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  "author": "[{\"given_name\": \"Mauro\", \"name\": \"Marty\", 
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  "author": "[{\"given_name\": \"Mauro\", \"name\": \"Marty\", 
            
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\"email\": \"mauro.marty@wsl.ch\", \"data_credit\": [], 
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\"email\": \"mauro.marty@wsl.ch\", \"data_credit\": [], 
            
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\"identifier\": \"0000-0002-0943-2454\", \"affiliation\": \"Remote 
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\"identifier\": \"0000-0002-0943-2454\", \"affiliation\": \"Remote 
            
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Sensing, Landscape Change Science, Swiss Federal Institute for Forest, 
5
Sensing, Landscape Change Science, Swiss Federal Institute for Forest, 
            
6
Snow and Landscape Research WSL, 8903 Birmensdorf, Switzerland\"}, 
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Snow and Landscape Research WSL, 8903 Birmensdorf, Switzerland\"}, 
            
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{\"given_name\": \"Christian\", \"name\": \"Ginzler\", \"email\": 
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{\"given_name\": \"Christian\", \"name\": \"Ginzler\", \"email\": 
            
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\"christian.ginzler@wsl.ch\", \"data_credit\": [], \"identifier\": 
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\"christian.ginzler@wsl.ch\", \"data_credit\": [], \"identifier\": 
            
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\"0000-0001-6365-2151\", \"affiliation\": \"Remote Sensing, Landscape 
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\"0000-0001-6365-2151\", \"affiliation\": \"Remote Sensing, Landscape 
            
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Change Science, Swiss Federal Institute for Forest, Snow and Landscape 
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Change Science, Swiss Federal Institute for Forest, Snow and Landscape 
            
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Research WSL, 8903 Birmensdorf, Switzerland\"}, {\"given_name\": 
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Research WSL, 8903 Birmensdorf, Switzerland\"}, {\"given_name\": 
            
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\"Lars\", \"name\": \"Waser\", \"email\": \"lars.waser@wsl.ch\", 
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\"Lars\", \"name\": \"Waser\", \"email\": \"lars.waser@wsl.ch\", 
            
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\"data_credit\": [], \"identifier\": \"D-5937-2011\", \"affiliation\": 
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\"data_credit\": [], \"identifier\": \"D-5937-2011\", \"affiliation\": 
            
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\"Swiss Federal Institute for Forest, Snow and Landscape Research WSL 
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\"Swiss Federal Institute for Forest, Snow and Landscape Research WSL 
            
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\"}, {\"given_name\": \"Livia\", \"name\": \"Piermattei\", \"email\": 
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\"}, {\"given_name\": \"Livia\", \"name\": \"Piermattei\", \"email\": 
            
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\"livia.piermattei@geo.uzh.ch\", \"data_credit\": [], \"identifier\": 
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\"livia.piermattei@geo.uzh.ch\", \"data_credit\": [], \"identifier\": 
            
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\"0000-0003-2814-8659\", \"affiliation\": \"UZH\"}]",
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\"0000-0003-2814-8659\", \"affiliation\": \"UZH\"}]",
            
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  "author_email": null,
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  "author_email": null,
            
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  "creator_user_id": "f4025a3a-f778-465c-8fb7-81389a440660",
            
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  "date": 
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  "date": 
            
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:\"collected\",\"date\":\"1979-05-01\",\"end_date\":\"2006-10-31\"}]",
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:\"collected\",\"date\":\"1979-05-01\",\"end_date\":\"2006-10-31\"}]",
            
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  "doi": "10.16904/envidat.528",
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  "doi": "10.16904/envidat.528",
            
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  "funding": "[{\"institution\":\"WSL - 
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  "funding": "[{\"institution\":\"WSL - 
            
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NFI\",\"grant_number\":\"\",\"institution_url\":\"\"}]",
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NFI\",\"grant_number\":\"\",\"institution_url\":\"\"}]",
            
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  "groups": [],
            
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  "license_id": "CC0-1.0",
            
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  "license_title": "Creative Commons Zero - No Rights Reserved (CC0 
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  "license_title": "Creative Commons Zero - No Rights Reserved (CC0 
            
