基于遥感和GIS的观测气温订正及对LUCC响应研究
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摘要
气候变暖已是不争事实,客观地评价和预测全球及区域变暖趋势是科学界共同关注的话题。城市化作为影响台站观测气温均一性的一个重要方面,其所造成的局部区域土地利用和覆被的变化,严重影响到台站气温的非均一性问题,但城市化对气温的影响和温室气体类似,是个持续增长的过程,不存在突变点,这就为均一化订正带来了困难。针对这个十分有意义的科学问题,本论文的研究思路是：综合考虑气温变化的时空特征,以台站气温数据序列为核心,以多源遥感数据、多期土地利用数据、DEM数据、城市人口、经济等数据为辅助,以气温订正作为贯穿本论文的主线,以获取背景气温为主要切入点,以台站下垫面各土地类型对观测气温的影响程度为重要补充,进行安徽省80个台站气温订正以及台站气温和土地利用及覆被变化关系的研究。
通过本论文的研究,得出的结论是：①安徽省各区域气候存在典型的地域分异规律,以淮河、长江、大别山区以及江南山区等界限和自然区域可以分为六大局地气候,进一步细分为八大局地气候。②安徽省各土地类型之间转化较剧烈,以耕地的减少和建设用地的增加最为明显；其中,耕地以转入建设用地和林地为主,建设用地的增加主要体现在乡村建设及居民点上；面积广大的林地和耕地是主导气温差异的主体,城镇用地虽然温度较高,但总体面积过小,增温贡献率低。③安徽省各区、各级城市的增温趋势、热岛强度及其增强趋势也各不相同。20万人以上城市普遍受到城市化的影响,以大、中等城市的热岛强度及增温趋势最为明显,且中等城市存在着较平稳的增温趋势和热岛强度变化；而20万人以下小城市则较弱且相互差异不明显,20万人基本是城市热岛影响显著与否的分界线。④通过人工神经网络筛选10-20万人口的小城市台站后得出：大部分小城市台站和10万人口以下的台站增温趋势及强度基本一致,仅有3个台站可以划入受城市化影响较强台站行列。⑤城市台站下垫面环境对于台站观测气温影响较大,城镇用地、耕地、林草地和热岛强度密切相关,三者合理影响范围为4km左右,随着距离增加影响力迅速降低,而水体却有着较远的影响范围。
本论文研究工作的创新性主要体现在以下几个方面：
(1)首次根据气候的地域差异进行了气温订正的针对性研究,摆脱了因地域原因所造成的台站间气候条件不一致所造成的订正误差,克服了元数据缺失所造成的订正困难,并简化了订正难度。
(2)充实了国内对大、中、小城市在热岛研究上的不足,系统地分析了大、中、小城市的热岛特征,尤其是在中、小城市的分析上,得出了20万人口是安徽省城市热岛效应显著与否的分界线,并对于城乡台站的界定,给出了参考。
(3)突破了以往仅以城市人口或者其他单一数据进行城乡台站划分的片面性,客观地利用城市人口、台站下垫面各土地利用类型为依据,依人工神经网络来进行城乡台站的划分。
(4)充分考虑了台站下垫面环境是影响台站气温的决定性因素,首次基于台站周边一定圆形缓冲区范围内,利用获取的土地利用和变化状况,系统分析了台站周边下垫面各土地类型及其变化对台站气温观测的影响范围及强度。
Global warming is an inarguable truth; therefore evaluating and forecasting the global and regional warming trends is often addressed in the scientific community. As one of the important factors which influence the homogeneity of the temperature measured by meteorological stations, urbanization has lead to regional Land Use and Land Cover Changes (LUCC). But the influence of urbanization is similar to that of greenhouse gases which are increasing gradually without mutation. Therefore the correction of temperature trends affecting homogeneity caused by urbanization is a difficult issue.
Aiming at addressing this meaningful scientific problem, the academic methodology of this paper is that: In order to do temperature correction and to study the relationship between temperature and LUCC, we choose eighty meteorological stations in Anhui province, utilize the temporal and spatial characteristics of the air temperature, use the time series temperature data, multi-source remote sensing data, multi-period land-use data, a DEM, city population and economic data, then perform a temperature correction, get the background air temperature, and finally analyze the stations' underlying influence on the measured temperature.
