MODIS波段比值算法在太湖蓝藻水华预警及应急监测中的应用

为从宏观上快速掌控蓝藻水华发生状况,提高遥感信息处理的准确度,选取太湖上空2008年4～10月的18幅MODIS影像数据源,应用近红外波段2和可见光波段4的比值算法对太湖蓝藻水华进行了提取实验,并与目视判读结果进行了比对分析.结果表明,经过大气校正且无云层干扰的情况下,比值算法与目视判读结果吻合度较好,平均相对偏差为5.4%,有83.3%的样本相对偏差小于30%.2008年4月25日与5月22日的比值算法验证分析表明,在蓝藻暴发初期和蓝藻的快速增殖期,比值算法均能较好的区分水体与藻类,比值算法与目视解译的结果偏差分别为4.3%和10.2%.比值算法分析识别快,能有效避免因个人经验引起的差异;将比值算法与目视判读相结合,能够大大提高判读的准确度,可以在太湖蓝藻水华预警及应急监测中进行业务化应用.

MODIS Band Ratio Algorithm about Cyanobacteria Bloom in Taihu Lake Applied in Emergent Monitoring

To monitor the status of the cyanobacteria bloom in large scale rapidly and improve the accuracy of information extraction from remote sensing images,EOS/MODIS data was used as the data source for its free getting,high spectrum resolution and high time resolution,conversion model of ratio algorithm(Band2/Band4)which were calibrated according to the atmosphere factor was applied in information extractiing of Taihu cyanobacteria bloom.18 images being selected from April to November in 2008 applied in the mode...