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1.0)",
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1.0)",
            
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  "license_url": "https://creativecommons.org/publicdomain/zero/1.0/",
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  "license_url": "https://creativecommons.org/publicdomain/zero/1.0/",
            
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  "maintainer": 
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  "maintainer": 
            
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:\"mauro.marty@wsl.ch\",\"given_name\":\"Mauro\",\"name\":\"Marty\"}",
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:\"mauro.marty@wsl.ch\",\"given_name\":\"Mauro\",\"name\":\"Marty\"}",
            
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  "maintainer_email": null,
            
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  "metadata_created": "2024-05-31T08:51:24.684748",
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  "metadata_created": "2024-05-31T08:51:24.684748",
            
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  "metadata_modified": "2024-08-29T11:34:38.728246",
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  "metadata_modified": "2025-03-04T10:59:28.803637",
            
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  "name": "historical-vegetation-height-model-nfi",
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  "name": "historical-vegetation-height-model-nfi",
            
38
  "notes": "The main datasets available are 4 nationwide **Digital 
38
  "notes": "The main datasets available are 4 nationwide **Digital 
            
39
Surface Models (DSMs)** and corresponding **Vegetation Height Models 
39
Surface Models (DSMs)** and corresponding **Vegetation Height Models 
            
40
(VHMs)** with a spatial resolution of 1 m.\nThe Vegetation Height 
40
(VHMs)** with a spatial resolution of 1 m.\nThe Vegetation Height 
            
41
Models are calculated by subtraction of a Digital Terrain Model 
41
Models are calculated by subtraction of a Digital Terrain Model 
            
42
(swissAlti3d version 2017, swisstopo) from the generated DSMs. DSMs 
42
(swissAlti3d version 2017, swisstopo) from the generated DSMs. DSMs 
            
43
were derived by image matching of **scanned historical images** 
43
were derived by image matching of **scanned historical images** 
            
44
(panchromatic 8-bit) acquired with a RC10 frame camera, in the context 
44
(panchromatic 8-bit) acquired with a RC10 frame camera, in the context 
            
45
of the swisswide image acquisition campaigns of swisstopo.\nNationwide 
45
of the swisswide image acquisition campaigns of swisstopo.\nNationwide 
            
46
products could be generated for the **four epochs** \n 1979-1985 / 
46
products could be generated for the **four epochs** \n 1979-1985 / 
            
47
1985-1991 / 1990-1998 / 1998-2006.\n\nAdditional information about 
47
1985-1991 / 1990-1998 / 1998-2006.\n\nAdditional information about 
            
48
successful image matching vs. interpolation of pixels and about the 
48
successful image matching vs. interpolation of pixels and about the 
            
49
year of image acquisition are available in the corresponding files 
49
year of image acquisition are available in the corresponding files 
            
50
(**matched_area_xxxx_xxxx_binay.tif** and 
50
(**matched_area_xxxx_xxxx_binay.tif** and 
            
51
**meta_acquisition_year_xxxx_xxxx.json**, respectively).\n\nTo 
51
**meta_acquisition_year_xxxx_xxxx.json**, respectively).\n\nTo 
            
52
separate vegetation from non-vegetation areas a mask derived from a 
52
separate vegetation from non-vegetation areas a mask derived from a 
            
53
combination of information of the Topographic landscape model - TLM 
53
combination of information of the Topographic landscape model - TLM 
            
54
(swisstopo) and a NDVI layer was used and is supplied as 
54
(swisstopo) and a NDVI layer was used and is supplied as 
            
55
**\"TLM_mask.tif\"**\n\nDue to the occurrence of unrealistic 
55
**\"TLM_mask.tif\"**\n\nDue to the occurrence of unrealistic 
            
56
vegetation height values caused by the failure of the image matching 
56
vegetation height values caused by the failure of the image matching 
            
57
process (mainly overexposed images and clouds or very steep rocky 
57
process (mainly overexposed images and clouds or very steep rocky 
            
58
terrain), pixel values > 60 m were set to NoData and < 0 m to 0. 
58
terrain), pixel values > 60 m were set to NoData and < 0 m to 0. 
            
