利用交叉信息熵模拟东北地区水稻种植面积空间分布

作物时空分布变化是农业研究的重要内容。近30a来,东北地区水稻种植面积显著增加,为探讨东北地区水稻时空变化特征,进一步丰富和完善作物空间分布信息获取方法,研究作物空间分布对包括气候变化在内的多种影响因素的响应关系,该研究综合80年代以来的作物面积与产量统计数据、耕地数据、农业灌溉数据以及作物生长适宜性分布等多源数据,利用基于交叉信息熵原理的作物空间分配模型(spatial production allocation model,SPAM)构建了针对中国作物分布特点的SPAM-China模型,模拟了中国东北地区1980-2008年像元尺度上水稻空间分布信息。结果表明,模拟结果能较好地反映出东北地区水稻主要种植区域,近30a东北地区水稻种植时空变化特征显著,水稻种植区域向北向东扩展,种植重心北移了约1.76个纬度,中北部地区水稻种植面积增加且趋势明显,南部地区变化趋势不显著。

Using cross-entropy method simulates spatial distribution of rice in Northeast China

The crop's spatial-temporal pattern is critical to many agricultural studies. In the last 30 years, the rice area in Northeast China increased significantly, and has become one of the major rice producing regions in China. To explore the rice spatial-temporal change characteristics and enrich the crop spatial distribution information acquisition methods, this study combined such multi-source datasets as agricultural statistics data, cropland data, irrigation map and crop suitability, and uses a crop spatial distribution model SPAM (Spatial Production Allocation Model) which has been based on the cross-entropy theory and applied successfully in Brazil and Africa. We further modified the model and applied it to China, and named it SPAM-China. This model mainly has four modules that include a data consistency processing module which makes the multisource data a better spatial match, an agricultural statistical data input module, and a multisource data discrimination module that uses GAMS to optimize the procedure and improve the efficiency of the model, and a result output module. With the SPAM-China model, the study simulates the rice spatial distribution of Northeast China on the pixel scale in the past 30 years (1980-2008) and obtains four rice distribution maps.