CAJ | 학술논문

为了扩大气象卫星FY-3在科研、业务中的应用范围，将数据尽快用于遥感反演蒸散量业务工作中，根据FY-3/VIRR卫星通道特点，以山东为研究区域，基于地表能量平衡方程，结合地面气象要素，提出了利用FY-3卫星遥感数据进行区域蒸散反演的方法，建立了省级的区域逐日蒸散量估算系统。以2013年5月11日、8月20日、10月16日估算的日蒸散量为例，分析表明：基于FY-3/VIRR卫星反演的日蒸散量与利用Pen-man公式方法得到的数据对比，偏差分别为-0.19、-0.12和0.16 mm/d，相对偏差分别为10%、12%和11%；反演结果可准确揭示区域内不同地表覆盖类型的蒸散量的空间特点和差异性，结果较为合理；与同区域、同时段的 EOS/MODIS 蒸散产品进行对比分析表明：2种日蒸散产品的空间分布特征总体非常相似，相关系数在0.99以上，均方根差在0.36 mm以下，说明2种产品的一致性较好。利用中国新型自主研发的FY-3卫星资料估算蒸散量是可行的。
위료확대기상위성FY-3재과연、업무중적응용범위，장수거진쾌용우요감반연증산량업무공작중，근거FY-3/VIRR위성통도특점，이산동위연구구역，기우지표능량평형방정，결합지면기상요소，제출료이용FY-3위성요감수거진행구역증산반연적방법，건립료성급적구역축일증산량고산계통。이2013년5월11일、8월20일、10월16일고산적일증산량위례，분석표명：기우FY-3/VIRR위성반연적일증산량여이용Pen-man공식방법득도적수거대비，편차분별위-0.19、-0.12화0.16 mm/d，상대편차분별위10%、12%화11%；반연결과가준학게시구역내불동지표복개류형적증산량적공간특점화차이성，결과교위합리；여동구역、동시단적 EOS/MODIS 증산산품진행대비분석표명：2충일증산산품적공간분포특정총체비상상사，상관계수재0.99이상，균방근차재0.36 mm이하，설명2충산품적일치성교호。이용중국신형자주연발적FY-3위성자료고산증산량시가행적。
In order to expand meteorological satellite FY-3 in scientific research, the application of remote sensing inversion of the data is needed for evapotranspiration studies. Based on FY-3/VIRR channel characteristics and use of Shandong as a case study area, we proposed to use FY-3 satellite remote sensing data for regional evapotranspiration inversion and to establish a provincial regional daily evapotranspiration estimation system based on the surface energy balance equation in combination with ground meteorological elements ( air temperature and wind speed). To test our newly developed system for estimation of evapotranspiration, we used May 11, August 20, October 16, 2013 as our study dates. The results showed that evapotranspiration estimated from the inversion of the FY-3/VIRR data was respectively -0.19 mm/d, -0.12 mm/d, and 0.16 mm/d difference for the three tested dates as compared to the results obtained from the Penman equation. The relative deviation of the results between the two methods was 10%, 12% and 11% for the three tested dates, respectively. The tested results showed a better FY-3 data quality for the distribution patterns that reflected different types of surface evapotranspiration and features including the daily highest evapotranspiration in a variety of water surfaces. Followed by the types of water surface was the artificial influence of land uses such as arable land, urban, etc. The least affected by human activities for the evapotransiration was mainly natural vegetation and land cover types, such as woodlands, shrubs. The bare land had the lowest evapotranspiration inversion which accurately revealed the different land cover types in the area of evapotranspiration and the space characteristics and differences. Evapotranspiration spatial distribution of farmland has important implications for drought monitoring, irrigation, etc., It is necessary to conduct further analysis of cropland evaporation. Depending on grain yield, farmland can be divided into high, medium and low-yield fields. Evapotranspiration over the different grain yield types showed that amount evapotranspiration was high in the high and middle yield field and low in the low yield field. In the high and middle yield field, paddy water conditions were relatively good, soil water supply was adequate and crop growth was good resulting large amount of actual evapotranspiration. For the low yield field, soil water supply was poor resulting poor crop growth and hence small amount of actual evapotranspiration. The estimated result conformed to the water consumption characteristics of grain filling stage of wheat. The segment EOS/MODIS evapotranspiration product comparison analysis showed that: two kinds of daily ET overall spatial distribution was very similar with correlation coefficients >0.99 and the mean square root difference <0.36 mm. The above analysis showed that in the absence of data for measured evapotranspiration for all land cover types, the estimated daily ET using FY-3/VIRR through mutual comparison and verification of the results of the past studies were reasonable. This study showed a great potential in future evapotranspiration retrieval operation using Chinese FY-3/VIRR satellite data.