Changes
On May 7, 2021 at 7:28:09 AM UTC, Lars Waser:
-
No fields were updated. See the metadata diff for more details.
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\": \"lars.waser@wsl.ch\", | 4 | \"affiliation_03\": \"\", \"email\": \"lars.waser@wsl.ch\", | ||
5 | \"given_name\": \"Lars\", \"identifier\": \"D-5937-2011\", \"name\": | 5 | \"given_name\": \"Lars\", \"identifier\": \"D-5937-2011\", \"name\": | ||
6 | \"Waser\"}, {\"affiliation\": \"Swiss Federal Institute for Forest, | 6 | \"Waser\"}, {\"affiliation\": \"Swiss Federal Institute for Forest, | ||
7 | Snow and Landscape Research WSL \", \"affiliation_02\": \"\", | 7 | Snow and Landscape Research WSL \", \"affiliation_02\": \"\", | ||
8 | \"affiliation_03\": \"\", \"email\": \"christian.ginzler@wsl.ch\", | 8 | \"affiliation_03\": \"\", \"email\": \"christian.ginzler@wsl.ch\", | ||
9 | \"given_name\": \"Christian\", \"identifier\": \"E-9544-2012\", | 9 | \"given_name\": \"Christian\", \"identifier\": \"E-9544-2012\", | ||
10 | \"name\": \"Ginzler\"}]", | 10 | \"name\": \"Ginzler\"}]", | ||
11 | "author_email": null, | 11 | "author_email": null, | ||
12 | "creator_user_id": "6d44d5cd-9ac6-4100-bc2c-c02034a41b48", | 12 | "creator_user_id": "6d44d5cd-9ac6-4100-bc2c-c02034a41b48", | ||
13 | "date": "[{\"date\": \"2018-03-06\", \"date_type\": \"created\", | 13 | "date": "[{\"date\": \"2018-03-06\", \"date_type\": \"created\", | ||
14 | \"end_date\": \"\"}]", | 14 | \"end_date\": \"\"}]", | ||
15 | "doi": "10.16904/1000001.7", | 15 | "doi": "10.16904/1000001.7", | ||
16 | "funding": "[{\"grant_number\": \"\", \"institution\": \"Federal | 16 | "funding": "[{\"grant_number\": \"\", \"institution\": \"Federal | ||
17 | Office for the Environment (FOEN).\", \"institution_url\": \"\"}]", | 17 | Office for the Environment (FOEN).\", \"institution_url\": \"\"}]", | ||
18 | "groups": [], | 18 | "groups": [], | ||
19 | "id": "82d763fa-123a-4648-b827-0dec02a5efbc", | 19 | "id": "82d763fa-123a-4648-b827-0dec02a5efbc", | ||
20 | "isopen": false, | 20 | "isopen": false, | ||
21 | "language": "en", | 21 | "language": "en", | ||
22 | "license_id": "other-undefined", | 22 | "license_id": "other-undefined", | ||
23 | "license_title": "Other (Specified in the description)", | 23 | "license_title": "Other (Specified in the description)", | ||
24 | "maintainer": "{\"affiliation\": \"Swiss Federal Institute for | 24 | "maintainer": "{\"affiliation\": \"Swiss Federal Institute for | ||
25 | Forest, Snow and Landscape Research WSL \", \"email\": | 25 | Forest, Snow and Landscape Research WSL \", \"email\": | ||
26 | \"lars.waser@wsl.ch\", \"given_name\": \"Lars\", \"identifier\": | 26 | \"lars.waser@wsl.ch\", \"given_name\": \"Lars\", \"identifier\": | ||
27 | \"D-5937-2011\", \"name\": \"Waser\"}", | 27 | \"D-5937-2011\", \"name\": \"Waser\"}", | ||
28 | "maintainer_email": null, | 28 | "maintainer_email": null, | ||
29 | "metadata_created": "2018-04-03T10:38:30.545175", | 29 | "metadata_created": "2018-04-03T10:38:30.545175", | ||
t | 30 | "metadata_modified": "2021-05-07T07:27:03.921351", | t | 30 | "metadata_modified": "2021-05-07T07:28:09.920517", |
31 | "name": "forest-type-nfi", | 31 | "name": "forest-type-nfi", | ||
32 | "notes": "Two versions of the data are currently available: 2018 and | 32 | "notes": "Two versions of the data are currently available: 2018 and | ||
33 | 2016.\r\n\r\nThe 2018 version presents a remote sensing-based approach | 33 | 2016.\r\n\r\nThe 2018 version presents a remote sensing-based approach | ||
34 | for a countrywide mapping of the dominant leave type (DLT) with the | 34 | for a countrywide mapping of the dominant leave type (DLT) with the | ||
35 | two classes broadleaved and coniferous in Switzerland. The spatial | 35 | two classes broadleaved and coniferous in Switzerland. The spatial | ||
36 | resolution is 10 m with the fraction of the class broadleaf. The | 36 | resolution is 10 m with the fraction of the class broadleaf. The | ||
