f | { | f | { |
| "author": "[{\"affiliation\": \"Swiss Federal Research Institute | | "author": "[{\"affiliation\": \"Swiss Federal Research Institute |
| WSL; University of Z\\u00fcrich\", \"affiliation_02\": \"\", | | WSL; University of Z\\u00fcrich\", \"affiliation_02\": \"\", |
| \"affiliation_03\": \"\", \"data_credit\": [\"collection\", | | \"affiliation_03\": \"\", \"data_credit\": [\"collection\", |
| \"validation\", \"curation\", \"software\", \"publication\"], | | \"validation\", \"curation\", \"software\", \"publication\"], |
| \"email\": \"tiziana.li@t-online.de\", \"given_name\": \"Tiziana\", | | \"email\": \"tiziana.li@t-online.de\", \"given_name\": \"Tiziana\", |
| \"identifier\": \"0000-0002-0195-4119\", \"name\": \"Koch\"}, | | \"identifier\": \"0000-0002-0195-4119\", \"name\": \"Koch\"}, |
| {\"affiliation\": \"WSL\", \"affiliation_02\": \"\", | | {\"affiliation\": \"WSL\", \"affiliation_02\": \"\", |
| \"affiliation_03\": \"\", \"data_credit\": [\"validation\", | | \"affiliation_03\": \"\", \"data_credit\": [\"validation\", |
| \"publication\", \"supervision\"], \"email\": | | \"publication\", \"supervision\"], \"email\": |
| \"dominique.weber@wsl.ch\", \"given_name\": \"Dominique\", | | \"dominique.weber@wsl.ch\", \"given_name\": \"Dominique\", |
| \"identifier\": \"0000-0002-0402-9682\", \"name\": \"Weber\"}, | | \"identifier\": \"0000-0002-0402-9682\", \"name\": \"Weber\"}, |
| {\"affiliation\": \"Swiss Federal Institute for Forest, Snow and | | {\"affiliation\": \"Swiss Federal Institute for Forest, Snow and |
| Landscape Research WSL \", \"affiliation_02\": \"\", | | Landscape Research WSL \", \"affiliation_02\": \"\", |
| \"affiliation_03\": \"\", \"data_credit\": [\"publication\", | | \"affiliation_03\": \"\", \"data_credit\": [\"publication\", |
| \"supervision\"], \"email\": \"lars.waser@wsl.ch\", \"given_name\": | | \"supervision\"], \"email\": \"lars.waser@wsl.ch\", \"given_name\": |
| \"Lars\", \"identifier\": \"D-5937-2011\", \"name\": \"Waser\"}]", | | \"Lars\", \"identifier\": \"D-5937-2011\", \"name\": \"Waser\"}]", |
| "author_email": null, | | "author_email": null, |
| "creator_user_id": "06333ba0-47fe-41e8-9b65-5945024eca8a", | | "creator_user_id": "06333ba0-47fe-41e8-9b65-5945024eca8a", |
| "date": "[{\"date\": \"2017-01-01\", \"date_type\": \"collected\", | | "date": "[{\"date\": \"2017-01-01\", \"date_type\": \"collected\", |
| \"end_date\": \"2023-12-31\"}, {\"date\": \"2017-01-01\", | | \"end_date\": \"2023-12-31\"}, {\"date\": \"2017-01-01\", |
| \"date_type\": \"created\", \"end_date\": \"2023-12-31\"}]", | | \"date_type\": \"created\", \"end_date\": \"2023-12-31\"}]", |
| "doi": "10.16904/envidat.510", | | "doi": "10.16904/envidat.510", |
| "funding": "[{\"grant_number\": \"200021_184605\", \"institution\": | | "funding": "[{\"grant_number\": \"200021_184605\", \"institution\": |
| \"Swiss National Science Foundation\", \"institution_url\": \"\"}]", | | \"Swiss National Science Foundation\", \"institution_url\": \"\"}]", |
| "groups": [], | | "groups": [], |
| "id": "eb913ad8-aec4-472f-a827-179b4ec87371", | | "id": "eb913ad8-aec4-472f-a827-179b4ec87371", |
| "isopen": true, | | "isopen": true, |
| "language": "en", | | "language": "en", |
| "license_id": "cc-by-sa", | | "license_id": "cc-by-sa", |
| "license_title": "Creative Commons Attribution Share-Alike | | "license_title": "Creative Commons Attribution Share-Alike |
| (CC-BY-SA)", | | (CC-BY-SA)", |
