基于MODIS地表温度与气象数据的东北春玉米低温冷害监测  

Monitoring chilling damage of corn in the Northeast China based on MODIS LST and meteorological data

作　　者：黄然 黄健熙 张超 郭春明[3] 庄立伟 吴开华[1] 张竞成[1] 张垚 HUANG Ran;HUANG Jianxi;ZHANG Chao;GUO Chunming;ZHUANG Liwei;WU Kaihua;ZHANG Jingcheng;ZHANG Yao(School of Artificial Intelligence,Hangzhou Dianzi University,Hangzhou,310018,China;College of Land Science and Technology,China Agricultural University,Beijing 100083,China;Institute of Meteorological Sciences of Jilin Province,Changchun,Changchun 130062,China;National Meteorological Center,Beijing 100081,China)

机构地区：[1]杭州电子科技大学人工智能学院,杭州310018 [2]中国农业大学土地科学与技术学院,北京100083 [3]吉林省气象科学研究所,长春130062 [4]国家气象中心,北京100081

出　　处：《遥感学报》2024年第10期2500-2512,共13页NATIONAL REMOTE SENSING BULLETIN

基　　金：浙江省自然科学基金(编号:LQ21D010006)。

摘　　要：低温冷害是影响东北玉米生长发育及产量形成的主要气象灾害。以东北地区为研究区,利用2003年—2015年的MODIS陆地表面温度LST(Land Surface Temperature)数据产品、植被指数VI(Vegetation Index)数据产品与气象站点观测的日平均气温数据,构建以LST、VI和太阳赤纬(Ds)为自变量的日平均气温估算模型;结合时空数据融合方法,完成覆盖研究区的逐日的1 km空间分辨率的日平均气温数据集,逐年计算≥10°C的积温;结合玉米障碍型低温冷害指标和延迟型冷害指标,开展研究区2003年—2015年研究区玉米低温冷害遥感监测。监测结果显示,本研究区在2003年、2005年、2006年、2009年和2011年遭受大范围的延迟型低温冷害,与相关文献和农业农村部种植业司玉米单产数据分析对比结果表明,玉米障碍型低温冷害和延迟型低温冷害遥感监测结果与实际情况相符。Corn has become one of the most important crops in China at present.The study area in this work,which includes Jilin Province,Liaoning Province,Heilongjiang Province,and the four eastern cities of Inner Mongolia Autonomous Region(Hulun Buir,Tongliao,Chifeng,and Xing’an League),is the most important corn production area.The area is also located at the northern limit of corn planting area.Notably,the temporal and spatial distribution of chilling damage is highly important to increase yield and quality.This study aims to integrate MODIS and meteorological data for monitoring corn chilling damage in Northeast China.The algorithm was computed in two steps.In the first step,the remote sensing estimation model of air temperature were established.In the second step,the sterile-type chilling damage and delayed-type chilling damage on corn were monitored based on the full coverage daily mean air temperature and the corn chilling damage indicator.Satellite data,including LST,EVI,and quality control data derived from TERRA/AQUA-MODIS,and ground-based data,including daily mean air temperature and phenological data observed by 234 meteorological stations,from 2003 to 2015 were collected for data analysis,image processing,and mapping.The remote sensing estimation model of air temperature was established by multi-variated linear regression using the MODIS LST,EVI,and solar declination of cloud-free pixels as independent variables,and daily mean air temperature observed by meteorological stations was used as a dependent variable.The meteorological stations were divided into two parts according to the coordinates.Daily mean air temperature measured by two thirds of station(156)from 2003 to 2013 was used to establish the daily average temperature estimation model,and the remaining data including the observations of 78 meteorological stations from 2003 to 2013 and the observation data of all stations in 2014 and 2015 were used to validate the model.The MODIS EVI production is the composited production on the 16th day.The S-G filte

关 键 词：遥感 MODIS 陆地表面温度 数据融合 低温冷害 春玉米 

分 类 号：TP701[自动化与计算机技术—检测技术与自动化装置] P2[自动化与计算机技术—控制科学与工程]