37 | classification approach incorporates a random forest classifier, | 37 | classification approach incorporates a random forest classifier, | ||
38 | explanatory variables from multispectral Sentinel-2, multi-temporal | 38 | explanatory variables from multispectral Sentinel-2, multi-temporal | ||
39 | Sentinel-1 data and a Digital Terrain Model (DTM) from Airborne Laser | 39 | Sentinel-1 data and a Digital Terrain Model (DTM) from Airborne Laser | ||
40 | Scanning (ALS) data. The models were calibrated using digitized | 40 | Scanning (ALS) data. The models were calibrated using digitized | ||
41 | training polygons and independently validated data from the National | 41 | training polygons and independently validated data from the National | ||
42 | Forest Inventory (NFI). Whereas high model overall accuracies (0.97) | 42 | Forest Inventory (NFI). Whereas high model overall accuracies (0.97) | ||
43 | and kappa (0.96) were achieved, the comparison of the tree type map | 43 | and kappa (0.96) were achieved, the comparison of the tree type map | ||
44 | with independent NFI data revealed deviations in mixed | 44 | with independent NFI data revealed deviations in mixed | ||
45 | stands.\r\n\r\nIn the 2016 version (3 m spatial resolution), the | 45 | stands.\r\n\r\nIn the 2016 version (3 m spatial resolution), the | ||
46 | classification approach incorporates a random forest classifier, | 46 | classification approach incorporates a random forest classifier, | ||
47 | explanatory variables from multispectral aerial imagery and a Digital | 47 | explanatory variables from multispectral aerial imagery and a Digital | ||
48 | Terrain Model (DTM) from Airborne Laser Scanning (ALS) data, digitized | 48 | Terrain Model (DTM) from Airborne Laser Scanning (ALS) data, digitized | ||
49 | training polygons and independent validation data from the National | 49 | training polygons and independent validation data from the National | ||
50 | Forest Inventory (NFI). Whereas high model overall accuracies (0.99) | 50 | Forest Inventory (NFI). Whereas high model overall accuracies (0.99) | ||
51 | and kappa (0.98) were achieved, the comparison of the tree type map | 51 | and kappa (0.98) were achieved, the comparison of the tree type map | ||
52 | with independent NFI data revealed significant deviations that are | 52 | with independent NFI data revealed significant deviations that are | ||
53 | related to underestimations of broadleaved trees (median of 3.17%).", | 53 | related to underestimations of broadleaved trees (median of 3.17%).", | ||
54 | "num_resources": 4, | 54 | "num_resources": 4, | ||
55 | "num_tags": 5, | 55 | "num_tags": 5, | ||
56 | "organization": { | 56 | "organization": { | ||
57 | "approval_status": "approved", | 57 | "approval_status": "approved", | ||
58 | "created": "2017-04-20T16:51:21.920128", | 58 | "created": "2017-04-20T16:51:21.920128", | ||
59 | "description": "We develop and apply comprehensive and robust | 59 | "description": "We develop and apply comprehensive and robust | ||
60 | methods to extract and classify natural objects from continuous and | 60 | methods to extract and classify natural objects from continuous and | ||
61 | discrete raster datasets. Relevant features are acquired to describe | 61 | discrete raster datasets. Relevant features are acquired to describe | ||
62 | changes in landscape and land resources at different levels using | 62 | changes in landscape and land resources at different levels using | ||
63 | image data. Mathematical-statistical methods are adopted for automatic | 63 | image data. Mathematical-statistical methods are adopted for automatic | ||
64 | detection and description of image objects. Thus we contribute | 64 | detection and description of image objects. Thus we contribute | ||
65 | concepts, methods and data to describe/detect area wide changes and | 65 | concepts, methods and data to describe/detect area wide changes and | ||