| "license_url": "https://creativecommons.org/licenses/by-sa/4.0/", | | "license_url": "https://creativecommons.org/licenses/by-sa/4.0/", |
| "maintainer": "{\"affiliation\": \"\", \"email\": | | "maintainer": "{\"affiliation\": \"\", \"email\": |
| \"tiziana.li@t-online.de\", \"given_name\": \"Tiziana\", | | \"tiziana.li@t-online.de\", \"given_name\": \"Tiziana\", |
| \"identifier\": \"\", \"name\": \"Koch\"}", | | \"identifier\": \"\", \"name\": \"Koch\"}", |
| "maintainer_email": null, | | "maintainer_email": null, |
| "metadata_created": "2024-05-23T09:00:09.022414", | | "metadata_created": "2024-05-23T09:00:09.022414", |
n | "metadata_modified": "2024-07-09T05:59:40.261188", | n | "metadata_modified": "2024-07-09T05:59:59.963828", |
| "name": "sentinel-2-imagery-of-switzerland", | | "name": "sentinel-2-imagery-of-switzerland", |
t | "notes": "# Sentinel-2 imagery of Switzerland \r\n\r\nWe processed | t | "notes": "\r\nWe processed Sentinel-2 images from 2017 to 2023 for |
| Sentinel-2 images from 2017 to 2023 for Switzerland with the Software | | Switzerland with the Software FORCE (Frantz 2019). The respective |
| FORCE (Frantz 2019). The respective parameter files can be found here: | | parameter files can be found here: |
| [Github](https://github.com/TLKoch/Sentinel-2_CH). All the images | | [Github](https://github.com/TLKoch/Sentinel-2_CH). All the images |
| consist of several TB and therefore, access will be granted upon | | consist of several TB and therefore, access will be granted upon |
| request. \r\nThe available bands (in spatial reference system EPSG | | request. \r\nThe available bands (in spatial reference system EPSG |
| 3035) are the following:\r\n*Red, Green, Blue, NIR, Red-Edge-1, | | 3035) are the following:\r\n*Red, Green, Blue, NIR, Red-Edge-1, |
| Red-Edge-2, Red-Edge-3, SWIR-1, SWIR-2*\r\nThe available indices (in | | Red-Edge-2, Red-Edge-3, SWIR-1, SWIR-2*\r\nThe available indices (in |
| spatial reference system EPSG 3035) are the following:\r\n*CCI, CIRE, | | spatial reference system EPSG 3035) are the following:\r\n*CCI, CIRE, |
| NDWI/NDMI, NDVI, EVI*\r\nFurther indices might be provided upon | | NDWI/NDMI, NDVI, EVI*\r\nFurther indices might be provided upon |
| request.\r\n\r\n\r\n### Processing\r\nAfter downloading Level 1 data | | request.\r\n\r\n\r\n### Processing\r\nAfter downloading Level 1 data |
| for the 14 Sentinel-2 tiles covering Switzerland (T31TGN, T32TLT, | | for the 14 Sentinel-2 tiles covering Switzerland (T31TGN, T32TLT, |
| T32TMT, T32UMU, T32TNT, T32TPT, T31TGM, T32TLS, T32TMS, T32TNS, | | T32TMT, T32UMU, T32TNT, T32TPT, T31TGM, T32TLS, T32TMS, T32TNS, |
| T32TPS, T32TLR, T32TMR, T32TNR) with an estimated cloud cover of less | | T32TPS, T32TLR, T32TMR, T32TNR) with an estimated cloud cover of less |
| than 80 \\%, we processed the data further with FORCE v. | | than 80 \\%, we processed the data further with FORCE v. |
| 3.7.8-12.\r\nFORCE was used for radiometric correction, including | | 3.7.8-12.\r\nFORCE was used for radiometric correction, including |
| atmospheric and topographic corrections using the digital elevation | | atmospheric and topographic corrections using the digital elevation |
| model from Copernicus Land Monitoring Service (EU-DEM v. 1.1), with a | | model from Copernicus Land Monitoring Service (EU-DEM v. 1.1), with a |
| 25 m spatial resolution, a bidirectional reflectance distribution | | 25 m spatial resolution, a bidirectional reflectance distribution |
