Search results for "kartoitus"

showing 10 items of 61 documents

Kotelosienet : Ascomycota

2019

lajistokartoitusuhanalaiset lajitkotelosienetsienetuhanalaiset sienet
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Hämähäkkieläimet : Arachnida

2019

lajistokartoitusuhanalaiset lajituhanalaiset eläimethämähäkkieläimet
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VARIABILITY OF REMOTE SENSING SPECTRAL INDICES IN BOREAL LAKE BASINS

2018

Remotely sensed hyperspectral data has widely been used to determine water quality parameters in oceanic waters. However in freshwater basins the dependence between the hyperspectral data and the parameters is more complicated. In this work some ideas are presented concerning the study of this dependence. The data used in this study were collected from the lake Hiidenvesi in southern Finland. The hyperspectral data consists of reflectances in 36 bands in the wavelength area 508…878 nm and the separately measured water quality parameters are turbidity, blue-green algae, chlorophyll, pH and dissolved oxygen. Hyperspectral data was used as bare band reflectances, but also in the …

lcsh:Applied optics. Photonics010504 meteorology & atmospheric scienceshyperspectral imaging0211 other engineering and technologiesMagnitude (mathematics)02 engineering and technologylcsh:Technology01 natural sciencesoptically complex watersTurbidity021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensinglcsh:Tlcsh:TA1501-1820Hyperspectral imagingvedenlaatuWavelengthBoreallcsh:TA1-2040Remote sensing (archaeology)spectral indicesEnvironmental sciencekaukokartoitusWater qualitylcsh:Engineering (General). Civil engineering (General)The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Minimal learning machine in anomaly detection from hyperspectral images

2020

Abstract. Anomaly detection from hyperspectral data needs computationally efficient methods to process the data when the data gathering platform is a drone or a cube satellite. In this study, we introduce a minimal learning machine for hyperspectral anomaly detection. Minimal learning machine is a novel distance-based classification algorithm, which is now modified to detect anomalies. Besides being computationally efficient, minimal learning machine is also easy to implement. Based on the results, we show that minimal learning machine is efficient in detecting global anomalies from the hyperspectral data with low false alarm rate.

lcsh:Applied optics. PhotonicsComputer sciencehyperspectral imagingData needs0211 other engineering and technologies02 engineering and technologylcsh:TechnologyConstant false alarm rateremote sensing0202 electrical engineering electronic engineering information engineering021101 geological & geomatics engineeringData collectionlcsh:Tbusiness.industryspektrikuvausProcess (computing)lcsh:TA1501-1820Hyperspectral imagingPattern recognitionminimal learning machineDroneanomaly detectionkoneoppiminenMinimal learning machinelcsh:TA1-2040020201 artificial intelligence & image processingAnomaly detectionArtificial intelligencekaukokartoituslcsh:Engineering (General). Civil engineering (General)business
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Autonomous hyperspectral UAS photogrammetry for environmental monitoring applications

2014

Abstract. The unmanned airborne system (UAS) remote sensing using lightweight multi- and hyperspectral imaging sensors offer new possibilities for the environmental monitoring applications. Based on the accurate measurements of the way in which the object reflect and emit energy, wide range of affecting variables can be monitored. Condition for reliable applications is reliable and accurate input data. In many applications, installation of geometric and radiometric reference targets in the object area is challenging, for instance, in forest or water areas. On the other hand, UASs are often operated in very poor conditions, under clouds or under variable cloud cover. Our objective is to deve…

lcsh:Applied optics. PhotonicsgeometryPoint cloudradiometryphotogrammetrylcsh:Technologykalibrointiremote sensingEnvironmental monitoringRemote sensingBlock (data storage)fotogrammetriaData processingblockForest inventorylcsh:Tlcsh:TA1501-1820Hyperspectral imagingcalibrationGeographyPhotogrammetryhyperspectrallcsh:TA1-2040Precision agriculturekaukokartoitusgeometriaUASlcsh:Engineering (General). Civil engineering (General)point cloud
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Updating strategies for distance based classification model with recursive least squares

