date: 2024-08-25T09:52:02Z
pdf:PDFVersion: 1.7
pdf:docinfo:title: A systematic review of spatial disaggregation methods for climate action planning
xmp:CreatorTool: Elsevier
access_permission:can_print_degraded: true
subject: Energy and AI, 17 (2024) 100386. doi:10.1016/j.egyai.2024.100386
dc:format: application/pdf; version=1.7
pdf:docinfo:custom:robots: noindex
pdf:docinfo:creator_tool: Elsevier
access_permission:fill_in_form: true
pdf:docinfo:custom:CreationDate--Text: 25th August 2024
pdf:encrypted: false
dc:title: A systematic review of spatial disaggregation methods for climate action planning
modified: 2024-08-25T09:52:02Z
cp:subject: Energy and AI, 17 (2024) 100386. doi:10.1016/j.egyai.2024.100386
pdf:docinfo:custom:CrossMarkDomains[1]: elsevier.com
robots: noindex
pdf:docinfo:subject: Energy and AI, 17 (2024) 100386. doi:10.1016/j.egyai.2024.100386
pdf:docinfo:creator: Shruthi Patil
meta:author: Noah Pflugradt
meta:creation-date: 2024-08-25T08:44:35Z
pdf:docinfo:custom:CrossmarkMajorVersionDate: 2010-04-23
created: Sun Aug 25 10:44:35 CEST 2024
access_permission:extract_for_accessibility: true
Creation-Date: 2024-08-25T08:44:35Z
pdf:docinfo:custom:CrossMarkDomains[2]: sciencedirect.com
ElsevierWebPDFSpecifications: 7.0
pdf:docinfo:custom:doi: 10.1016/j.egyai.2024.100386
pdf:docinfo:custom:CrossmarkDomainExclusive: true
Author: Noah Pflugradt
producer: Acrobat Distiller 8.1.0 (Windows)
CrossmarkDomainExclusive: true
pdf:docinfo:producer: Acrobat Distiller 8.1.0 (Windows)
CreationDate--Text: 25th August 2024
doi: 10.1016/j.egyai.2024.100386
dc:description: Energy and AI, 17 (2024) 100386. doi:10.1016/j.egyai.2024.100386
Keywords: Spatial downscaling,Proxy data,Mass-preserving,Climate action plans,Spatial autocorrelation,Machine learning,Geostatistical models
access_permission:modify_annotations: true
dc:creator: Noah Pflugradt
description: Energy and AI, 17 (2024) 100386. doi:10.1016/j.egyai.2024.100386
dcterms:created: 2024-08-25T08:44:35Z
Last-Modified: 2024-08-25T09:52:02Z
dcterms:modified: 2024-08-25T09:52:02Z
title: A systematic review of spatial disaggregation methods for climate action planning
xmpMM:DocumentID: uuid:1b499bed-4ce8-4c0c-b682-0d58baae1cbe
Last-Save-Date: 2024-08-25T09:52:02Z
CrossMarkDomains[1]: elsevier.com
pdf:docinfo:keywords: Spatial downscaling,Proxy data,Mass-preserving,Climate action plans,Spatial autocorrelation,Machine learning,Geostatistical models
pdf:docinfo:modified: 2024-08-25T09:52:02Z
meta:save-date: 2024-08-25T09:52:02Z
Content-Type: application/pdf
X-Parsed-By: org.apache.tika.parser.DefaultParser
creator: Noah Pflugradt
dc:subject: Spatial downscaling,Proxy data,Mass-preserving,Climate action plans,Spatial autocorrelation,Machine learning,Geostatistical models
pdf:docinfo:custom:ElsevierWebPDFSpecifications: 7.0
access_permission:assemble_document: true
xmpTPg:NPages: 12
access_permission:extract_content: true
access_permission:can_print: true
CrossMarkDomains[2]: sciencedirect.com
meta:keyword: Spatial downscaling,Proxy data,Mass-preserving,Climate action plans,Spatial autocorrelation,Machine learning,Geostatistical models
access_permission:can_modify: true
pdf:docinfo:created: 2024-08-25T08:44:35Z
CrossmarkMajorVersionDate: 2010-04-23