| function (BRDF) correction, and an adjacency effect correction. For | | function (BRDF) correction, and an adjacency effect correction. For |
| cloud masking, the improved Fmask algorithm with buffers of 300 m for | | cloud masking, the improved Fmask algorithm with buffers of 300 m for |
| clouds, 90 m for shadows, and 30 m for snow were used (Frantz et al. | | clouds, 90 m for shadows, and 30 m for snow were used (Frantz et al. |
| 2018; Zhu et al. 2015). All bands were resampled using cubic | | 2018; Zhu et al. 2015). All bands were resampled using cubic |
| convolution to 10 m spatial resolution. Shadows, low and poor | | convolution to 10 m spatial resolution. Shadows, low and poor |
| illumination as well as saturation were masked out. The | | illumination as well as saturation were masked out. The |
| co-registration of all images was made with monthly composites of | | co-registration of all images was made with monthly composites of |
| near-infrared Landsat Collection 2 images from 2014 to 2021 | | near-infrared Landsat Collection 2 images from 2014 to 2021 |
| (Rengarajan et al. 2020;Rufin et al. 2021). With this the geometric | | (Rengarajan et al. 2020;Rufin et al. 2021). With this the geometric |
| consistency improved. The processed images are available in tiles of | | consistency improved. The processed images are available in tiles of |
| 30 by 30 km. \r\n\r\n\r\n### Example images\r\nUploaded is an | | 30 by 30 km. \r\n\r\n\r\n### Example images\r\nUploaded is an |
| example of the index EVI for one of the generated 30 by 30 km tiles | | example of the index EVI for one of the generated 30 by 30 km tiles |
| located around the city of Z\u00fcrich. The values are multiplied by | | located around the city of Z\u00fcrich. The values are multiplied by |
| 10.000. The date of the image is 24.07.2018.\r\n", | | 10.000. The date of the image is 24.07.2018.\r\n", |
| "num_resources": 1, | | "num_resources": 1, |
| "num_tags": 5, | | "num_tags": 5, |
| "organization": { | | "organization": { |
| "approval_status": "approved", | | "approval_status": "approved", |
| "created": "2017-04-20T16:51:21.920128", | | "created": "2017-04-20T16:51:21.920128", |
| "description": "We develop and apply comprehensive and robust | | "description": "We develop and apply comprehensive and robust |
| methods to extract and classify natural objects from continuous and | | methods to extract and classify natural objects from continuous and |
| discrete raster datasets. Relevant features are acquired to describe | | discrete raster datasets. Relevant features are acquired to describe |
| changes in landscape and land resources at different levels using | | changes in landscape and land resources at different levels using |
| image data. Mathematical-statistical methods are adopted for automatic | | image data. Mathematical-statistical methods are adopted for automatic |
| detection and description of image objects. Thus we contribute | | detection and description of image objects. Thus we contribute |
| concepts, methods and data to describe/detect area wide changes and | | concepts, methods and data to describe/detect area wide changes and |
| processes in the resources of landscape.\r\n\r\n### Tasks and main | | processes in the resources of landscape.\r\n\r\n### Tasks and main |
| research\r\n\r\n* Development and application of methods to extract | | research\r\n\r\n* Development and application of methods to extract |
