Changes
On October 14, 2021 at 3:05:42 PM UTC, Administrator:
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Changed value of field
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topublished
in Soil sealing Barcelona and Milan different territorial levels
f | 1 | { | f | 1 | { |
2 | "author": "[{\"affiliation\": \"University of Bamberg\", | 2 | "author": "[{\"affiliation\": \"University of Bamberg\", | ||
3 | \"affiliation_02\": \"WSL, Land Change Science, Land-use systems\", | 3 | \"affiliation_02\": \"WSL, Land Change Science, Land-use systems\", | ||
4 | \"affiliation_03\": \"\", \"data_credit\": [\"validation\", | 4 | \"affiliation_03\": \"\", \"data_credit\": [\"validation\", | ||
5 | \"curation\", \"publication\", \"supervision\"], \"email\": | 5 | \"curation\", \"publication\", \"supervision\"], \"email\": | ||
6 | \"sofia.pagliarin@uni-bamberg.de\", \"given_name\": \"Sofia\", | 6 | \"sofia.pagliarin@uni-bamberg.de\", \"given_name\": \"Sofia\", | ||
7 | \"identifier\": \"0000-0003-4846-6072\", \"name\": \"Pagliarin\"}]", | 7 | \"identifier\": \"0000-0003-4846-6072\", \"name\": \"Pagliarin\"}]", | ||
8 | "author_email": null, | 8 | "author_email": null, | ||
9 | "creator_user_id": "4f075d7a-2215-4465-b317-3a06ba799272", | 9 | "creator_user_id": "4f075d7a-2215-4465-b317-3a06ba799272", | ||
10 | "date": "[{\"date\": \"2020-03-01\", \"date_type\": \"created\", | 10 | "date": "[{\"date\": \"2020-03-01\", \"date_type\": \"created\", | ||
11 | \"end_date\": \"2021-05-07\"}]", | 11 | \"end_date\": \"2021-05-07\"}]", | ||
12 | "doi": "10.16904/envidat.251", | 12 | "doi": "10.16904/envidat.251", | ||
13 | "extras": [ | 13 | "extras": [ | ||
14 | { | 14 | { | ||
15 | "key": "Count", | 15 | "key": "Count", | ||
16 | "value": "No. of 20x20mt cells (from raster)" | 16 | "value": "No. of 20x20mt cells (from raster)" | ||
17 | }, | 17 | }, | ||
18 | { | 18 | { | ||
19 | "key": "Labels", | 19 | "key": "Labels", | ||
20 | "value": | 20 | "value": | ||
21 | "bcn_city,bcn_amb,bcn_grc,bcn_fua,mi_city,mi_pim,mi_grc,mi_fua" | 21 | "bcn_city,bcn_amb,bcn_grc,bcn_fua,mi_city,mi_pim,mi_grc,mi_fua" | ||
22 | }, | 22 | }, | ||
23 | { | 23 | { | ||
24 | "key": "Value", | 24 | "key": "Value", | ||
25 | "value": "0-100" | 25 | "value": "0-100" | ||
26 | }, | 26 | }, | ||
27 | { | 27 | { | ||
28 | "key": "km2", | 28 | "key": "km2", | ||
29 | "value": "Count field converted in km2" | 29 | "value": "Count field converted in km2" | ||
30 | } | 30 | } | ||
31 | ], | 31 | ], | ||
32 | "funding": "[{\"grant_number\": \"PA357311\", \"institution\": \"DFG | 32 | "funding": "[{\"grant_number\": \"PA357311\", \"institution\": \"DFG | ||
33 | (Deutsche Forschungsgemeinschaft)\", \"institution_url\": \"\"}]", | 33 | (Deutsche Forschungsgemeinschaft)\", \"institution_url\": \"\"}]", | ||
34 | "groups": [], | 34 | "groups": [], | ||
35 | "id": "34fc9c0c-1c90-4f87-b3a9-76cc0e888eda", | 35 | "id": "34fc9c0c-1c90-4f87-b3a9-76cc0e888eda", | ||
36 | "isopen": true, | 36 | "isopen": true, | ||
37 | "language": "en", | 37 | "language": "en", | ||
38 | "license_id": "cc-by-sa", | 38 | "license_id": "cc-by-sa", | ||
39 | "license_title": "Creative Commons Attribution Share-Alike | 39 | "license_title": "Creative Commons Attribution Share-Alike | ||
40 | (CC-BY-SA)", | 40 | (CC-BY-SA)", | ||
41 | "license_url": "https://creativecommons.org/licenses/by-sa/4.0/", | 41 | "license_url": "https://creativecommons.org/licenses/by-sa/4.0/", | ||
42 | "maintainer": "{\"affiliation\": \"University of Bamberg\", | 42 | "maintainer": "{\"affiliation\": \"University of Bamberg\", | ||
43 | \"email\": \"sofia.pagliarin@uni-bamberg.de\", \"given_name\": | 43 | \"email\": \"sofia.pagliarin@uni-bamberg.de\", \"given_name\": | ||
