4D objects-by-change: Spatiotemporal segmentation of geomorphic surface change from LiDAR time series
Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets co...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Anders, Katharina [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020transfer abstract |
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| Schlagwörter: |
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| Umfang: |
12 |
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| Übergeordnetes Werk: |
Enthalten in: In Vitro and In Vivo UV Light Skin Protection by an Antioxidant Derivative of NSAID Tolfenamic Acid - Skiadopoulos, V. ELSEVIER, 2013, official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS), Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:159 ; year:2020 ; pages:352-363 ; extent:12 |
| Links: |
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| DOI / URN: |
10.1016/j.isprsjprs.2019.11.025 |
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| Katalog-ID: |
ELV048823287 |
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| 245 | 1 | 0 | |a 4D objects-by-change: Spatiotemporal segmentation of geomorphic surface change from LiDAR time series |
| 264 | 1 | |c 2020transfer abstract | |
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| 520 | |a Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. | ||
| 520 | |a Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. | ||
| 650 | 7 | |a Beach monitoring |2 Elsevier | |
| 650 | 7 | |a Temporal domain |2 Elsevier | |
| 650 | 7 | |a Terrestrial laser scanning |2 Elsevier | |
| 650 | 7 | |a High-frequency observation |2 Elsevier | |
| 650 | 7 | |a Spatiotemporal analysis |2 Elsevier | |
| 700 | 1 | |a Winiwarter, Lukas |4 oth | |
| 700 | 1 | |a Lindenbergh, Roderik |4 oth | |
| 700 | 1 | |a Williams, Jack G. |4 oth | |
| 700 | 1 | |a Vos, Sander E. |4 oth | |
| 700 | 1 | |a Höfle, Bernhard |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |a Skiadopoulos, V. ELSEVIER |t In Vitro and In Vivo UV Light Skin Protection by an Antioxidant Derivative of NSAID Tolfenamic Acid |d 2013 |d official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) |g Amsterdam [u.a.] |w (DE-627)ELV016966376 |
| 773 | 1 | 8 | |g volume:159 |g year:2020 |g pages:352-363 |g extent:12 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.isprsjprs.2019.11.025 |3 Volltext |
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10.1016/j.isprsjprs.2019.11.025 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000843.pica (DE-627)ELV048823287 (ELSEVIER)S0924-2716(19)30285-0 DE-627 ger DE-627 rakwb eng 570 VZ 610 VZ 620 VZ 52.57 bkl 53.36 bkl Anders, Katharina verfasserin aut 4D objects-by-change: Spatiotemporal segmentation of geomorphic surface change from LiDAR time series 2020transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. Beach monitoring Elsevier Temporal domain Elsevier Terrestrial laser scanning Elsevier High-frequency observation Elsevier Spatiotemporal analysis Elsevier Winiwarter, Lukas oth Lindenbergh, Roderik oth Williams, Jack G. oth Vos, Sander E. oth Höfle, Bernhard oth Enthalten in Elsevier Skiadopoulos, V. ELSEVIER In Vitro and In Vivo UV Light Skin Protection by an Antioxidant Derivative of NSAID Tolfenamic Acid 2013 official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) Amsterdam [u.a.] (DE-627)ELV016966376 volume:159 year:2020 pages:352-363 extent:12 https://doi.org/10.1016/j.isprsjprs.2019.11.025 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_70 52.57 Energiespeicherung VZ 53.36 Energiedirektumwandler elektrische Energiespeicher VZ AR 159 2020 352-363 12 |
| spelling |
10.1016/j.isprsjprs.2019.11.025 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000843.pica (DE-627)ELV048823287 (ELSEVIER)S0924-2716(19)30285-0 DE-627 ger DE-627 rakwb eng 570 VZ 610 VZ 620 VZ 52.57 bkl 53.36 bkl Anders, Katharina verfasserin aut 4D objects-by-change: Spatiotemporal segmentation of geomorphic surface change from LiDAR time series 2020transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. Beach monitoring Elsevier Temporal domain Elsevier Terrestrial laser scanning Elsevier High-frequency observation Elsevier Spatiotemporal analysis Elsevier Winiwarter, Lukas oth Lindenbergh, Roderik oth Williams, Jack G. oth Vos, Sander E. oth Höfle, Bernhard oth Enthalten in Elsevier Skiadopoulos, V. ELSEVIER In Vitro and In Vivo UV Light Skin Protection by an Antioxidant Derivative of NSAID Tolfenamic Acid 2013 official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) Amsterdam [u.a.] (DE-627)ELV016966376 volume:159 year:2020 pages:352-363 extent:12 https://doi.org/10.1016/j.isprsjprs.2019.11.025 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_70 52.57 Energiespeicherung VZ 53.36 Energiedirektumwandler elektrische Energiespeicher VZ AR 159 2020 352-363 12 |
| allfields_unstemmed |
10.1016/j.isprsjprs.2019.11.025 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000843.pica (DE-627)ELV048823287 (ELSEVIER)S0924-2716(19)30285-0 DE-627 ger DE-627 rakwb eng 570 VZ 610 VZ 620 VZ 52.57 bkl 53.36 bkl Anders, Katharina verfasserin aut 4D objects-by-change: Spatiotemporal segmentation of geomorphic surface change from LiDAR time series 2020transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. Beach monitoring Elsevier Temporal domain Elsevier Terrestrial laser scanning Elsevier High-frequency observation Elsevier Spatiotemporal analysis Elsevier Winiwarter, Lukas oth Lindenbergh, Roderik oth Williams, Jack G. oth Vos, Sander E. oth Höfle, Bernhard oth Enthalten in Elsevier Skiadopoulos, V. ELSEVIER In Vitro and In Vivo UV Light Skin Protection by an Antioxidant Derivative of NSAID Tolfenamic Acid 2013 official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) Amsterdam [u.a.] (DE-627)ELV016966376 volume:159 year:2020 pages:352-363 extent:12 https://doi.org/10.1016/j.isprsjprs.2019.11.025 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_70 52.57 Energiespeicherung VZ 53.36 Energiedirektumwandler elektrische Energiespeicher VZ AR 159 2020 352-363 12 |
| allfieldsGer |
