MODTRAN model was used for the atmospheric correction of one HJ-1B / CCD2 image,and the effect of atmospheric correction was evaluated from the changes of spectral characteristics of typical ground objects,the compari...MODTRAN model was used for the atmospheric correction of one HJ-1B / CCD2 image,and the effect of atmospheric correction was evaluated from the changes of spectral characteristics of typical ground objects,the comparison with the MODIS surface reflectance product,and the effect on normalized differential vegetation index( NDVI). The results show that atmospheric correction eliminated the increase effect in visible bands and the absorption in near-infrared band. Atmospheric correction results and the MODIS surface reflectance product with high accuracy were highly consistent in the reflectance of vegetation,water and residents,and the average error of vegetation was 12.8%. According to the comparison of changing characteristics of NDVI before and after atmospheric correction,it could be found that atmospheric correction had corrected NDVI of mixed pixels and made it more reasonable. NDVI of each kind of ground objects improved,among which NDVI of vegetation increased most greatly,which can help differentiate vegetation from other ground objects. In a word,MODTRAN model has a good effect on atmospheric correction of HJ /CCD images.展开更多
为了实现干旱半干旱灌区地表信息低成本、高效率的动态监测,利用HJ-CCD数据的多时相和多光谱信息,探讨了平罗县土地利用遥感分类方法。首先建立研究区内典型地物的NDVI时间序列曲线,提取反映该区物候模式的时序特征参数;然后对土壤信息...为了实现干旱半干旱灌区地表信息低成本、高效率的动态监测,利用HJ-CCD数据的多时相和多光谱信息,探讨了平罗县土地利用遥感分类方法。首先建立研究区内典型地物的NDVI时间序列曲线,提取反映该区物候模式的时序特征参数;然后对土壤信息丰富的3月份多光谱影像进行主成分变换,选取第1主成分(PC1)作为光谱特征参数,最后基于分类回归树(classification and regression tree,CART)算法进行决策树监督分类。总体分类精度达到92.26%,Kappa系数为0.91,比最大似然法分类结果精度提高了2.58%。研究表明:构建的NDVI时间序列曲线对研究区内的地类具有较强的代表性,提取的时间维和光谱维的分类参数对各地类均有很好地区分性,CART决策树算法分类结果清晰准确且精度较高。该方法为HJ小卫星在干旱半干旱区等区域的深入应用提供科学依据和实证基础。展开更多
基金Supported by National Natural Science Foundation of China(41171336)
文摘MODTRAN model was used for the atmospheric correction of one HJ-1B / CCD2 image,and the effect of atmospheric correction was evaluated from the changes of spectral characteristics of typical ground objects,the comparison with the MODIS surface reflectance product,and the effect on normalized differential vegetation index( NDVI). The results show that atmospheric correction eliminated the increase effect in visible bands and the absorption in near-infrared band. Atmospheric correction results and the MODIS surface reflectance product with high accuracy were highly consistent in the reflectance of vegetation,water and residents,and the average error of vegetation was 12.8%. According to the comparison of changing characteristics of NDVI before and after atmospheric correction,it could be found that atmospheric correction had corrected NDVI of mixed pixels and made it more reasonable. NDVI of each kind of ground objects improved,among which NDVI of vegetation increased most greatly,which can help differentiate vegetation from other ground objects. In a word,MODTRAN model has a good effect on atmospheric correction of HJ /CCD images.
文摘为了实现干旱半干旱灌区地表信息低成本、高效率的动态监测,利用HJ-CCD数据的多时相和多光谱信息,探讨了平罗县土地利用遥感分类方法。首先建立研究区内典型地物的NDVI时间序列曲线,提取反映该区物候模式的时序特征参数;然后对土壤信息丰富的3月份多光谱影像进行主成分变换,选取第1主成分(PC1)作为光谱特征参数,最后基于分类回归树(classification and regression tree,CART)算法进行决策树监督分类。总体分类精度达到92.26%,Kappa系数为0.91,比最大似然法分类结果精度提高了2.58%。研究表明:构建的NDVI时间序列曲线对研究区内的地类具有较强的代表性,提取的时间维和光谱维的分类参数对各地类均有很好地区分性,CART决策树算法分类结果清晰准确且精度较高。该方法为HJ小卫星在干旱半干旱区等区域的深入应用提供科学依据和实证基础。
