral plant water stress relationships for specific tree species in this study. Seventy seven spectral reflectance indices and specific individual spectral wavelengths useful for detecting plant water stress, plant pigment content, the presence of stress related pigments in vegetation, and changes in leaf cellular structure, were investigated using hand-held spectroscopy. Ground-based measurements of plant water stress were taken on 75 sample trees. In this study, the measurement of predawn leaf water potential has been identified as a key methodology for linking remotely sensed assessments of plant water stress to actual plant water stress; a reading of -0.8 MPa was used to separate stressed trees from unstressed trees in the landscape (Cleary and Zaerr, 1984). The results of the predawn leaf water potential measurements ranged from -0.56 to -0.68 MPa at unstressed sites, and from -0.93 to -1.78 MPa at stressed sites. A novel approach of using spectral reflectance indices derived from previous studies was used to identify specific indices which are applicable to South Africa and to the three species investigated in the WGB. Maximal multiple linear regression models were derived for all possible combinations of plant water stress measurements and the 77 spectral reflectance indices extracted from leaf-level spectral reflectance data, and included the interactions of district and species. The results of the multiple linear regression models indicated that the (695/690) index, DATT index (850-710)/(850-680), near infra-red index (710/760) and the water band (900/970) index performed well and accounted for more than 50% of the variance in the data. The stepwise regression model derived between chlorophyll b content and the DATT index was selected as the “best” model, having the highest adjusted R2 of 69.3%. This was shown to be the most robust model in this application, which could be used at different locations for different species to predict chlorophyll content at the leaf-level. Satellite earth observation data were acquired from two data sources for this investigation; the Hyperion hyperspectral sensor (United States Geological Survey Earth Resources Observation Systems) and the Proba Chris pseudo-hyperspectral sensor (European Space Agency). The Hyperion sensor was selected to obtain high spatial and spectral resolution data, whereas the Proba Chris sensor provided high spatial and medium spectral resolution earth observation data. Twelve vegetation indices designed to capture changes in canopy water status, plant pigment content and changes in plant cellular structure, were selected and derived from the satellite remote sensing imagery. Ground-based measurements of plant water stress undertaken during late July 2004 were used for ground-truthing the Hyperion image, while measurements undertaken during July 2005 and August 2005 were used for ground-truthing the Proba Chris images. Predawn leaf water potential measurements undertaken for the three species, ranged from -0.42 to -0.78 MPa at unstressed sites, and -0.95 to -4.66 MPa at stressed sites. Predawn leaf water potentials measured for E. camaldulensis trees sampled in species trials in Vaal River were significantly different between stressed and non stressed trees (t = 3.39, 8df, P = 0.009). In contrast, E. camaldulensis trees sampled near a pan within the Welkom mining district, which had greater access to water but were exposed to higher concentrations of salts and inorganic contaminants, displayed differences in total chlorophyll content (t = -2.20, 8df, P = 0.059), carotenoid content (t = -5.68, 8df, P < 0.001) and predawn leaf water potential (t = 4.25, 8df, P = 0.011) when compared to trees sampled on farmland. E. sideroxylon trees sampled close to a farm dam in the West Wits mining district displayed differences in predawn leaf water potential (t = 69.32, 8df, P < 0.001) and carotenoid content (t = -2.13, 8df, P = 0.066) when compared to stressed trees further upslope away from the water source. Multiple linear regressions revealed that the predawn leaf water potential greenness normalised difference vegetation index model, and the predawn leaf water potential water band index model were the “best” surrogate measures of plant water stress when using broad band multispectral satellite and narrow-band hyperspectral satellite data respectively. It was concluded from these investigations that vegetation indices designed to capture changes in plant water content/plant water status and spectral changes in the red edge region of the spectrum, performed well when applied to high spectral resolution remote sensing data. The greenness normalised difference vegetation index was considered to be a fairly robust index, which was highly correlated to chlorophyll fluorescence and predawn leaf water potential. It is recommended that this index has the potential to be used to map spatial patterns of winter-time plant stress for different genera/species and in different geographical locations. Airborne remote sensing surveys were conducted to investigate the application of high spatial resolution remote sensing data to detect plant water stress. Multispectral airborne imagery was acquired by Land Resource International (PTY) Ltd, South Africa. Ground-based measurements of plant water stress were carried out during July and August 2005.Four individual spectral bands and two vegetation spectral reflectance indices, which are sensitive to changes in plant pigment content, were derived from the processed multispectral images viz. red, green, blue and near-infrared spectral bands and the normalised difference vegetation index (NDVI) and greenness normalised difference vegetation index (GNDVI).The results of the multispectral airborne study revealed that carotenoid content together with the green spectral waveband resulted in the “best” surrogate measure of plant water stress when using broad-band multispectral airborne data. Airborne remote sensing surveys were conducted by Bar-Kal Systems Engineering Ltd, Israel, to investigate the application of hyperspectral airborne imagery to detect plant