{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T16:41:27Z","timestamp":1784652087689,"version":"3.55.0"},"reference-count":77,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T00:00:00Z","timestamp":1606694400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Gridded CO2 emission maps at the urban scale can aid the design of low-carbon development strategies. However, the large uncertainties associated with such maps increase policy-related risks. Therefore, an investigation of the uncertainties in gridded maps at the urban scale is essential. This study proposed an analytic workflow to assess uncertainty propagation during the gridding process. Gridded CO2 emission maps were produced using two resolutions of geospatial datasets (e.g., remote sensing satellite-derived products) for Jinjiang City, China, and a workflow was applied to analyze uncertainties. The workflow involved four submodules that can be used to evaluate the uncertainties of CO2 emissions in gridded maps, caused by the gridded model and input. Fine-resolution (30 m) maps have a larger spatial variation in CO2 emissions, which gives the fine-resolution maps a higher degree of uncertainty propagation. Furthermore, the uncertainties of gridded CO2 emission maps, caused by inserting a random error into spatial proxies, were found to decrease after the gridding process. This can be explained by the \u201ccompensation of error\u201d phenomenon, which may be attributed to the cancellation of the overestimated and underestimated values among the different sectors at the same grid. This indicates a nonlinear change between the sum of the uncertainties for different sectors and the actual uncertainties in the gridded maps. In conclusion, the present workflow determined uncertainties were caused by the gridded model and input. These results may aid decision-makers in establishing emission reduction targets, and in developing both low-carbon cities and community policies.<\/jats:p>","DOI":"10.3390\/rs12233932","type":"journal-article","created":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T20:10:22Z","timestamp":1606767022000},"page":"3932","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Investigating the Uncertainties Propagation Analysis of CO2 Emissions Gridded Maps at the Urban Scale: A Case Study of Jinjiang City, China"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0858-4728","authenticated-orcid":false,"given":"Shaoqing","family":"Dai","sequence":"first","affiliation":[{"name":"Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500AE Enschede, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yin","family":"Ren","sequence":"additional","affiliation":[{"name":"Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China"},{"name":"Ningbo Urban Environment Observation and Research Station-NUEORS, Chinese Academy of Sciences, Ningbo 315800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shudi","family":"Zuo","sequence":"additional","affiliation":[{"name":"Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Ningbo Urban Environment Observation and Research Station-NUEORS, Chinese Academy of Sciences, Ningbo 315800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengyi","family":"Lai","sequence":"additional","affiliation":[{"name":"Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiajia","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengyu","family":"Xie","sequence":"additional","affiliation":[{"name":"Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bingchu","family":"Chen","sequence":"additional","affiliation":[{"name":"Stuart Weitzman School of Design, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1016\/j.jclepro.2018.10.034","article-title":"Cities: The core of climate change mitigation","volume":"207","author":"Mi","year":"2019","journal-title":"J. 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