| natural objects from continuous data.\r\n* Development of methods for | | natural objects from continuous data.\r\n* Development of methods for |
| a comprehensive description of natural and anthropogenetic boundaries | | a comprehensive description of natural and anthropogenetic boundaries |
| in continuous pattern (e.g. map signatures, vegetation transition, | | in continuous pattern (e.g. map signatures, vegetation transition, |
| forest borders).\r\n* Development and application of methods to | | forest borders).\r\n* Development and application of methods to |
| extract 3D-information from remotely sensed data for description of | | extract 3D-information from remotely sensed data for description of |
| natural structures and changes. The main focus lies on wood and its | | natural structures and changes. The main focus lies on wood and its |
| embedding/interaction within/with the landscape.\r\n* Conception and | | embedding/interaction within/with the landscape.\r\n* Conception and |
| development of data acquisition based on high resolution remote | | development of data acquisition based on high resolution remote |
| sensing data.\r\n* Conception, development and maintenance of the | | sensing data.\r\n* Conception, development and maintenance of the |
| software interface in area wide data acquisition using airborne remote | | software interface in area wide data acquisition using airborne remote |
| sensing data.\r\n* Scientific expert advice and support in the fields | | sensing data.\r\n* Scientific expert advice and support in the fields |
| of photogrammetry and survey at WSL. Maintenance, enhancements and | | of photogrammetry and survey at WSL. Maintenance, enhancements and |
| future development in these specific fields.\r\n* Adequate | | future development in these specific fields.\r\n* Adequate |
| presentation of scientific results on national level and in noted | | presentation of scientific results on national level and in noted |
| international journals and at international | | international journals and at international |
| congresses/workshops/symposia.\r\n\r\n__Further information__: | | congresses/workshops/symposia.\r\n\r\n__Further information__: |
| l/organization/research-units/landscape-dynamics/remote-sensing.html", | | l/organization/research-units/landscape-dynamics/remote-sensing.html", |
| "id": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", | | "id": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", |
| "image_url": "2018-07-10-102816.481589LogoWSL.svg", | | "image_url": "2018-07-10-102816.481589LogoWSL.svg", |
| "is_organization": true, | | "is_organization": true, |
| "name": "remote-sensing", | | "name": "remote-sensing", |
| "state": "active", | | "state": "active", |
| "title": "Remote Sensing", | | "title": "Remote Sensing", |
| "type": "organization" | | "type": "organization" |
| }, | | }, |
| "owner_org": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", | | "owner_org": "5243fbb4-e4e6-4779-9672-32a7ef33d5f9", |
| "private": false, | | "private": false, |
| "publication": "{\"publication_year\": \"2024\", \"publisher\": | | "publication": "{\"publication_year\": \"2024\", \"publisher\": |
| \"EnviDat\"}", | | \"EnviDat\"}", |
| "publication_state": "published", | | "publication_state": "published", |
| "related_datasets": "", | | "related_datasets": "", |
| "related_publications": " * D. Frantz, \u201cFORCE\u2014Landsat + | | "related_publications": " * D. Frantz, \u201cFORCE\u2014Landsat + |