44 | \"Sofia\", \"identifier\": \"0000-0003-4846-6072\", \"name\": | 44 | \"Sofia\", \"identifier\": \"0000-0003-4846-6072\", \"name\": | ||
45 | \"Pagliarin\"}", | 45 | \"Pagliarin\"}", | ||
46 | "maintainer_email": null, | 46 | "maintainer_email": null, | ||
47 | "metadata_created": "2021-10-14T07:59:40.502820", | 47 | "metadata_created": "2021-10-14T07:59:40.502820", | ||
n | 48 | "metadata_modified": "2021-10-14T14:52:39.713317", | n | 48 | "metadata_modified": "2021-10-14T15:05:42.162806", |
49 | "name": "soil-sealing-barcelona-milan", | 49 | "name": "soil-sealing-barcelona-milan", | ||
50 | "notes": "__Dataset description__<br /> \r\nThis dataset is a | 50 | "notes": "__Dataset description__<br /> \r\nThis dataset is a | ||
51 | recalculation of the Copernicus 2015 high resolution layer (HRL) of | 51 | recalculation of the Copernicus 2015 high resolution layer (HRL) of | ||
52 | imperviousness density data (IMD) at different spatial/territorial | 52 | imperviousness density data (IMD) at different spatial/territorial | ||
53 | scales for the case studies of Barcelona and Milan. The selected | 53 | scales for the case studies of Barcelona and Milan. The selected | ||
54 | spatial/territorial scales are the following: \r\n\r\n * a)\tBarcelona | 54 | spatial/territorial scales are the following: \r\n\r\n * a)\tBarcelona | ||
55 | city boundaries\r\n * b)\tBarcelona metropolitan area, \u00c0rea | 55 | city boundaries\r\n * b)\tBarcelona metropolitan area, \u00c0rea | ||
56 | Metropolitana de Barcelona (AMB)\r\n * c)\tBarcelona greater city | 56 | Metropolitana de Barcelona (AMB)\r\n * c)\tBarcelona greater city | ||
57 | (Urban Atlas)\r\n * d)\tBarcelona functional urban area (Urban | 57 | (Urban Atlas)\r\n * d)\tBarcelona functional urban area (Urban | ||
58 | Atlas)\r\n * e)\tMilan city boundaries\r\n * f)\tMilan metropolitan | 58 | Atlas)\r\n * e)\tMilan city boundaries\r\n * f)\tMilan metropolitan | ||
59 | area, Piano Intercomunale Milanese (PIM)\r\n * g)\tMilan greater city | 59 | area, Piano Intercomunale Milanese (PIM)\r\n * g)\tMilan greater city | ||
60 | (Urban Atlas)\r\n * h)\tMilan functional urban area (Urban | 60 | (Urban Atlas)\r\n * h)\tMilan functional urban area (Urban | ||
61 | Atlas)\r\n\r\nIn each of the spatial/territorial scales listed above, | 61 | Atlas)\r\n\r\nIn each of the spatial/territorial scales listed above, | ||
62 | the number of 20x20mt cells corresponding to each of the 101 values of | 62 | the number of 20x20mt cells corresponding to each of the 101 values of | ||
63 | imperviousness (0-100% soil sealing: 0% means fully non-sealed area; | 63 | imperviousness (0-100% soil sealing: 0% means fully non-sealed area; | ||
64 | 100% means fully sealed area) is provided, as well as the converted | 64 | 100% means fully sealed area) is provided, as well as the converted | ||
65 | measure into squared kilometres (km2). <br /> <br /> | 65 | measure into squared kilometres (km2). <br /> <br /> | ||
66 | \r\n\r\n\r\n__Dataset composition__<br /> \r\nThe dataset is provided | 66 | \r\n\r\n\r\n__Dataset composition__<br /> \r\nThe dataset is provided | ||
67 | in .csv format and is composed of: <br /> | 67 | in .csv format and is composed of: <br /> | ||
68 | \r\n\r\n_IMD15_BCN_MI_Sources.csv_: Information on data sources <br /> | 68 | \r\n\r\n_IMD15_BCN_MI_Sources.csv_: Information on data sources <br /> | ||
69 | \r\n\r\n _IMD15_BCN.csv_: This file refers to the 2015 high resolution | 69 | \r\n\r\n _IMD15_BCN.csv_: This file refers to the 2015 high resolution | ||
70 | layer of imperviousness density (IMD) for the selected | 70 | layer of imperviousness density (IMD) for the selected | ||
71 | territorial/spatial scales in Barcelona: \r\n * a)\tBarcelona city | 71 | territorial/spatial scales in Barcelona: \r\n * a)\tBarcelona city | ||
