地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (3): 396-404.doi: 10.12082/dqxxkx.2018.170553

• 遥感科学与应用技术 • 上一篇    

Google Earth Engine平台支持下的赣南柑橘果园遥感提取研究

徐晗泽宇1(), 刘冲1, 王军邦2, 齐述华1,*()   

  1. 1. 江西师范大学 鄱阳湖湿地与流域研究教育部重点实验室 地理与环境学院,南昌 330022
    2. 中国科学院地理科学与资源研究所 生态系统网络观测与模拟重点实验室 北京 100101
  • 收稿日期:2017-11-21 修回日期:2017-12-23 出版日期:2018-03-20 发布日期:2018-03-20
  • 通讯作者: 齐述华 E-mail:giser_orange@qq.com;qishuhua11@163.com
  • 作者简介:

    作者简介:徐晗泽宇(1993-),男,甘肃嘉峪关人,硕士生,主要从事土地利用变化研究。E-mail: giser_orange@qq.com

  • 基金资助:
    国家自然科学基金项目(41261069、41601453);江西省重大生态安全问题监控协同创新中心资助项目(JXS-EW-00)

Study on Extraction of Citrus Orchard in Gannan Region Based on Google Earth Engine Platform

XU Hanzeyu1(), LIU Chong1, WANG Junbang2, QI Shuhua1,*()   

  1. 1. School of Geography and Environment, Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China
    2. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • Received:2017-11-21 Revised:2017-12-23 Online:2018-03-20 Published:2018-03-20
  • Contact: QI Shuhua E-mail:giser_orange@qq.com;qishuhua11@163.com
  • Supported by:
    National Natural Science Foundation of China, No.41261069, 41601453;The Collaborative Innovation Center For Major Ecological Security Issues of Jiangxi Province and Monitoring Implementation, No. JXS-EW-00).

摘要:

赣南地区是中国柑橘主产区,柑橘种植产业经数十年发展已具较大规模。本文利用Google Earth Engine平台,使用2140景Landsat影像进行像元级融合,重构目标年份季节最小云量影像集,构建多维分类特征集,利用随机森林分类算法,实现了1990、1995、2000、2005、2010和2016年赣南柑橘果园的分布制图。结果表明:利用Google Earth Engine平台可实现大量遥感影像数据的高效处理;最小云量影像合成方法能够有效解决多云多雨地区高质量光学影像获取困难的问题;以最小云量影像合成构建的数据集,使用随机森林分类算法能够有效提取赣南柑橘果园,分类平均总体精度和Kappa系数分别为93.15%和0.90,分类效果良好;赣南柑橘果园面积由1990年9.77 km2扩大为2016年2200.34 km2,2005年以后呈大规模扩张趋势,果园分布由零星分布,逐步形成连片化的聚集分布特点,柑橘果园用地的主要来源为林地、灌丛和耕地。

关键词: 赣南, 柑橘果园, Google Earth Engine, 最小云量, 影像重构, 分类

Abstract:

Gannan region is located in the southern Jiangxi Province, China. Gannan region includes 2 districts and 15 counties in Ganzhou. It has hilly land resources and its climate conditions are benefit to plant citrus. With the support and guidance from local government, Gannan region has experienced the boom of citrus planting and become the largest citrus production region in China over the past decades. Despite the economic success, the rapid and extensive citrus orchard expansion has brought great concern about ecological consequences. It is necessary to map citrus orchard for understanding the effects of citrus expansion. The objective of this study is to map the citrus orchard in 1990, 1995, 2000, 2005, 2010 and 2016 in Gannan Region. An image composite method was applied and total 2140 tiles of Landsat historical images were employed to generate seasonal images with lowest cloud composite at the pixel level. Random Forest classifier was used to classify multiple dimensional features from spectral, spatial and topographic domains. The image composite and classification were implemented with Google Earth Engine (GEE) platform. Results showed that: (1) GEE can effectively execute complex workflows of remote sensing data processing and information digging. (2) Lowest cloud composite at the pixel level is a reliable method of producing clear seasonal images for the region influenced by cloud and rain frequently. (3) Random forest classifier was suitable for mapping citrus orchard with an average overall accuracy (OA) of 93.15% and a Kappa coefficient of 0.90. (4) The citrus orchard has expanded extensively with the area from 9.77 km2 in 1990 to 2200.34 km2 in 2016. Citrus orchard was becoming clustered especially in Xunwu, Xinfeng and Anyuan and was mainly converted from forest, bush and cropland.

Key words: Gannan region, citrus orchard, Google Earth Engine, lowest cloud coverage, image composite, classification