66 | processes in the resources of landscape.\r\n\r\n### Tasks and main | 66 | processes in the resources of landscape.\r\n\r\n### Tasks and main | ||
67 | research\r\n\r\n* Development and application of methods to extract | 67 | research\r\n\r\n* Development and application of methods to extract | ||
68 | natural objects from continuous data.\r\n* Development of methods for | 68 | natural objects from continuous data.\r\n* Development of methods for | ||
69 | a comprehensive description of natural and anthropogenetic boundaries | 69 | a comprehensive description of natural and anthropogenetic boundaries | ||
70 | in continuous pattern (e.g. map signatures, vegetation transition, | 70 | in continuous pattern (e.g. map signatures, vegetation transition, | ||
71 | forest borders).\r\n* Development and application of methods to | 71 | forest borders).\r\n* Development and application of methods to | ||
72 | extract 3D-information from remotely sensed data for description of | 72 | extract 3D-information from remotely sensed data for description of | ||
73 | natural structures and changes. The main focus lies on wood and its | 73 | natural structures and changes. The main focus lies on wood and its | ||
74 | embedding/interaction within/with the landscape.\r\n* Conception and | 74 | embedding/interaction within/with the landscape.\r\n* Conception and | ||
75 | development of data acquisition based on high resolution remote | 75 | development of data acquisition based on high resolution remote | ||
76 | sensing data.\r\n* Conception, development and maintenance of the | 76 | sensing data.\r\n* Conception, development and maintenance of the | ||
77 | software interface in area wide data acquisition using airborne remote | 77 | software interface in area wide data acquisition using airborne remote | ||
78 | sensing data.\r\n* Scientific expert advice and support in the fields | 78 | sensing data.\r\n* Scientific expert advice and support in the fields | ||
79 | of photogrammetry and survey at WSL. Maintenance, enhancements and | 79 | of photogrammetry and survey at WSL. Maintenance, enhancements and | ||
80 | future development in these specific fields.\r\n* Adequate | 80 | future development in these specific fields.\r\n* Adequate | ||
81 | presentation of scientific results on national level and in noted | 81 | presentation of scientific results on national level and in noted | ||
82 | international journals and at international | 82 | international journals and at international | ||
83 | congresses/workshops/symposia.\r\n\r\n__Further information__: | 83 | congresses/workshops/symposia.\r\n\r\n__Further information__: | ||
84 | l/organization/research-units/landscape-dynamics/remote-sensing.html", | 84 | l/organization/research-units/landscape-dynamics/remote-sensing.html", | ||
85 | "id": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", | 85 | "id": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", | ||
86 | "image_url": "2018-07-10-102816.481589LogoWSL.svg", | 86 | "image_url": "2018-07-10-102816.481589LogoWSL.svg", | ||
87 | "is_organization": true, | 87 | "is_organization": true, | ||
88 | "name": "remote-sensing", | 88 | "name": "remote-sensing", | ||
89 | "state": "active", | 89 | "state": "active", | ||
90 | "title": "Remote Sensing", | 90 | "title": "Remote Sensing", | ||
91 | "type": "organization" | 91 | "type": "organization" | ||
92 | }, | 92 | }, | ||
93 | "owner_org": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", | 93 | "owner_org": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", | ||
94 | "private": false, | 94 | "private": false, | ||
95 | "publication": "{\"publication_year\": \"2021\", \"publisher\": | 95 | "publication": "{\"publication_year\": \"2021\", \"publisher\": | ||
96 | \"National Forest Inventory (NFI)\"}", | 96 | \"National Forest Inventory (NFI)\"}", | ||
97 | "publication_state": "published", | 97 | "publication_state": "published", | ||
98 | "related_datasets": "", | 98 | "related_datasets": "", | ||