72 | boundaries (label: bcn_city) \r\n * b)\tBarcelona metropolitan area, | 72 | boundaries (label: bcn_city) \r\n * b)\tBarcelona metropolitan area, | ||
73 | \u00c0rea metropolitana de Barcelona (AMB) (label: bcn_amb)\r\n * | 73 | \u00c0rea metropolitana de Barcelona (AMB) (label: bcn_amb)\r\n * | ||
74 | c)\tBarcelona greater city (Urban Atlas) (label: bcn_grc)\r\n * | 74 | c)\tBarcelona greater city (Urban Atlas) (label: bcn_grc)\r\n * | ||
75 | d)\tBarcelona functional urban area (Urban Atlas) (label: | 75 | d)\tBarcelona functional urban area (Urban Atlas) (label: | ||
76 | bcn_fua)\r\n\r\n _IMD15_MI.csv_: This file refers to the 2015 high | 76 | bcn_fua)\r\n\r\n _IMD15_MI.csv_: This file refers to the 2015 high | ||
77 | resolution layer of imperviousness density (IMD) for the selected | 77 | resolution layer of imperviousness density (IMD) for the selected | ||
78 | territorial/spatial scales in Milan: \r\n * e)\tMilan city boundaries | 78 | territorial/spatial scales in Milan: \r\n * e)\tMilan city boundaries | ||
79 | (label: mi_city)\r\n * f)\tMilan metropolitan area, Piano | 79 | (label: mi_city)\r\n * f)\tMilan metropolitan area, Piano | ||
80 | intercomunale milanese (PIM) (label: mi_pim)\r\n * g)\tMilan greater | 80 | intercomunale milanese (PIM) (label: mi_pim)\r\n * g)\tMilan greater | ||
81 | city (Urban Atlas) (label: mi_grc)\r\n * h)\tMilan functional urban | 81 | city (Urban Atlas) (label: mi_grc)\r\n * h)\tMilan functional urban | ||
82 | area (Urban Atlas) (label: mi_fua)\r\n\r\n_IMD15_BCN_MI.mpk_: the | 82 | area (Urban Atlas) (label: mi_fua)\r\n\r\n_IMD15_BCN_MI.mpk_: the | ||
83 | shareable project in Esri ArcGIS format including the HRL IMD data in | 83 | shareable project in Esri ArcGIS format including the HRL IMD data in | ||
84 | raster format for each of the territorial boundaries as specified in | 84 | raster format for each of the territorial boundaries as specified in | ||
85 | letter a)-h). <br /> \r\n\r\nRegarding the territorial scale as per | 85 | letter a)-h). <br /> \r\n\r\nRegarding the territorial scale as per | ||
86 | letter f), the list of municipalities included in the Milan | 86 | letter f), the list of municipalities included in the Milan | ||
87 | metropolitan area in 2016 was provided to me in 2016 from a person | 87 | metropolitan area in 2016 was provided to me in 2016 from a person | ||
88 | working at the PIM. <br /> \r\n\r\nIn the IMD15_BCN.csv and | 88 | working at the PIM. <br /> \r\n\r\nIn the IMD15_BCN.csv and | ||
89 | IMD15_MI.csv, the following columns are included:\r\n\r\n * Level: the | 89 | IMD15_MI.csv, the following columns are included:\r\n\r\n * Level: the | ||
90 | territorial level as defined above (a)-d) for Barcelona and e)-h) for | 90 | territorial level as defined above (a)-d) for Barcelona and e)-h) for | ||
91 | Milan);\r\n * Value: the 101 values of imperviousness density | 91 | Milan);\r\n * Value: the 101 values of imperviousness density | ||
92 | expressed as a percentage of soil sealing (0-100%: 0% means fully | 92 | expressed as a percentage of soil sealing (0-100%: 0% means fully | ||
93 | non-sealed area; 100% means fully sealed area);\r\n * Count: the | 93 | non-sealed area; 100% means fully sealed area);\r\n * Count: the | ||
94 | number of 20x20mt cells corresponding to a certain percentage of soil | 94 | number of 20x20mt cells corresponding to a certain percentage of soil | ||
95 | sealing or imperviousness; \r\n * Km2: the conversion of the 20x20mt | 95 | sealing or imperviousness; \r\n * Km2: the conversion of the 20x20mt | ||
96 | cells into squared kilometres (km2) to facilitate the use of the | 96 | cells into squared kilometres (km2) to facilitate the use of the | ||
