摘要
以陕西省夏季干旱过程监测为例,采用风云系列最新极轨气象卫星FY-3D/MERSⅠ-Ⅱ数据,利用其250 m空间分辨率红光和近红外通道构建NIR-Red特征空间,建立垂直干旱指数(PDI)、改进型垂直干旱指数(MPDI),并与综合气象干旱指数(CI)进行相关性分析。结果表明:FY-3D/MERSⅠ-Ⅱ数据在陕西省的干旱遥感监测中具有良好的适用性,PDI、MPDI与CI呈显著负相关,相关系数分别为-0.135和-0.110,达到显著水平,PDI在陕西省夏季旱情动态监测中表现更好;2019年陕西省夏季旱区主要集中在榆林北部和渭北旱腰带,5月下旬的干旱过程最为严重,对冬小麦产量有较大影响;相较于国际气象卫星和陆地卫星数据,国产FY-3D/MERSⅠ-Ⅱ数据具有更高的时空分辨率,在进行农业干旱动态监测方面具很大潜力。
Taking the monitoring of summer drought in Shaanxi Province as an example, using FY-3 D/MERSⅠ-Ⅱ data-the latest polar-orbiting meteorological satellite of Feng Yun series, we constructed the NIR-Red feature space using red and near-infrared channels of 250 m spatial resolution, built perpendicular drought index(PDI), and Modified Perpendicular Drought Index(MPDI), and correlation analysis was conducted on PDI, MPDI, and Compound Index(CI). The results showed that(1) FY-3 D/MERSⅠ-Ⅱ data had good applicability of remote-sensing monitoring of drought in Shaanxi Province. Both PDI and MPDI had significant negative correlation with CI with the correlation coefficients of-0.135 and-0.110, respectively, but PDI had a better result in summer drought dynamic monitoring in Shaanxi Province.(2) Drought region focused in northern Yulin and drought area of Weibei;the most serious drought process was in late May, which had a serious affection on winter wheat yield. Dynamic monitoring provided theoretical basis for taking effective measures to ease up the serious drought condition and increased crop yield by rapid acquisition of the result.(3) FY-3 D/MERSⅠ-Ⅱ data had higher temporal and spatial resolution compared with meteorological satellite and Landsat data abroad, which held great potential for dynamic monitoring of agricultural drought, which is becoming a focus area of research.
作者
权文婷
王旭东
李红梅
QUAN Wenting;WANG Xudong;LI Hongmei(Shaanxi Meteorological Service Center of Agricultural Remote Sensing and Economic Crop,Xi’an,Shaanxi 710000,China;Xi’an Jiaotong University,Xi’an,Shaanxi 710049,China)
出处
《干旱地区农业研究》
CSCD
北大核心
2021年第1期158-163,共6页
Agricultural Research in the Arid Areas
基金
政府间国际科技创新合作/港澳台科技创新合作重点专项项目(2019YFE0127200)。