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2 Teledetekcja Środowiska

2 2012

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Zróżnicowanie spektralne wybranych gatunków muraw wysokogórskich Doliny Gąsienicowej narażonych na wydeptywanie

Kycko M., Zagajewski B., Kozłowska A., Oprządek M.

Teledetekcja Środowiska

2012

T. 47

75--86

This paper presents analysis of plant cover condition in Gasienicowa Valley in the Tatra Mts. depending on various trampling intensity. Measurements were taken with ASD FieldSpec 3 spectrometer (its spectral range is 350-2500nm) on 8 dominant plant species of alpine swards: Juncus trifidus, Oreochloa disticha, Agrostis rupestris, Deschampsia flexuosa, Festuca airoides, Festuca picta, Luzula alpino-pilosa, Nardus stricta. These plant species were located: 0-5m, 5-10m and more than 10m distant from a touristic trail (control point). Spectral characteristics as well as vegetation indices were analyzed with ANOVA test, which showed differiential resistance to trampling of investigated plant species. The most resistant species were: Nardus stricta and Deschampsia flexuosa, whereas Oreochloa disticha and Festuca airoides appeared to be vulnerable to trampling. However, all vegetation indices for plant species were in its optimum range, so it proves that they are in a good condition. The analysis of vegetation indices enabled choosing those groups, which are the most useful in the research of mountain vegetation condition. They are: NDVI, ARVI, EVI from the broadband greeness group and mSR705 and mNDVI from narrowband greenness group (measuring chlorophyll content and cell structure), as well as WBI, NDWI, NDII from canopy water content group. The most important factor that effects investigated plant species condition is water content. The research showed that hyperspectral analysis is useful in studying human impact on vegetation cover and needs to be developed.

Analiza zależności między zawartością wody w roślinach zmierzoną w terenie a teledetekcyjnymi wskaźnikami roślinności

Niedzielko J., Milczarek M., Szepietowska M., Pokrzywnicka M., Boral B., Łach G., Kaźmierczak M., Jarocińska A.

Teledetekcja Środowiska

2012

T. 47

43--57

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.