97 | dataset.<br /> <br /> \r\n\r\n__Further information on the | 97 | dataset.<br /> <br /> \r\n\r\n__Further information on the | ||
98 | Dataset__<br /> \r\nThis dataset is the result of a combination | 98 | Dataset__<br /> \r\nThis dataset is the result of a combination | ||
99 | between different databases of different types and that have been | 99 | between different databases of different types and that have been | ||
100 | downloaded from different sources. Below, I describe the main steps in | 100 | downloaded from different sources. Below, I describe the main steps in | ||
101 | data management that resulted in the production of the dataset in an | 101 | data management that resulted in the production of the dataset in an | ||
102 | Esri ArcGIS (ArcMap, Version 10.7) project.<br /> \r\n\r\n 1. The high | 102 | Esri ArcGIS (ArcMap, Version 10.7) project.<br /> \r\n\r\n 1. The high | ||
103 | resolution layer (HRL) of the imperviousness density data (IMD) for | 103 | resolution layer (HRL) of the imperviousness density data (IMD) for | ||
104 | 2015 has been downloaded from the official website of Copernicus. At | 104 | 2015 has been downloaded from the official website of Copernicus. At | ||
105 | the time of producing the dataset (April/May 2021), the 2018 version | 105 | the time of producing the dataset (April/May 2021), the 2018 version | ||
106 | of the IMD HRL database was not yet validated, so the 2015 version was | 106 | of the IMD HRL database was not yet validated, so the 2015 version was | ||
107 | chosen instead. The type of this dataset is raster. \r\n\r\n 2. For | 107 | chosen instead. The type of this dataset is raster. \r\n\r\n 2. For | ||
108 | both Barcelona and Milan, shapefiles of their administrative | 108 | both Barcelona and Milan, shapefiles of their administrative | ||
109 | boundaries have been downloaded from official sources, i.e. the ISTAT | 109 | boundaries have been downloaded from official sources, i.e. the ISTAT | ||
110 | (Italian National Statistical Institute) and the ICGC (Catalan | 110 | (Italian National Statistical Institute) and the ICGC (Catalan | ||
111 | Institute for Cartography and Geology). These files have been | 111 | Institute for Cartography and Geology). These files have been | ||
112 | reprojected to match the IMD HRL projection, i.e. ETRS 1989 | 112 | reprojected to match the IMD HRL projection, i.e. ETRS 1989 | ||
113 | LAEA.\r\n\r\n 3. Urban Atlas (UA) boundaries for the Greater Cities | 113 | LAEA.\r\n\r\n 3. Urban Atlas (UA) boundaries for the Greater Cities | ||
114 | (GRC) and Functional Urban Areas (FUA) of Barcelona and Milan have | 114 | (GRC) and Functional Urban Areas (FUA) of Barcelona and Milan have | ||
115 | been checked and reconstructed in Esri ArcGIS from the administrative | 115 | been checked and reconstructed in Esri ArcGIS from the administrative | ||
116 | boundaries files by using a Eurostat correspondence table. This is | 116 | boundaries files by using a Eurostat correspondence table. This is | ||
117 | because at the time of the dataset creation (April/May 2021), the 2018 | 117 | because at the time of the dataset creation (April/May 2021), the 2018 | ||
118 | Urban Atlas shapefiles for these two cities were not fully updated or | 118 | Urban Atlas shapefiles for these two cities were not fully updated or | ||
119 | validated on the Copernicus Urban Atlas website. Therefore, I had to | 119 | validated on the Copernicus Urban Atlas website. Therefore, I had to | ||
120 | re-create the GRC and FUA boundaries by using the Eurostat | 120 | re-create the GRC and FUA boundaries by using the Eurostat | ||
121 | correspondence table as an alternative (but still official) data | 121 | correspondence table as an alternative (but still official) data | ||
