Browsing by Subject "defoliation"

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  • Kantola, Tuula; Vastaranta, Mikko; Yu, Xiaowei; Lyytikäinen-Saarenmaa, Päivi; Holopainen, Markus; Talvitie, Mervi; Kaasalainen, Sanna; Solberg, Svein; Hyyppä, Juha (2010)
    Climate change and rising temperatures have been observed to be related to the increase of forest insect damage in the boreal zone. The common pine sawfly (Diprion pini L.) (Hymenoptera, Diprionidae) is regarded as a significant threat to boreal pine forests. Defoliation by D. pini can cause severe growth loss and tree mortality in Scots pine (Pinus sylvestris L.) (Pinaceae). In this study, logistic LASSO regression, Random Forest (RF) and Most Similar Neighbor method (MSN) were investigated for predicting the defoliation level of individual Scots pines using the features derived from airborne laser scanning (ALS) data and aerial images. Classification accuracies from 83.7% (kappa 0.67) to 88.1% (kappa 0.76) were obtained depending on the method. The most accurate result was produced using RF with a combination of data from the two sensors, while the accuracies when using ALS and image features separately were 80.7% and 87.4%, respectively. Evidently, the combination of ALS and aerial images in detecting needle losses is capable of providing satisfactory estimates for individual trees.
  • Junttila, Samuli (Helsingin yliopisto, 2014)
    The effect of forest health and structure to the relative surface temperature captured by airborne thermal imagery was investigated in Norway Spruce-dominated stands in Southern Finland. Canopy surface temperature has long been recognized useful in monitoring vegetation water status. Recent studies have shown also its potential in monitoring vegetation health. Airborne thermal imagery, Airborne Light Detection and Ranging (LiDAR) and field measurements were acquired from the area of interest (AOI). The relative surface temperature correlated most negatively with the logarithm of stem volume, Lorey’s height and logarithm of basal area at resolution of 254m2 (9-m radius). In other words, taller and older stands had colder surface temperatures. In addition, LiDAR metrics, such as height percentiles and canopy cover percentage, were compared with surface temperature. Standard deviation of canopy height model, height features (H90, CHM_max) and canopy cover percentage were most strongly negatively correlated with the surface temperature. On average, higher surface temperatures were detected in defoliated canopies indicating that thermal images may provide some additional information for classifying forests health status. However, the surface temperature of defoliated plots varied considerably. It was also found that surface temperature differences between canopy and ground responses were higher in defoliated plots. Based on the results, forest health and structure affect to the surface temperature captured by airborne thermal imagery and these effects should be taken into account when developing forest health mapping applications using thermal imagery.
  • Junttila, Oula Samuli; Vastaranta, Mikko Antero; Hämäläinen, Jarno; Latva-käyrä, Petri; Holopainen, Markus Edvard; Hernandez-Clemente, Rocio; Hyyppä, Hannu; Navarro-Cerrillo, Rafael (2017)
    The effect of forest structure and health on the relative surface temperature captured by airborne thermal imagery was investigated in Norway Spruce-dominated stands in Southern Finland. Airborne thermal imagery, airborne scanning light detection and ranging (LiDAR) data and 92 field-measured sample plots were acquired at the area of interest. The surface temperature correlated most negatively with the logarithm of stem volume, Lorey’s height and the logarithm of basal area at a resolution of 254 m2 (9-m radius). LiDAR-derived metrics: the standard deviations of the canopy heights, canopy height (upper percentiles and maximum height) and canopy cover percentage were most strongly negatively correlated with the surface temperature. Although forest structure has an effect on the detected surface temperature, higher temperatures were detected in severely defoliated canopies and the difference was statistically significant. We also found that the surface temperature differences between the segmented canopy and the entire plot were greater in the defoliated plots, indicating that thermal images may also provide some additional information for classifying forests health status. Based on our results, the effects of forest structure on the surface temperature captured by airborne thermal imagery should be taken into account when developing forest health mapping applications using thermal imagery.
