The impact of heat waves on surface urban heat island and local economy in Cluj-Napoca city, Romania View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-07-12

AUTHORS

Ioana Herbel, Adina-Eliza Croitoru, Adina Viorica Rus, Cristina Florina Roşca, Gabriela Victoria Harpa, Antoniu-Flavius Ciupertea, Ionuţ Rus

ABSTRACT

The association between heat waves and the urban heat island effect can increase the impact on environment and society inducing biophysical hazards. Heat stress and their associated public health problems are among the most frequent. This paper explores the heat waves impact on surface urban heat island and on the local economy loss during three heat periods in Cluj-Napoca city in the summer of 2015. The heat wave events were identified based on daily maximum temperature, and they were divided into three classes considering the intensity threshold: moderate heat waves (daily maximum temperature exceeding the 90th percentile), severe heat waves (daily maximum temperature over the 95th percentile), and extremely severe heat waves (daily maximum temperature exceeding the 98th percentile). The minimum length of an event was of minimum three consecutive days. The surface urban heat island was detected based on land surface temperature derived from Landsat 8 thermal infrared data, while the economic impact was estimated based on data on work force structure and work productivity in Cluj-Napoca derived from the data released by Eurostat, National Bank of Romania, and National Institute of Statistics. The results indicate that the intensity and spatial extension of surface urban heat island could be governed by the magnitude of the heat wave event, but due to the low number of satellite images available, we should consider this information only as preliminary results. Thermal infrared remote sensing has proven to be a very efficient method to study surface urban heat island, due to the fact that the synoptic conditions associated with heat wave events usually favor cloud free image. The resolution of the OLI_TIRS sensor provided good results for a mid-extension city, but the low revisiting time is still a drawback. The potential economic loss was calculated for the working days during heat waves and the estimated loss reached more than 2.5 mil. EUR for each heat wave day at city scale, cumulating more than 38 mil. EUR for the three cases considered. More... »

PAGES

681-695

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00704-017-2196-4

DOI

http://dx.doi.org/10.1007/s00704-017-2196-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1090598684


