---
OA_type: closed access
_id: '22534'
abstract:
- lang: eng
  text: Tree planting is a prevalent strategy to mitigate urban heat. Tree cooling
    efficiency(TCE), defined as the temperature reduction for a 1% tree cover increase,
    plays animportant role in urban climate as it regulates the capacity of trees
    to alter the sur-face energy and water budget. However, the spatial variation
    and more importantly,temporal heterogeneity of TCE in global cities are not fully
    explored. Here, we usedLandsat-based tree cover and land surface temperature (LST)
    to compare TCEs at areference air temperature and tree cover level across 806
    global cities and to exploretheir potential drivers with a boosted regression
    tree (BRT) machine learning model.From the results, we found that TCE is spatially
    regulated by not only leaf area index(LAI) but climate variables and anthropogenic
    factors especially city albedo, withouta specific variable dominating the others.
    However, such spatial difference is attenu-ated by the decrease of TCE with tree
    cover, most pronounced in midlatitude cities.During the period 2000–2015, more
    than 90% of analyzed cities showed an increas-ing trend in TCE, which is likely
    explained by a combined result of the increase in LAI,intensified solar radiation
    due to decreased aerosol content, increase in urban vaporpressure deficit (VPD)
    and decrease of city albedo. Concurrently, significant urbanafforestation occurred
    across many cities showing a global city-scale mean tree coverincrease of 5.3
    ± 3.8% from 2000 to 2015. Over the growing season, such increasescombined with
    an increasing TCE were estimated to on average yield a midday sur-face cooling
    of 1.5 ± 1.3°C in tree-covered urban areas. These results are offeringnew insights
    into the use of urban afforestation as an adaptation to global warmingand urban
    planners may leverage them to provide more cooling benefits if trees areprimarily
    planted for this purpose.
article_processing_charge: No
article_type: original
author:
- first_name: Jiacheng
  full_name: Zhao, Jiacheng
  last_name: Zhao
- first_name: Xiang
  full_name: Zhao, Xiang
  last_name: Zhao
- first_name: Donghai
  full_name: Wu, Donghai
  last_name: Wu
- first_name: Naika
  full_name: Meili, Naika
  last_name: Meili
- first_name: Simone
  full_name: Fatichi, Simone
  id: cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6
  last_name: Fatichi
citation:
  ama: Zhao J, Zhao X, Wu D, Meili N, Fatichi S. Satellite‐based evidence highlights
    a considerable increase of urban tree cooling benefits from 2000 to 2015. <i>Global
    Change Biology</i>. 2023;29(11):3085-3097. doi:<a href="https://doi.org/10.1111/gcb.16667">10.1111/gcb.16667</a>
  apa: Zhao, J., Zhao, X., Wu, D., Meili, N., &#38; Fatichi, S. (2023). Satellite‐based
    evidence highlights a considerable increase of urban tree cooling benefits from
    2000 to 2015. <i>Global Change Biology</i>. Wiley. <a href="https://doi.org/10.1111/gcb.16667">https://doi.org/10.1111/gcb.16667</a>
  chicago: Zhao, Jiacheng, Xiang Zhao, Donghai Wu, Naika Meili, and Simone Fatichi.
    “Satellite‐based Evidence Highlights a Considerable Increase of Urban Tree Cooling
    Benefits from 2000 to 2015.” <i>Global Change Biology</i>. Wiley, 2023. <a href="https://doi.org/10.1111/gcb.16667">https://doi.org/10.1111/gcb.16667</a>.
  ieee: J. Zhao, X. Zhao, D. Wu, N. Meili, and S. Fatichi, “Satellite‐based evidence
    highlights a considerable increase of urban tree cooling benefits from 2000 to
    2015,” <i>Global Change Biology</i>, vol. 29, no. 11. Wiley, pp. 3085–3097, 2023.
  ista: Zhao J, Zhao X, Wu D, Meili N, Fatichi S. 2023. Satellite‐based evidence highlights
    a considerable increase of urban tree cooling benefits from 2000 to 2015. Global
    Change Biology. 29(11), 3085–3097.
  mla: Zhao, Jiacheng, et al. “Satellite‐based Evidence Highlights a Considerable
    Increase of Urban Tree Cooling Benefits from 2000 to 2015.” <i>Global Change Biology</i>,
    vol. 29, no. 11, Wiley, 2023, pp. 3085–97, doi:<a href="https://doi.org/10.1111/gcb.16667">10.1111/gcb.16667</a>.
  short: J. Zhao, X. Zhao, D. Wu, N. Meili, S. Fatichi, Global Change Biology 29 (2023)
    3085–3097.
das_tickbox: '1'
date_created: 2026-07-27T12:30:24Z
date_published: 2023-06-01T00:00:00Z
date_updated: 2026-08-12T08:28:41Z
day: '01'
doi: 10.1111/gcb.16667
extern: '1'
external_id:
  pmid:
  - '36876991 '
intvolume: '        29'
issue: '11'
keyword:
- Climate change
- Remote sensing
- Tree cooling efficiency
- Tree cover
- Urban afforestation
language:
- iso: eng
month: '06'
oa_version: None
page: 3085-3097
pmid: 1
publication: Global Change Biology
publication_identifier:
  eissn:
  - 1365-2486
  issn:
  - 1354-1013
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Satellite‐based evidence highlights a considerable increase of urban tree cooling
  benefits from 2000 to 2015
type: journal_article
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 29
year: '2023'
...