The conclusion is:①The regional climate of AnHui has a typical spatial distribution; with the Huaihe River, Yangtze River, Dabie mountainous areas, Jiangnan mountainous areas and natural regions as boundaries. It can be divided into six kinds of regional climate zones and eight subdivided regional climate zones.
②There have been violent transformations between different land cover types. Arable land has suffered the greatest loss while urban land has made the greatest gains. The decrease in arable land is mainly due to conversion into urban land and forest land while the increased urban land cover mainly comes from rural construction and settlements. Although the temperature in urban land is high, it is so small that it has little contribution to the temperature increase. Therefore the increased forest and arable land cover is the main reason for the difference in temperature.
③The trend of increasing temperature and heat-island intensity are different among districts and cities in Anhui Province. Urbanization mainly affects temperatures of cities which have more than 200,000 people; so the affects are most noticeable in the large and medium-sized cities, with steady trends apparent in medium-sized cities. But the small cities under 200,000 people are very small, therefore 200,000 people appears to be the population threshold for cities to show a heat island effect in the temperature data.
④After analyzing the weather data station in small cities with populations between 100,000 and 200,000 by using an artificial neural network (ANN), we can draw a conclusion that the majority of stations in small cities as well as stations with a population bellow 100,000 show almost the same temperature tendency and intensity, with only three stations influenced greatly by urbanization.
⑤The underlying local environment in urban stations has a great influence on a station's temperature observations, with a close relationship revealed among building, lawn and the intensity of the urban heat island. The influential distance is about three kilometers and it decreases dramatically as the distance increases. Bodies of water have further influence.
The innovating points of this research are as follows:
(1) This research is the first one to look at the effects of the regional variations in the temperature records, thus getting rid of correcting errors leaded by climate differences which result from regional conditions and taking over correcting difficulties resulting from missing metadata and simplifying the procedure.
(2) Overcoming the disadvantages in research of heat island of big, moderate and small cities and systematic analysis is carried out in heat-land's characteristic especially in the analysis of moderate and small cities. We have determined a boundary of the heat-island effect in Anhui province, and provide a reference to define the urban stations from the rural ones.
(3) We break through the traditional methods of considering the city population and other single data separately; We take both the city population and the meteorological stations’underlying land-use type into account, using ANN to separate the urban stations from the rural ones.
(4) Among all the factors, the station underlying environment is a determining factor. Taking this into consideration, we do a certain buffer analysis based on observations, analyze LUCC's influence on temperature measured by meteorological stations, and finally get the range and the intensity of this influence.
通过本论文的研究,得出的结论是：①安徽省各区域气候存在典型的地域分异规律,以淮河、长江、大别山区以及江南山区等界限和自然区域可以分为六大局地气候,进一步细分为八大局地气候。②安徽省各土地类型之间转化较剧烈,以耕地的减少和建设用地的增加最为明显；其中,耕地以转入建设用地和林地为主,建设用地的增加主要体现在乡村建设及居民点上；面积广大的林地和耕地是主导气温差异的主体,城镇用地虽然温度较高,但总体面积过小,增温贡献率低。③安徽省各区、各级城市的增温趋势、热岛强度及其增强趋势也各不相同。20万人以上城市普遍受到城市化的影响,以大、中等城市的热岛强度及增温趋势最为明显,且中等城市存在着较平稳的增温趋势和热岛强度变化；而20万人以下小城市则较弱且相互差异不明显,20万人基本是城市热岛影响显著与否的分界线。④通过人工神经网络筛选10-20万人口的小城市台站后得出：大部分小城市台站和10万人口以下的台站增温趋势及强度基本一致,仅有3个台站可以划入受城市化影响较强台站行列。⑤城市台站下垫面环境对于台站观测气温影响较大,城镇用地、耕地、林草地和热岛强度密切相关,三者合理影响范围为4km左右,随着距离增加影响力迅速降低,而水体却有着较远的影响范围。
本论文研究工作的创新性主要体现在以下几个方面：
(1)首次根据气候的地域差异进行了气温订正的针对性研究,摆脱了因地域原因所造成的台站间气候条件不一致所造成的订正误差,克服了元数据缺失所造成的订正困难,并简化了订正难度。
(2)充实了国内对大、中、小城市在热岛研究上的不足,系统地分析了大、中、小城市的热岛特征,尤其是在中、小城市的分析上,得出了20万人口是安徽省城市热岛效应显著与否的分界线,并对于城乡台站的界定,给出了参考。
(3)突破了以往仅以城市人口或者其他单一数据进行城乡台站划分的片面性,客观地利用城市人口、台站下垫面各土地利用类型为依据,依人工神经网络来进行城乡台站的划分。
(4)充分考虑了台站下垫面环境是影响台站气温的决定性因素,首次基于台站周边一定圆形缓冲区范围内,利用获取的土地利用和变化状况,系统分析了台站周边下垫面各土地类型及其变化对台站气温观测的影响范围及强度。
Global warming is an inarguable truth; therefore evaluating and forecasting the global and regional warming trends is often addressed in the scientific community. As one of the important factors which influence the homogeneity of the temperature measured by meteorological stations, urbanization has lead to regional Land Use and Land Cover Changes (LUCC). But the influence of urbanization is similar to that of greenhouse gases which are increasing gradually without mutation. Therefore the correction of temperature trends affecting homogeneity caused by urbanization is a difficult issue.
