BazTech - Yadda

1

Ocena skuteczności modeli transferu promieniowania w badaniach stanu roślinności łąk

Jarocińska A.

Teledetekcja Środowiska

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2012

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T. 48

1--52

EN

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.

2

Przetwarzanie wstępne danych z hiperspektralnego sensora satelitarnego HYPERION

Głowienka E.

Archiwum Fotogrametrii, Kartografii i Teledetekcji

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2008

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Vol. 18a

131--140

PL

W artykule przedstawiono metodykę przetwarzania wstępnego satelitarnych danych hiperspektralnych z sensora HYPERION. Jest to sensor umieszczony na platformie satelity EO-1 (Earth Observing - 1) wraz z multispektralnym sensorem ALI (Advanced Land Image). Hyperion rejestruje obraz w 242 kanałach z rozdzielczością spektralną 10 nm dla zakresów 357÷1058 nm (70 kanałów VNIR) oraz 852÷2576 nm (172 kanałów SWIR), z rozdzielczością przestrzenną 30 m. W artykule przedstawiono wyniki metod przetwarzania danych hiperspektralnych dla fragmentu sceny HYPERIONA. Przetwarzanie wstępne tzw. pre-processing wymaga odpowiedniego przygotowania i analizy danych. Przeprowadzane w programie ENVI (Environment for Visualizing Image) procedury pre-processingu obrazu HYPERIONA, podzielone zostały na dwa główne etapy. W pierwszym etapie wykonano, tzw. destriping, czyli usuwanie zakłóceń spowodowanych niestabilnością sensora lub wadliwie działającymi detektorami oraz korekcję efektu smile, ujawniającego się w obrazach hiperspektralnych w postaci gradientu jasności. Do identyfikacji kanałów obarczonych efektem smile a także do częściowego wyeliminowania tego zakłócenia wykorzystano transformację Minimum Noise Fraction (MNF) oraz Inverse MNF. W drugim etapie pre-processingu wykonana została korekcja atmosferyczna obrazu HYPERIONA. Korekcję przeprowadzono za pomocą programu Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) dostępnego, jako moduł programu ENVI. W wyniku dokonanego na obrazie HYPERIONA pre-processingu, usunięte zostały zakłócenia stripingu, smilingu oraz zakłócenia związane z wpływem atmosfery.

EN

The paper presents methodology of preliminary pre-processing of spaceborne hyperspectral data. HYPERION is a sensor, placed on the platform of EO-1 (Earth Observing-1) satellite, which records images in 242 channels, at the spectral resolution of 10 nm and the spatial resolution of 30 m. The paper described results of processing hyperspectral data for the HYPERION’s scene fragment. Preliminary processing, or the so-called pre-processing requires proper preparation and analysis of data. Procedures of pre-processing a HYPERION's image, performed with the use of ENVI (Environment for Visualizing Image) software, were split into two main stages. The first stage involved the so-called destriping, or the removal of interference caused by the instability of the sensor and defectively operating detectors. Another very important measure, aimed at preparing the image for the subsequent extraction of its thematic information was the removal of the "smile" effect, revealed in hyperspectral images in the form of the brightness gradient. The Minimum Noise Fraction (MNF) and Inverse MNF transformations were applied to identify those channels burdened with the "smile" effect, and also to partially eliminate that interference. The second stage of pre-processing involved the atmospheric correction of the HYPERION's image. That correction was achieved by means of Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) programme, available as a module of ENVI software. The pre-processing resulted in removal of striping, smiling, and interfering of atmosphere's impact.

3

Wpływ orki na dwukierunkową charakterystykę odbicia spektralnego od powierzchni gleb w zakresie optycznym

Faryś M.

Archiwum Fotogrametrii, Kartografii i Teledetekcji

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2000

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Vol. 10

34-1--34-12

PL

Prezentowana praca ma na celu określenie wpływu orki na dwukierunkową charakterystykę odbicia spektralnego od powierzchni gleb w zakresie optycznym. Kierunkowość geometrii powierzchni gleb wymaga zbadania wpływu orientacji poziomej kierunku zabiegu na wartość odbicia od analizowanych powierzchni. Wyjaśnienia zjawiska dokonano za pomocą analizy pomiarów spektralnych od powierzchni trzech typów gleb różniących się barwą, składem granulometrycznym, sekwencją uziarnienia, zawartością materii organicznej. W wyniku badań stwierdzono, że wraz ze zmianą orientacji kierunku zabiegów względem promieni słonecznych, następują zmiany w rozkładzie znormalizowanego odbicia w funkcji kąta zenitalnego obserwacji.