2022

Abstract. The idea is to create a self-learning Minimal Learning Machine (MLM) model that is computationally efficient, easy to implement and performs with high accuracy. The study has two hypotheses. Experiment A examines the possibilities of introducing new classes with Recursive Least Squares (RLS) updates for the pre-trained self learning-MLM model. The idea of experiment B is to simulate the push broom spectral imagers working principles, update and test the model based on a stream of pixel spectrum lines on a continuous scanning process. Experiment B aims to train the model with a significantly small amount of labelled reference points and update it continuously with (RLS) to reach ma…

luokitus (toiminta)Minimal Learning Machinemachine learningkoneoppiminenclassificationhyperspectral imagingkaukokartoitusRecursive Least Squaresreal-time computationhyperspektrikuvantaminen
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What makes segmentation good? A case study in boreal forest habitat mapping

2013

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 as reference polygons agains…

luokitus (toiminta)Watershedbusiness.industryComputer scienceSegmentation-based object categorizationta1172ta1171Scale-space segmentationImage segmentationMachine learningcomputer.software_genreRandom forestsegmentointiRankingGeneral Earth and Planetary SciencesSegmentationArtificial intelligencekaukokartoitusbusinessDigital elevation modelcomputerlidarlaserkeilausluokitusInternational Journal of Remote Sensing
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Miten kymmenjärjestelmä hallitaan peruskoulun viidennellä luokalla?

2014

Ilonen, L. & Kangas, P. 2014. Miten kymmenjärjestelmä hallitaan peruskoulun viidennellä luokalla? Jyväskylän yliopisto. Kokkolan yliopistokeskus Chydenius. Kasvatustieteen pro gradu –tutkielma. 68 s. ja 3 liitettä. Kymppi-kartoitus on materiaali, jota voidaan käyttää kymmenjärjestelmän osaamisen kartoittamiseen perusopetuksessa. Tutkimuksen tarkoituksena oli selvittää Kymppi-kartoituksen avulla kymmenjärjestelmän hallintaa peruskoulun viidennellä luokalla. Kohdejoukkona oli erään pirkanmaalaisen koulun 79 viidennen luokan oppilasta, jotka tekivät kartoituksen huhtikuussa 2013. Tutkimusmenetelmänä käytimme mixed methods –menetelmää, jossa yhdistyy määrällinen ja laadullinen tutkimus. Määräll…

matematiikkaoppiminenvarhaiset matemaattiset taidotmatematiikan oppiminenmatemaattiset taidotkymmenjärjestelmäKymppi-kartoitusalakoulu
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Editorial for the Special Issue “Frontiers in Spectral Imaging and 3D Technologies for Geospatial Solutions”

2019

This Special Issue hosts papers on the integrated use of spectral imaging and 3D technologies in remote sensing, including novel sensors, evolving machine learning technologies for data analysis, and the utilization of these technologies in a variety of geospatial applications. The presented results showed improved results when multimodal data was used in object analysis.

medicine.medical_specialtyGeospatial analysisComputer sciencehyperspectral imagingSciencecomputer.software_genrehyperspectral imaging; point cloud; sensor integration; data fusion; machine learning; deep learning; classification; estimation; semantic segmentation; object detection; point cloud filteringmedicine3D-mallinnussensor integrationpoint cloud filteringdata fusionestimationbusiness.industryDeep learningspektrikuvausQHyperspectral imagingdeep learningobject detectionSensor fusionObject (computer science)Data scienceObject detectionsemantic segmentationSpectral imagingVariety (cybernetics)classificationpoint cloud filteringsegmentointikoneoppiminenmachine learningclassificationGeneral Earth and Planetary SciencesArtificial intelligencekaukokartoitusbusinesscomputerpoint cloudRemote Sensing
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Toimialan vaikutus laskentatoimeen : tarkastelussa suomalainen vaatetusteollisuus

1998

mentaalikartoituskausaalikarttavaatetusteollisuuslaskentatoimistrategiatoimiala
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