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Impacts of land cover changes on surface albedo in China, the United States, India and Brazil

  • role： First author第一作者
  • Affiliation：

    Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing100101, China

    University of Chinese Academy of Sciences, Beijing100049, China

  • Email：zhengyuhan16@mails.ucas.ac.cn
  • Introduction：郑瑜晗，1994年生 , 女, 硕士研究生, 研究方向为生态环境遥感与信息系统。E-mail:zhengyuhan16@mails.ucas.ac.cn
ZHENG Yuhan12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing100101, China

  • Email：huanglin@igsnrr.ac.cn
  • Introduction：黄麟 ，1981年生 , 女, 副研究员, 研究方向为土地利用变化及其生态效应。E-mail: huanglin@igsnrr.ac.cn
HUANG Lin1*,  
  • Affiliation：

    Satellite Environment Center, Ministry of Ecology and Environment, Beijing100094, China

ZHAI Jun3

Resümee

With the deepening research of global change, it is increasingly recognized that at the regional scale, changes in land use/land cover caused by human activities such as deforestation, urban expansion, and farmland reclamation affected the land surface characteristics and thus play a dominant factor in land surface radiative budget and energy balance, which is a key link in understanding the impact of human activities on global climate change.Based on the 30 m Globe Land 30 dataset and 1000 m MODIS albedo products, this study quantitatively analyzed the spatial variations of surface albedo at interannual and seasonal scales, and compared its characteristics between farmland, forest, grassland and artificial surfaces in different climate zones among China, the United States, India, and Brazil. Then the changes in albedo due to reclamation and urbanization were further simulated.Results show that (1) the interannual surface albedo from 2000 to 2015 showed a slight decline in India and a weak increase in Brazil, which had a obvious spatial heterogeneity in China and the United States. The arid and semi-arid zones in China and humid zones in middle and low latitudes of the United States showed decline trends, however the humid subtropical zones in China and the microthermal as well as the arid zones in the United States were opposite. (2) Under the snow-free condition, the interannual surface albedo of the farmland, forest, grassland and artificial surfaces have country differences. The surface albedo of the four types were high in summer and low in winter, and were obviously higher in arid and semi-arid zones than in humid zones. The albedo of humid subtropical zones in China has increased which is contrary to the arid and semiarid zones. Except for the farmland in arid zones in the United States that showed a relatively strong interannual trend, others generally declined. All types have decreased in India, however raised in Brazil. (3) Compared to the snow-free condition, when under the snow condition, the surface albedo of the four land cover types have raised. The albedo changes in forest are 0.06 to 0.26, which is the smallest, and 0.17 to 0.38 in cultivated land, which is the highest. And the albedo changes of forest in China is higher than that in the United States. (4) Reclamation and urbanization on forest will increase the albedo in all months, which will be more aggravated in arid zones than in humid zones. Reclamation on grassland will increase the albedo in India, Brazil, humid subtropical zones in China, and the United States. But the changes due to urbanization further demonstrate the variations between countries and zones that impacted by the original land cover types, seasons and background climate.Therefore, even under the same climatic background, the variation of surface albedo has different directions and magnitudes in different countries. The spatial heterogeneity of albedo changes can reflect the differences in natural geographic background and can also reflect the differentiation in human disturbances such as different land use patterns and eco-environment policies which may helps the further analysis and understanding of the driving mechanism of the impacts on land surface characteristics caused by land use/land cover changes.

Schlüsselwort

remote sensing;land cover changes;surface albedo;inter-national comparison;climate zone differentiation;spatial variations

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