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/04", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Earth Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0401", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Atmospheric Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Faculty of Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania", 
          "id": "http://www.grid.ac/institutes/grid.7399.4", 
          "name": [
            "Faculty of Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Herbel", 
        "givenName": "Ioana", 
        "id": "sg:person.016275776004.75", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016275776004.75"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Faculty of Geography, Department of Physical and Technical Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania", 
          "id": "http://www.grid.ac/institutes/grid.7399.4", 
          "name": [
            "Faculty of Geography, Department of Physical and Technical Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Croitoru", 
        "givenName": "Adina-Eliza", 
        "id": "sg:person.01045473546.59", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01045473546.59"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Faculty of Economics and Business Administration, Department of Political Economy, Babe\u015f-Bolyai University, 58-60, Teodor Mihali Street, 400591, Cluj-Napoca, Romania", 
          "id": "http://www.grid.ac/institutes/grid.7399.4", 
          "name": [
            "Faculty of Economics and Business Administration, Department of Political Economy, Babe\u015f-Bolyai University, 58-60, Teodor Mihali Street, 400591, Cluj-Napoca, Romania"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rus", 
        "givenName": "Adina Viorica", 
        "id": "sg:person.013724757336.99", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013724757336.99"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Faculty of Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania", 
          "id": "http://www.grid.ac/institutes/grid.7399.4", 
          "name": [
            "Faculty of Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ro\u015fca", 
        "givenName": "Cristina Florina", 
        "id": "sg:person.011271755325.70", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011271755325.70"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Faculty of Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania", 
          "id": "http://www.grid.ac/institutes/grid.7399.4", 
          "name": [
            "Faculty of Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Harpa", 
        "givenName": "Gabriela Victoria", 
        "id": "sg:person.013356207204.96", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013356207204.96"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Faculty of Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania", 
          "id": "http://www.grid.ac/institutes/grid.7399.4", 
          "name": [
            "Faculty of Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ciupertea", 
        "givenName": "Antoniu-Flavius", 
        "id": "sg:person.014606666427.87", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014606666427.87"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Faculty of Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania", 
          "id": "http://www.grid.ac/institutes/grid.7399.4", 
          "name": [
            "Faculty of Geography, Babe\u015f-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rus", 
        "givenName": "Ionu\u0163", 
        "id": "sg:person.011763246204.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011763246204.35"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s00704-014-1250-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047199580", 
          "https://doi.org/10.1007/s00704-014-1250-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00704-008-0019-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017570488", 
          "https://doi.org/10.1007/s00704-008-0019-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00484-009-0256-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011622748", 
          "https://doi.org/10.1007/s00484-009-0256-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00704-008-0088-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000497055", 
          "https://doi.org/10.1007/s00704-008-0088-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11069-009-9406-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033650164", 
          "https://doi.org/10.1007/s11069-009-9406-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nclimate2623", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034647969", 
          "https://doi.org/10.1038/nclimate2623"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-07-12", 
    "datePublishedReg": "2017-07-12", 
