ACCURACY COMPARISON OF DIGITAL SURFACE MODELS CREATED BY UNMANNED AERIAL SYSTEMS IMAGERY AND TERRESTRIAL LASER SCANNER
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
ACCURACY COMPARISON OF DIGITAL SURFACE MODELS CREATED BY UNMANNED AERIAL SYSTEMS IMAGERY AND TERRESTRIAL LASER SCANNER ; volume:XL-1/W2 ; year:2013 ; pages:281-286
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XL-1/W2 (2013), 281-286
- Urheber
- DOI
-
10.5194/isprsarchives-XL-1-W2-281-2013
- URN
-
urn:nbn:de:101:1-2017121142961
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:25 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Naumann, Matthias
- Geist, Michael
- Bill, Ralf
- Niemeyer, Frank
- Grenzdörffer, Görres
Ähnliche Objekte (12)
INTEGRATING TERRESTRIAL LIDAR WITH POINT CLOUDS CREATED FROM UNMANNED AERIAL VEHICLE IMAGERY
Assessing water erosion processes in degraded area using unmanned aerial vehicle imagery
UNMANNED AERIAL VEHICLES PRODUCE HIGH-RESOLUTION, SEASONALLY-RELEVANT IMAGERY FOR CLASSIFYING WETLAND VEGETATION
POST-FIRE FORESTRY RECOVERY MONITORING USING HIGH-RESOLUTION MULTISPECTRAL IMAGERY FROM UNMANNED AERIAL VEHICLES
Identifying rice field weeds from unmanned aerial vehicle remote sensing imagery using deep learning
DEVELOPING SPECIES SPECIFIC VEGETATION MAPS USING MULTI-SPECTRAL HYPERSPATIAL IMAGERY FROM UNMANNED AERIAL VEHICLES
ASSESSMENT OF THE QUALITY OF DIGITAL TERRAIN MODEL PRODUCED FROM UNMANNED AERIAL SYSTEM IMAGERY
Mission planning for unmanned aerial vehicles
UNMANNED AERIAL VEHICLE IN CADASTRAL APPLICATIONS
Photogrammetric mapping using unmanned aerial vehicle
Convolutional Neural Network Maps Plant Communities in Semi-Natural Grasslands Using Multispectral Unmanned Aerial Vehicle Imagery
Technical Note: Flow velocity and discharge measurement in rivers using terrestrial and unmanned-aerial-vehicle imagery
INTEGRATING TERRESTRIAL LIDAR WITH POINT CLOUDS CREATED FROM UNMANNED AERIAL VEHICLE IMAGERY
Assessing water erosion processes in degraded area using unmanned aerial vehicle imagery
UNMANNED AERIAL VEHICLES PRODUCE HIGH-RESOLUTION, SEASONALLY-RELEVANT IMAGERY FOR CLASSIFYING WETLAND VEGETATION
POST-FIRE FORESTRY RECOVERY MONITORING USING HIGH-RESOLUTION MULTISPECTRAL IMAGERY FROM UNMANNED AERIAL VEHICLES
Identifying rice field weeds from unmanned aerial vehicle remote sensing imagery using deep learning
DEVELOPING SPECIES SPECIFIC VEGETATION MAPS USING MULTI-SPECTRAL HYPERSPATIAL IMAGERY FROM UNMANNED AERIAL VEHICLES
ASSESSMENT OF THE QUALITY OF DIGITAL TERRAIN MODEL PRODUCED FROM UNMANNED AERIAL SYSTEM IMAGERY
Mission planning for unmanned aerial vehicles
UNMANNED AERIAL VEHICLE IN CADASTRAL APPLICATIONS
Photogrammetric mapping using unmanned aerial vehicle
Convolutional Neural Network Maps Plant Communities in Semi-Natural Grasslands Using Multispectral Unmanned Aerial Vehicle Imagery
Technical Note: Flow velocity and discharge measurement in rivers using terrestrial and unmanned-aerial-vehicle imagery
INTEGRATING TERRESTRIAL LIDAR WITH POINT CLOUDS CREATED FROM UNMANNED AERIAL VEHICLE IMAGERY
Assessing water erosion processes in degraded area using unmanned aerial vehicle imagery
UNMANNED AERIAL VEHICLES PRODUCE HIGH-RESOLUTION, SEASONALLY-RELEVANT IMAGERY FOR CLASSIFYING WETLAND VEGETATION
POST-FIRE FORESTRY RECOVERY MONITORING USING HIGH-RESOLUTION MULTISPECTRAL IMAGERY FROM UNMANNED AERIAL VEHICLES
Identifying rice field weeds from unmanned aerial vehicle remote sensing imagery using deep learning
DEVELOPING SPECIES SPECIFIC VEGETATION MAPS USING MULTI-SPECTRAL HYPERSPATIAL IMAGERY FROM UNMANNED AERIAL VEHICLES
ASSESSMENT OF THE QUALITY OF DIGITAL TERRAIN MODEL PRODUCED FROM UNMANNED AERIAL SYSTEM IMAGERY
Mission planning for unmanned aerial vehicles
UNMANNED AERIAL VEHICLE IN CADASTRAL APPLICATIONS
Photogrammetric mapping using unmanned aerial vehicle
Convolutional Neural Network Maps Plant Communities in Semi-Natural Grasslands Using Multispectral Unmanned Aerial Vehicle Imagery