122 | source. The use of the Eurostat correspondence table with the codes | 122 | source. The use of the Eurostat correspondence table with the codes | ||
123 | and names of municipalities was also useful to detect discrepancies, | 123 | and names of municipalities was also useful to detect discrepancies, | ||
124 | basically stemming from changes in municipality names and codes and | 124 | basically stemming from changes in municipality names and codes and | ||
125 | that created inconsistent spatial features. When detected, these | 125 | that created inconsistent spatial features. When detected, these | ||
126 | discrepancies have been checked with the ISTAT and ICGC offices in | 126 | discrepancies have been checked with the ISTAT and ICGC offices in | ||
127 | charge of producing Urban Atlas data before the final GRC and FUA | 127 | charge of producing Urban Atlas data before the final GRC and FUA | ||
128 | boundaries were defined.<br /> \r\n\r\nSteps 2) and 3) were the most | 128 | boundaries were defined.<br /> \r\n\r\nSteps 2) and 3) were the most | ||
129 | time consuming, because they required other tools to be used in Esri | 129 | time consuming, because they required other tools to be used in Esri | ||
130 | ArcGIS, like spatial joins and geoprocessing tools for shapefiles (in | 130 | ArcGIS, like spatial joins and geoprocessing tools for shapefiles (in | ||
131 | particular dissolve and area re-calculator in editing sessions) for | 131 | particular dissolve and area re-calculator in editing sessions) for | ||
132 | each of the spatial/territorial scales as indicated in letters a)-h). | 132 | each of the spatial/territorial scales as indicated in letters a)-h). | ||
133 | <br /> \r\n\r\nOnce the databases for both Barcelona and Milan as | 133 | <br /> \r\n\r\nOnce the databases for both Barcelona and Milan as | ||
134 | described in points 2) and 3) were ready (uploaded in Esri ArcGIS, | 134 | described in points 2) and 3) were ready (uploaded in Esri ArcGIS, | ||
135 | reprojected and their correctness checked), they have been | 135 | reprojected and their correctness checked), they have been | ||
136 | \u2018crossed\u2019 (i.e. clipped) with the IMD HRL as described in | 136 | \u2018crossed\u2019 (i.e. clipped) with the IMD HRL as described in | ||
137 | point 1) and a specific raster for each territorial level has been | 137 | point 1) and a specific raster for each territorial level has been | ||
138 | calculated. The procedure in Esri ArcGIS was the following:\r\n\r\n * | 138 | calculated. The procedure in Esri ArcGIS was the following:\r\n\r\n * | ||
139 | Clipping: Arctoolbox > Data management tools > Raster > Raster | 139 | Clipping: Arctoolbox > Data management tools > Raster > Raster | ||
140 | Processing > Clip. The \u2018input\u2019 file is the HRL IMD raster | 140 | Processing > Clip. The \u2018input\u2019 file is the HRL IMD raster | ||
141 | file as described in point 1) and the \u2018output\u2019 file is each | 141 | file as described in point 1) and the \u2018output\u2019 file is each | ||
142 | of the spatial/territorial files. The option \"Use Input Features for | 142 | of the spatial/territorial files. The option \"Use Input Features for | ||
143 | Clipping Geometry (optional)\u201d was selected for each of the | 143 | Clipping Geometry (optional)\u201d was selected for each of the | ||
144 | clipping. \r\n * Delete and create raster attribute table: Once the | 144 | clipping. \r\n * Delete and create raster attribute table: Once the | ||
145 | clipping has been done, the raster has to be recalculated first | 145 | clipping has been done, the raster has to be recalculated first | ||