    "description": "The association between heat waves and the urban heat island effect can increase the impact on environment and society inducing biophysical hazards. Heat stress and their associated public health problems are among the most frequent. This paper explores the heat waves impact on surface urban heat island and on the local economy loss during three heat periods in Cluj-Napoca city in the summer of 2015. The heat wave events were identified based on daily maximum temperature, and they were divided into three classes considering the intensity threshold: moderate heat waves (daily maximum temperature exceeding the 90th percentile), severe heat waves (daily maximum temperature over the 95th percentile), and extremely severe heat waves (daily maximum temperature exceeding the 98th percentile). The minimum length of an event was of minimum three consecutive days. The surface urban heat island was detected based on land surface temperature derived from Landsat 8 thermal infrared data, while the economic impact was estimated based on data on work force structure and work productivity in Cluj-Napoca derived from the data released by Eurostat, National Bank of Romania, and National Institute of Statistics. The results indicate that the intensity and spatial extension of surface urban heat island could be governed by the magnitude of the heat wave event, but due to the low number of satellite images available, we should consider this information only as preliminary results. Thermal infrared remote sensing has proven to be a very efficient method to study surface urban heat island, due to the fact that the synoptic conditions associated with heat wave events usually favor cloud free image. The resolution of the OLI_TIRS sensor provided good results for a mid-extension city, but the low revisiting time is still a drawback. The potential economic loss was calculated for the working days during heat waves and the estimated loss reached more than 2.5 mil. EUR for each heat wave day at city scale, cumulating more than 38 mil. EUR for the three cases considered.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s00704-017-2196-4", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1086664", 
        "issn": [
          "0177-798X", 
          "1434-4483"
        ], 
        "name": "Theoretical and Applied Climatology", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "3-4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "133"
      }
    ], 
    "keywords": [
      "urban heat island", 
      "Landsat 8 thermal infrared data", 
      "surface urban heat island", 
      "heat island", 
      "thermal infrared data", 
      "wave events", 
      "wave impact", 
      "urban heat island effect", 
      "heat island effect", 
      "Cluj-Napoca city", 
      "land surface temperature", 
      "remote sensing", 
      "heat wave events", 
      "maximum temperature", 
      "satellite images", 
      "surface temperature", 
      "island effect", 
      "cloud-free images", 
      "waves", 
      "severe heat waves", 
      "heat waves", 
      "city scale", 
      "synoptic conditions", 
      "infrared data", 
      "economy loss", 
      "temperature", 
      "free images", 
      "MIL", 
      "moderate heat waves", 
      "efficient method", 
      "sensors", 
      "heat wave days", 
      "heat wave impacts", 
      "daily maximum temperature", 
      "sensing", 
      "spatial extension", 
      "preliminary results", 
      "wave days", 
      "better results", 
      "biophysical hazards", 
      "results", 
      "potential economic losses", 
      "intensity threshold", 
      "drawbacks", 
      "force structure", 
      "islands", 
      "images", 
      "stress", 
      "loss", 
      "structure", 
      "conditions", 
      "resolution", 
      "magnitude", 
      "minimum length", 
      "EUR", 
      "method", 
      "impact", 
      "economic losses", 
      "events", 
      "Cluj-Napoca", 
      "hazards", 
      "heat period", 
      "length", 
      "problem", 
      "environment", 
      "city", 
      "summer", 
      "data", 
      "intensity", 
      "time", 
      "effect", 
      "work force structure", 
      "scale", 
      "Romania", 
      "threshold", 
      "productivity", 
      "extension", 
      "economic impact", 
      "number", 
      "period", 
      "low number", 
      "cases", 
      "information", 
      "local economy", 
      "fact", 
      "Institute", 
      "heat stress", 
      "banks", 
      "National Institute", 
      "class", 
      "statistics", 
      "days", 
      "economy", 
      "consecutive days", 
      "association", 
      "paper", 
      "society", 
      "health problems", 
      "Eurostat", 
      "National Bank", 
      "public health problem"
    ], 
    "name": "The impact of heat waves on surface urban heat island and local economy in Cluj-Napoca city, Romania", 
    "pagination": "681-695", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1090598684"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00704-017-2196-4"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00704-017-2196-4", 
      "https://app.dimensions.ai/details/publication/pub.1090598684"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-12-01T06:36", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221201/entities/gbq_results/article/article_734.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s00704-017-2196-4"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00704-017-2196-4'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00704-017-2196-4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00704-017-2196-4'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00704-017-2196-4'