---
_id: '9827'
abstract:
- lang: eng
  text: 'The Nearest neighbour search (NNS) is a fundamental problem in many application
    domains dealing with multidimensional data. In a concurrent setting, where dynamic
    modifications are allowed, a linearizable implementation of the NNS is highly
    desirable.This paper introduces the LockFree-kD-tree (LFkD-tree ): a lock-free
    concurrent kD-tree, which implements an abstract data type (ADT) that provides
    the operations Add, Remove, Contains, and NNS. Our implementation is linearizable.
    The operations in the LFkD-tree use single-word read and compare-and-swap (Image
    1 ) atomic primitives, which are readily supported on available multi-core processors.
    We experimentally evaluate the LFkD-tree using several benchmarks comprising real-world
    and synthetic datasets. The experiments show that the presented design is scalable
    and achieves significant speed-up compared to the implementations of an existing
    sequential kD-tree and a recently proposed multidimensional indexing structure,
    PH-tree.'
article_processing_charge: No
article_type: original
author:
- first_name: Bapi
  full_name: Chatterjee, Bapi
  id: 3C41A08A-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-2742-4028
- first_name: Ivan
  full_name: Walulya, Ivan
  last_name: Walulya
- first_name: Philippas
  full_name: Tsigas, Philippas
  last_name: Tsigas
citation:
  ama: Chatterjee B, Walulya I, Tsigas P. Concurrent linearizable nearest neighbour
    search in LockFree-kD-tree. <i>Theoretical Computer Science</i>. 2021;886:27-48.
    doi:<a href="https://doi.org/10.1016/j.tcs.2021.06.041">10.1016/j.tcs.2021.06.041</a>
  apa: Chatterjee, B., Walulya, I., &#38; Tsigas, P. (2021). Concurrent linearizable
    nearest neighbour search in LockFree-kD-tree. <i>Theoretical Computer Science</i>.
    Elsevier. <a href="https://doi.org/10.1016/j.tcs.2021.06.041">https://doi.org/10.1016/j.tcs.2021.06.041</a>
  chicago: Chatterjee, Bapi, Ivan Walulya, and Philippas Tsigas. “Concurrent Linearizable
    Nearest Neighbour Search in LockFree-KD-Tree.” <i>Theoretical Computer Science</i>.
    Elsevier, 2021. <a href="https://doi.org/10.1016/j.tcs.2021.06.041">https://doi.org/10.1016/j.tcs.2021.06.041</a>.
  ieee: B. Chatterjee, I. Walulya, and P. Tsigas, “Concurrent linearizable nearest
    neighbour search in LockFree-kD-tree,” <i>Theoretical Computer Science</i>, vol.
    886. Elsevier, pp. 27–48, 2021.
  ista: Chatterjee B, Walulya I, Tsigas P. 2021. Concurrent linearizable nearest neighbour
    search in LockFree-kD-tree. Theoretical Computer Science. 886, 27–48.
  mla: Chatterjee, Bapi, et al. “Concurrent Linearizable Nearest Neighbour Search
    in LockFree-KD-Tree.” <i>Theoretical Computer Science</i>, vol. 886, Elsevier,
    2021, pp. 27–48, doi:<a href="https://doi.org/10.1016/j.tcs.2021.06.041">10.1016/j.tcs.2021.06.041</a>.
  short: B. Chatterjee, I. Walulya, P. Tsigas, Theoretical Computer Science 886 (2021)
    27–48.
corr_author: '1'
date_created: 2021-08-08T22:01:31Z
date_published: 2021-09-13T00:00:00Z
date_updated: 2024-10-09T21:00:45Z
day: '13'
department:
- _id: DaAl
doi: 10.1016/j.tcs.2021.06.041
external_id:
  isi:
  - '000694718900004'
intvolume: '       886'
isi: 1
keyword:
- Concurrent data structure
- kD-tree
- Nearest neighbor search
- Similarity search
- Lock-free
- Linearizability
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://publications.lib.chalmers.se/records/fulltext/232185/232185.pdf
month: '09'
oa: 1
oa_version: Submitted Version
page: 27-48
publication: Theoretical Computer Science
publication_identifier:
  issn:
  - 0304-3975
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Concurrent linearizable nearest neighbour search in LockFree-kD-tree
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 886
year: '2021'
...