146 | through Arctoolbox > Data management tools > Raster > Raster | 146 | through Arctoolbox > Data management tools > Raster > Raster | ||
147 | properties > Delete Raster Attribute Table and then through Arctoolbox | 147 | properties > Delete Raster Attribute Table and then through Arctoolbox | ||
148 | > Data management tools > Raster > Raster properties > Build Raster | 148 | > Data management tools > Raster > Raster properties > Build Raster | ||
149 | Attribute Table; the \"overwrite\" option has been selected. <br /> | 149 | Attribute Table; the \"overwrite\" option has been selected. <br /> | ||
150 | \r\n\r\nOther tools used for the raster files in Esri ArcGIS have been | 150 | \r\n\r\nOther tools used for the raster files in Esri ArcGIS have been | ||
151 | the spatial analyst tools (in particular, Zonal > Zonal Statistics). | 151 | the spatial analyst tools (in particular, Zonal > Zonal Statistics). | ||
152 | As an additional check, the colour scheme of each of the newly created | 152 | As an additional check, the colour scheme of each of the newly created | ||
153 | raster for each of the spatial/territorial attributes as per letters | 153 | raster for each of the spatial/territorial attributes as per letters | ||
154 | a)-h) above has been changed to check the consistency of its overlay | 154 | a)-h) above has been changed to check the consistency of its overlay | ||
155 | with the original HRL IMD file. However, a perfect match between the | 155 | with the original HRL IMD file. However, a perfect match between the | ||
156 | shapefiles as per letters a)-h) and the raster files could not be | 156 | shapefiles as per letters a)-h) and the raster files could not be | ||
157 | achieved since the raster files are composed of 20x20mt cells.<br /> | 157 | achieved since the raster files are composed of 20x20mt cells.<br /> | ||
158 | \r\n\r\nThe newly created attribute tables of each of the raster files | 158 | \r\n\r\nThe newly created attribute tables of each of the raster files | ||
159 | have been exported and saved as .txt files. These .txt files have then | 159 | have been exported and saved as .txt files. These .txt files have then | ||
160 | been copied in the excel corresponding to the final published | 160 | been copied in the excel corresponding to the final published | ||
161 | dataset.\r\n", | 161 | dataset.\r\n", | ||
162 | "num_resources": 4, | 162 | "num_resources": 4, | ||
163 | "num_tags": 6, | 163 | "num_tags": 6, | ||
164 | "organization": { | 164 | "organization": { | ||
165 | "approval_status": "approved", | 165 | "approval_status": "approved", | ||
166 | "created": "2019-01-16T10:05:56.219606", | 166 | "created": "2019-01-16T10:05:56.219606", | ||
167 | "description": "The land-use systems group studies landscape | 167 | "description": "The land-use systems group studies landscape | ||
168 | patterns and processes and their changes over time. We focus on | 168 | patterns and processes and their changes over time. We focus on | ||
169 | cultural landscapes and their multifunctionality while conducting | 169 | cultural landscapes and their multifunctionality while conducting | ||
170 | research in the following topics:\r\n\r\n- Development of models for | 170 | research in the following topics:\r\n\r\n- Development of models for | ||
171 | simulating future landscape dynamics and for estimating the resulting | 171 | simulating future landscape dynamics and for estimating the resulting | ||
172 | landscape services;\r\n- Application and further development of | 172 | landscape services;\r\n- Application and further development of | ||
173 | landscape genetic methods and theories;\r\n- Analysis of historical | 173 | landscape genetic methods and theories;\r\n- Analysis of historical | ||
