CAJ | 학술논문

乡镇是秸秆焚烧最直接责任主体，开展镇（乡）区域农作物秸秆产生量估算方法研究，可为镇（乡）区域秸秆资源规划和收储设施选址提供有效方法。该文以泗洪县车门乡为试验，研究利用MODIS卫星遥感影像时间序列数据和天地图免费遥感影像数据，建立区域秸秆资源量及其空间分布的估算方法。根据天地图选取样本田块，通过网站获取MODIS-EVI时间序列数据，确定作物类型-EVI 参数判别准则；选取图像识别样本田块，以图像参数为判别变量做判别分析，确定作物类型-图像参数判别准则。基于以上方法，完成全乡秸秆资源面积和秸秆产生量估算。水稻秸秆资源量1.77万t，可收集水稻秸秆资源量1.27万t，小麦秸秆资源量2.78万t，可收集小麦秸秆资源量为1.51万t；通过实际调研得知，该地水稻秸秆实际资源发生量约为1.82万t，小麦秸秆实际资源发生量约为2.75万t，估算数据和实际数据的误差仅为2.7%和1.1%，证明了该方法可以较准确的估算实际值，而且方便易用，节约成本。
향진시갈간분소최직접책임주체，개전진（향）구역농작물갈간산생량고산방법연구，가위진（향）구역갈간자원규화화수저설시선지제공유효방법。해문이사홍현차문향위시험，연구이용MODIS위성요감영상시간서렬수거화천지도면비요감영상수거，건립구역갈간자원량급기공간분포적고산방법。근거천지도선취양본전괴，통과망참획취MODIS-EVI시간서렬수거，학정작물류형-EVI 삼수판별준칙；선취도상식별양본전괴，이도상삼수위판별변량주판별분석，학정작물류형-도상삼수판별준칙。기우이상방법，완성전향갈간자원면적화갈간산생량고산。수도갈간자원량1.77만t，가수집수도갈간자원량1.27만t，소맥갈간자원량2.78만t，가수집소맥갈간자원량위1.51만t；통과실제조연득지，해지수도갈간실제자원발생량약위1.82만t，소맥갈간실제자원발생량약위2.75만t，고산수거화실제수거적오차부위2.7%화1.1%，증명료해방법가이교준학적고산실제치，이차방편역용，절약성본。
Township is the main direct part of duty for straw burning. It is very important for an effective method to estimate the total amount of straws in small-scale region, such as Chinese townships. Research of township regional estimation methods for crop straw production would provides an effective approach for the township straw resources’ planning and storage facilities location. This study aims to estimate straw production and their spatial distribution by using MODIS time series data and free world map image data in Chemen experimental site of Sihong County. The estimation process included three steps. Firstly, an uniformly distributed and relatively large field patch were chosen as the sample plot according to the electronic map. A field survey was conducted to investigate the current planting types. Then the “Crop type-EVI parameter” discriminant function and rules were established by setting crop type as classification variable and annual time series EVI as discriminatory variable, its MODIS-EVI time series data of the sample plot was collected online, and the accuracy rate was 97.37% in the case of setting confidence level of 95%.Secondly, sample plots’ images were recognized based on the field surveys data. The discriminant analysis was used to implement the “Crop type-EVI parameter” discriminant function and rules. There blocks were discriminated as rice stubble wheat planting type, and 8 for dryland wheat type, free lands exactly judge right, The correct total of 109 blocks, the judge accuracy rate of 90.8%; after the exclusion of free lands, the judge accuracy rate of 88.2%.In order to improve the classification accuracy, this paper adopted assistant judgment by the Chemen township autumn map world remote sensing image data in 2012. Meanwhile, field investigation and verification were combined with, drawn the image of Chemen township straw resources type distribution map. The residents, woodland, rivers and other objects classify through on-the-spot investigation. Wheat, rice stubble wheat, dryland wheat, free lands were classified by discriminant classification rules, and then combined with time series data to revise the field investigation results. Thirdly, we extracted the free world map image data corresponding to each field patch and judged the crop types in the region according the rule approached. Subsequently, straw resource area and straw yield and of the whole county were estimated, which included 1.77 million tons of rice straw resources, collecting rice straw resources volume of 1.27 million tons, 2.78 million tons of wheat straw resources, collection of wheat straw resources amount to 1.51 million tons, the dryland of Gangzhu, Tuanjie village planted corn, soybean, peanut mixed cropping, but unable to statistics identify and estimate. The results showed that this method could get more accurate straw production area, resources yield and the spatial distribution data in small-scale regions, compared with the traditional investigation method, this method is faster and easier. All operations of the process have been developed into plug-in, which is integrated into the software Croplab. Users only need simple operation knowledge can be completed, and does not require too much knowledge of statistics and technical, especially for investigation and planning of rural area of straw resources.