| Sentinel-2 Analysis Ready Data and Beyond,\u201d Remote Sensing, vol. | | Sentinel-2 Analysis Ready Data and Beyond,\u201d Remote Sensing, vol. |
| 11, no. 9, 2019.\r\n\r\n * D. Frantz, E. Ha\u00df, A. Uhl, J. | | 11, no. 9, 2019.\r\n\r\n * D. Frantz, E. Ha\u00df, A. Uhl, J. |
| Stoffels, and J. Hill, \u201cImprovement of the Fmask algorithm for | | Stoffels, and J. Hill, \u201cImprovement of the Fmask algorithm for |
| Sentinel-2 images: Separating clouds from bright surfaces based on | | Sentinel-2 images: Separating clouds from bright surfaces based on |
| parallax effects,\u201d Remote Sensing of Environment, vol. 215, pp. | | parallax effects,\u201d Remote Sensing of Environment, vol. 215, pp. |
| 471\u2013481, 2018.\r\n\r\n * R. Rengarajan, M. Choate, J. Storey, S. | | 471\u2013481, 2018.\r\n\r\n * R. Rengarajan, M. Choate, J. Storey, S. |
| Franks, E. Micijevic, J. J. Butler, X. Xiong, and X. Gu, \u201cLandsat | | Franks, E. Micijevic, J. J. Butler, X. Xiong, and X. Gu, \u201cLandsat |
| Collection-2 geometric calibration updates,\u201d 2020.\r\n\r\n * P. | | Collection-2 geometric calibration updates,\u201d 2020.\r\n\r\n * P. |
| Rufin, D. Frantz, L. Yan, and P. Hostert, \u201cOperational | | Rufin, D. Frantz, L. Yan, and P. Hostert, \u201cOperational |
| Coregistration of the Sentinel-2A/B Image Archive Using Multitemporal | | Coregistration of the Sentinel-2A/B Image Archive Using Multitemporal |
| Landsat Spectral Averages,\u201d IEEE Geoscience and Remote Sensing | | Landsat Spectral Averages,\u201d IEEE Geoscience and Remote Sensing |
| Letters, vol. 18, no. 4, pp. 712\u2013716, 2021.\r\n\r\n * Z. Zhu, S. | | Letters, vol. 18, no. 4, pp. 712\u2013716, 2021.\r\n\r\n * Z. Zhu, S. |
| Wang, and C. E. Woodcock, \u201cImprovement and expansion of the Fmask | | Wang, and C. E. Woodcock, \u201cImprovement and expansion of the Fmask |
| algorithm: cloud, cloud shadow, and snow detection for Landsats | | algorithm: cloud, cloud shadow, and snow detection for Landsats |
| 4\u20137, 8, and Sentinel 2 images,\u201d Remote Sensing of | | 4\u20137, 8, and Sentinel 2 images,\u201d Remote Sensing of |
| Environment, vol. 159, pp. 269\u2013277, 2015.", | | Environment, vol. 159, pp. 269\u2013277, 2015.", |
| "relationships_as_object": [], | | "relationships_as_object": [], |
| "relationships_as_subject": [], | | "relationships_as_subject": [], |
| "resource_type": "dataset", | | "resource_type": "dataset", |
| "resource_type_general": "dataset", | | "resource_type_general": "dataset", |
| "resources": [ | | "resources": [ |
| { | | { |
| "cache_last_updated": null, | | "cache_last_updated": null, |
| "cache_url": null, | | "cache_url": null, |
| "created": "2024-05-23T09:00:28.099450", | | "created": "2024-05-23T09:00:28.099450", |
| "description": "An example of the index EVI for one of the | | "description": "An example of the index EVI for one of the |
| generated 30 by 30 km tiles located around the city of Z\u00fcrich. | | generated 30 by 30 km tiles located around the city of Z\u00fcrich. |
| The values are multiplied by 10.000. The date of the image is | | The values are multiplied by 10.000. The date of the image is |
| 24.07.2018.", | | 24.07.2018.", |
| "doi": "", | | "doi": "", |
| "format": "tif", | | "format": "tif", |
| "hash": "", | | "hash": "", |
| "id": "5d61e0ec-f785-45ba-8281-8668855ee94b", | | "id": "5d61e0ec-f785-45ba-8281-8668855ee94b", |
| "last_modified": "2024-05-23T11:03:53.738000", | | "last_modified": "2024-05-23T11:03:53.738000", |