  • Latva-Käyrä, Petri (Helsingfors universitet, 2012)
    The intensity and frequency of insect outbreaks have increased in Finland in the last decades and they are expected to increase even further in the future due to global climate change. In 1998-2001 Finland suffered the most severe insect outbreak ever recorded, over 500,000 hectares. The outbreak was caused by the common pine sawfly (Diprion pini L.). The outbreak has continued in the study area, Palokangas, ever since. To find a good method to monitor this type of outbreaks, the purpose of this study was to examine the efficacy of multitemporal ERS-2 and ENVISAT SAR imagery for estimating Scots pine defoliation. The study area, Palokangas, is located in Ilomantsi district, Eastern-Finland and consists mainly even-aged Scots pine forests on relatively dry soils. Most of the forests in the area are young or middle-aged managed forests. The study material was comprised of multi-temporal ERS-2 and ENVISAT synthetic aperture radar (SAR) data. The images had been taken between the years 2001 and 2008. The field data consisted 16 sample plots which had been measured seven times between the years 2002 and 2009. In addition, eight sample plots were added afterwards to places which were known to have had cuttings during the study period. Three methods were tested to estimate Scots pine defoliation: unsupervised k-means clustering, supervised linear discriminant analysis (LDA) and logistic regression. In addition, it was assessed if harvested areas could be differentiated from the defoliated forest using the same methods. Two different speckle filters were used to determine the effect of filtering on the SAR imagery and subsequent results. The logistic regression performed best, producing a classification accuracy of 81.6% (kappa 0.62) with two classes (no defoliation, >20% defoliation). LDA accuracy was with two classes at best 77.7% (kappa 0.54) and k-means 72.8 (0.46). In general, the largest speckle filter, 5 x 5 image window, performed best. When additional classes were added the accuracy was usually degraded on a step-by-step basis. The results were good, but because of the restrictions in the study they should be confirmed with independent data, before full conclusions can be made that results are reliable. The restrictions include the small size field data and, thus, the problems with accuracy assessment (no separate testing data) as well as the lack of meteorological data from the imaging dates.
  • Lyytikäinen, Minna (Helsingfors universitet, 2013)
    Climate change and following extreme weather patterns can increase forest damages caused by pest insects especially in higher latitudes. The number, density and intensity of damages by pest insects already have increased because of the changing conditions. Pest insects can e.g. cause reduced tree growth and even tree death. Defoliation by the Common Pine Sawfly (Diprion pini L.) causes severe growth losses and tree mortality of Scots Pine (Pinus sylvestris L.). D. pini has caused damages in Finland over 500 000 hectares between years 1997–2001. The field work was carried out in Palokangas area, Ilomantsi, eastern Finland in years 2002–2010. Stand- and tree-wise characteristics were measured on 11 plots. Tree-wise defoliation with 10% accuracy and amount of D. pini cocoons and fallen shoots of P. sylvestris were estimated annually. In addition, radial tree growths were measured from total of n trees in 2010. The aim this study was to estimate the effect of the natural enemies on population densities of D. pini. The aim was also to estimate the effect of the defoliation caused by D. pini on tree growth. In addition, the aim was also to estimate the consequence of a beetle attack by pith borers (Tomicus spp.) to the defoliation. Effect of natural enemies as regulative factors was estimated from D. pini cocoons. Natural enemies were divided into birds, small mammals and to insect families of Ichneumonidae, Chalcidoidea, Tachinidae, Elateridae and Carabidae. Consequence of beetle attack was assessed from fallen shoots. Tree growth simulation was used to estimate economic losses. Growth losses were estimated from drill chip sample. Logistic regression was used to explicate tree-wise defoliation with tree- and stand-wise variables. Two different classification schemes with threshold values of 20% (class 1) and 30% (class 2) of defoliation were used in regression. The major regulative factor was Ichneumonid parasites (22%) and the second powerful regulative factor was small mammals (21%). Relative proportion of natural enemies increased along the research period as defoliation percentages decreased. Consequence of beetle attack was most violent in 2004 (17 shoots/ m²). Plot-wise defoliation level varied significantly between the years and the plots. The mean defoliation level was 37% in 2002 and 22% in 2010. The most substantial defoliation was in plot 9 in 2005, over 99%. Simulated economic losses were perceptible only on plots 9 and 16; 2785 € and 1623 € per hectare, respectively. Defoliation by D. pini caused growth losses for radial growth in different defoliation classes. The mean growth loss of severe damaged trees (70–100% of defoliation) was approximately 65% and of trees with low defoliation level (0–10% of defoliation) 40%. Classification accuracy of logistic regression for class 1 was 92.4% with kappa value of 0.81 and 94.2% and 0.84 for class 2, respectively. The results of this study showed that control of natural enemies effected on D. pini density. Population density of D. pini affected the defoliation level; when population density was low the defoliation was milder. Peak sawfly densities can affect tree growth during outbreaks. Consequence beetle attack by the pith borers was only slight and delayed.