Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: fAPAR

Sortuj według:

Ogranicz wyniki do:

Zróżnicowanie kosodrzewiny w Tatrach, w świetle badań teledetekcyjnych

Zwijacz-Kozica M.

Teledetekcja Środowiska

2010

T. 44

1--61

Dwarf mountain pine (Pinus mugo Turra) is the main component in the subalpine belt in the Tatra National Park, where the study was conducted. From the ecological point of view dwarf pine plays an important role in the sensitive mountainous area. Until now there were no studies focused on structure of dwarf pine community and there were also no attempts to work out methodology for detailed qualitative and quantitative description of dwarf pine. In this study for the first time it was aimed to prepare methodology of dwarf pine characterization and monitoring using hyperspectral data. Analysis involved processing of airborne and satellite images data and field measurements. Presented study evaluated linear predictive models between vegetation indices derived from radiometrically corrected air- borne imaging spectrometer ROSIS, spectral field and laboratory measurements and field measurements of dwarf pine biophysical variables (LAI, fAPAR). Narrow band vegetation indices were computed on the basis of all possible two-band combinations of set of vegetation indices (VI, NDVI, PVI, SAVI2, TSAVI). VI based on ROSIS wavebands 510 nm and 630 nm was linearly related to leaf area index (R2=0,48). VI and NDVI based on FieldSpec HH wavebands 886 nm and 518 nm performed better and were linearly related to LAI (R2=0,72). TSAVI based on ROSIS wavebands 658 nm and 570 nm was linearly related to the fraction of absorbed photosynthetically active radiation (R2=0,72). SAVI2 based on FieldSpec HH wavebands 747 nm and 703 nm was linearly related to fAPAR (R2=0,81). Analysed indices of vegetation condition were correlated (R2>0,90) with spectral vegetation indices based on FieldSpec Pro laboratory data. The study shows that for hyperspectral image data covering spectral region of visible light and near infrared, linear regression models can be applied to quantify LAI and fAPAR with satisfying accuracy. Models involving spectral information from sensors that have wider spectral range have better potential to linearly quantify biophysical vegetation parameters involving spectral vegetation indices. Vegetation indices that have the best relation to LAI and fAPAR were based on wavebands related to spectral features. It can be assumed that hyperspectral data contain information relevant to the estimation of vegetation biophysical parameters. In this study it was investigated if dwarf pine community differs spectrally within study site. To assess presence and extent of the spectral differentiation the set of field and laboratory spectral measurements were used. Reflectance curves were compared visually and using the statistical test. It was demonstrated that the majority of the studied dwarf pine plots have a characteristic signature. Parts of the electromagnetic spectrum which offer greatest information content for discriminating between and identifying dwarf pine spectral types were indicated. It was also examined if any of abiotic components of environment (altitude above sea level, aspect, slope, soil type, geology, global radiation and temperature) has an influence on the spatial distribution of LAI and fAPAR values. WMP (index of tie strength) and MP (tie strength) were used to assess an extent of the influence. It was found that neither of investigated abiotic factors affects LAI and fAPAR values.

Remote sensing tools for analyzing state and condition of vegetation

Jarocińska A., Zagajewski B.

