%0 Journal Article
%T Simple Method of Forest Type Inventory by Joining Low Resolution Remote Sensing of Vegetation Indices with Spatial Information from the Corine Land Cover Database
%A Jaros£¿aw J. Zawadzki
%A Karol Prze£¿dziecki
%A Karol Szymankiewicz
%A Wojciech Marczewski
%J ISRN Forestry
%D 2013
%R 10.1155/2013/529193
%X The paper presents a simple, inexpensive, and effective method allowing for frequent classification of the forest type coniferous, deciduous, and mixed using medium and low resolution remote sensing images. The proposed method is based on the set of vegetation indices such as NDVI, LAI, FAPAR, and LAIxCab calculated from MODIS and MERIS satellite data. The method uses seasonal changes of the above-mentioned vegetation indices within annual cycle. The main idea was to collect and carefully analyse seasonal changes in vegetation indices in a given ecosystem type proven by a Corine Land Cover, 2006 database, and to compare them afterwards with those of a particular forest under study. Each type of a forest ecosystem has its own specific dynamics of development, thus enabling recognition of the type by comparing temporal changes of the proposed measures based on vegetation indices. Temporal measures of changes were created for selected reference stands by the ratios of particular indices determined in July and April, which are the middle and the beginning of a vegetation season in Poland, respectively. The analysed vegetation indices were additionally provided with chosen statistical measures. The statistical analyses were carried out for Poland¡¯s main national parks which represent the natural stands of temperate climate. 1. Introduction Forests cover about 31% of the land [1], and their role in the natural environment and in human activities is essential. For example, forests have a significant influence on the composition of dust and atmospheric gases, air and soil temperature, the amount of water present, and forested areas, both in soil and in vegetation cover. Forests also play an important role in the exchange of water between the soil and the atmosphere. Forest management requires timely and accurate information on forests [2] and remote sensing methods have been used for forest inventory for decades [3¨C5]. A major problem in forest research is the diversity of ecosystems, which provides for the possible couplings of various physical and biological processes, especially when there is a need of mesoscale assessments. It is therefore essential how large areas can be represented by the data (satellite, terrestrial, and statistical assessment) and what time resolution measurements are performed with. For all these reasons, studies on forest ecosystem, have always required considerable effort and resources. In remote observations of forests, spectral analysis allows for the determination of various biophysical parameters such as NDVI, LAI (leaf area
%U http://www.hindawi.com/journals/isrn.forestry/2013/529193/