---
_id: '5549'
abstract:
- lang: eng
  text: "This repository contains the experimental part of the CAV 2015 publication
    Counterexample Explanation by Learning Small Strategies in Markov Decision Processes.\r\nWe
    extended the probabilistic model checker PRISM to represent strategies of Markov
    Decision Processes as Decision Trees.\r\nThe archive contains a java executable
    version of the extended tool (prism_dectree.jar) together with a few examples
    of the PRISM benchmark library.\r\nTo execute the program, please have a look
    at the README.txt, which provides instructions and further information on the
    archive.\r\nThe archive contains scripts that (if run often enough) reproduces
    the data presented in the publication."
article_processing_charge: No
author:
- first_name: Andreas
  full_name: Fellner, Andreas
  id: 42BABFB4-F248-11E8-B48F-1D18A9856A87
  last_name: Fellner
citation:
  ama: 'Fellner A. Experimental part of CAV 2015 publication: Counterexample Explanation
    by Learning Small Strategies in Markov Decision Processes. 2015. doi:<a href="https://doi.org/10.15479/AT:ISTA:28">10.15479/AT:ISTA:28</a>'
  apa: 'Fellner, A. (2015). Experimental part of CAV 2015 publication: Counterexample
    Explanation by Learning Small Strategies in Markov Decision Processes. Institute
    of Science and Technology Austria. <a href="https://doi.org/10.15479/AT:ISTA:28">https://doi.org/10.15479/AT:ISTA:28</a>'
  chicago: 'Fellner, Andreas. “Experimental Part of CAV 2015 Publication: Counterexample
    Explanation by Learning Small Strategies in Markov Decision Processes.” Institute
    of Science and Technology Austria, 2015. <a href="https://doi.org/10.15479/AT:ISTA:28">https://doi.org/10.15479/AT:ISTA:28</a>.'
  ieee: 'A. Fellner, “Experimental part of CAV 2015 publication: Counterexample Explanation
    by Learning Small Strategies in Markov Decision Processes.” Institute of Science
    and Technology Austria, 2015.'
  ista: 'Fellner A. 2015. Experimental part of CAV 2015 publication: Counterexample
    Explanation by Learning Small Strategies in Markov Decision Processes, Institute
    of Science and Technology Austria, <a href="https://doi.org/10.15479/AT:ISTA:28">10.15479/AT:ISTA:28</a>.'
  mla: 'Fellner, Andreas. <i>Experimental Part of CAV 2015 Publication: Counterexample
    Explanation by Learning Small Strategies in Markov Decision Processes</i>. Institute
    of Science and Technology Austria, 2015, doi:<a href="https://doi.org/10.15479/AT:ISTA:28">10.15479/AT:ISTA:28</a>.'
  short: A. Fellner, (2015).
contributor:
- first_name: Jan
  id: 44CEF464-F248-11E8-B48F-1D18A9856A87
  last_name: Kretinsky
datarep_id: '28'
date_created: 2018-12-12T12:31:29Z
date_published: 2015-08-13T00:00:00Z
date_updated: 2025-09-23T08:23:15Z
day: '13'
ddc:
- '004'
department:
- _id: KrCh
- _id: ToHe
doi: 10.15479/AT:ISTA:28
ec_funded: 1
file:
- access_level: open_access
  checksum: b8bcb43c0893023cda66c1b69c16ac62
  content_type: application/zip
  creator: system
  date_created: 2018-12-12T13:02:31Z
  date_updated: 2020-07-14T12:47:00Z
  file_id: '5597'
  file_name: IST-2015-28-v1+2_Fellner_DataRep.zip
  file_size: 49557109
  relation: main_file
file_date_updated: 2020-07-14T12:47:00Z
has_accepted_license: '1'
keyword:
- Markov Decision Process
- Decision Tree
- Probabilistic Verification
- Counterexample Explanation
license: https://creativecommons.org/publicdomain/zero/1.0/
month: '08'
oa: 1
oa_version: Published Version
project:
- _id: 2581B60A-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '279307'
  name: 'Quantitative Graph Games: Theory and Applications'
- _id: 25832EC2-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: S 11407_N23
  name: Rigorous Systems Engineering
publisher: Institute of Science and Technology Austria
publist_id: '5564'
related_material:
  record:
  - id: '1603'
    relation: popular_science
    status: public
status: public
title: 'Experimental part of CAV 2015 publication: Counterexample Explanation by Learning
  Small Strategies in Markov Decision Processes'
tmp:
  image: /images/cc_0.png
  legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
  name: Creative Commons Public Domain Dedication (CC0 1.0)
  short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2015'
...