Aiming at addressing this meaningful scientific problem, the academic methodology of this paper is that: In order to do temperature correction and to study the relationship between temperature and LUCC, we choose eighty meteorological stations in Anhui province, utilize the temporal and spatial characteristics of the air temperature, use the time series temperature data, multi-source remote sensing data, multi-period land-use data, a DEM, city population and economic data, then perform a temperature correction, get the background air temperature, and finally analyze the stations' underlying influence on the measured temperature.
The conclusion is:①The regional climate of AnHui has a typical spatial distribution; with the Huaihe River, Yangtze River, Dabie mountainous areas, Jiangnan mountainous areas and natural regions as boundaries. It can be divided into six kinds of regional climate zones and eight subdivided regional climate zones.
②There have been violent transformations between different land cover types. Arable land has suffered the greatest loss while urban land has made the greatest gains. The decrease in arable land is mainly due to conversion into urban land and forest land while the increased urban land cover mainly comes from rural construction and settlements. Although the temperature in urban land is high, it is so small that it has little contribution to the temperature increase. Therefore the increased forest and arable land cover is the main reason for the difference in temperature.
③The trend of increasing temperature and heat-island intensity are different among districts and cities in Anhui Province. Urbanization mainly affects temperatures of cities which have more than 200,000 people; so the affects are most noticeable in the large and medium-sized cities, with steady trends apparent in medium-sized cities. But the small cities under 200,000 people are very small, therefore 200,000 people appears to be the population threshold for cities to show a heat island effect in the temperature data.
④After analyzing the weather data station in small cities with populations between 100,000 and 200,000 by using an artificial neural network (ANN), we can draw a conclusion that the majority of stations in small cities as well as stations with a population bellow 100,000 show almost the same temperature tendency and intensity, with only three stations influenced greatly by urbanization.
⑤The underlying local environment in urban stations has a great influence on a station's temperature observations, with a close relationship revealed among building, lawn and the intensity of the urban heat island. The influential distance is about three kilometers and it decreases dramatically as the distance increases. Bodies of water have further influence.
The innovating points of this research are as follows:
(1) This research is the first one to look at the effects of the regional variations in the temperature records, thus getting rid of correcting errors leaded by climate differences which result from regional conditions and taking over correcting difficulties resulting from missing metadata and simplifying the procedure.
(2) Overcoming the disadvantages in research of heat island of big, moderate and small cities and systematic analysis is carried out in heat-land's characteristic especially in the analysis of moderate and small cities. We have determined a boundary of the heat-island effect in Anhui province, and provide a reference to define the urban stations from the rural ones.
(3) We break through the traditional methods of considering the city population and other single data separately; We take both the city population and the meteorological stations’underlying land-use type into account, using ANN to separate the urban stations from the rural ones.
(4) Among all the factors, the station underlying environment is a determining factor. Taking this into consideration, we do a certain buffer analysis based on observations, analyze LUCC's influence on temperature measured by meteorological stations, and finally get the range and the intensity of this influence.
引文
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