99 | "related_publications": "", | 99 | "related_publications": "", | ||
100 | "relationships_as_object": [], | 100 | "relationships_as_object": [], | ||
101 | "relationships_as_subject": [], | 101 | "relationships_as_subject": [], | ||
102 | "resource_type": "dataset", | 102 | "resource_type": "dataset", | ||
103 | "resource_type_general": "dataset", | 103 | "resource_type_general": "dataset", | ||
104 | "resources": [ | 104 | "resources": [ | ||
105 | { | 105 | { | ||
106 | "cache_last_updated": null, | 106 | "cache_last_updated": null, | ||
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108 | "created": "2021-04-23T08:02:00.149511", | 108 | "created": "2021-04-23T08:02:00.149511", | ||
109 | "description": "This dataset presents a remote sensing-based | 109 | "description": "This dataset presents a remote sensing-based | ||
110 | approach for a countrywide mapping of the Dominant Leave Type (DLT) | 110 | approach for a countrywide mapping of the Dominant Leave Type (DLT) | ||
111 | with the two classes broadleaved and coniferous in Switzerland. The | 111 | with the two classes broadleaved and coniferous in Switzerland. The | ||
112 | spatial resolution is 10 m with the fraction of the class broadleaved. | 112 | spatial resolution is 10 m with the fraction of the class broadleaved. | ||
113 | The classification approach incorporates a random forest classifier, | 113 | The classification approach incorporates a random forest classifier, | ||
114 | explanatory variables from freely available Copernicus multispectral | 114 | explanatory variables from freely available Copernicus multispectral | ||
115 | Sentinel-2, multi-temporal Sentinel-1 data and a Digital Terrain Model | 115 | Sentinel-2, multi-temporal Sentinel-1 data and a Digital Terrain Model | ||
116 | (DTM) based on Airborne Laser Scanning (ALS) (SwissAlti3D) data. The | 116 | (DTM) based on Airborne Laser Scanning (ALS) (SwissAlti3D) data. The | ||
117 | models were calibrated using digitized training polygons and | 117 | models were calibrated using digitized training polygons and | ||
118 | independently validated data from the National Forest Inventory (NFI). | 118 | independently validated data from the National Forest Inventory (NFI). | ||
119 | Whereas high model overall accuracies (0.97) and kappa (0.96) were | 119 | Whereas high model overall accuracies (0.97) and kappa (0.96) were | ||
120 | achieved, the comparison of the tree type map with independent NFI | 120 | achieved, the comparison of the tree type map with independent NFI | ||
121 | data revealed deviations in mixed stands.\r\n\r\nData 'Forest Type NFI | 121 | data revealed deviations in mixed stands.\r\n\r\nData 'Forest Type NFI | ||
122 | 2018' available on request (lars.waser@wsl.ch).", | 122 | 2018' available on request (lars.waser@wsl.ch).", | ||
123 | "doi": "10.16904/1000001.6", | 123 | "doi": "10.16904/1000001.6", | ||
124 | "format": "GeoTIFF", | 124 | "format": "GeoTIFF", | ||
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131 | "name": "2018 Forest Type (current)", | 131 | "name": "2018 Forest Type (current)", | ||
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139 | "size": 191049626, | 139 | "size": 191049626, | ||
140 | "state": "active", | 140 | "state": "active", | ||
141 | "url": | 141 | "url": | ||
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143 | "url_type": "upload" | 143 | "url_type": "upload" | ||
144 | }, | 144 | }, | ||
145 | { | 145 | { | ||
146 | "cache_last_updated": null, | 146 | "cache_last_updated": null, | ||
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148 | "created": "2021-03-27T04:57:32.557727", | 148 | "created": "2021-03-27T04:57:32.557727", | ||
149 | "description": "Data 'Forest Type NFI 2016' available on request | 149 | "description": "Data 'Forest Type NFI 2016' available on request | ||
150 | (lars.waser@wsl.ch).", | 150 | (lars.waser@wsl.ch).", | ||