174 | changes in ecosystems and landscapes (focus on the past 100 to 250 | 174 | changes in ecosystems and landscapes (focus on the past 100 to 250 | ||
175 | years);\r\n- Analysis of ecological implications of landscape and | 175 | years);\r\n- Analysis of ecological implications of landscape and | ||
176 | ecosystem changes in the context of the field of historical | 176 | ecosystem changes in the context of the field of historical | ||
177 | ecology;\r\n- Analysis of actors, driving forces, and land change and | 177 | ecology;\r\n- Analysis of actors, driving forces, and land change and | ||
178 | their interaction to understand the causes of landscape change\r\n- | 178 | their interaction to understand the causes of landscape change\r\n- | ||
179 | Contributing to the further development of landscape planning, based, | 179 | Contributing to the further development of landscape planning, based, | ||
180 | for example, on conflict analysis and the evaluation of planning | 180 | for example, on conflict analysis and the evaluation of planning | ||
181 | instruments. \r\n\r\nThe landscape ecology group combines methods and | 181 | instruments. \r\n\r\nThe landscape ecology group combines methods and | ||
182 | theories from natural sciences and social sciences on spatial scales | 182 | theories from natural sciences and social sciences on spatial scales | ||
183 | from single ecosystems to continents. We are equally committed to | 183 | from single ecosystems to continents. We are equally committed to | ||
184 | theory development and innovative applications.", | 184 | theory development and innovative applications.", | ||
185 | "id": "ecfa6cd4-9e88-4bba-b815-bd177d84ae11", | 185 | "id": "ecfa6cd4-9e88-4bba-b815-bd177d84ae11", | ||
186 | "image_url": "2019-01-16-090556.2007782000px-LogoWSL.svg.png", | 186 | "image_url": "2019-01-16-090556.2007782000px-LogoWSL.svg.png", | ||
187 | "is_organization": true, | 187 | "is_organization": true, | ||
188 | "name": "land-use-systems", | 188 | "name": "land-use-systems", | ||
189 | "state": "active", | 189 | "state": "active", | ||
190 | "title": "Land-use systems", | 190 | "title": "Land-use systems", | ||
191 | "type": "organization" | 191 | "type": "organization" | ||
192 | }, | 192 | }, | ||
193 | "owner_org": "ecfa6cd4-9e88-4bba-b815-bd177d84ae11", | 193 | "owner_org": "ecfa6cd4-9e88-4bba-b815-bd177d84ae11", | ||
194 | "private": false, | 194 | "private": false, | ||
195 | "publication": "{\"publication_year\": \"2021\", \"publisher\": | 195 | "publication": "{\"publication_year\": \"2021\", \"publisher\": | ||
196 | \"EnviDat\"}", | 196 | \"EnviDat\"}", | ||
t | 197 | "publication_state": "approved", | t | 197 | "publication_state": "published", |
198 | "related_datasets": "", | 198 | "related_datasets": "", | ||
199 | "related_publications": "", | 199 | "related_publications": "", | ||
200 | "relationships_as_object": [], | 200 | "relationships_as_object": [], | ||
201 | "relationships_as_subject": [], | 201 | "relationships_as_subject": [], | ||
202 | "resource_type": "dataset", | 202 | "resource_type": "dataset", | ||
203 | "resource_type_general": "dataset", | 203 | "resource_type_general": "dataset", | ||
204 | "resources": [ | 204 | "resources": [ | ||
205 | { | 205 | { | ||
206 | "cache_last_updated": null, | 206 | "cache_last_updated": null, | ||
207 | "cache_url": null, | 207 | "cache_url": null, | ||
208 | "created": "2021-10-14T08:11:40.347236", | 208 | "created": "2021-10-14T08:11:40.347236", | ||
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353 | "subtitle": "", | 353 | "subtitle": "", | ||
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395 | "vocabulary_id": null | 395 | "vocabulary_id": null | ||
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