[{"year":"2023","publication_status":"published","volume":29,"issue":"11","month":"06","author":[{"first_name":"Jiacheng","last_name":"Zhao","full_name":"Zhao, Jiacheng"},{"first_name":"Xiang","last_name":"Zhao","full_name":"Zhao, Xiang"},{"full_name":"Wu, Donghai","first_name":"Donghai","last_name":"Wu"},{"full_name":"Meili, Naika","first_name":"Naika","last_name":"Meili"},{"full_name":"Fatichi, Simone","id":"cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6","last_name":"Fatichi","first_name":"Simone"}],"pmid":1,"page":"3085-3097","intvolume":"        29","date_updated":"2026-08-12T08:28:41Z","OA_type":"closed access","type":"journal_article","oa_version":"None","scopus_import":"1","date_created":"2026-07-27T12:30:24Z","publication":"Global Change Biology","external_id":{"pmid":["36876991 "]},"status":"public","abstract":[{"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.","lang":"eng"}],"language":[{"iso":"eng"}],"article_type":"original","citation":{"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>","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.","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>","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.","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>."},"user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","title":"Satellite‐based evidence highlights a considerable increase of urban tree cooling benefits from 2000 to 2015","day":"01","keyword":["Climate change","Remote sensing","Tree cooling efficiency","Tree cover","Urban afforestation"],"article_processing_charge":"No","publication_identifier":{"eissn":["1365-2486"],"issn":["1354-1013"]},"extern":"1","doi":"10.1111/gcb.16667","publisher":"Wiley","das_tickbox":"1","date_published":"2023-06-01T00:00:00Z","_id":"22534","quality_controlled":"1"},{"article_processing_charge":"No","publication_identifier":{"issn":["0304-3975"]},"day":"13","keyword":["Concurrent data structure","kD-tree","Nearest neighbor search","Similarity search","Lock-free","Linearizability"],"department":[{"_id":"DaAl"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","title":"Concurrent linearizable nearest neighbour search in LockFree-kD-tree","oa":1,"_id":"9827","quality_controlled":"1","date_published":"2021-09-13T00:00:00Z","isi":1,"doi":"10.1016/j.tcs.2021.06.041","publisher":"Elsevier","page":"27-48","author":[{"last_name":"Chatterjee","orcid":"0000-0002-2742-4028","first_name":"Bapi","full_name":"Chatterjee, Bapi","id":"3C41A08A-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Ivan","last_name":"Walulya","full_name":"Walulya, Ivan"},{"full_name":"Tsigas, Philippas","last_name":"Tsigas","first_name":"Philippas"}],"volume":886,"month":"09","year":"2021","publication_status":"published","language":[{"iso":"eng"}],"citation":{"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.","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>","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>","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.","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>."},"article_type":"original","corr_author":"1","main_file_link":[{"url":"https://publications.lib.chalmers.se/records/fulltext/232185/232185.pdf","open_access":"1"}],"type":"journal_article","date_created":"2021-08-08T22:01:31Z","oa_version":"Submitted Version","publication":"Theoretical Computer Science","scopus_import":"1","status":"public","external_id":{"isi":["000694718900004"]},"abstract":[{"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.","lang":"eng"}],"intvolume":"       886","date_updated":"2024-10-09T21:00:45Z"},{"article_processing_charge":"No","tmp":{"short":"CC0 (1.0)","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","image":"/images/cc_0.png","name":"Creative Commons Public Domain Dedication (CC0 1.0)"},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","license":"https://creativecommons.org/publicdomain/zero/1.0/","title":"Experimental part of CAV 2015 publication: Counterexample Explanation by Learning Small Strategies in Markov Decision Processes","oa":1,"keyword":["Markov Decision Process","Decision Tree","Probabilistic Verification","Counterexample Explanation"],"day":"13","department":[{"_id":"KrCh"},{"_id":"ToHe"}],"date_published":"2015-08-13T00:00:00Z","_id":"5549","doi":"10.15479/AT:ISTA:28","file":[{"date_updated":"2020-07-14T12:47:00Z","file_name":"IST-2015-28-v1+2_Fellner_DataRep.zip","file_id":"5597","checksum":"b8bcb43c0893023cda66c1b69c16ac62","file_size":49557109,"content_type":"application/zip","date_created":"2018-12-12T13:02:31Z","access_level":"open_access","relation":"main_file","creator":"system"}],"publisher":"Institute of Science and Technology Austria","author":[{"last_name":"Fellner","first_name":"Andreas","id":"42BABFB4-F248-11E8-B48F-1D18A9856A87","full_name":"Fellner, Andreas"}],"year":"2015","contributor":[{"id":"44CEF464-F248-11E8-B48F-1D18A9856A87","first_name":"Jan","last_name":"Kretinsky"}],"file_date_updated":"2020-07-14T12:47:00Z","related_material":{"record":[{"relation":"popular_science","id":"1603","status":"public"}]},"month":"08","type":"research_data","publist_id":"5564","date_created":"2018-12-12T12:31:29Z","oa_version":"Published Version","status":"public","has_accepted_license":"1","abstract":[{"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.","lang":"eng"}],"ec_funded":1,"citation":{"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>.","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>","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>.","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>","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)."},"datarep_id":"28","ddc":["004"],"date_updated":"2025-09-23T08:23:15Z","project":[{"grant_number":"279307","_id":"2581B60A-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Quantitative Graph Games: Theory and Applications"},{"grant_number":"S 11407_N23","_id":"25832EC2-B435-11E9-9278-68D0E5697425","name":"Rigorous Systems Engineering","call_identifier":"FWF"}]}]