Articles containing the keyword 'mapping'

Silva Fennica Issue 69 includes presentations held in 1948-1950 in the fourth professional development courses, arranged for foresters working in the Forest Service. The presentations focus on practical issues in forest management and administration, especially in regional level. The education was arranged by Forest Service.

Forest Service begun the aerial mapping of the state forests in northern Finland in 1948. This presentation describes the state of the work, practices and methods of the work.

• Olenius, E-mail: lo@mm.unknown

Silva Fennica Issue 69 includes presentations held in 1948-1950 in the fourth professional development courses, arranged for foresters working in the Forest Service. The presentations focus on practical issues in forest management and administration, especially in regional level. The education was arranged by Forest Service.

This presentation describes the development of aerial mapping, its principles and methods. The use of aerial photographs and the costs of the method is discussed.

• Linnamies, E-mail: ol@mm.unknown

A new method for the co-registration of single tree data in forest stands and forest plots applicable to static as well as dynamic data capture is presented. This method consists of a stem diameter weighted linking algorithm that improves the linking accuracy when operating on diverse diameter stands with stem position errors in the single tree detectors. A co-registration quality metric threshold, Q_T, is also introduced which makes it possible to discriminate between correct and incorrect stem map co-registrations with high probability (>99%). These two features are combined to a simultaneous location and mapping-based co-registration method that operates with high linking accuracy and that can handle sensors with drifting errors and signal bias. A test with simulated data shows that the method has an 89.35% detection rate. The statistics of different settings in a simulation study are presented, where the effect of stem density and position errors were investigated. A test case with real sensor data from a forest stand shows that the average nearest neighbor distances decreased from 1.90 m to 0.51 m, which indicates the feasibility of this method.

• Olofsson, Section of Forest Remote Sensing, Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden https://orcid.org/0000-0002-2836-2316 E-mail: kenneth.olofsson@slu.se
• Holmgren, Section of Forest Remote Sensing, Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden https://orcid.org/0000-0002-7112-8015 E-mail: johan.holmgren@slu.se

Dalbergia latifolia Roxb., commonly known as rosewood, is one of the highly valuable tropical timber species of Nepal. The tree species was widely distributed in the past, however, over-exploitation of natural habitat, deforestation, forest conversion for agriculture, illegal logging and the invasion of alien species resulted in the classification of this species as vulnerable by the IUCN (International Union for Conservation of Nature) category. So, the prediction of habitat suitability and potential distribution of the species is required to develop restoration mechanisms and conservation interventions. In this study, we modelled the suitable habitat of D. latifolia over the entire possible range of Nepal using a Maxent model. We compiled 23 environmental variables (19 bioclimatic, 3 topographic and a vegetative layer), however, only 12 least correlated variables along with 43 spatially representative presence locations were retained for model prediction. We used a receiver operating characteristic (ROC) curve to assess the model’s performance and a Jackknife procedure to evaluate the relative importance of predictor variables. The model was statistically significant with an area under the curve (AUC) value of 0.969. The internal Jackknife test indicated that elevation was the most important variable for the model prediction with 71.3% contribution followed by mean temperature of driest quarter (9.8%). The most (>0.6) suitable habitat for the D. latifolia was 235 484 hectares with large sections of area in two provinces whereas, the western most provinces were not suitable for D. latifolia as per Maxent model. The information presented here can provide a framework for nature conservation planning, monitoring and habitat management of this rare and endangered species.

• Mahatara, Forest Research and Training Centre, Government of Nepal, P.O. Box 3339, Babarmahal, Kathmandu 44600, Nepal E-mail: honeystar73@gmail.com
• Acharya, Forest Research and Training Centre, Government of Nepal, P.O. Box 3339, Babarmahal, Kathmandu 44600, Nepal E-mail: acharya.amulkumar@gmail.com
• Dhakal, Forest Research and Training Centre, Government of Nepal, P.O. Box 3339, Babarmahal, Kathmandu 44600, Nepal E-mail: dhakalbp.shorea@gmail.com
• Sharma, Forest Research and Training Centre, Government of Nepal, P.O. Box 3339, Babarmahal, Kathmandu 44600, Nepal E-mail: dipeshsharmadiyu2015@gmail.com
• Ulak, Forest Research and Training Centre, Government of Nepal, P.O. Box 3339, Babarmahal, Kathmandu 44600, Nepal E-mail: sunitaulak@gmail.com
• Paudel, Agriculture Forestry University, P.O. Box 13712 Rampur, Chitwan, Nepal E-mail: prashant.paudel88@gmail.com