151 | "doi": "10.16904/1000001.3", | 151 | "doi": "10.16904/1000001.3", | ||
152 | "format": "GeoTIFF", | 152 | "format": "GeoTIFF", | ||
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159 | "name": "2016 Forest Type", | 159 | "name": "2016 Forest Type", | ||
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168 | "state": "active", | 168 | "state": "active", | ||
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175 | "created": "2018-04-03T10:42:10.760550", | 175 | "created": "2018-04-03T10:42:10.760550", | ||
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185 | "name": "Wall-to-Wall Tree Type Mapping from Countrywide | 185 | "name": "Wall-to-Wall Tree Type Mapping from Countrywide | ||
186 | Airborne Remote Sensing Surveys", | 186 | Airborne Remote Sensing Surveys", | ||
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194 | "state": "active", | 194 | "state": "active", | ||
195 | "url": | 195 | "url": | ||
196 | "https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:14162", | 196 | "https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:14162", | ||
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225 | ], | 225 | ], | ||
226 | "spatial": | 226 | "spatial": | ||
227 | 80838],[10.49203,47.80838],[10.49203,45.81802],[5.95587,45.81802]]]}", | 227 | 80838],[10.49203,47.80838],[10.49203,45.81802],[5.95587,45.81802]]]}", | ||
228 | "spatial_info": "Switzerland", | 228 | "spatial_info": "Switzerland", | ||
229 | "state": "active", | 229 | "state": "active", | ||
230 | "subtitle": "", | 230 | "subtitle": "", | ||
231 | "tags": [ | 231 | "tags": [ | ||
232 | { | 232 | { | ||
233 | "display_name": "FOREST", | 233 | "display_name": "FOREST", | ||
234 | "id": "90cd0d8f-8df0-4b78-ac11-6e38c2a22106", | 234 | "id": "90cd0d8f-8df0-4b78-ac11-6e38c2a22106", | ||
235 | "name": "FOREST", | 235 | "name": "FOREST", | ||
236 | "state": "active", | 236 | "state": "active", | ||
237 | "vocabulary_id": null | 237 | "vocabulary_id": null | ||
238 | }, | 238 | }, | ||
239 | { | 239 | { | ||
240 | "display_name": "FOREST INVENTORY", | 240 | "display_name": "FOREST INVENTORY", | ||
241 | "id": "d1b2883f-be82-426b-8a5e-fd6d36bc2855", | 241 | "id": "d1b2883f-be82-426b-8a5e-fd6d36bc2855", | ||
242 | "name": "FOREST INVENTORY", | 242 | "name": "FOREST INVENTORY", | ||
243 | "state": "active", | 243 | "state": "active", | ||
244 | "vocabulary_id": null | 244 | "vocabulary_id": null | ||
245 | }, | 245 | }, | ||
246 | { | 246 | { | ||
247 | "display_name": "FOREST TYPE", | 247 | "display_name": "FOREST TYPE", | ||
248 | "id": "52ad8bb3-8ec8-4e9d-8798-858d7662c3e4", | 248 | "id": "52ad8bb3-8ec8-4e9d-8798-858d7662c3e4", | ||
249 | "name": "FOREST TYPE", | 249 | "name": "FOREST TYPE", | ||
250 | "state": "active", | 250 | "state": "active", | ||
251 | "vocabulary_id": null | 251 | "vocabulary_id": null | ||
252 | }, | 252 | }, | ||
253 | { | 253 | { | ||
254 | "display_name": "NFI", | 254 | "display_name": "NFI", | ||
255 | "id": "0a74eb64-cf7b-42df-b2d4-1a5ad8171458", | 255 | "id": "0a74eb64-cf7b-42df-b2d4-1a5ad8171458", | ||
256 | "name": "NFI", | 256 | "name": "NFI", | ||
257 | "state": "active", | 257 | "state": "active", | ||
258 | "vocabulary_id": null | 258 | "vocabulary_id": null | ||
259 | }, | 259 | }, | ||
260 | { | 260 | { | ||
261 | "display_name": "REMOTE SENSING", | 261 | "display_name": "REMOTE SENSING", | ||
262 | "id": "1bc9d51e-2500-44a7-857b-13710a59e4be", | 262 | "id": "1bc9d51e-2500-44a7-857b-13710a59e4be", | ||
263 | "name": "REMOTE SENSING", | 263 | "name": "REMOTE SENSING", | ||
264 | "state": "active", | 264 | "state": "active", | ||
265 | "vocabulary_id": null | 265 | "vocabulary_id": null | ||
266 | } | 266 | } | ||
267 | ], | 267 | ], | ||
268 | "title": "Forest Type NFI", | 268 | "title": "Forest Type NFI", | ||
269 | "type": "dataset", | 269 | "type": "dataset", | ||
270 | "url": null, | 270 | "url": null, | ||
271 | "version": "2018 (current)" | 271 | "version": "2018 (current)" | ||
272 | } | 272 | } |