摘要
农村居民点的植被覆盖率是反映农村居民点居住环境的重要参考指标之一.为探究无人机可见光光谱分析技术应用于农村居民点居住环境调查的可行性,以案例区的无人机可见光遥感影像为数据源,分别采用植被指数阈值二分法和回归模型法对案例区的植被覆盖率进行估算.分析结果显示,植被指数阈值二分法中选择可见光波段差异植被指数(VDVI)和绿波归一化植被指数(GNVI)能够较好地区分植被区域和非植被区域,植被覆盖率估算结果为41.60%,Kappa系数和总体分类精度分别为0.9784和0.99;回归模型法中分别建立植被覆盖率与可见光波段差异植被指数(VDVI)和红绿蓝植被指数(RGBRI)的5种回归模型,其中植被覆盖率与红绿蓝植被指数(RGBRI)的三次多项式回归模型的相关系数(R2)最大,均方根误差(RMSE)最小,分别为0.9331和0.04086,反演的案例区的植被覆盖率为42.65%.因此,基于无人机可见光光谱的两种农村居民点的植被覆盖率估算方法均满足精度的要求.为避免误差因素的影响和提高估算结果的准确度,实践中,可以选择两种方法估算结果的平均值作为最后的农村居民点植被覆盖率的估算结果.
The vegetation coverage ratio(VCR)of rural residential areas is one of the important reference indexes to reflect the living environment of rural communities.In order to explore the feasibility of applying visible spectral analysis technology of UAV in the estimation of VCR in rural residential areas,the visible spectral remote sensing images of UAV in the case area was used in this study with vegetation index(VI)threshold dichotomy and regression model method respectively to estimate VCR in the case area.Analysis results showed that VI threshold dichotomy could well distinguish the vegetation areas from the non-vegetation areas with VDVI(Visible-band Difference Vegetation Index)and GNVI(Green Normalized Vegetation Index).The estimated VCR was 41.60%,and the Kappa coefficient and overall classification accuracy were 0.9784 and 0.99,respectively.In regression model method,5 regression models related to VCR,VDVI and RGBRI were set up.The correlation coefficient between vegetation coverage ratio and RGBRI's cubic polynomial regression model was the largest,and the root-mean-square errors were the smallest(0.9331 and 0.04086,respectively).VCR in the case area of inversion was 42.65%.Therefore,both methods based on the visible spectrum of UAV to estimate VCR of rural residential areas meet the requirements of accuracy.To avoid the influence of error and improve the accuracy of the estimated results,the average value of the estimated results of both methods can be selected in practice as the final estimation result.
作者
宋利利
杨安琪
柳露露
夏艺菲
SONG Lili;YANG Anqi;LIU Lulu;XIA Yifei(College of Landscape Architecture,Henan Institute of Science and Technology,Xinxiang 453003,China)
出处
《河南科技学院学报（自然科学版）》
2020年第5期65-72,共8页
Journal of Henan Institute of Science and Technology(Natural Science Edition)
基金
国家自然科学基金青年基金项目(41901237)
河南省高等学校重点科研项目(19B170004)
河南科技学院2019年大学生创新创业项目(2019CX042)。
关键词
无人机
可见光光谱
植被指数
植被覆盖率
UVA
visible spectrum
vegetation index
vegetation coverage ratio
