摘要
为了推进草原综合顺序分类的实用化进程,在草地发生学原理指导下,在草原综合顺序分类中引入甘肃省2008年每日1km分辨率的MODIS地表温度产品(MYD11A1)和0.5km分辨率的MODIS地表反照率产品(MYD09GA),反演土壤水分和地表年积温,划分热量级和湿润度级,并对甘肃省草地进行分类,以野外调查数据为相对真值验证了结果,评价了分类精度。结果表明:甘肃省天然草地横跨寒冷-寒温-微温-暖温-暖热5个热量级,极干-干旱-微干-微润-湿润-潮湿6个湿润度级,共26个类,其中暖温干旱暖温带半荒漠类、微温干旱温带半荒漠类和寒温潮湿温性针叶林类是甘肃省最主要的几种草地类型,占全省面积的43.43%;草地类的分布呈现出明显的垂直地带性,类别划分结果符合研究区域的气候、地理位置和地貌特征。研究减少了以往综合顺序分类对气象站点分布和插值方法的依赖性,从数据源的角度解决了综合顺序分类法中站点数据向区域数据转换这一难题,改善了点数据外推的边界模糊问题,拓展了草原综合顺序分类的研究手段和方法,为推进草原综合顺序分类实用化进程提供了新的思路。
Grassland classification is a fundamental need of grassland science. It is also a challenge to develop a comprehensive grassland classification system because of the multivariable and multi-functional features of grassland ecosystem. The Comprehensive and Sequential Classification System of Grassland （CSCS）, one of well known grassland classification systems, involves a hierarchy of three classification levels （class-subclass-type, class is the basic level） and is advanced in quantification indicators. However, there are at least two aspects need to be improved at the basic classification level of CSCS： 1） the grasslands are grouped into classes according to the data involving annual precipitation and accumulative temperature, which are collected from meteorological stations. These data reflect the near-surface atmosphere hydrothermal conditions instead of the actual habitat of grasses; 2） The data of precipitation and temperature from ground observation can only present the conditions within a small area, but they are used through extrapolation to a larger region. In order to resolve the problems, the areal data of land surface temperature and soil moisture are introduced by quantitative remote sensing as main data sources for the basic classification level of CSCS to replace the parameters of precipitation and atmosphere temperature from ground observation. In this paper, the MODIS land surface temperature product （MYD11A1, daily with 1km resolution） and MODIS land surface reflection product （MYD09GA, daily with 0.5 km resolution） of Gansu province in 2008 were used to invert soil moisture based on Thermal Inertia Model with the help of a Soil Moisture Inversion Platform （SMIP） developped from ENVI/IDL. Then, the annual accumulative land surface temperature （〉0℃Σθ） and annual sum of soil moisture were carried out, and then they were fitted with annual accumulative temperature （〉0℃Σθ＇） and precipitation data from meteorological stations respectively. Thermal zones
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2013年第1期126-133,I0002,共9页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家自然科学基金项目"草地综合顺序分类与中国草地NPP的耦合研究"(30960264)
关键词
遥感
水分
温度
草原综合顺序分类法
甘肃省
remote sensing, moisture, temperature, comprehensive and sequential classification system of grasslands （CSCS）, Gansu province