water stress. Six vegetation spectral reflectance indices designed to capture changes in plant pigment and plant water status/content, were derived from the processed hyperspectral images. When using airborne hyperspectral data, predawn leaf water potential with the normalized difference water index was selected as the most appropriate model. It was concluded, upon evaluation of the multiple linear regression models, that the airborne hyperspectral data produced several more regression models with higher adjusted R2 values (Ra2 range 6.2 - 76.2%) when compared to the airborne multispectral data (Ra2 range 6 - 50.1). Exploration of relationships between vegetation indices derived from leaf-level, satellite and airborne spectral reflectance data and ground-based measurements used as “surrogate” measures of plant water stress, revealed that several prominent and recurring spectral reflectance indices could be applied to identify species-specific plant water stress within the Welkom, Vaal River and West Wits mining districts. The models recommended for mapping and detecting spatial patterns of plant water stress when using different sources of remote sensing data are as follows: the chlorophyll b DATT spectral reflectance model when derived from leaf-level spectral reflectance data, can be applied across all three mining districts the predawn leaf water potential GNDVI spectral reflectance model and predawn leaf water potential water band index spectral reflectance model when utilising satellite multispectral and hyperspectral remote sensing data carotenoid content green band spectral reflectance model can be used for airborne multispectral resolution data predawn leaf water potential NDVI spectral reflectance model is best suited for airborne high spatial and hyperspectral resolution data. These results indicate that measurements of predawn leaf water potential and plant pigment content have been identified as key methodologies for ground-truthing of remotely sensed data and can be used as surrogate measures of plant water stress. Some preliminary research was undertaken to evaluate if wood anatomy characteristics could be used as a non-destructive and rapid low-cost survey approach for identifying trees which are experiencing long-term plant stress. Seventy two wood core samples were extracted and analysed. Predawn leaf water potential measurements were used to classify stressed and unstressed trees. Relative differences in radial vessel diameter, vessel frequency and wood density were examined. Comparison of the radial vessel diameter and vessel frequency measurements revealed significant differences in three of the five comparative sampling sites (p <0.05). The results of the density analyses were significantly different for all five comparative sampling sites (p < 0.01). In general, trees experiencing higher plant water stress displayed smaller vessel diameters, compared to less stressed or healthy trees. Sites which were influenced by high levels of contaminated water also displayed smaller vessel diameters, indicating that the uptake of contaminants could affect the wood anatomy of plants. Trees considered to be experiencing higher plant water stress displayed higher vessel frequency. This preliminary study showed that plant stress does influence the wood anatomical characteristics (radial vessel diameter, vessel frequency and wood density) in E. camaldulensis, E. sideroxylon and S. lancea in the three mining districts. Spatial patterns of trees, mapped in the three gold mining districts, Welkom (27º57´S, 26º34´E) in the Free State Province, Vaal River (26º55´S, 26º40´E) located in the North West Province, and West Wits (26º25´S, 27º21´E) located in Gauteng, which were not experiencing winter-time water stress were correlated to site characteristics such as average soil depth, percent clay in the topsoil, groundwater chloride and sulphate concentrations, total dissolved solids, electrical conductivity and groundwater water level. The spectral reflectance model derived between predawn leaf water potential and the green normalised difference vegetation index using broad-band multispectral Proba Chris satellite data was used to map spatial patterns of unstressed trees across the three mining districts. Very high resolution (75 cm) multispectral airborne images acquired by LRI in 2005 were used to demarcate and classify vegetation using the maximum likelihood supervised classification technique. Interpolated surfaces of groundwater chloride and sulphate concentrations, total dissolved solids, electrical conductivity, pH and groundwater table levels were created using the kriging geostatistical interpolation technique for each mining district. Random sample analyses between stressed and unstressed trees were extracted in order to determine whether site characteristics were significantly different (using t-tests). Site characteristic surfaces which were significantly different from stressed areas were spatially linked to trees which were not experiencing winter-time plant water stress for each tree species investigated in each mining district. This spatial correlation was used to make recommendations and prioritise sites for the establishment of future block plantings. Analysis of the site characteristic data and the geophysical surveys undertaken in the three mining districts which provided detailed information on groundwater saturation and an indication of the salinity conditions, confirmed the presence of relatively shallow and saline groundwater sources. This would imply that tree roots could access the relatively shallow groundwater even during the dry winter season and assist in containing contaminated groundwater seeping into surrounding lands. Keywords : airborne imagery, ground-based measurements of plant water stress, hyperspectral, leaf-level spectroscopy, multispectral, satellite imagery, spatial patterns of unstressed trees, spectral reflectance indices
Jarocińska, Anna. "Zastosowanie modeli transferu promieniowania w hiperspektralnych badaniach stanu roślinności łąk." Doctoral thesis, 2012. http://depotuw.ceon.pl/handle/item/94.