59
\n\nAll datasets are available in the Reference System **LV95 (EPSG: 
59
\n\nAll datasets are available in the Reference System **LV95 (EPSG: 
            
60
2056) LN02 (EPSG: 5728)** and share the common **extent definition** 
60
2056) LN02 (EPSG: 5728)** and share the common **extent definition** 
            
61
(xmin ymin xmax ymax): 2480000 1070000 2840000 1300000\n",
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(xmin ymin xmax ymax): 2480000 1070000 2840000 1300000\n",
            
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  "num_resources": 5,
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  "num_resources": 5,
            
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  "num_tags": 6,
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  "num_tags": 6,
            
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  "organization": {
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  "organization": {
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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    "created": "2017-04-20T16:51:21.920128",
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    "created": "2017-04-20T16:51:21.920128",
            
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    "description": "We develop and apply comprehensive and robust 
67
    "description": "We develop and apply comprehensive and robust 
            
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methods to extract and classify natural objects from continuous and 
68
methods to extract and classify natural objects from continuous and 
            
69
discrete raster datasets. Relevant features are acquired to describe 
69
discrete raster datasets. Relevant features are acquired to describe 
            
70
changes in landscape and land resources at different levels using 
70
changes in landscape and land resources at different levels using 
            
71
image data. Mathematical-statistical methods are adopted for automatic 
71
image data. Mathematical-statistical methods are adopted for automatic 
            
72
detection and description of image objects. Thus we contribute 
72
detection and description of image objects. Thus we contribute 
            
73
concepts, methods and data to describe/detect area wide changes and 
73
concepts, methods and data to describe/detect area wide changes and 
            
74
processes in the resources of landscape.\r\n\r\n### Tasks and main 
74
processes in the resources of landscape.\r\n\r\n### Tasks and main 
            
75
research\r\n\r\n* Development and application of methods to extract 
75
research\r\n\r\n* Development and application of methods to extract 
            
76
natural objects from continuous data.\r\n* Development of methods for 
76
natural objects from continuous data.\r\n* Development of methods for 
            
77
a comprehensive description of natural and anthropogenetic boundaries 
77
a comprehensive description of natural and anthropogenetic boundaries 
            
78
in continuous pattern (e.g. map signatures, vegetation transition, 
78
in continuous pattern (e.g. map signatures, vegetation transition, 
            
79
forest borders).\r\n* Development and application of methods to 
79
forest borders).\r\n* Development and application of methods to 
            
80
extract 3D-information from remotely sensed data for description of 
80
extract 3D-information from remotely sensed data for description of 
            
81
natural structures and changes. The main focus lies on wood and its 
81
natural structures and changes. The main focus lies on wood and its 
            
82
embedding/interaction within/with the landscape.\r\n* Conception and 
82
embedding/interaction within/with the landscape.\r\n* Conception and 
            
83
development of data acquisition based on high resolution remote 
83
development of data acquisition based on high resolution remote 
            
84
sensing data.\r\n* Conception, development and maintenance of the 
84
sensing data.\r\n* Conception, development and maintenance of the 
            
85
software interface in area wide data acquisition using airborne remote 
85
software interface in area wide data acquisition using airborne remote 
            
86
sensing data.\r\n* Scientific expert advice and support in the fields 
86
sensing data.\r\n* Scientific expert advice and support in the fields 
            
87
of photogrammetry and survey at WSL. Maintenance, enhancements and 
87
of photogrammetry and survey at WSL. Maintenance, enhancements and 
            
88
future development in these specific fields.\r\n* Adequate 
88
future development in these specific fields.\r\n* Adequate 
            
89
presentation of scientific results on national level and in noted 
89
presentation of scientific results on national level and in noted 
            
90
international journals and at international 
90
international journals and at international 
            
91
congresses/workshops/symposia.\r\n\r\n__Further information__: 
91
congresses/workshops/symposia.\r\n\r\n__Further information__: 
            
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l/organization/research-units/landscape-dynamics/remote-sensing.html",
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l/organization/research-units/landscape-dynamics/remote-sensing.html",
            
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