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On June 18, 2021 at 9:15:44 AM UTC, Administrator:
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Added resource 2019 Vegetation Height Model NFI (current) to Vegetation Height Model NFI
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to resource 2015 Vegetation Height Model NFI in Vegetation Height Model NFI -
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to resource Countrywide Stereo-Image Matching for Updating Digital Surface Models in the Framework of the Swiss National Forest Inventory in Vegetation Height Model NFI -
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to resource Thumbnail in Vegetation Height Model NFI -
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to resource 2012 Vegetation Height Model NFI in Vegetation Height Model NFI -
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to resource 2016 Vegetation Height Model NFI (current) in Vegetation Height Model NFI
f | 1 | { | f | 1 | { |
2 | "author": "[{\"affiliation\": \"Swiss Federal Institute for Forest, | 2 | "author": "[{\"affiliation\": \"Swiss Federal Institute for Forest, | ||
3 | Snow and Landscape Research WSL \", \"affiliation_02\": \"\", | 3 | Snow and Landscape Research WSL \", \"affiliation_02\": \"\", | ||
4 | \"affiliation_03\": \"\", \"email\": \"christian.ginzler@wsl.ch\", | 4 | \"affiliation_03\": \"\", \"email\": \"christian.ginzler@wsl.ch\", | ||
5 | \"given_name\": \"Christian\", \"identifier\": \"E-9544-2012\", | 5 | \"given_name\": \"Christian\", \"identifier\": \"E-9544-2012\", | ||
6 | \"name\": \"Ginzler\"}]", | 6 | \"name\": \"Ginzler\"}]", | ||
7 | "author_email": null, | 7 | "author_email": null, | ||
8 | "creator_user_id": "6d44d5cd-9ac6-4100-bc2c-c02034a41b48", | 8 | "creator_user_id": "6d44d5cd-9ac6-4100-bc2c-c02034a41b48", | ||
9 | "date": "[{\"date\": \"2007-05-01\", \"date_type\": \"created\", | 9 | "date": "[{\"date\": \"2007-05-01\", \"date_type\": \"created\", | ||
10 | \"end_date\": \"2012-09-30\"}, {\"date\": \"2017-09-30\", | 10 | \"end_date\": \"2012-09-30\"}, {\"date\": \"2017-09-30\", | ||
11 | \"date_type\": \"created\", \"end_date\": \"\"}]", | 11 | \"date_type\": \"created\", \"end_date\": \"\"}]", | ||
12 | "doi": "10.16904/1000001.1", | 12 | "doi": "10.16904/1000001.1", | ||
13 | "extras": [ | 13 | "extras": [ | ||
14 | { | 14 | { | ||
15 | "key": "dora_link", | 15 | "key": "dora_link", | ||
16 | "value": "" | 16 | "value": "" | ||
17 | } | 17 | } | ||
18 | ], | 18 | ], | ||
19 | "funding": "[{\"grant_number\": \"\", \"institution\": \"Federal | 19 | "funding": "[{\"grant_number\": \"\", \"institution\": \"Federal | ||
20 | Office for the Environment (FOEN).\", \"institution_url\": \"\"}]", | 20 | Office for the Environment (FOEN).\", \"institution_url\": \"\"}]", | ||
21 | "groups": [], | 21 | "groups": [], | ||
22 | "id": "d0e70abe-cc8a-4d91-8798-fa2d9991230f", | 22 | "id": "d0e70abe-cc8a-4d91-8798-fa2d9991230f", | ||
23 | "isopen": true, | 23 | "isopen": true, | ||
24 | "language": "en", | 24 | "language": "en", | ||
25 | "license_id": "odc-odbl", | 25 | "license_id": "odc-odbl", | ||
26 | "license_title": "ODbL with Database Contents License (DbCL)", | 26 | "license_title": "ODbL with Database Contents License (DbCL)", | ||
27 | "license_url": "https://opendefinition.org/licenses/odc-odbl", | 27 | "license_url": "https://opendefinition.org/licenses/odc-odbl", | ||
28 | "maintainer": "{\"affiliation\": \"Swiss Federal Institute for | 28 | "maintainer": "{\"affiliation\": \"Swiss Federal Institute for | ||
29 | Forest, Snow and Landscape Research WSL \", \"email\": | 29 | Forest, Snow and Landscape Research WSL \", \"email\": | ||
30 | \"christian.ginzler@wsl.ch\", \"given_name\": \"Christian\", | 30 | \"christian.ginzler@wsl.ch\", \"given_name\": \"Christian\", | ||
31 | \"identifier\": \"E-9544-2012\", \"name\": \"Ginzler\"}", | 31 | \"identifier\": \"E-9544-2012\", \"name\": \"Ginzler\"}", | ||
32 | "maintainer_email": null, | 32 | "maintainer_email": null, | ||
33 | "metadata_created": "2017-05-01T12:38:08.518327", | 33 | "metadata_created": "2017-05-01T12:38:08.518327", | ||
n | 34 | "metadata_modified": "2021-06-18T09:11:04.072224", | n | 34 | "metadata_modified": "2021-06-18T09:15:44.825849", |
35 | "name": "vegetation-height-model-nfi", | 35 | "name": "vegetation-height-model-nfi", | ||
36 | "notes": "A national vegetation height model was calculated for | 36 | "notes": "A national vegetation height model was calculated for | ||
37 | Switzerland using digital aerial images.\r\nWe used the stereo aerial | 37 | Switzerland using digital aerial images.\r\nWe used the stereo aerial | ||
38 | images acquired by the Federal Office of Topography swisstopo using | 38 | images acquired by the Federal Office of Topography swisstopo using | ||
39 | the ADS80 sensor to first calculate a digital\r\nsurface model (DSM) | 39 | the ADS80 sensor to first calculate a digital\r\nsurface model (DSM) | ||
