基于定量遥感的甘肃省草原综合顺序分类

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1 km 分辨率的 MODIS 地表温度产品（MYD11A1）和0.5 km 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...

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Published in农业工程学报 Vol. 29; no. 1; pp. 126 - 133
Main Author 吴静 李纯斌 胡自治 张德罡 柳小妮 申正东
Format Journal Article
LanguageChinese
Published 甘肃农业大学草业学院,兰州 730070%甘肃农业大学资源与环境学院,兰州 730070 2013
Subjects
水分
温度
甘肃省
草原综合顺序分类法
遥感
温度
甘肃省
草原综合顺序分类法
Gansu province
temperature
remote sensing
comprehensive and sequential classification system of grasslands (CSCS)
遥感
moisture
水分
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ISSN1002-6819
DOI10.3969/j.issn.1002-6819.2013.01.017

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Summary: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1 km 分辨率的 MODIS 地表温度产品（MYD11A1）和0.5 km 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.
Bibliography:Wu Jing, Li Chunbin, Hu Zizhi, Zhang Degang, Liu Xiaoni, Shen Zhengdong （1. College Pratacultural Science, Gansu Agricultural UniversitY, Lanzhou 730070, China;2. College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China）
11-2047/S
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 col
ISSN:1002-6819
DOI:10.3969/j.issn.1002-6819.2013.01.017