{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T13:13:44Z","timestamp":1778591624369,"version":"3.51.4"},"reference-count":37,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2014,5,21]],"date-time":"2014-05-21T00:00:00Z","timestamp":1400630400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The vegetation in the forest-tundra ecotone zone is expected to be highly affected by climate change and requires effective monitoring techniques. Airborne laser scanning (ALS) has been proposed as a tool for the detection of small pioneer trees for such vast areas using laser height and intensity data. The main objective of the present study was to assess a possible improvement in the performance of classifying tree  and nontree laser echoes from high-density ALS data. The data were collected along  a 1000 km long transect stretching from southern to northern Norway. Different geostatistical and statistical measures derived from laser height and intensity values were used to extent and potentially improve more simple models ignoring the spatial context. Generalised linear models (GLM) and support vector machines (SVM) were employed as classification methods. Total accuracies and Cohen\u2019s kappa coefficients were calculated and compared to those of simpler models from a previous study. For both classification methods, all models revealed total accuracies similar to the results of the simpler models. Concerning classification performance, however, the comparison of the kappa coefficients indicated a significant improvement for some models both using GLM and SVM, with classification accuracies &gt;94%.<\/jats:p>","DOI":"10.3390\/rs6054582","type":"journal-article","created":{"date-parts":[[2014,5,21]],"date-time":"2014-05-21T10:38:31Z","timestamp":1400668711000},"page":"4582-4599","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Improving Classification of Airborne Laser Scanning Echoes in the Forest-Tundra Ecotone Using Geostatistical and Statistical Measures"],"prefix":"10.3390","volume":"6","author":[{"given":"Nadja","family":"Stumberg","sequence":"first","affiliation":[{"name":"Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 \u00c5s, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2230-1288","authenticated-orcid":false,"given":"Marius","family":"Hauglin","sequence":"additional","affiliation":[{"name":"Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 \u00c5s, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ole","family":"Bollands\u00e5s","sequence":"additional","affiliation":[{"name":"Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 \u00c5s, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5534-049X","authenticated-orcid":false,"given":"Terje","family":"Gobakken","sequence":"additional","affiliation":[{"name":"Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 \u00c5s, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erik","family":"N\u00e6sset","sequence":"additional","affiliation":[{"name":"Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 \u00c5s, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2014,5,21]]},"reference":[{"key":"ref_1","unstructured":"Watson, R., Zinyowerea, M.C., and Moss, R.H. (1996). Climate Change 1995: Impacts, Adaptations and Mitigation of Climate Change: Scientific-Technical Analysis. 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