This page appeared first in Dec 1996 - Last modified April 6, 2012.
Work related: [Main, Research, Teaching, WebLog] Other:[Family, Botanics, Amateur radio, Links, Webmail]
 ContactHome: Bölsinniityntie 13, 06830 Kulloonkylä, Finland Phone: +358 400 218305 Skype: "korpelapuonti" E-mail: ilkka-dot-korpela{}gmail-dot-com, WX in Harabacka, Rain Radar. Work: UH Forest Sc Dept in Viikki, Academy of Finland, Senior Research Fellow. Docent @ UEF, Forest inventory (CV, Publications) Latokartanonkaari 7, Metsätieteiden talo, 4th floor, r. 418, NLS-map. E-mail: ilkka-dot-korpela{}helsinki-dot-fi Snail-mail: MMVAR-Dept, POB 27, 00014 Univ. of Helsinki, Finland Phone +358 9 191 58182. These are my shared-and-accessible-from-anywhere-there's-WWW archives (1996-) hosted by University of Helsinki. © Ilkka Korpela unless otherwise noted. Activities Hyytiälä Remote Sensing Experiment 1994-: html Field measurement campaign of 2009: BLOG "Long-term" arrangement of permanent field observations and airborne remote sensing data by Ilkka Korpela et al. Field observations and metadata to RS observations are documented in the web. Editor of PileUP! Contest Journal 2006-2011: html A pdf-journal by Contest Club Finland, which I was the editor for in 6 years. The club had less than 100 members but we had 1500-5000 international readers per issue. Google-Hyytiälä 2006, Landscape changes 1946-:html, svg, avi A 3-month project we did to support 100-yr-jubilee of Hyytiälä (2010), in which the aerial images 1946-2006 were oriented and some of the 'events' seen in the imagery were documented by interviewing senior foresters and local people in Hyytiälä. |
Recent Research Full-waveform LiDAR: Low vegetation mapping - Simulated vs. real case. Using reflectance anisotrory of trees for enhanced species classification Mapping of understory trees in discrete-return LiDAR data. Detection of snow breaks in bi-temporal LiDAR data. Variation and anisotropy of reflectance of trees in ADS40 images. Non-parametric imputation in LiDAR-based single-tree remote sensing. Accuracy assessment of ADS40 reflectance calibrated images. LiDAR range- and AGC-normalization in forest vegetation classification. Tree species classification in discrete-return LiDAR data. LiDAR in the assesment of mire surface patterns, vegetation, and habitats. Teaching UH Photogrammetric forest inventory MARV4/2-07, MARV1-08, 2009, 2010, 2011 NOVA PhD-course 2009: The 3D high-resolution remote sensing data in forest inventory. UH 2009 Skogbruk runt om Östersjön -kurs: Laserkanning och fotogrammetri ppt UEF: 2010, 2012 Advanced remote sensing. Evo 2010: Sensor fusion. UH: Python programming 2011, 2012 (moodle, login as guest) Talks Photogrammetric-geodetic tree mapping, March 2008 pdf. Remote sensing in Forestry, Helsinki, May 2008 pdf. Mapping of understory lichens with LiDAR, Physense-seminar, Helsinki, June 2008 pdf. Yksittäisten puiden inventointi laser- ja ilmakuva-aineistosta, Evo, 25.11.08, pdf. Hyytiälä RS experiment. FGI Kirkkonummi, May.2009, pdf. Using discrete-return LiDAR for tree species recognition, Helsinki May 2009, pdf. Multispectral images in forest Monitoring, Gävle November 2010, pdf. Puulajitulkinta ADS40 kuvilta - Aaltomuotolaser, Evo, November 2010, pdf. Understory tree mapping using LiDAR, ISPRS Hannover, June 2011, pdf. Optical RS of mires. Ås, Norway, June 2011. pdf. LIDARin geometria ja radiometria, UH Nov 2011. pdf. Kaikki irti laserkeilauksesta, Helsinki, Dec 2011. pdf. Any sense in BRDF at tree level? Helsinki, April 4, 2012. pdf. |