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Wyszukujesz frazę "Jarocińska, A." wg kryterium: Wszystkie pola

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    Tytuł:
    Modelowanie charakterystyk spektralnych heterogenicznych zbiorowisk trawiastych przy użyciu modelu transferu promieniowania
    Simulating spectrum for heterogeneous meadows using a Radiative Transfer Model
    Autorzy:
    Jarocińska, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/132270.pdf
    Data publikacji:
    2011
    Wydawca:
    Polskie Towarzystwo Geograficzne
    Tematy:
    model
    transfer promieniowania
    łąki
    PROSPECT
    Radiative Transfer Model
    meadows
    Opis:
    Meadows are important ecosystems and should be protected. Also, in Poland organic agriculture and farming, where crops from meadows are used, is getting more popular. That is why meadows monitoring and predicting crops is important issue. Much information can be calculated from spectrum of plants and that is why remote sensing data are very useful tool. Two approaches are used to calculate biophysical variables: statistical and modelling. In statistical, values from field measurements have to be compared with images. In modelling, radiative transfer models are used. RTM are physical models based on the fundamental equation of radiative transfer. After all necessary adjustments, models can give the description of the canopy with fewer field measurements. In this paper model on leaf level was chosen. PROSPECT uses only five input variables: chlorophyll and carotenoid content, water content, dry matter and leaf structure parameter. Model is normally used to homogeneous canopy, like corn. In this paper, PROSPECT was used to simulate spectrum for heterogenic meadows using field measurements. Biophysical variables were collected during field measurements in the Bystrzanka catchment in the Low Beskid Mountains. In the same time more than 10 samples of spectrum were collected using ASD FieldSpec 3 FR and then averaged. The minimum size of polygon was 100m2. All input parameters for every polygon were included into the model and spectrum was modelled. Then spectrum was compared with measured samples of each polygon. In the end the vegetation indices were calculated using two kinds of spectrum and compared. All used vegetation indices are describing plant condition or crop monitoring: Normalized Difference Vegetation Index, Red Edge Normalized Difference Vegetation Index, Photochemical Reflectance Index, Normalized Difference Nitrogen Index, Normalized Difference Lignin Index, Cellulose Absorption Index, Carotenoid Reflectance Index, Water Band Index and Moisture Stress Index. Researches shows, that it is possible to simulate spectra for heterogeneous meadows using PROSPECT. The average RMSE value for all polygons was 0,0346, which mean the spectra are well modelled. The biggest mistake was for near infrared range, where is the strongest influence of dry matter content. The differences between measured and modelled spectrum were also noticed on the part of visible light – 400-500nm. For most calculated vegetation indices values were similar for both kinds of spectra. Values of NDVI,WBI and NDLI were very close. The biggest differences were noticed form PRI and CRI.
    Źródło:
    Teledetekcja Środowiska; 2011, 46; 29-42
    1644-6380
    Pojawia się w:
    Teledetekcja Środowiska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Ocena skuteczności modeli transferu promieniowania w badaniach stanu roślinności łąk
    Evaluation of radiative transfer models to simulate meadows reflectance
    Autorzy:
    Jarocińska, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/132309.pdf
    Data publikacji:
    2012
    Wydawca:
    Polskie Towarzystwo Geograficzne
    Tematy:
    łąka
    krzywe
    odbicie spektralne
    Radiative Transfer Model
    PROSPECT
    SAIL
    meadows
    spectral reflectance
    Opis:
    Vegetation 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 analyzes the interactions 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 recognise the object and check its characteristics analysing 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 most extensively use. In Poland 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 modelling the state of the heterogeneous vegetation cover of seminatural meadows in Poland. Two approaches are used to canopy analysis: statistical and modelling. In the statistic approach, biophysical parameters calculated from the image are correlated with reflectance or transmittance from fi eld 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 modelling. 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 consisting 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 refl ectance and diffusion on a leaf level. It is often employed with other models that describe whole canopy. Leaf has the same properties on both sides, the reflection from the leaves is Lambertian. 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, this kind of ecosystem is normally rather heterogeneous and modelling is quite difficult. In this study two Radiative Transfer Models (PROSPECT-5 and 4SAIL) were used on single leaves and a whole canopy level. In order to acquire the input data to both, models model and reference spectrums the fi eld 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 spectral reflectance obtained from the model was compared with field data. Based on the calculated Root Mean Square Error the simulation was verified. The RMSE values were calculated for whole range from 400 to 2500 nm and for specific ranges. The correctness of simulated spectra were analysed 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 the infrared using PROSPECT. Generally bigger errors were noticed in the infrared, especially middle infrared range. The effectiveness of the reflectance simulation was not influenced by different kind of meadows. Apart from that, better results were obtained on meadows with higher biomass value, bigger Leaf Area Index and lower water content. 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.