Roczniki Geomatyki

2009

T. 7, z. 2

47-53

Hyperspectral data, which are characterized by very high spectral, spatial and radiometric resolutions, allow the analysis of the biometric properties of plants in different wavelengths of the electromagnetic spectrum. This kind of data can be applied to interpretation of vegetation, land cover forecast biomass and crops and also for analyzing plant condition, because vegetation cover is a very good indicator of environmental condition. All the spectral characteristics of plants can be measured and analyzed quantitatively using different vegetation indices, which are a mathematical combination of various bands. The most frequently used regions of the spectrum are visible, red-near infrared edge, near and middle infrared. In these regions it is possible to measure chlorophyll, carotenoids and other pigment content, fresh and dry biomass, water and nutrient content, internal leaf structure, soil moisture and plant surface temperature. In this study, four of the vegetation indices have been analysed: Normalized Difference Vegetation Index (Rouse et al., 1973; Griffith et al., 2002), Soil Adjusted Vegetation Index (Huete, 1988), Leaf Area Index (Surlock, 2001; Haboudane et al., 2004) and fAPAR - fraction of Absorbed Photosynthetically Active Radiation (Moreau, Li, 1996). These indices measure the condition of plants and estimate the quantity of biomass. Correctly calculated indices offer much information about the functionality of an ecosystem. Such vegetation indices are broadly used for vegetation monitoring. The main purpose of the research was an analysis of plant condition using remote sensing methods. Maps of spatial distribution of the NDVI, SAVI, LAI and fAPAR were prepared using ground and airborne measurements (DAIS 7915 products were corrected and verified by field measurements). Indices from airborne and ground level measurements were also correlated. The studies took place in the Low Beskid Mountains., which constitute one of the most natural parts of the Polish Carpathian Mountains (Fig. 3). The area extends from 49o34'- 49o41'N to 21o01'-21o09'E, with an altitude range of 400-750 m. The study area focuses on the Bystrzanka catchment around the town of Szymbark. This catchment has an area of around 13.5 km2. The largest part of the area, 40%, is covered by forest. Meadows and pasture comprise 28% of the area. A small fragment of the area is covered by arable land. The area is defined as a natural and seminatural environment. The human influence is relatively low and natural processes are not disturbed, so that vegetation can be used here as an indicator of other ecosystem components (soils, microclimate etc.)

Techniki teledetekcyjne umożliwiają prowadzenie monitoringu przyrodniczego roślinności, w tym dokładną analizę fizjologii oraz właściwości biometrycznych. W artykule przedstawiony jest sposób badania kondycji roślinności wykorzystujący teledetekcyjne wskaźniki roślinności oraz związki mię dzy wskaźnikami mierzonymi z poziomu naziemnego i pułapu lotniczego. Badania były prowadzone na terenach naturalnych i ekstensywnie wykorzystywanych rolniczo zlewni Bystrzanki w Beskidzie Niskim. W badaniach wykorzystano dwa rodzaje danych: wartości wskaźników NDVI, SAVI, LAI i fAPAR pobranych na poziomie terenowym oraz obraz hiperspektralny ze skanera lotniczego DAIS 7915. Pobrano dane z poziomu terenowego. Następnie utworzono obrazy wskaźników w dwóch progra mach ATCOR i ENVI 4.3 (obraz wskaźnika NDVI). Obrazy wskaźników SAVI, LAI i fAPAR uzyskane z pierwszego programu były w jednostkach niezgodnych dla wskaźników, dlatego wymagały dalszych transformacji. Pobrano wartości wskaźników z obrazów. Następnie przeprowadzono analizy staty styczne porównując wartości z obrazów z danymi terenowymi, uzyskując równania regresji, których użyto do transformacji obrazów. Ostatnim etapem było utworzenie map przestrzennego rozkładu czterech wskaźników oraz mapy kondycji roślinności biorącej pod uwagę wartości wskaźników SAVI, LAI i fAPAR. Stwierdzono, że użycie teledetekcyjnych wskaźników roślinności ułatwia pozyskiwanie informacji o stanie roślinności i obiektywizuje te dane. Zanotowano korelacje między wskaźnikami NDVI i LAI oraz NDVI i fAPAR, są one zdecydowanie silniejsze na poziomie lotniczym. Na ścisłość korelacji wpływa sposób pobierania danych oraz sposób użytkowania terenu. Techniki hiperspektralne stwa rzają dodatkowe możliwości pozyskiwania informacji przez analizę krzywej odbicia spektralnego, a nie jedynie jej wycinków, tak jak w przypadku technik wielospektralnych. Wykorzystując tak utworzo ne wskaźniki możliwa jest dokładniejsza analiza roślinności. Stwierdzono, że na badanym terenie wskaźniki NDVI, SAVI, LAI i fAPAR mają wysokie wartości. Na podstawie mapy kondycji roślinności stwierdzono, że na przeważającym obszarze roślinność była w dobrym stanie.