40 | with a very high spatial resolution\r\n(1 \u00d7 1 m). The DSM was | 40 | with a very high spatial resolution\r\n(1 \u00d7 1 m). The DSM was | ||
41 | then normalized to obtain the actual\r\nvegetation heights using a | 41 | then normalized to obtain the actual\r\nvegetation heights using a | ||
42 | digital terrain model (DTM)\r\nbased on laser data with the buildings | 42 | digital terrain model (DTM)\r\nbased on laser data with the buildings | ||
43 | masked out, and to\r\nproduce a vegetation height model (VHM). Such a | 43 | masked out, and to\r\nproduce a vegetation height model (VHM). Such a | ||
44 | model\r\nwill be calculated in the framework of the Swiss National | 44 | model\r\nwill be calculated in the framework of the Swiss National | ||
45 | Forest Inventory (NFI) with consistent methods and a very\r\nhigh | 45 | Forest Inventory (NFI) with consistent methods and a very\r\nhigh | ||
46 | level of detail. For covering the whole of Switzerland,\r\nwe use | 46 | level of detail. For covering the whole of Switzerland,\r\nwe use | ||
47 | summer aerial images from six years.", | 47 | summer aerial images from six years.", | ||
n | 48 | "num_resources": 5, | n | 48 | "num_resources": 6, |
49 | "num_tags": 5, | 49 | "num_tags": 5, | ||
50 | "organization": { | 50 | "organization": { | ||
51 | "approval_status": "approved", | 51 | "approval_status": "approved", | ||
52 | "created": "2017-04-20T16:51:21.920128", | 52 | "created": "2017-04-20T16:51:21.920128", | ||
53 | "description": "We develop and apply comprehensive and robust | 53 | "description": "We develop and apply comprehensive and robust | ||
54 | methods to extract and classify natural objects from continuous and | 54 | methods to extract and classify natural objects from continuous and | ||
55 | discrete raster datasets. Relevant features are acquired to describe | 55 | discrete raster datasets. Relevant features are acquired to describe | ||
56 | changes in landscape and land resources at different levels using | 56 | changes in landscape and land resources at different levels using | ||
57 | image data. Mathematical-statistical methods are adopted for automatic | 57 | image data. Mathematical-statistical methods are adopted for automatic | ||
58 | detection and description of image objects. Thus we contribute | 58 | detection and description of image objects. Thus we contribute | ||
59 | concepts, methods and data to describe/detect area wide changes and | 59 | concepts, methods and data to describe/detect area wide changes and | ||
60 | processes in the resources of landscape.\r\n\r\n### Tasks and main | 60 | processes in the resources of landscape.\r\n\r\n### Tasks and main | ||
61 | research\r\n\r\n* Development and application of methods to extract | 61 | research\r\n\r\n* Development and application of methods to extract | ||
62 | natural objects from continuous data.\r\n* Development of methods for | 62 | natural objects from continuous data.\r\n* Development of methods for | ||
63 | a comprehensive description of natural and anthropogenetic boundaries | 63 | a comprehensive description of natural and anthropogenetic boundaries | ||
64 | in continuous pattern (e.g. map signatures, vegetation transition, | 64 | in continuous pattern (e.g. map signatures, vegetation transition, | ||
65 | forest borders).\r\n* Development and application of methods to | 65 | forest borders).\r\n* Development and application of methods to | ||
66 | extract 3D-information from remotely sensed data for description of | 66 | extract 3D-information from remotely sensed data for description of | ||
67 | natural structures and changes. The main focus lies on wood and its | 67 | natural structures and changes. The main focus lies on wood and its | ||
68 | embedding/interaction within/with the landscape.\r\n* Conception and | 68 | embedding/interaction within/with the landscape.\r\n* Conception and | ||
69 | development of data acquisition based on high resolution remote | 69 | development of data acquisition based on high resolution remote | ||
70 | sensing data.\r\n* Conception, development and maintenance of the | 70 | sensing data.\r\n* Conception, development and maintenance of the | ||
71 | software interface in area wide data acquisition using airborne remote | 71 | software interface in area wide data acquisition using airborne remote | ||
72 | sensing data.\r\n* Scientific expert advice and support in the fields | 72 | sensing data.\r\n* Scientific expert advice and support in the fields | ||
73 | of photogrammetry and survey at WSL. Maintenance, enhancements and | 73 | of photogrammetry and survey at WSL. Maintenance, enhancements and | ||
74 | future development in these specific fields.\r\n* Adequate | 74 | future development in these specific fields.\r\n* Adequate | ||
75 | presentation of scientific results on national level and in noted | 75 | presentation of scientific results on national level and in noted | ||