    Źródło:
    Teledetekcja Środowiska; 2012, 48; 1-52
    1644-6380
    Pojawia się w:
    Teledetekcja Środowiska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Korelacje naziemnych i lotniczych teledetekcyjnych wskaźników roślinności dla zlewni Bystrzanki
    Correlations of ground- and airborne-level acquired vegetation indices of the Bystrzanka catchment
    Autorzy:
    Jarocińska, A.
    Zagajewski, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/132257.pdf
    Data publikacji:
    2008
    Wydawca:
    Polskie Towarzystwo Geograficzne
    Tematy:
    zlewnia rzeki
    roślinność
    teledetekcja
    wskaźnik
    river basin
    vegetation
    indices
    remote sensing
    Źródło:
    Teledetekcja Środowiska; 2008, 40; 100-124
    1644-6380
    Pojawia się w:
    Teledetekcja Środowiska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Zmienność wilgotności w dolinie górnej Narwi w okresie 20 lat na podstawie transformacji Tasseled Cap i wskaźników wilgotności
    Wetness change detection in the upper Narew valley for 20 years using Tasseled Cap transformation and wetness indices
    Autorzy:
    Jarocińska, A.
    Nasiłowska, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/132281.pdf
    Data publikacji:
    2009
    Wydawca:
    Polskie Towarzystwo Geograficzne
    Tematy:
    zmienność
    wilgotność
    Tasseled Cap
    MSI
    NDII
    Narew
    wetness
    changes
    Narew valley
    Opis:
    Wetness monitoring is very important issue especially on wetlands ecosystems, because they are very vulnerable to changes, particularly those made by human. The upper Narew valley with eminence was analyzed. Described area is in north-eastern Poland and covers the valley from Tykocin to Łazy. This area is unique wetland habitat in Europe. In natural part is an anastomosing river system, whereas second part is covered by agricultural areas (wetlands which were drained in ‘70 of XX century). The aim of this paper is to demonstrate quantitative multitemporal analyses of changes in this environment by using various wetness indices and comparing them. To investigate the amount of changes the images from Landsat were used: from TM and ETM+ scanner (available from http://glovis.usgs.gov/). They were from two time series: the end of XX century (1989, 1992, 1993 and 1994) and the beginning of XXI century (2006 and 2007). All of the images were from the beginning or the middle of the vegetation season. In addition, meteorological data were used (from www. tutiempo.es), to detect the precipitation influence on analyzed indices. NDVI was calculated using image from the 2006, then the mask was created to remove all apart from the vegetation (everything under 0,4). After that the Tasseled Cap transformation was made to obtain Wetness band (TCW). Values under -37 on image from 1993 were masked to eliminate cloudy areas. In next step two wetness indices were calculated: Normalized Difference Infrared Index (NDII) and Moisture Stress Index (MSI). TCW is based on visual, near-infrared and-middle infrared electromagnetic radiation, because of that it could depend on atmospheric conditions. NDII and MSI are calculated only from 4th and 5th Landsat bands. Scattering from aerosols in that part of wavelength is weaker and doesn’t have big impact on indices values. Three describing indices are used when atmospheric correction isn’t possible or needed. Values of the three parameters were mapped by dividing into four classes: higher, medium, lower and the lowest wetness. Maps were averaged in the two time series (end of XX and beginning of XXI century). They were reclassified into tree difference maps to show the differences in wetness conditions and between various indices. Three maps showing changes in wetness were classified into five categories: much more wet, more wet, no changes, drier and much drier. These set of data could be compared. The results show that about 55% of analyzing area is stable. Table 3 present that about 2% of all changes were big. About 30% of total amount of transformation are connected with drainage areas. Areas which were more wet cover about 10%. Drained areas are getting extremely wet based on TCW, but opposite tendency can be noted on MSI and NDII maps. Big discrepancy between the maps of changes was discovered. TCW showed that the natural valley is getting drier and eminences are getting wet, but the results are different for the other two analyzed indices. Apart from that, some of the results are different for the parameters. In further research this kind of analysis should be compared with land cover and field measurements.
