地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (2): 246-253.doi: 10.12082/dqxxkx.2018.170360
徐凯健1,2(), 田庆久1,*(
), 杨闫君1,2, 徐念旭1,2
收稿日期:
2017-08-03
修回日期:
2017-10-10
出版日期:
2018-03-02
发布日期:
2018-03-02
作者简介:
作者简介:徐凯健(1991-),男,博士生,研究方向为多尺度环境遥感应用。E-mail:
基金资助:
XU Kaijian1,2(), TIAN Qingjiu1,*(
), YANG Yanjun1,2, XU Nianxu1,2
Received:
2017-08-03
Revised:
2017-10-10
Online:
2018-03-02
Published:
2018-03-02
Supported by:
摘要:
不同空间分辨率遥感影像对区域土地覆被类型识别精度的影响是目前土地资源遥感研究中的热点议题。本文基于准同步的卫星传感器影像,以福建省长汀县河田盆地为研究区,结合野外调查的实验样本,依次采用最大似然法(MLC)、支持向量机(SVM)和人工神经网络(ANN)3种分类器,分析土地覆被分类结果在中高空间尺度序列(1~50 m)下的变化响应特征。结果表明:不同空间尺度下的地物分类结果存在显著差异(P<0.05),其中总分类精度和Kappa系数均随影像分辨率的降低而先升高后降低,并于4 m分辨率处达到峰值,该结果与各类地物光谱反射率的空间尺度变化特征密切相关;而不同分类器对各空间尺度影像分类结果的影响程度差异较大(P<0.05),其中SVM的分类精度最优,MLC次之,ANN的结果较差。此外,伴随影像空间分辨率的降低,不同土地覆被类型面积提取结果的变化规律不同,导致同类地物在不同空间尺度下的提取结果出现较大差异,表明在使用多源分辨率遥感数据进行土地监测等相关研究时,其伴随的结果误差不容忽视。
徐凯健, 田庆久, 杨闫君, 徐念旭. 遥感土地覆被分类的空间尺度响应研究[J]. 地球信息科学学报, 2018, 20(2): 246-253.DOI:10.12082/dqxxkx.2018.170360
XU Kaijian,TIAN Qingjiu,YANG Yanjun,XU Nianxu. Response of Spatial Scale for Land Cover Classification of Remote Sensing[J]. Journal of Geo-information Science, 2018, 20(2): 246-253.DOI:10.12082/dqxxkx.2018.170360
表1
研究选用遥感影像信息
传感器类型 | 波段名称 | 波长信息/μm | 空间分辨率/m | 成像日期 |
---|---|---|---|---|
GF-2 PMS1 | 蓝/绿 | 0.45~0.52/0.52~0.59 | 1/4 | 2015-08-27 2015-08-27 |
红/近红外 | 0.63~0.69/0.77~0.89 | 1/4 | ||
GF-1 PMS2 | 蓝/绿 | 0.45~0.52/0.52~0.59 | 2/8 | 2015-09-17 2015-09-17 |
红/近红外 | 0.63~0.69/0.77~0.89 | 2/8 | ||
GF-1 WFV4 | 蓝/绿 | 0.45~0.52/0.52~0.59 | 16 | 2015-08-03 2015-08-03 |
红/近红外 | 0.63~0.69/0.77~0.89 | 16 | ||
Landsat-8 OLI | 蓝/绿 | 0.45~0.52/0.53~0.60 | 30 | 2015-09-18 2015-09-18 |
红/近红外 | 0.63~0.68/0.85~0.89 | 30 | ||
GF-4 PMS | 蓝/绿 | 0.45~0.52/0.52~0.60 | 50 | 2016-08-01 2016-08-01 |
红/近红外 | 0.63~0.69/0.76~0.90 | 50 |
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