摘要
农作物生长的季节周期对环境变化敏感,研究农作物生长季长度的时空变化规律对于农业应对气候变化、保障国家粮食安全有重要意义。在区域尺度上卫星遥感是揭示作物生长季长度时空特征的有效手段,但遥感数据须经地面观测校正才能更准确反映作物的真实生长状况。该研究以黑龙江省水稻生长的开始和结束日期为研究对象,通过在气象参数、遥感数据和地面站记录数据之间建立转换函数的方法,将站点观测的水稻生长季数据在空间上外推到站点以外区域,实现地面观测数据由点到面的扩展。结果表明:(1)仅包含积温因子的模型优于同时考虑积温和降水的模型;(2)利用模型校正后的黑龙江省水稻生长季长度,在空间上存在自西南向东北逐渐延长的趋势。该研究为区域尺度农作物生长季长度观测数据的融合提供一种新方法。
The seasonal dynamics of crop growth are sensitive to environmental change. The characterization of spatial-temporal patterns of the crop growing season is essential for climate change adaptation and food security im-provements. Although satellite remote sensing is an effective means of detecting growing season changes at regional scales, satellite data has to be calibrated before being used. Here we spatially extrapolate the start and end of the growing season of rice in Heilongjiang province of Northeast China by establishing a transfer function between satel-lite-ground observed difference of growing season dates and climatic parameters. Our results show that:(1) Ac-cumulative temperature is a better parameter, than rainfall, in transfer function establishment; ( 2 ) length of the rice growing season tends to increase from southwest to northeast in Heilongjiang province. This paper provides a new method of data fusion in growing season characterization at regional scales.
出处
《中国农业资源与区划》
北大核心
2016年第8期12-20,共9页
Chinese Journal of Agricultural Resources and Regional Planning
基金
中央级公益性科研院所基本科研业务费专项"CAAS-UGent全球变化与粮食安全联合实验室科技创新能力建设"(IARRP-015-28)
关键词
生长季
遥感
空间建模
积温
水稻
growing season
remote sensing
special model
accumulated temperature
rice
