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中国农学通报

中国农学通报 ›› 2021, Vol. 37 ›› Issue (16): 108-118.doi: 10.11924/j.issn.1000-6850.casb2020-0432

所属专题： 资源与环境

• 资源·环境·生态·土壤·气象 • 上一篇    下一篇

基于多时相MODIS数据监测水、旱作物种植面积及空间分布

姜蓝齐1,2(), 王萍1,2, 姜丽霞1,2, 宫丽娟1,2, 于成龙1,2, 李秀芬1,2()   

  1. 1黑龙江省气象科学研究所,哈尔滨 150030
    2中国气象局东北地区生态气象创新开放实验室,哈尔滨 150030
  • 收稿日期:2020-09-07 修回日期:2020-10-10 出版日期:2021-06-05 发布日期:2021-06-16
  • 通讯作者: 李秀芬
  • 作者简介:姜蓝齐,女,1988年出生,黑龙江哈尔滨人,博士,主要从事陆面过程监测与变化研究。通信地址：150030 哈尔滨市香坊区电碳路71号,Tel：0451-55112109,E-mail： jianglanqi@126.com。
  • 基金资助:
    国家自然科学基金项目“东北地区大豆干旱形成的时序特征及多源协同诊断研究”(31671576);“基于生态位模型的高寒区大豆潜在适生性研究”(31801253);黑龙江省自然科学基金项目“黑龙江省作物种植结构变化对区域气候的影响研究”(D2018007);中国气象局东北地区生态气象创新开放实验室开放研究基金“黑龙江省水稻生产对未来气候变化的适应”(stqx201801);黑龙江省寒区湿地生态与环境研究重点实验室基金“寒地稻田湿地CO2/CH4排放通量及影响因素研究”(201904)

Estimation of Crop Planting Area and Spatial Distribution Based on MODIS NDVI Time-series Data of Rice and Dry Farmland Crops

Jiang Lanqi1,2(), Wang Ping1,2, Jiang Lixia1,2, Gong Lijuan1,2, Yu Chenglong1,2, Li Xiufen1,2()   

  1. 1Heilongjiang Province Institute of Meteorological Sciences, Harbin 150030
    2Innovation and Opening Laboratory of Regional Eco-Meteorology in Northeast, China Meteorological Administration, Harbin 150030
  • Received:2020-09-07 Revised:2020-10-10 Online:2021-06-05 Published:2021-06-16
  • Contact: Li Xiufen

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摘要：

针对农业信息服务中大范围水田、旱田种植面积信息调查业务的现状与需求,以黑龙江省为研究区,通过分析水田、旱田作物发育期特征、MODIS数据植被指数(NDVI、EVI、LSWI)时序特征,引入积温条件分区构建决策规则,提取检测农田与其他、水田与旱田作物种植的空间分布。以实地调查地面验证点对分类结果进行验证,结果表明,分类结果达到了较高的识别精度,分类结果的总体精度为90.68%,Kappa系数为0.81,其中水稻制图精度为81.13%,用户精度为97.73%;旱地制图精度为98.46%,用户精度为87.07%;与不考虑积温条件相比,分类结果总体精度提高了12.77%,水稻制图精度提高了22.57%,旱地制图精度提高了5.94%。本研究通过引入积温条件,提高了大范围水稻、旱地作物提取精度,具有自动化程度高、分类结果稳定的特点。

关键词: 水稻, 旱田作物, 种植面积, 植被指数, MODIS

Abstract:

Aiming at the current situation and demand of paddy and dry farmland planting area survey in agriculture information service, we took Heilongjiang Province as the study area, by analyzing the characteristics of crop growing stage and the timer-series of vegetation index (NDVI, EVI and LSWI), we introduced accumulative temperature condition, then the spatial distribution was studied on cropland and others, and paddy rice and dry farmland crops. The classification results were verified with field investigation on verification points. The results showed that a high mapping accuracy of the classification was obtained, the overall accuracy reached 90.68%, the Kappa coefficient was 0.81. The mapping accuracy of rice planting area was 81.13% and the user accuracy was 97.73%, and that of dry farmland crops was 98.46% and 87.07%, respectively. Compared with the classification results without accumulative temperature, the overall accuracy was increased by 12.77%. The mapping accuracy of rice and dry farmland crop was increased by 22.57% and 5.94%, respectively. The finding of this study could improve the classification precision though introducing the accumulative temperature, and this method is featured with high automatic degree and stable classification results.

Key words: paddy rice, dry farmland crop, planting area, vegetation index, MODIS

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