東華大學圖書館 |

Impacts of Land Use and Land Cover Change on Regional Climate in China.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Impacts of Land Use and Land Cover Change on Regional Climate in China./
作者:	He, Yaqian.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	106 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-03, Section: A.
Contained By:	Dissertations Abstracts International80-03A.
標題:	Asian Studies. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10830966
ISBN:	9780438321052

Impacts of Land Use and Land Cover Change on Regional Climate in China.
He, Yaqian.

Impacts of Land Use and Land Cover Change on Regional Climate in China. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 106 p.

Source: Dissertations Abstracts International, Volume: 80-03, Section: A.

Thesis (Ph.D.)--West Virginia University, 2018.

This item must not be sold to any third party vendors.

The purpose of this research is to investigate, using an empirical approach, the effects of land use and land cover change (LULCC) on the regional climate of China. Land surface is one of the important factors in determining regional climate. Changed land surface conditions (e.g. changes in albedo, soil moisture, surface roughness, and leaf area index) due to LULCC have caused significant impacts to regional climates across the globe. China, which is home to more than 1.3 billion people, has experienced extensive LULCC since the economic reform of 1978. Summer and Autumn rainfall in China has significantly increased in the south and decreased in the north in the past four decades. Understanding the influences of LULCC on regional climate variability of China will greatly improve climate forecasts, directly benefiting society, including famers and water resources managers. Consequently, an integrated study on the role of LULCC on regional climate of China is of great necessity. In order to tackle the role of LULCC on regional climate in China, I divided this study into three parts. First, I produced a continuous series of annual land use and land cover (LULC) maps of China from 1982 to 2013 using random forest classification of 19 phenological metrics derived from Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) third generation NDVI (NDVI3g) data. The 19 phenological metrics include start of growing season, end of growing season, maximum and minimum NDVI values, and so on. The classifier was trained using reference data derived from the MODIS land cover type product (MCD12Q1). The resulting AVHRR LULC maps were compared to the annual MODIS LULC products for the years 2001-2012, and an agreement of between 69.3% and 72.5% was found. Similarly, the overall consistency between the AVHRR LULC maps and the Chinese Land-Use/cover (CLU) dataset, for the years 1995, 2000, 2005, and 2010, was found to be 64.3%, 64.3%, 63.0%, and 64.4%, respectively. Based on a more traditional error evaluation using high resolution 2012 Google Earth images as a reference source, the overall accuracy of a simplified eight-class version of the 2012 LULC map was estimated to be 73.8%, which is not significantly different from the accuracy of the MODIS map of the same year. These inter-comparison and accuracy evaluation indicate the reliability of our AVHRR LULC maps. Secondly, I explored the effects of three spatial scaling methods on correlations among LULC data and a land surface climatic variable, latent heat flux. Scaling by a fractional method preserved significant correlations among LULC data and latent heat flux at all three studied scales (0.5°, 1.0°, and 2.5°), whereas nearest neighbor and majority aggregation methods caused these correlations to diminish and even become statistically non-significant at coarser spatial scales (i.e., 2.5°). Based on the fractional method, I identified fractional changes in croplands, forests, and grasslands in China using the continuous series of LULC maps from 1982 to 2012. Relative to common LULC change analyses conducted over two time steps or several time periods, this annually-resolved and 31-year time-series of LULC maps enables robust interpretation of LULC change. Specifically, the annual resolution of these data enabled us to more precisely observe three key and statistically significant LULCC trends and transitions that could have consequential effects on land-atmosphere interaction: (1) decreasing grasslands being replaced by increasing croplands in the Northeast China plain and the Yellow river basin, (2) decreasing croplands being replaced by increasing forests in the Yangtze river basin, and (3) decreasing grasslands being replaced by increasing forests in Southwest China. Finally, I examined the impacts of croplands expansion on temperature in the troposphere during late summer of August and September in Northeast China from 1982 to 2010. By using statistical methods including correlation analysis, linear regression analysis, and Granger-causality test, the relationships between croplands fractions and climatic variables (i.e., latent heat flux, sensible heat flux, surface temperature, multi-level temperature, and geopotential height) and their underlying physical mechanisms were investigated. I found that the increased croplands in Northeast China results in increased latent heat flux in the regions with significantly increased croplands. The increased latent heat flux decreases surface temperature. The cooling effect of cropland expansion in Northeast China also extends to upper-level troposphere. Overall, this dissertation contributes to multidisciplinary geospatial research by applying remote sensing and climatological analyses to study the roles of LULCC in affecting regional climate of China. The 32 years of sequential annual LULC maps generated by this dissertation provide a valuable database of LULCC information for China. (Abstract shortened by ProQuest.).

