Automated tree detection and crown delineation using airborne laser scanner data in heterogeneous East-Central Europe forest with different species mix

Identifying tree locations is a basic step in the derivation of other tree parameters using remote sensing techniques, particularly when using airborne laser scanning. There are several techniques for identifying tree positions. In this paper, we present a raster-based method for determining tree position and delineating crown coverage. We collected data from nine research plots that supported different mixes of species. We applied a raster-based method to raster layers with six different spatial resolutions and used terrestrial measurement data as reference data. Tree identification at a spatial resolution of 1.5 m was demonstrated to be the most accurate, with an average identification ratio (IR) of 95% and average detection ratio of 68% being observed. At a higher spatial resolution of 0.5 m, IR was overestimated by more than 600%. At a lower spatial resolution of 3 m, IR was underestimated at less than 44% of terrestrial measurements. The inventory process was timed to enable evaluation of the time efficiency of automatic methods.

THE BROAD SENSE CONCEPT AND CALCULATION METHODS OF TREE CROWN OVERLAP

The broad sense overlap concept and types of tree crown overlap were defined in the paper through analping function between the factors of tree crown overlap. The formulas of overlap area and overlap rate were derived from definite integral form. At the same time, many formulas were acquired while the projective figures of tree crown were circle. Application ways of these formulae were illustrated with a concrete caculation process.

Effects of Persian turpentine tree litter and slope aspect on soil chemical properties in a Zagros forest,Iran

For analyzing the effects of forest litter and slope aspect on soil properties eight soil samples were collected at a depth of 0–10 cm near(i.e.,beneath the crown)and away from(i.e.,not influenced by crown)five Persian turpentine trees each on a north and a south slope at the same elevation in a Zagros forest,Iran.The litter beneath tree crowns and slope exposure were found to have significant interactive effects on C,N,P,K,and electrical conductivity of the soils,however,Ca,Mg and the soil pH were not significantly influenced by these factors.The soil beneath the crowns was enriched in cations compared to more distal positions.Generally,Persian turpentine trees have positive impacts on soil properties in the forest.Degrading or killing these trees by sap extraction,extreme grazing,cutting,fire and expansion of agriculture will lead to significant losses in soil fertility and increases in soil erosion.

An automatic extraction method for individual tree crowns based on self-adaptive mutual information and tile computing

Forest data acquisition,which is of crucial importance for modeling global biogeochemical cycles and climate,makes a contribution to building the ecological Digital Earth(DE).Due to the complex calculations and large volumes of data associated with high-resolution images of large areas,accurate and effective extraction of individual tree crowns remains challenging.In this study,two GeoEye-1 panchromatic images of Beihai and Ningbo in China with areas of 5 and 25 km2,respectively,were used as experimental data to establish a novel method for the automatic extraction of individual tree crowns based on a self-adaptive mutual information(SMI)algorithm and tile computing technology(SMI-TCT).To evaluate the performance of the algorithm,four commonly used algorithms were also applied to extract the individual tree crowns.The overall accuracy of the proposed method for the two experimental areas was superior to that of the four other algorithms,with maximum extraction accuracies of 85.7%and 63.8%.Moreover,the results also indicated that the novel method was suitable for individual tree crowns extraction in sizeable areas because of the multithread parallel computing technology.

Estimating Stem Volume Using QuickBird Imagery and Allometric Relationships for Open Populus xiaohei Plantations

There has been a great deal of interest in studying the crown of trees using remote sensing data. In this study, crown width was extracted from high-resolution QuickBird images for open Populus xiaohei plantations. Regression models for predicting the individual stem volumes of Populus xiaohei were established using extracted crown width, as well as estimated tree parameters （i.e. diameter at breast height [DBH] and tree height） as predictors. Our results indicated that crown width could be accurately extracted from QuickBird images using a multi-scale segmentation approach with a mean relative error of 5.74%, especially for wide-spacing stands. Using either extracted crown width alone or with estimated DBH and tree height can successfully estimate individual stem volume of Populus xiaohei with the R2 value ranging from 0.87 to 0.92 depending on different model forms. In particular, the two second-order polynomial models （model 2 and model 6）, based on QuickBird image-derived crown widths and estimated DBH and tree heights, respectively, were the best at describing the relationship between stem volume and tree characteristics.