[Spatiotemporal Distribution of Aerosol Optical Depth Based on Landsat Data in the Hinterland of the Guanzhong Basin and Its Relationship with Urbanization].

aerosol optical depth (AOD) deep blue algorithm (DB) empirical orthogonal function (EOF) spatial and temporal changes urbanization

Journal

Huan jing ke xue= Huanjing kexue
ISSN: 0250-3301
Titre abrégé: Huan Jing Ke Xue
Pays: China
ID NLM: 8405344

Informations de publication

Date de publication:
08 Jun 2021
Historique:
entrez: 25 5 2021
pubmed: 26 5 2021
medline: 26 5 2021
Statut: ppublish

Résumé

Aerosol optical depth (AOD) is one of the most fundamental optical properties of aerosols that characterizes the attenuation of light by aerosols and is an indicator of regional air pollution. Based on the blue band surface reflectance database from the MOD09A1 products for the period 2000-2019 and the ASTER spectral database, AOD was estimated from Landsat TM/OLI data using the deep blue algorithm (DB). Multi-year average/annual average and seasonal AOD values for the period 2000-2019 were then calculated to analyze the spatial characteristics and temporal variations of AOD using the empirical orthogonal function method (EOF). Furthermore, the impacts of urbanization on the spatio-temporal distribution of AOD were analyzed. The obtained results are summarized as follows:① The multi-year average AOD spatial distribution in the hinterland of the Guanzhong Basin was significantly affected by topography and human activities, with higher AOD values and variationsin areas of low altitude and high-intensity human activities compared to the surrounding mountains. Thus, changes in AOD in the study area are mainly affected by anthropogenic factors. AOD also showed significant seasonal variations, whereby spring (0.34) > summer (0.33) > autumn (0.23) > winter (0.12), and the largest regional differences occurred in summer; ② The annual average AOD (from 2000-2019) showed the trend of "increase-decrease-increase", and reached a maximum in 2005, with the high AOD area gradually moving to the south. The distribution of AOD values in spring and summer was relatively discrete, while it is in a low-value agglomeration state in winter; ③ Three main AOD spatial distribution modes were identified based on the EOF, which had cumulative contribution rate of 83.0%. The spatial distribution trend of AOD showed regional consistency, with feature vectors consistent with the altitude, thus reflecting the difference of AOD at different altitudes. Taking the Qinling Mountains as the dividing line, the AOD presented the "north-south" pattern, AOD showed a "north-south" pattern, reflecting the uniqueness of the regional development in the Guanzhong Basin compared to the southern Qinling Mountains. The "southeast-northwest" distribution pattern indicated that the AOD presented a reverse change trend between urban and non-urban; and ④ The results of correlation analysis between the AOD and urbanization revealed a positive correlation with permanent population density (

Identifiants

pubmed: 34032069
doi: 10.13227/j.hjkx.202010018
doi:

Types de publication

English Abstract Journal Article

Langues

chi

Sous-ensembles de citation

IM

Pagination

2699-2712

Auteurs

Yu-Rong Zheng (YR)

College of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, China.
Shaanxi Xi'an Urban Forest Ecosystem Research Station, Northwest University, Xi'an 710127, China.

Xu-Hong Wang (XH)

College of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, China.
Shaanxi Xi'an Urban Forest Ecosystem Research Station, Northwest University, Xi'an 710127, China.

Xiu Zhang (X)

College of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, China.
Shaanxi Xi'an Urban Forest Ecosystem Research Station, Northwest University, Xi'an 710127, China.

Gui-Gui Hu (GG)

College of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, China.

Xiu-Juan Liang (XJ)

College of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, China.
Shaanxi Xi'an Urban Forest Ecosystem Research Station, Northwest University, Xi'an 710127, China.

Lin-Zhi Niu (LZ)

College of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, China.
Shaanxi Xi'an Urban Forest Ecosystem Research Station, Northwest University, Xi'an 710127, China.

Hai-Qing Han (HQ)

College of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, China.
Shaanxi Xi'an Urban Forest Ecosystem Research Station, Northwest University, Xi'an 710127, China.

Classifications MeSH