10.1016/j.isprsjprs.2019.11.025 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000843.pica (DE-627)ELV048823287 (ELSEVIER)S0924-2716(19)30285-0 DE-627 ger DE-627 rakwb eng 570 VZ 610 VZ 620 VZ 52.57 bkl 53.36 bkl Anders, Katharina verfasserin aut 4D objects-by-change: Spatiotemporal segmentation of geomorphic surface change from LiDAR time series 2020transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. Beach monitoring Elsevier Temporal domain Elsevier Terrestrial laser scanning Elsevier High-frequency observation Elsevier Spatiotemporal analysis Elsevier Winiwarter, Lukas oth Lindenbergh, Roderik oth Williams, Jack G. oth Vos, Sander E. oth Höfle, Bernhard oth Enthalten in Elsevier Skiadopoulos, V. ELSEVIER In Vitro and In Vivo UV Light Skin Protection by an Antioxidant Derivative of NSAID Tolfenamic Acid 2013 official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) Amsterdam [u.a.] (DE-627)ELV016966376 volume:159 year:2020 pages:352-363 extent:12 https://doi.org/10.1016/j.isprsjprs.2019.11.025 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_70 52.57 Energiespeicherung VZ 53.36 Energiedirektumwandler elektrische Energiespeicher VZ AR 159 2020 352-363 12 |
| allfieldsSound |
10.1016/j.isprsjprs.2019.11.025 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000843.pica (DE-627)ELV048823287 (ELSEVIER)S0924-2716(19)30285-0 DE-627 ger DE-627 rakwb eng 570 VZ 610 VZ 620 VZ 52.57 bkl 53.36 bkl Anders, Katharina verfasserin aut 4D objects-by-change: Spatiotemporal segmentation of geomorphic surface change from LiDAR time series 2020transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. Beach monitoring Elsevier Temporal domain Elsevier Terrestrial laser scanning Elsevier High-frequency observation Elsevier Spatiotemporal analysis Elsevier Winiwarter, Lukas oth Lindenbergh, Roderik oth Williams, Jack G. oth Vos, Sander E. oth Höfle, Bernhard oth Enthalten in Elsevier Skiadopoulos, V. ELSEVIER In Vitro and In Vivo UV Light Skin Protection by an Antioxidant Derivative of NSAID Tolfenamic Acid 2013 official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) Amsterdam [u.a.] (DE-627)ELV016966376 volume:159 year:2020 pages:352-363 extent:12 https://doi.org/10.1016/j.isprsjprs.2019.11.025 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_70 52.57 Energiespeicherung VZ 53.36 Energiedirektumwandler elektrische Energiespeicher VZ AR 159 2020 352-363 12 |
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Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. |
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Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. |
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Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies. |
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A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic evolution over varying spatial and temporal scales. Current analyses however are mostly conducted based on pairwise surface or object-based change, which typically require the selection of thresholds and intervals to identify the processes involved and fail to account for the full history of change. Detected change may therefore be difficult to attribute to one or more underlying geomorphic processes causing the surface alteration. We present an automatic method for 4D change analysis that includes the temporal domain by using the history of surface change to extract the period and spatial extent of changes. A 3D space-time array of surface change values is derived from an hourly TLS time series acquired at a sandy beach over five months (2967 point clouds). Change point detection is performed in the time series at individual locations and used to identify change processes, such as the appearance and disappearance of an accumulation form. These provide the seed to spatially segment ‘4D objects-by-change’ using a metric of time series similarity in a region growing approach. Results are compared to pairwise surface change for three selected cases of anthropogenic and natural processes on the beach. The obtained information reflects the evolution of a change process and its spatial extent over the change period, thereby improving upon the results of pairwise analysis. The method allows the detection and spatiotemporal delineation of even subtle changes induced by sand transport on the surface. 4D objects-by-change can therefore provide new insights on spatiotemporal characteristics of geomorphic activity, particularly in settings of continuous surfaces with dynamic morphologies.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Beach monitoring</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Temporal domain</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Terrestrial laser scanning</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">High-frequency observation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Spatiotemporal analysis</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Winiwarter, Lukas</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lindenbergh, Roderik</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Williams, Jack G.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Vos, Sander E.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Höfle, Bernhard</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Skiadopoulos, V. ELSEVIER</subfield><subfield code="t">In Vitro and In Vivo UV Light Skin Protection by an Antioxidant Derivative of NSAID Tolfenamic Acid</subfield><subfield code="d">2013</subfield><subfield code="d">official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS)</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV016966376</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:159</subfield><subfield code="g">year:2020</subfield><subfield code="g">pages:352-363</subfield><subfield code="g">extent:12</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.isprsjprs.2019.11.025</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">52.57</subfield><subfield code="j">Energiespeicherung</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">53.36</subfield><subfield code="j">Energiedirektumwandler</subfield><subfield code="j">elektrische Energiespeicher</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">159</subfield><subfield code="j">2020</subfield><subfield code="h">352-363</subfield><subfield code="g">12</subfield></datafield></record></collection>
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