地球信息科学学报 ›› 2013, Vol. 15 ›› Issue (4): 611-617.doi: 10.3724/SP.J.1047.2013.00611

• 遥感科学与应用技术 • 上一篇    下一篇

四川草原MODIS数据的产草量估算

傅新宇1,2, 唐川江3, 张新跃3, 张绪校3, 周俗3, 黄耀欢1, 江东1   

  1. 1. 中国科学院地理科学与资源研究所 资源环境信息系统国家重点实验室, 北京 100101;
    2. 中国科学院大学, 北京 100049;
    3. 四川省草原工作总站, 成都 610041
  • 收稿日期:2013-01-17 修回日期:2013-02-27 出版日期:2013-08-08 发布日期:2013-08-08
  • 通讯作者: 唐川江(1972- ),男,四川开江人,硕士,研究方向为草原资源遥感监测。E-mail:chuanjiangt@163.com E-mail:chuanjiangt@163.com
  • 作者简介:傅新宇(1988- ),女,山东人,硕士生,研究方向为资源环境遥感应用。E-mail:fuxy@lreis.ac.cn
  • 基金资助:

    四川省草原工作总站委托项目(SC-20120621);地震行业科研专项项目(201208018-3)。

Estimation of Grass Yield Based on MODIS Data in Sichuan Province, China

FU Xinyu1,2, TANG Chuanjiang3, ZHANG Xinyue3, ZHANG Xuxiao3, ZHOU Su3, HUANG Yaohuan1, JIANG Dong1   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Sichuan Grassland General Workstation, Chengdu 610041, China
  • Received:2013-01-17 Revised:2013-02-27 Online:2013-08-08 Published:2013-08-08

摘要:

四川草原是我国5大牧区之一,其可利用的天然草地占全省草原总面积的85%,准确掌握草原产草量信息对草原管理和当地经济发展具有重要意义。本研究利用2011年7月MODIS不同分辨率(250m、500m、1km)NDVI、EVI产品和同期地面调查数据(共181个采样点),对四川草原4种主要草地类型(即高寒草甸草地、高寒灌木草地、高寒沼泽草地和山地疏林草地)产草量鲜重分类型建立估产模型。研究发现,NDVI对该地区4种主要草地类型产草量的拟合效果普遍优于EVI;相对于500m和1km的遥感数据,250m的遥感数据拟合效果较好;分草地类型建立模型的效果优于对全体样本建立模型;该地区除高寒沼泽草地用幂函数模型拟合效果较好外,其余均用指数模型进行建模效果较好;对该地区各草地类型建立的最优估产模型,精度均在70%以上,回归判定系数R2在0.75以上;利用最优模型对2011年四川省草原进行估产,总体估产精度约为90%。

关键词: MODIS, NDVI, 产草量, EVI

Abstract:

Grassland in Sichuan Province is one of the five most important pastoral areas in China. Available natural grassland accounts for 85% of the total grassland area of Sichuan Province. Accurate grass yield is significant for management of grassland and local economics. In this study, data of MODIS-NDVI/EVI with different resolution (250m, 500m, 1km) in July of 2011 was utilized to model the relationship between grass yield of the four main types (i.e., alpine meadow type, alpine shrub grassland, alpine swamp grassland and mountain drain grassland) and RS data, respectively. Vegetation coverage combined with NDVI/EVI was used to reduce the effect of mixed pixel. The main conclusions are as follows: NDVI was better than EVI to establish the relationship. Data of 250m was ideal among data of different resolution tested. Model for each main type of grassland was better than model for all the four grassland types. Exponential model was better to simulate the relationship compared with other models for the four main types of grassland except for alpine swamp grassland. And for alpine swamp grassland, power function model was better. Optimization model for each of the four main type grassland was obtained. Accuracy of each optimization model was more than 70% while R2 was larger than 0.75. Then these optimization models were utilized to estimate grass yield of Sichuan Province in 2011 and the accuracy of estimation was about 90%. This suggests that these optimization models are feasible and the accuracy is satisfied in practice.

Key words: EVI, MODIS, yield of grass, NDVI