首页> 外文会议>Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International >Bioclimatic modeling the spatial distribution of mountain forests in the Qilian Mountains, Northwest of China, using down-scaled climatic models
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Bioclimatic modeling the spatial distribution of mountain forests in the Qilian Mountains, Northwest of China, using down-scaled climatic models

机译:利用降尺度气候模型对中国祁连山山区森林的空间分布进行生物气候模拟

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Study on the Climate-Vegetation Coupling Relationship (CVCR) has been an attractive field in geography and ecology since the late 19th century. Its results are very helpful for decision-making of vegetation ecological restoration. However, it is hard for scientists to know precisely about the quantified relationships between a variety of vegetation types and a set of climatic parameters because of poor matching between spatially limited climatic data and high-resolution vegetation maps. In this article, the authors suggest new high-resolution distributing models that combine temperature and precipitation respectively with altitude, latitude, slope, and aspect, and perform regression analysis to deduce two equations linking temperature and precipitation respectively with readily observed altitude, slope and aspect. Using the two equations, mean annual temperature, mean monthly temperature, and annual precipitation for each cell can be calculated based upon the digital elevation model. The calculated results of models running are consistent with the actual conditions of temperature and precipitation in alpine zones of Qilian Mountains. According to the statistics of the distributing precipitation model, the regional annual precipitation maximum in Qilian Mountains occurs at 4500 m above sea level (a.s.l.). According to interpretation of Landsat TM/ETM+ imagery data, the actual areas of mountain forests in the study area are 422.94 km/sup 2/. The coupling relationship of mountain forests with both temperature and precipitation is achieved by combining the distributing temperature model with distributing precipitation model in the area of mountain forests together. The CVCR analysis indicates the mean annual temperature of -2.7/spl sim/0.8/spl deg/C, the mean July temperature of 9.3/spl sim/13.7/spl deg/C in the area of mountain forests, and the annual precipitation is more than 360 mm. According to the above-mentioned coupling relationships, a map which illustrates the potential extent of mountain forests is created. Statistics shows that under conditions without human-induced interruptions, potential areas of mountain forests would reach up to 6937.12 km/sup 2/. It means that, the present conditions of both types of forests only account for about 6% of the inferred potential areas.
机译:自19世纪末以来,气候与植被耦合关系(CVCR)的研究一直是地理和生态学领域的一个有吸引力的领域。其结果对植被生态恢复的决策非常有帮助。但是,由于空间有限的气候数据与高分辨率植被图之间的匹配性差,科学家很难准确了解各种植被类型与一组气候参数之间的量化关系。在本文中,作者提出了一种新的高分辨率分布模型,该模型将温度和降水分别与高度,纬度,坡度和坡度相结合,并进行回归分析,以推导出分别将温度和降水与海拔高度,坡度和坡度联系起来的两个方程式。 。使用这两个方程,可以根据数字高程模型计算每个单元的年平均温度,月平均温度和年降水量。模型运行的计算结果与祁连山高寒区气温和降水的实际情况相吻合。根据分布降水模型的统计,祁连山地区年降水量最大值出现在海拔4500 m处(a.s.l.)。根据对Landsat TM / ETM +影像数据的解释,研究区域内的山林实际面积为422.94 km / sup 2 /。通过将分布森林温度分布模型与降水分布模型相结合,建立了山区森林温度与降水量的耦合关系。 CVCR分析表明,山区森林地区的年平均温度为-2.7 / spl sim / 0.8 / spl deg / C,7月的平均温度为9.3 / spl sim / 13.7 / spl deg / C。超过360毫米。根据上述耦合关系,创建了一个地图,该地图说明了山林的潜在范围。统计数据显示,在没有人为干扰的条件下,潜在的山区森林面积将达到6937.12 km / sup 2 /。这意味着,这两种类型森林的当前状况仅占推断潜在面积的6%左右。

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