A new climatic classification of afforestation in Three-North regions of China with multi-source remote sensing data
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- 作者：Xiao Zheng ; Jiaojun Zhu
- 刊名：Theoretical and Applied Climatology
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：127
- 期：1-2
- 页码：465-480
- 全文大小：
- 刊物类别：Earth and Environmental Science
- 刊物主题：Atmospheric Sciences; Climatology; Atmospheric Protection/Air Quality Control/Air Pollution; Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution;
- 出版者：Springer Vienna
- ISSN：1434-4483
- 卷排序：127
文摘
Afforestation and reforestation activities achieve high attention at the policy agenda as measures for carbon sequestration in order to mitigate climate change. The Three-North Shelter Forest Program, the largest ecological afforestation program worldwide, was launched in 1978 and will last until 2050 in the Three-North regions (accounting for 42.4 % of China’s territory). Shelter forests of the Three-North Shelter Forest Program have exhibited severe decline after planting in 1978 due to lack of detailed climatic classification. Besides, a comprehensive assessment of climate adaptation for the current shelter forests was lacking. In this study, the aridity index determined by precipitation and reference evapotranspiration was employed to classify climatic zones for the afforestation program. The precipitation and reference evapotranspiration with 1-km resolution were estimated based on data from the tropical rainfall measuring mission and moderate resolution imaging spectroradiometer, respectively. Then, the detailed climatic classification for the afforestation program was obtained based on the relationship between the different vegetation types and the aridity index. The shelter forests in 2008 were derived from Landsat TM in the Three-North regions. In addition, climatic zones and shelter forests were corrected by comparing with natural vegetation map and field surveys. By overlaying the shelter forests on the climatic zones, we found that 16.30 % coniferous forests, 8.21 % broadleaved forests, 2.03 % mixed conifer-broadleaved forests, and 10.86 % shrubs were not in strict accordance with the climate conditions. These results open new perspectives for potential use of remote sensing techniques for afforestation management.