 

This table displays all metadata directly associated to this object as RDF triples.

228 TRIPLES      21 PREDICATES      131 URIs      117 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00704-017-2196-4 schema:about anzsrc-for:04
2 anzsrc-for:0401
3 schema:author N8c65f68c24df42e68ff7619cc3709385
4 schema:citation sg:pub.10.1007/s00484-009-0256-x
5 sg:pub.10.1007/s00704-008-0019-3
6 sg:pub.10.1007/s00704-008-0088-3
7 sg:pub.10.1007/s00704-014-1250-8
8 sg:pub.10.1007/s11069-009-9406-z
9 sg:pub.10.1038/nclimate2623
10 schema:datePublished 2017-07-12
11 schema:datePublishedReg 2017-07-12
12 schema:description The association between heat waves and the urban heat island effect can increase the impact on environment and society inducing biophysical hazards. Heat stress and their associated public health problems are among the most frequent. This paper explores the heat waves impact on surface urban heat island and on the local economy loss during three heat periods in Cluj-Napoca city in the summer of 2015. The heat wave events were identified based on daily maximum temperature, and they were divided into three classes considering the intensity threshold: moderate heat waves (daily maximum temperature exceeding the 90th percentile), severe heat waves (daily maximum temperature over the 95th percentile), and extremely severe heat waves (daily maximum temperature exceeding the 98th percentile). The minimum length of an event was of minimum three consecutive days. The surface urban heat island was detected based on land surface temperature derived from Landsat 8 thermal infrared data, while the economic impact was estimated based on data on work force structure and work productivity in Cluj-Napoca derived from the data released by Eurostat, National Bank of Romania, and National Institute of Statistics. The results indicate that the intensity and spatial extension of surface urban heat island could be governed by the magnitude of the heat wave event, but due to the low number of satellite images available, we should consider this information only as preliminary results. Thermal infrared remote sensing has proven to be a very efficient method to study surface urban heat island, due to the fact that the synoptic conditions associated with heat wave events usually favor cloud free image. The resolution of the OLI_TIRS sensor provided good results for a mid-extension city, but the low revisiting time is still a drawback. The potential economic loss was calculated for the working days during heat waves and the estimated loss reached more than 2.5 mil. EUR for each heat wave day at city scale, cumulating more than 38 mil. EUR for the three cases considered.
13 schema:genre article
14 schema:isAccessibleForFree false
15 schema:isPartOf N0f9e74fb519f481984bfba59ea43ae33
16 N71a0c16e446f4c05b78c5b2fbd6e3dfa
17 sg:journal.1086664
18 schema:keywords Cluj-Napoca
19 Cluj-Napoca city
20 EUR
21 Eurostat
22 Institute
23 Landsat 8 thermal infrared data
24 MIL
25 National Bank
26 National Institute
27 Romania
28 association
29 banks
30 better results
31 biophysical hazards
32 cases
33 city
34 city scale
35 class
36 cloud-free images
37 conditions
38 consecutive days
39 daily maximum temperature
40 data
41 days
42 drawbacks
43 economic impact
44 economic losses
45 economy
46 economy loss
47 effect
48 efficient method
49 environment
50 events
51 extension
52 fact
53 force structure
54 free images
55 hazards
56 health problems
57 heat island
58 heat island effect
59 heat period
60 heat stress
61 heat wave days
62 heat wave events
63 heat wave impacts
64 heat waves
65 images
66 impact
67 information
68 infrared data
69 intensity
70 intensity threshold
71 island effect
72 islands
73 land surface temperature
74 length
75 local economy
76 loss
77 low number
78 magnitude
79 maximum temperature
80 method
81 minimum length
82 moderate heat waves
83 number
84 paper
85 period
86 potential economic losses
87 preliminary results
88 problem
89 productivity
90 public health problem
91 remote sensing
92 resolution
93 results
94 satellite images
95 scale
96 sensing
97 sensors
98 severe heat waves
99 society
100 spatial extension
101 statistics
102 stress
103 structure
104 summer
105 surface temperature
106 surface urban heat island
107 synoptic conditions
108 temperature
109 thermal infrared data
110 threshold
111 time
112 urban heat island
113 urban heat island effect
114 wave days
115 wave events
116 wave impact
117 waves
118 work force structure
119 schema:name The impact of heat waves on surface urban heat island and local economy in Cluj-Napoca city, Romania
120 schema:pagination 681-695
121 schema:productId Ndaa4656c186e4442ba6c26cff554fbe8
122 Ne1f5822fea9f48169524652b459cef6f
123 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090598684
124 https://doi.org/10.1007/s00704-017-2196-4
125 schema:sdDatePublished 2022-12-01T06:36
126 schema:sdLicense https://scigraph.springernature.com/explorer/license/
127 schema:sdPublisher N42b5d27df7d347c4855cca9a623179fa
128 schema:url https://doi.org/10.1007/s00704-017-2196-4
129 sgo:license sg:explorer/license/
130 sgo:sdDataset articles
131 rdf:type schema:ScholarlyArticle
132 N09b6f553f3804f87b4a0fd719193bb70 rdf:first sg:person.011271755325.70
133 rdf:rest N54216699aef54b21a21432fcb580fb54
