The use of hyperspectral imaging for parametrization of the growing season in the context of the characteristics of soil cover
The main objective of the project is to determine parameters of the growing season - beginning, end and duration, combined with the properties of soil cover (grain-size distribution, permeability, bulk density and porosity, consistency, abundance of selected micro - and macronutrients, characteristics of organic matter, C: N ratio, iron content), at different spatial and temporal scales.
An additional aim is multi-aspect validation of remote sensing methods, among others on the basis of laboratory analyses.
The study will be carried out on twelve research plots, diversified in terms of land use. Six points will include farmland, three - grassland, three - forest land. The surfaces will vary in terms of soil and habitat; will be selected with reference to the grid square corresponding to the range of data (pixels) from satellite MODIS observations, allowing direct comparison of satellite data to the data obtained with the use of UAV and direct methods. Each of the research plots will be characterized in detail in terms of the soil cover. Throughout the study period monitoring will be carried out on the plots, covering aquisition of low-altitude hyperspectral imaging from the air vehicle (UAV). In paralel, moisture content of the soil surface will be investigated (TDR). Periodically in situ spectroradiometric measurements will be carried out as well as collection of soil samples, in which following parameters will be assessed: amount of organic carbon, total nitrogen and iron. In addition, continuous monitoring of phenological appearances will be conducted using autonomous cameras installed in each test area.
The whole locally collected spectra data will be linked to the satellite data, which will develop methods of downscalling data with low spatial resolution.
Information collected during the project will be used to develop a model, estimating the date of the individual phases of development of plants, depending on weather conditions and characteristics of the various habitats. The model will be tested on the basis of historical data from other parts of the country, which will allow evaluation of this model.
Implementation of primary and secondary objectives of the research project will verify and systematize the knowledge of the factors determining the nature and dynamics of the growing season.
Assessment of the usefulness and appropriateness of the various remote sensing methods of research in natural environment recognition will be also possible.
The issue taken in the project fits in perfectly the existing trends of searching and use of noninvasive, yet fast, low-cost and reliable research techniques.