ISBN: 9780438321052Subjects--Topical Terms:

1669375
Asian Studies.
Subjects--Index Terms:

China

Impacts of Land Use and Land Cover Change on Regional Climate in China.
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520 $a The purpose of this research is to investigate, using an empirical approach, the effects of land use and land cover change (LULCC) on the regional climate of China. Land surface is one of the important factors in determining regional climate. Changed land surface conditions (e.g. changes in albedo, soil moisture, surface roughness, and leaf area index) due to LULCC have caused significant impacts to regional climates across the globe. China, which is home to more than 1.3 billion people, has experienced extensive LULCC since the economic reform of 1978. Summer and Autumn rainfall in China has significantly increased in the south and decreased in the north in the past four decades. Understanding the influences of LULCC on regional climate variability of China will greatly improve climate forecasts, directly benefiting society, including famers and water resources managers. Consequently, an integrated study on the role of LULCC on regional climate of China is of great necessity. In order to tackle the role of LULCC on regional climate in China, I divided this study into three parts. First, I produced a continuous series of annual land use and land cover (LULC) maps of China from 1982 to 2013 using random forest classification of 19 phenological metrics derived from Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) third generation NDVI (NDVI3g) data. The 19 phenological metrics include start of growing season, end of growing season, maximum and minimum NDVI values, and so on. The classifier was trained using reference data derived from the MODIS land cover type product (MCD12Q1). The resulting AVHRR LULC maps were compared to the annual MODIS LULC products for the years 2001-2012, and an agreement of between 69.3% and 72.5% was found. Similarly, the overall consistency between the AVHRR LULC maps and the Chinese Land-Use/cover (CLU) dataset, for the years 1995, 2000, 2005, and 2010, was found to be 64.3%, 64.3%, 63.0%, and 64.4%, respectively. Based on a more traditional error evaluation using high resolution 2012 Google Earth images as a reference source, the overall accuracy of a simplified eight-class version of the 2012 LULC map was estimated to be 73.8%, which is not significantly different from the accuracy of the MODIS map of the same year. These inter-comparison and accuracy evaluation indicate the reliability of our AVHRR LULC maps. Secondly, I explored the effects of three spatial scaling methods on correlations among LULC data and a land surface climatic variable, latent heat flux. Scaling by a fractional method preserved significant correlations among LULC data and latent heat flux at all three studied scales (0.5°, 1.0°, and 2.5°), whereas nearest neighbor and majority aggregation methods caused these correlations to diminish and even become statistically non-significant at coarser spatial scales (i.e., 2.5°). Based on the fractional method, I identified fractional changes in croplands, forests, and grasslands in China using the continuous series of LULC maps from 1982 to 2012. Relative to common LULC change analyses conducted over two time steps or several time periods, this annually-resolved and 31-year time-series of LULC maps enables robust interpretation of LULC change. Specifically, the annual resolution of these data enabled us to more precisely observe three key and statistically significant LULCC trends and transitions that could have consequential effects on land-atmosphere interaction: (1) decreasing grasslands being replaced by increasing croplands in the Northeast China plain and the Yellow river basin, (2) decreasing croplands being replaced by increasing forests in the Yangtze river basin, and (3) decreasing grasslands being replaced by increasing forests in Southwest China. Finally, I examined the impacts of croplands expansion on temperature in the troposphere during late summer of August and September in Northeast China from 1982 to 2010. By using statistical methods including correlation analysis, linear regression analysis, and Granger-causality test, the relationships between croplands fractions and climatic variables (i.e., latent heat flux, sensible heat flux, surface temperature, multi-level temperature, and geopotential height) and their underlying physical mechanisms were investigated. I found that the increased croplands in Northeast China results in increased latent heat flux in the regions with significantly increased croplands. The increased latent heat flux decreases surface temperature. The cooling effect of cropland expansion in Northeast China also extends to upper-level troposphere. Overall, this dissertation contributes to multidisciplinary geospatial research by applying remote sensing and climatological analyses to study the roles of LULCC in affecting regional climate of China. The 32 years of sequential annual LULC maps generated by this dissertation provide a valuable database of LULCC information for China. (Abstract shortened by ProQuest.).
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