134 N0f9e74fb519f481984bfba59ea43ae33 schema:issueNumber 3-4
135 rdf:type schema:PublicationIssue
136 N40e9e32cce8f48e6a1d97adf398d61f3 rdf:first sg:person.013724757336.99
137 rdf:rest N09b6f553f3804f87b4a0fd719193bb70
138 N42b5d27df7d347c4855cca9a623179fa schema:name Springer Nature - SN SciGraph project
139 rdf:type schema:Organization
140 N504c378bea704751ae17b87db5ae0326 rdf:first sg:person.014606666427.87
141 rdf:rest N63b4849c8a60420aac4af2aab347f937
142 N54216699aef54b21a21432fcb580fb54 rdf:first sg:person.013356207204.96
143 rdf:rest N504c378bea704751ae17b87db5ae0326
144 N63b4849c8a60420aac4af2aab347f937 rdf:first sg:person.011763246204.35
145 rdf:rest rdf:nil
146 N71a0c16e446f4c05b78c5b2fbd6e3dfa schema:volumeNumber 133
147 rdf:type schema:PublicationVolume
148 N8c65f68c24df42e68ff7619cc3709385 rdf:first sg:person.016275776004.75
149 rdf:rest Na28f00a12fe84f5a8e5e5891dc7ffbce
150 Na28f00a12fe84f5a8e5e5891dc7ffbce rdf:first sg:person.01045473546.59
151 rdf:rest N40e9e32cce8f48e6a1d97adf398d61f3
152 Ndaa4656c186e4442ba6c26cff554fbe8 schema:name dimensions_id
153 schema:value pub.1090598684
154 rdf:type schema:PropertyValue
155 Ne1f5822fea9f48169524652b459cef6f schema:name doi
156 schema:value 10.1007/s00704-017-2196-4
157 rdf:type schema:PropertyValue
158 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
159 schema:name Earth Sciences
160 rdf:type schema:DefinedTerm
161 anzsrc-for:0401 schema:inDefinedTermSet anzsrc-for:
162 schema:name Atmospheric Sciences
163 rdf:type schema:DefinedTerm
164 sg:journal.1086664 schema:issn 0177-798X
165 1434-4483
166 schema:name Theoretical and Applied Climatology
167 schema:publisher Springer Nature
168 rdf:type schema:Periodical
169 sg:person.01045473546.59 schema:affiliation grid-institutes:grid.7399.4
170 schema:familyName Croitoru
171 schema:givenName Adina-Eliza
172 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01045473546.59
173 rdf:type schema:Person
174 sg:person.011271755325.70 schema:affiliation grid-institutes:grid.7399.4
175 schema:familyName Roşca
176 schema:givenName Cristina Florina
177 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011271755325.70
178 rdf:type schema:Person
179 sg:person.011763246204.35 schema:affiliation grid-institutes:grid.7399.4
180 schema:familyName Rus
181 schema:givenName Ionuţ
182 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011763246204.35
183 rdf:type schema:Person
184 sg:person.013356207204.96 schema:affiliation grid-institutes:grid.7399.4
185 schema:familyName Harpa
186 schema:givenName Gabriela Victoria
187 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013356207204.96
188 rdf:type schema:Person
189 sg:person.013724757336.99 schema:affiliation grid-institutes:grid.7399.4
190 schema:familyName Rus
191 schema:givenName Adina Viorica
192 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013724757336.99
193 rdf:type schema:Person
194 sg:person.014606666427.87 schema:affiliation grid-institutes:grid.7399.4
195 schema:familyName Ciupertea
196 schema:givenName Antoniu-Flavius
197 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014606666427.87
198 rdf:type schema:Person
199 sg:person.016275776004.75 schema:affiliation grid-institutes:grid.7399.4
200 schema:familyName Herbel
201 schema:givenName Ioana
202 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016275776004.75
203 rdf:type schema:Person
204 sg:pub.10.1007/s00484-009-0256-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1011622748
205 https://doi.org/10.1007/s00484-009-0256-x
206 rdf:type schema:CreativeWork
207 sg:pub.10.1007/s00704-008-0019-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017570488
208 https://doi.org/10.1007/s00704-008-0019-3
209 rdf:type schema:CreativeWork
210 sg:pub.10.1007/s00704-008-0088-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000497055
211 https://doi.org/10.1007/s00704-008-0088-3
212 rdf:type schema:CreativeWork
213 sg:pub.10.1007/s00704-014-1250-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047199580
214 https://doi.org/10.1007/s00704-014-1250-8
215 rdf:type schema:CreativeWork
216 sg:pub.10.1007/s11069-009-9406-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1033650164
217 https://doi.org/10.1007/s11069-009-9406-z
218 rdf:type schema:CreativeWork
219 sg:pub.10.1038/nclimate2623 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034647969
220 https://doi.org/10.1038/nclimate2623
221 rdf:type schema:CreativeWork
222 grid-institutes:grid.7399.4 schema:alternateName Faculty of Economics and Business Administration, Department of Political Economy, Babeş-Bolyai University, 58-60, Teodor Mihali Street, 400591, Cluj-Napoca, Romania
223 Faculty of Geography, Babeş-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania
224 Faculty of Geography, Department of Physical and Technical Geography, Babeş-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania
225 schema:name Faculty of Economics and Business Administration, Department of Political Economy, Babeş-Bolyai University, 58-60, Teodor Mihali Street, 400591, Cluj-Napoca, Romania
226 Faculty of Geography, Babeş-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania
227 Faculty of Geography, Department of Physical and Technical Geography, Babeş-Bolyai University, 5-7, Clinicilor Street, 400006, Cluj-Napoca, Romania
228 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...