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Spatial Patterns and Driving Forces of Greenhouse Land Change in Shouguang City, China
Yu, Bohua1; Song, Wei1; Lang, Yanqing1,2
2017-03-01
Source PublicationSUSTAINABILITY
ISSN2071-1050
Volume9Issue:3Pages:15
Corresponding AuthorSong, Wei(songw@igsnrr.ac.cn)
AbstractAs an important facet of modern agricultural development, greenhouses satisfy ever-increasing demands for agricultural production and, therefore, constitute a growing proportion of global agriculture. However, just a handful of countries regularly collect statistics on the land cover of greenhouse infrastructure. Even when collected, these data cannot provide the detailed spatial information required for environmental risk assessment. It is, therefore, important to map spatial changes in greenhouse land cover using remote sensing (RS) approaches to determine the underlying factors driving these changes. In this paper, we apply a support vector machine (SVM) algorithm to identify greenhouse land cover in Shouguang City, China. Enhanced thematic mapper (ETM) images were selected as the data source for land use classification in this study as they can be freely acquired and offer the necessary spatial resolution. We then used a binary logistic regression model to quantitatively discern the mechanisms underlying changes in greenhouse land cover. The results of this study show that greenhouse land cover in Shouguang increased by 50.51% between 2000 and 2015, and that 90.39% of this expansion took place between 2010 and 2015. Elevation, slope, precipitation, and the distance to the nearest rural settlements and coastline are all significant factors driving expansion in greenhouse land cover, while distance to the nearest urban areas, rivers, roads, railways, and coastline have contributed to contractions in this land use type. Our research provided a practical approach to allow the detection of changes in greenhouse land cover in the countries with using free or low-cost satellite images.
Keywordland use change greenhouse land driving forces logistic regression Shouguang city China
DOI10.3390/su9030359
WOS KeywordGENERALIZED LINEAR-MODELS ; CLUE-S MODEL ; CLASSIFICATION APPROACH ; LOGISTIC-REGRESSION ; PLASTIC GREENHOUSE ; URBAN EXPANSION ; COVER CHANGE ; IMAGERY ; GROWTH ; AREAS
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41171079] ; National Natural Science Foundation of China[41501192] ; National Natural Science Foundation of China[41671177] ; National Key Basic Research Program of China[2015CB452702] ; National Key Research and Development Program[2016YFA0602402]
Funding OrganizationNational Natural Science Foundation of China ; National Key Basic Research Program of China ; National Key Research and Development Program
WOS Research AreaEnvironmental Sciences & Ecology
WOS SubjectEnvironmental Sciences ; Environmental Studies
WOS IDWOS:000398714100036
PublisherMDPI AG
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/64638
Collection中国科学院地理科学与资源研究所
Corresponding AuthorSong, Wei
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
2.Chongqing Jiaotong Univ, Coll Architecture & Urban Planning, Chongqing 400074, Peoples R China
Recommended Citation
GB/T 7714
Yu, Bohua,Song, Wei,Lang, Yanqing. Spatial Patterns and Driving Forces of Greenhouse Land Change in Shouguang City, China[J]. SUSTAINABILITY,2017,9(3):15.
APA Yu, Bohua,Song, Wei,&Lang, Yanqing.(2017).Spatial Patterns and Driving Forces of Greenhouse Land Change in Shouguang City, China.SUSTAINABILITY,9(3),15.
MLA Yu, Bohua,et al."Spatial Patterns and Driving Forces of Greenhouse Land Change in Shouguang City, China".SUSTAINABILITY 9.3(2017):15.
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