publication . Doctoral thesis . Article . 2013

What makes segmentation good? A case study in boreal forest habitat mapping

Markku Kuitunen; Aleksi Räsänen; Anssi Lensu; Antti T. Rusanen;
Open Access English
  • Published: 01 Jan 2013
  • Publisher: University of Jyväskylä
  • Country: Finland
Abstract
Segmentation goodness evaluation is a set of approaches meant for deciding which segmentation is good. In this study, we tested different supervised segmentation evaluation measures and visual interpretation in the case of boreal forest habitat mapping in Southern Finland. The data used were WorldView-2 satellite imagery, a lidar digital elevation model (DEM), and a canopy height model (CHM) in 2 m resolution. The segmentation methods tested were the fractal net evolution approach (FNEA) and IDRISI watershed segmentation. Overall, 252 different segmentation methods, layers, and parameter combinations were tested. We also used eight different habitat delineations...
Subjects
free text keywords: elinympäristötyypit, suojeluarvot, lajirunsaus, airborne laser scanning, conservation value, habitat type, object-based image analysis, segmentation, species richness, spectral images, metsämaisema, habitaatti, objektiperustainen kuva-analyysi, kaukokartoitus, paikkatietomenetelmät, luokittelumenetelmät, segmentointi, laserkeilaus, elinympäristöluokittelu, ta1171, ta1172, General Earth and Planetary Sciences, ta1183, luokitus, remote sensing, lidar, classification, Machine learning, computer.software_genre, computer, Segmentation-based object categorization, Watershed, Ranking, Random forest, Computer science, Scale-space segmentation, Digital elevation model, Artificial intelligence, business.industry, business, Image segmentation
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