{"title":"量化区域多重因素对净初级植被生产力和净生态系统生产力时空变化机制的影响:以中国江淮流域为例","authors":"Huimin Chen, Benlin Wang, Liangfeng Zheng, ZhengAmirReza Shahtahmassebi","doi":"10.14358/pers.23-00017r2","DOIUrl":null,"url":null,"abstract":"Despite much valuable research on the mechanisms for spatio-temporal changesof net primary vegetation productivity (NPP) and net ecosystem productivity (NEP), there is a paucity of information on assessing impacts of regional multiple factors on spatiotemporal researchs of NPP and NEP\n in the complex environment. This study attempts to bridge this information gap using the Jianghuai Basin in China as a case study. Using a field campaign, remotely sensed imagery, socioeconomic data, and meteorological parameters, we developed a framework based on the Carnegie‐Ames‐Stanford\n Approach (CASA) model, correlation technique, trend analysis, and landscape metrics to measure spatiotemporal changes in NPP and NEP from 2001 to 2018. The derived changes were then linked to regional multiple factors including climate, landscape factors, human activity, and land use change.\n The results of the research can provide a scientific basis for vegetation evaluation, ecosystem assessment, and other aspects of the region.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":" 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantifying Impacts of Regional Multiple Factors on Spatiotemporal the Mechanisms for Spatio-temporal changes of Net Primary Vegetation Productivity and Net Ecosystem Productivity: An Example in the Jianghuai River Basin, China\",\"authors\":\"Huimin Chen, Benlin Wang, Liangfeng Zheng, ZhengAmirReza Shahtahmassebi\",\"doi\":\"10.14358/pers.23-00017r2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite much valuable research on the mechanisms for spatio-temporal changesof net primary vegetation productivity (NPP) and net ecosystem productivity (NEP), there is a paucity of information on assessing impacts of regional multiple factors on spatiotemporal researchs of NPP and NEP\\n in the complex environment. This study attempts to bridge this information gap using the Jianghuai Basin in China as a case study. Using a field campaign, remotely sensed imagery, socioeconomic data, and meteorological parameters, we developed a framework based on the Carnegie‐Ames‐Stanford\\n Approach (CASA) model, correlation technique, trend analysis, and landscape metrics to measure spatiotemporal changes in NPP and NEP from 2001 to 2018. The derived changes were then linked to regional multiple factors including climate, landscape factors, human activity, and land use change.\\n The results of the research can provide a scientific basis for vegetation evaluation, ecosystem assessment, and other aspects of the region.\",\"PeriodicalId\":211256,\"journal\":{\"name\":\"Photogrammetric Engineering & Remote Sensing\",\"volume\":\" 4\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Photogrammetric Engineering & Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14358/pers.23-00017r2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Photogrammetric Engineering & Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14358/pers.23-00017r2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantifying Impacts of Regional Multiple Factors on Spatiotemporal the Mechanisms for Spatio-temporal changes of Net Primary Vegetation Productivity and Net Ecosystem Productivity: An Example in the Jianghuai River Basin, China
Despite much valuable research on the mechanisms for spatio-temporal changesof net primary vegetation productivity (NPP) and net ecosystem productivity (NEP), there is a paucity of information on assessing impacts of regional multiple factors on spatiotemporal researchs of NPP and NEP
in the complex environment. This study attempts to bridge this information gap using the Jianghuai Basin in China as a case study. Using a field campaign, remotely sensed imagery, socioeconomic data, and meteorological parameters, we developed a framework based on the Carnegie‐Ames‐Stanford
Approach (CASA) model, correlation technique, trend analysis, and landscape metrics to measure spatiotemporal changes in NPP and NEP from 2001 to 2018. The derived changes were then linked to regional multiple factors including climate, landscape factors, human activity, and land use change.
The results of the research can provide a scientific basis for vegetation evaluation, ecosystem assessment, and other aspects of the region.