    Źródło:
    Teledetekcja Środowiska; 2009, 41; 51-57
    1644-6380
    Pojawia się w:
    Teledetekcja Środowiska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Analiza zależności między zawartością wody w roślinach zmierzoną w terenie a teledetekcyjnymi wskaźnikami roślinności
    Analysis of the relationships between vegetation water content obtained from field measurements and vegetation indices
    Autorzy:
    Niedzielko, J.
    Milczarek, M.
    Szepietowska, M.
    Pokrzywnicka, M.
    Boral, B.
    Łach, G.
    Kaźmierczak, M.
    Jarocińska, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/132373.pdf
    Data publikacji:
    2012
    Wydawca:
    Polskie Towarzystwo Geograficzne
    Tematy:
    teledetekcyjne wskaźniki roślinności
    Landsat
    zawartość wody w roślinach
    Kanada
    vegetation indices
    vegetation water content
    Canada
    Opis:
    Monitoring the plant moisture has a significant role in geographical research. It may be used, among the others, for climate modelling, agricultural predicting, rational water management, drought monitoring and determining vulnerability to the occurrence of the fire. Traditional methods, based on field measurements, are the most accurate, but also time-consuming. Therefore these methods can be applied only in a limited area. In order to explore bigger areas remote sensing methods are useful. To analyse plant condition and water content vegetation indices can be used. Their calculations are based on the reflectance in different bands. Despite many studies conducted on the development of remote sensing indices, still there is a need for verification of their accuracy and usefulness by comparing the results obtained through remote sensing tools with the results of field measurements. In this paper three indices are used: Moisture Stress Index (MSI), Normalized Difference Infrared Index (NDII) and transformation Tasseled Cap (the Wetness band). The aim of this study was to compare the value of vegetation indices calculated using images from Landsat 5 Thematic Mapper with the results of field measurement from five test areas of different type of land cover: cereal crops, non-cereal crops, forests, meadows and pastures. Research was carried out in province Ontario (Canada) and consisted of two stages. The first stage was the fi eld measurements, where the specified number of plant samples was collected and water content was calculated. The second stage consisted of the preparation of relevant satellite images (atmospheric correction and making the mosaic) and the calculation of vegetation indices. The study has shown, that statistical relationships between data sets obtained through remote sensing indices and calculated on the basis of field measurements are diverse for different indices. MSI and NDII values are significantly correlated with the water content in plants (R= -0.62 and 0.56, respectively). The correlation of TCW was rated as moderate (R=0.30). Spatial distribution of water content based on maps created using NDII and MSI is similar. It was noticed that TC Wetness transformation overestimates water content in cereal plants (smaller water content) and underestimates it in natural green plant ecosystems, which generally have higher water content. As a result, the range of water content values obtained from TCW is more narrow (dominates the class of 60-70% water in plants) than the range of values calculated using NDII and MSI. Both indices have more uniform distribution dominated by the classes of moderate water content (50-60%), rather wet plants (60-70%) and very wet plants (70-80%). Each index is characterized by different distribution of the water content. In general values calculated on the basis of NDII and MSI are higher than calculated using TCW. In order to perform more accurate analysis between values calculated using satellite images and the results of field measurements, the values of particular types of land cover should be compared.
    Źródło:
    Teledetekcja Środowiska; 2012, 47; 43-57
    1644-6380
    Pojawia się w:
    Teledetekcja Środowiska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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