基于遗传算法的条件植被温度指数的时间尺度转换方法

Time-Scale Transform of Multi-Temporal Vegetation Temperature Condition Index Based on the Genetic Algorithm

多时相VTCI遥感数据具有更多的旱情信息,能充分反映旱情对作物生长及产量的影响。不同时段发生干旱导致的作物减产率不同,研究基于多时相VTCI时间尺度转换的干旱影响评估的方法具有重要意义。针对关中平原冬小麦主要生育期VTCI的时间尺度转化问题进行了建模分析,研究了求解该问题的基于因子权重排序法与熵值法的归一组合赋权法(CAFE)、穷举法(EA)和遗传算法(GA)的过程和结果,其中EA可得到问题的最优权重值。结果表明:CAFE确定的冬小麦不同生育时期干旱对产量影响的权重值与EA获得的最优权重值相差较大,而GA获得的权重值等于或接近于最优权重值,其获得的加权VTCI与冬小麦单产的回归分析结果亦接近于EA而优于CAFE,精度较高,同时其运算过程的时间复杂度大大低于EA。GA对关中平原冬小麦各生育时期干旱对产量影响权重的确定较为合理,更适合于关中平原多时相VTCI数据时间尺度转换研究和干旱对冬小麦生产的影响评估研究。

Vegetation temperature condition index(VTCI)is a remotely sensed drought indicator,and has been applied to drought monitoring,predication and impact assessment.Multi-temporal VTCIs can cover more drought information related with crop yields,and the drought occurred at different crop growth stages and its degrees lead to diverse yield reduction rate.Therefore,it is of great significance to explore how to integrate useful information from multi-temporal remote sensing data to improve the precision of drought impact assessment.The modeling for temporal scale transformation of VTCIs at the main growth stages of winter wheat in the Guanzhong Plain was carried out by using the normalized combination of factor weight sorting method and entropy method(CAFE),the exhaustive attack method(EA)and the genetic algorithm(GA).The results showed that the weights of impact of droughts at the main growth stages on wheat yields determined by the CAFE had the large differences from the optimal weights obtained by the EA,while the weights determined by the GA were in agreement with the optimal weights.The genetic algorithm was superior to the CAFE in the regression analyses between the weighted VTCIs and the yields,and greatly improved the efficiency and precision of the drought impact.Meanwhile,the GA had the same performance of the GA,but the computation time of the GA was significantly lower than that of the CA.These results indicated that the weight at each growth stage of winter wheat in the Guanzhong Plain determined by the genetic algorithm was quite reasonable,and could more accurately reflect the drought information of the stage,and the GA was more suitable for the study on drought impact assessment.