| "metadata_modified": "2024-05-23T09:03:54.461091", | | "metadata_modified": "2024-05-23T09:03:54.461091", |
| "mimetype": "image/tiff", | | "mimetype": "image/tiff", |
| "mimetype_inner": null, | | "mimetype_inner": null, |
| "name": "EVI_20180724_example.tif", | | "name": "EVI_20180724_example.tif", |
| "package_id": "eb913ad8-aec4-472f-a827-179b4ec87371", | | "package_id": "eb913ad8-aec4-472f-a827-179b4ec87371", |
| "position": 0, | | "position": 0, |
| "resource_size": "{\"size_value\":\"\",\"size_units\":\"\"}", | | "resource_size": "{\"size_value\":\"\",\"size_units\":\"\"}", |
| "resource_type": null, | | "resource_type": null, |
| "restricted": | | "restricted": |
| {\"level\":\"public\",\"allowed_users\":\"\",\"shared_secret\":\"\"}", | | {\"level\":\"public\",\"allowed_users\":\"\",\"shared_secret\":\"\"}", |
| "size": 24317492, | | "size": 24317492, |
| "state": "active", | | "state": "active", |
| "url": | | "url": |
| 61e0ec-f785-45ba-8281-8668855ee94b/download/evi_20180724_example.tif", | | 61e0ec-f785-45ba-8281-8668855ee94b/download/evi_20180724_example.tif", |
| "url_type": "upload" | | "url_type": "upload" |
| } | | } |
| ], | | ], |
| "spatial": | | "spatial": |
| 838],[10.49203,47.80838],[10.49203,45.81802],[5.95587,45.81802]]]}]}", | | 838],[10.49203,47.80838],[10.49203,45.81802],[5.95587,45.81802]]]}]}", |
| "spatial_info": "Switzerland", | | "spatial_info": "Switzerland", |
| "state": "active", | | "state": "active", |
| "subtitle": "", | | "subtitle": "", |
| "tags": [ | | "tags": [ |
| { | | { |
| "display_name": "FORCE", | | "display_name": "FORCE", |
| "id": "6a4bfcdd-4f30-4d82-8a3c-ae371c2b60fa", | | "id": "6a4bfcdd-4f30-4d82-8a3c-ae371c2b60fa", |
| "name": "FORCE", | | "name": "FORCE", |
| "state": "active", | | "state": "active", |
| "vocabulary_id": null | | "vocabulary_id": null |
| }, | | }, |
| { | | { |
| "display_name": "RASTER PROCESSING", | | "display_name": "RASTER PROCESSING", |
| "id": "48a681f6-4145-4c82-8feb-545bff176d1f", | | "id": "48a681f6-4145-4c82-8feb-545bff176d1f", |
| "name": "RASTER PROCESSING", | | "name": "RASTER PROCESSING", |
| "state": "active", | | "state": "active", |
| "vocabulary_id": null | | "vocabulary_id": null |
| }, | | }, |
| { | | { |
| "display_name": "REMOTE SENSING", | | "display_name": "REMOTE SENSING", |
| "id": "1bc9d51e-2500-44a7-857b-13710a59e4be", | | "id": "1bc9d51e-2500-44a7-857b-13710a59e4be", |
| "name": "REMOTE SENSING", | | "name": "REMOTE SENSING", |
| "state": "active", | | "state": "active", |
| "vocabulary_id": null | | "vocabulary_id": null |
| }, | | }, |
| { | | { |
| "display_name": "SENTINEL-2", | | "display_name": "SENTINEL-2", |
| "id": "1fcb6de2-5d54-45cf-a42f-751cec4ebe86", | | "id": "1fcb6de2-5d54-45cf-a42f-751cec4ebe86", |
| "name": "SENTINEL-2", | | "name": "SENTINEL-2", |
| "state": "active", | | "state": "active", |
| "vocabulary_id": null | | "vocabulary_id": null |
| }, | | }, |
| { | | { |
| "display_name": "SWITZERLAND", | | "display_name": "SWITZERLAND", |
| "id": "97ac3564-bb88-46ad-9fe4-b7d606e0aa3a", | | "id": "97ac3564-bb88-46ad-9fe4-b7d606e0aa3a", |
| "name": "SWITZERLAND", | | "name": "SWITZERLAND", |
| "state": "active", | | "state": "active", |
| "vocabulary_id": null | | "vocabulary_id": null |
| } | | } |
| ], | | ], |
| "title": "Sentinel-2 imagery of Switzerland", | | "title": "Sentinel-2 imagery of Switzerland", |
| "type": "dataset", | | "type": "dataset", |
| "url": null, | | "url": null, |
| "version": "1.0" | | "version": "1.0" |
| } | | } |