Habitat metrics based on multi‐temporal Landsat imagery for mapping large mammal habitat

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: In: Remote sensing in ecology and conservation, Band 6, Ausgabe 1, Seite 52-69, 2019

Event: Veröffentlichung

(where): Berlin

(who): Humboldt-Universität zu Berlin

(when): 2020

Creator: Oeser, Julian
Heurich, Marco
Senf, Cornelius
Pflugmacher, Dirk
Belotti, Elisa
Kuemmerle, Tobias

DOI: 10.18452/22249

URN: urn:nbn:de:kobv:11-110-18452/22869-5

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 25.03.2025, 1:46 PM CET

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Associated

Oeser, Julian
Heurich, Marco
Senf, Cornelius
Pflugmacher, Dirk
Belotti, Elisa
Kuemmerle, Tobias
Humboldt-Universität zu Berlin

Time of origin

2020

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Instance segmentation of standing dead trees in dense forest from aerial imagery using deep learning

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Habitat metrics based on multi‐temporal Landsat imagery for mapping large mammal habitat

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Other Objects (12)

Habitat metrics based on multi‐temporal Landsat imagery for mapping large mammal habitat

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Instance segmentation of standing dead trees in dense forest from aerial imagery using deep learning

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Habitat metrics based on multi‐temporal Landsat imagery for mapping large mammal habitat

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Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat

Satellite‐based habitat monitoring reveals long‐term dynamics of deer habitat in response to forest disturbances

Satellite‐based habitat monitoring reveals long‐term dynamics of deer habitat in response to forest disturbances

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Remotely Sensed Single Tree Data Enable the Determination of Habitat Thresholds for the Three-Toed Woodpecker (Picoides tridactylus)

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Waldentwicklung im Bergwald nach Windwurf und Borkenkäferbefall

Instance segmentation of standing dead trees in dense forest from aerial imagery using deep learning

Assessing combinations of Landsat, Sentinel-2 and Sentinel-1 time series for detecting bark beetle infestations

Sensitivity of Landsat-8 OLI and TIRS data to foliar properties of early stage bark beetle (Ips typographus, L.) infestation

Habitat metrics based on multi‐temporal Landsat imagery for mapping large mammal habitat

Evaluating expert‐based habitat suitability information of terrestrial mammals with GPS‐tracking data

Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat

Satellite‐based habitat monitoring reveals long‐term dynamics of deer habitat in response to forest disturbances

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Evaluierung und Entwicklung von Methoden zur automatisierten Erfassung von Waldstrukturen aus Daten flugzeuggetragener Fernerkundungssensoren

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Instance segmentation of standing dead trees in dense forest from aerial imagery using deep learning

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Sensitivity of Landsat-8 OLI and TIRS data to foliar properties of early stage bark beetle (Ips typographus, L.) infestation

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