Повний текст джерелаVegetation analysis is an important problem in regional and global scale. Because of pollution of environment and changes in the ecosystems plant monitoring is very important. Remote sensing data can be easily used to plant monitoring. That kind of method is much faster and more reliable than traditional approaches. Spectrometry analyses the interaction between radiation and object and it uses measurement of radiation intensity as a function of wavelength. Each object emits and absorbs different quantity of radiation, so it is possible to recognize the object and check its characteristics analyzing the spectrum. The subject of the researches is Polish meadows. The human usage of the meadows determines its proper functioning. Grasslands, which consist of meadows and pastures, cover 10% of Poland. Meadows are mostly extensively used, the crops from meadows, hay and green forage, are very low. The meadows in Poland are floristically and morphologically very diverse. Many factors influence on this ecosystem and that is why the monitoring is very important. The aim of the researches is to study the possibility of use of the Radiative Transfer Models in modeling the state of the heterogeneous vegetation cover of seminatural meadows in Poland. To canopy analysis two approaches are used: statistic and modeling. In statistic approach, biophysical parameters calculated from the image are correlated with reflectance or transmittance from field measurements. In second approach physically based model is used to represent the photon transport inside leaves and canopy. The Radiative Transfer Models are based on the laws of optics. Developing the model results in better understanding of the interaction of light in canopy and leaves. The Radiative Transfer Models are often applied to vegetation modeling. The Radiative Transfer Models are physically based models which describe the interactions of radiation in atmosphere and vegetation. Adjusted models can be used to fast and precise analysis of biophysical parameters of the canopy. The canopy can be described as homogeneous layer consist of leaves and spaces. The Radiative Transfer Models are algorithms which vary by input and output parameters, the level of the analysis, kinds of plants and other modifications. Models are used on two levels: single leaf and whole canopy. The first model, which is used in this research, is PROSPECT, which describes the multidirectional reflectance and diffusion on leaf level. It is often employed with other models that describe whole canopy. The input parameters in the model are: chlorophyll and carotenoid content, Equivalent Water Thickness and dry matter content and also leaf structure parameter that describe the leaf structure and complexity. Second model, which is used in the study, is the canopy reflectance model SAIL (Scattering by Arbitrarily Inclined Leaves). It simulates the top of the canopy bidirectional reflectance and it describes the canopy structure in a fairly simple way. In this analysis the 4-SAIL model will be used. This version has few input parameters that describe plants and soil: spectrometric data – reflectance and transmittance from leaves (the output parameters form PROSPECT model), biophysical canopy parameters (Leaf Area Index, brown pigment content, mean leaf inclination angle), soil brightness parameter, reflectance geometry (Solar zenith angle, observer zenith angle, relative azimuth angle), ratio of diffuse to total incident radiation and two hot spot size parameters. The SAIL model is often combined with the model on leaf level – the PROSAIL model. The PROSPECT and SAIL are very rarely used to meadows, because this kind of ecosystem is normally rather heterogeneous and modeling is quite difficult. In this study two Radiative Transfer Models (PROSPECT-5 and 4SAIL) were used form modeling the reflectance on leaf and canopy level. In order to acquire the input data to both models model and reference spectrums the field measurements were done. The input parameters were recalculated using fields measurements and put into the models: PROSPECT and PROSAIL. Only one leaf structure parameter was fitted for each polygon individually. The field measurements were done in 2009 and 2010on 57 test polygons, that were located in Carpathian Foothills (near Gorlice) and on the Środkowopolskie Plains. For each model two datasets were calculated: first (PROSECT-1 and PROSAIL-1), where the input parameters were calculated directly from field measurements, and second (PROSPECT-2 and PROSAIL-2), where water, chlorophyll and carotenoid content were modified. Then, the spectral reflectance obtained from model was compared with field measurements. Based on the calculated Root Mean Square Error the simulation was verified. The RMSE values were calculated for whole range from 0,4-2,5 µm and for specific ranges. The correctness of simulated spectra were analyzed dependent on the type of meadows (cultivated meadows with reduced amount of biomass, cultivated meadows with high amount of biomass and not cultivated meadows) and the value of three different biophysical parameters (Leaf Area index, fresh biomass content and water content). Better results were obtained using PROSPECT model than PROSAIL. In the visible light more accurate values were calculated using PROSAIL and in infrared using PROSPECT. Generally bigger errors were noticed in the infrared, especially middle infrared. In the case of the second datasets (PROSPECT-2 and PROSAIL-2) the largest root mean square error was noticed in the near-infrared and the smallest in the range 0.4-0.6 µm. For both models in each range the RMSE was smaller for datasets PROSPECT-2 and PROSAIL-2 compared to the PROSPECT-1 and PROSAIL-1. The effectiveness of simulation reflectance was not influenced by different kind of meadows. The only differences were noticed in infrared, but were not statistically significant. Apart from that, better results were obtained on meadows with higher biomass value, bigger Leaf Area Index and lower water content for both models. The differences in infrared were statistically significant, especially for the PROSPECT-1 and PROSAIL-1 datasets. Most modeled vegetation indices have vales similar to the field measurements. Better results were notice for PROSPECT model. The smallest differences were for Water band index and also Normalized Difference Vegetation Index. Generally, the PROSPECT and PROSAIL radiative transfer models can be used to simulate the spectral reflectance of vegetation on heterogeneous meadows. The models can be used to estimate the biophysical parameters, but it is necessary to correct the values of input variables (especially water content). Meadows are very complex environment and some of the parameters should be adjusted. The type of the meadow is irrelevant to the correctness of the simulation, while the effectiveness of simulation is much more influenced by the values of biophysical parameters.