Novel information on silver birch (Betula pendula Roth) foliar element contents and their seasonal, between-habitat and leaf level variations are provided by applying fine-scaled element mapping with micro X-ray fluorescence. In the monthly leaf samples collected from May to October from six different habitats, pairwise scatter plots and Spearman’s rank correlations showed statistically significant positive correlations between Si, Al and Fe, and covariations between also many other pairs of elements. Of the ten elements studied, seven showed statistically significant changes in their average levels between May and June. The contents of P, S and K decreased in most habitats during the later season, whereas Ca and in some habitats also Mn and Zn increased. Comparing habitats, trees in the limestone habitat had relatively low content of Mg, strongly increasing levels of P until the late season, and high content of Ca and Fe. Other habitats also revealed distinctive particularities in their foliar elements, such as a high relative content of S and a low content of Ca at the seashore. Mn was high in three habitats, possibly due to bedrock characteristics. Except for P, the contents of all elements diverged between the midrib and other leaf areas. Zn content was particularly high in the leaf veins. Mn levels were highest at the leaf margins, indicating a possible sequestration mechanism for this potentially harmful element. Si may help to alleviate the metallic toxicities of Al and Fe. Because the growing season studied was dry, some trees developed symptoms of drought stress. The injured leaf parts had reduced levels of P, S and K, suggesting translocation of these nutrients before permanent damage.

• Kalliola, Department of geography and geology, University of Turku, FI-20014 Turku, Finland https://orcid.org/0000-0003-2454-8217 E-mail: risto.kalliola@utu.fi
• Saarinen, Department of geography and geology, University of Turku, FI-20014 Turku, Finland E-mail: tijusa@utu.fi
• Tanski, Department of geography and geology, University of Turku, FI-20014 Turku, Finland E-mail: niko.tanski@utu.fi

In remote sensing-based forest inventories 3D point cloud data, such as acquired from airborne laser scanning, are well suited for estimating the volume of growing stock and stand height, but tree species recognition often requires additional optical imagery. A combination of 3D data and optical imagery can be acquired based on aerial imaging only, by using stereo photogrammetric 3D canopy modeling. The use of aerial imagery is well suited for large-area forest inventories, due to low costs, good area coverage and temporally rapid cycle of data acquisition. Stereo-photogrammetric canopy modeling can also be applied to previously acquired imagery, such as for aerial ortho-mosaic production, assuming that the imagery has sufficient stereo overlap. In this study we compared two stereo-photogrammetric canopy models combined with contemporary satellite imagery in forest inventory. One canopy model was based on standard archived imagery acquired primarily for ortho-mosaic production, and another was based on aerial imagery whose acquisition parameters were better oriented for stereo-photogrammetric canopy modeling, including higher imaging resolution and greater stereo-coverage. Aerial and satellite data were tested in the estimation of growing stock volume, volumes of main tree species, basal area and diameter and height. Despite the better quality of the latter canopy model, the difference of the accuracy of the forest estimates based on the two different data sets was relatively small for most variables (differences in RMSEs were 0–20%, depending on variable). However, the estimates based on stereo-photogrammetrically oriented aerial data retained better the original variation of the forest variables present in the study area.

• Tuominen, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, P.O. Box 2, FI-00791 Helsinki, Finland E-mail: sakari.tuominen@luke.fi
• Balazs, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, P.O. Box 2, FI-00791 Helsinki, Finland E-mail: andras.balazs@luke.fi
• Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: annika.kangas@luke.fi

• Niemi, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland & Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute FGI, Geodeetinrinne 2, FI-02430, Finland E-mail: mikko.t.niemi@helsinki.fi
• Vastaranta, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland & Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute FGI, Geodeetinrinne 2, FI-02430, Finland E-mail: mikko.vastaranta@helsinki.fi
• Peuhkurinen, Arbonaut Oy Ltd., Latokartanontie 7 A, FI-00700, Finland E-mail: jussi.peuhkurinen@arbonaut.com
• Holopainen, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland & Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute FGI, Geodeetinrinne 2, FI-02430, Finland E-mail: markus.holopainen@helsinki.fi

• Rekola, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki E-mail: mika.rekola@helsinki.fi
• Valkeapää, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki E-mail: av@nn.fi
• Rantala, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki E-mail: tapio.rantala@helsinki.fi

• Kangas, University of Helsinki, Department of Forest Management, P.O. Box 27, FI-00014 University of Helsinki E-mail: annika.kangas@helsinki.fi
• Haapakoski, University of Helsinki, Department of Forest Management, P.O. Box 27, FI-00014 University of Helsinki E-mail: rh@nn.fi
• Tyrväinen, Finnish Forest Research Institute, P.O. Box 16, FI-96301 Rovaniemi, Finland. E-mail: lt@nn.fi