76 | international journals and at international | 76 | international journals and at international | ||
77 | congresses/workshops/symposia.\r\n\r\n__Further information__: | 77 | congresses/workshops/symposia.\r\n\r\n__Further information__: | ||
78 | l/organization/research-units/landscape-dynamics/remote-sensing.html", | 78 | l/organization/research-units/landscape-dynamics/remote-sensing.html", | ||
79 | "id": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", | 79 | "id": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", | ||
80 | "image_url": "2018-07-10-102816.481589LogoWSL.svg", | 80 | "image_url": "2018-07-10-102816.481589LogoWSL.svg", | ||
81 | "is_organization": true, | 81 | "is_organization": true, | ||
82 | "name": "remote-sensing", | 82 | "name": "remote-sensing", | ||
83 | "state": "active", | 83 | "state": "active", | ||
84 | "title": "Remote Sensing", | 84 | "title": "Remote Sensing", | ||
85 | "type": "organization" | 85 | "type": "organization" | ||
86 | }, | 86 | }, | ||
87 | "owner_org": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", | 87 | "owner_org": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", | ||
88 | "private": false, | 88 | "private": false, | ||
89 | "publication": "{\"publication_year\": \"2018\", \"publisher\": | 89 | "publication": "{\"publication_year\": \"2018\", \"publisher\": | ||
90 | \"National Forest Inventory (NFI)\"}", | 90 | \"National Forest Inventory (NFI)\"}", | ||
91 | "publication_state": "published", | 91 | "publication_state": "published", | ||
92 | "related_datasets": "", | 92 | "related_datasets": "", | ||
93 | "related_publications": "", | 93 | "related_publications": "", | ||
94 | "relationships_as_object": [], | 94 | "relationships_as_object": [], | ||
95 | "relationships_as_subject": [], | 95 | "relationships_as_subject": [], | ||
96 | "resource_type": "dataset", | 96 | "resource_type": "dataset", | ||
97 | "resource_type_general": "dataset", | 97 | "resource_type_general": "dataset", | ||
98 | "resources": [ | 98 | "resources": [ | ||
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102 | "created": "2018-04-03T05:11:09.208337", | 102 | "created": "2018-04-03T05:11:09.208337", | ||
103 | "description": "A national vegetation height model was | 103 | "description": "A national vegetation height model was | ||
104 | calculated for Switzerland using digital aerial images. We used the | 104 | calculated for Switzerland using digital aerial images. We used the | ||
105 | stereo aerial images acquired by the Federal Office of Topography | 105 | stereo aerial images acquired by the Federal Office of Topography | ||
106 | swisstopo using the ADS80 sensor to first calculate a digital surface | 106 | swisstopo using the ADS80 sensor to first calculate a digital surface | ||
107 | model (DSM) with a very high spatial resolution (1 \u00d7 1 m). The | 107 | model (DSM) with a very high spatial resolution (1 \u00d7 1 m). The | ||
108 | DSM was then normalized to obtain the actual vegetation heights using | 108 | DSM was then normalized to obtain the actual vegetation heights using | ||
109 | the digital terrain model (DTM) SwissAlti3D based on airborne laser | 109 | the digital terrain model (DTM) SwissAlti3D based on airborne laser | ||
110 | data. Buildings are masked out using the NDVI information of the | 110 | data. Buildings are masked out using the NDVI information of the | ||
111 | aerial images to produce a vegetation height model, and to produce a | 111 | aerial images to produce a vegetation height model, and to produce a | ||
112 | vegetation height model (VHM). Such a model will be calculated in the | 112 | vegetation height model (VHM). Such a model will be calculated in the | ||
113 | framework of the Swiss National Forest Inventory (NFI) with consistent | 113 | framework of the Swiss National Forest Inventory (NFI) with consistent | ||
114 | methods and a very high level of detail. For covering the whole of | 114 | methods and a very high level of detail. For covering the whole of | ||
115 | Switzerland, we used summer aerial images from 2011 to 2016.", | 115 | Switzerland, we used summer aerial images from 2011 to 2016.", | ||
116 | "doi": "10.16904/1000001.1", | 116 | "doi": "10.16904/1000001.1", | ||
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199 | "name": "Countrywide Stereo-Image Matching for Updating Digital | 202 | "name": "Countrywide Stereo-Image Matching for Updating Digital | ||
200 | Surface Models in the Framework of the Swiss National Forest | 203 | Surface Models in the Framework of the Swiss National Forest | ||
201 | Inventory", | 204 | Inventory", | ||
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289 | "type": "dataset", | 321 | "type": "dataset", | ||
290 | "url": null, | 322 | "url": null, | ||
291 | "version": "2019 (current)" | 323 | "version": "2019 (current)" | ||
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