资源简介

摘要： 反演模型对土壤水分评估结果有重要影响，基于此，以黄土沟壑区城市森林表层土壤为研究对象，以3期Landsat影像和实地土壤水分传感器测定数据为数据源，分别通过像元在二维空间（LST-NDVI与STR-NDVI，LST为地表温度，NDVI为归一化植被指数，STR为短波红外转换反射系数）中的散点图及其拟合的干燥边界与湿润边界，获取TOTRAM（热学—光学不规则梯形模型）和OPTRAM（光学不规则梯形模型）的参数，然后在像素水平上（30 m×30 m）反演出延安城市森林表层土壤水分（W），验证两模型的精度，并比较两模型估算结果的差异及线性边界与非线性边界对反演结果的影响。结果发现：①除OPTRAM 模型在Landsat 7和Landsat 8上干湿边界呈现非线性外，像素在LST-NDVI空间和STR—NDVI空间中的干湿边界均呈线性，且包络成不规则梯形形状;②与实地测定数据相比，TOTRAM与OPTRAM两模型的平均误差（ME）分别为0.009和0.0455，表明两模型估算结果均偏高，但OPTRAM模型的均方根误差（RMSE）较TOTRAM模型更接近0。OPTRAM模型估算的W值均匀地分布在1∶1参考线两侧，且位于参考线上的点数多于TOTRAM模型，表明OPTRAM准确度高于TOTRAM模型，且非线性边界的反演精度高于线性边界;③与TOTRAM模型相比，OPTRAM模型估算出的W空间分异规律与土地利用/覆被类型具有较高的相关性，且OPTRAM模型对植被覆盖度极低的区域敏感。因此，在后续研究中，应在OPTRAM模型中探讨干湿边界复杂性与模型准确性改善之间的关系，同时考虑周围环境、降雨量、森林干扰和NDVI饱和等因素对两模型估算准确性的影响。 关键词： 归一化植被指数;  土壤湿度;  卫星遥感;  地表温度;  地表反射率     Abstract: It is crucial for soil moisture assessment to know the prediction accuracy of inversion model. Urban forest surface soil in a gully-loess region (Yan’an), was taken as the research object, and the three scenes of Landsat satellite remotely sensed imagery in different periods and soil moisture sensor in situ measurement data were used as the data source. The parameters of TOTRAM (Thermal-Optical TRApezoid Model) and OPTRAM (OPtical TRApezoid Model) were obtained through the scatter diagram of pixels in two-dimensional spaces (LST-NDVI and STR-NDVI, LSTis land surface temperature,NDVIis normalized vegetation index, and STR is shortwave infrared conversion reflection coefficient) and their fitting dry edge and wet edge, respectively. Then, the w values (soil moisture in percentage) of Yan’an urban forest were retrieved at the pixel level (30 m by 30 m), the accuracy of the two models was verified, the differences between the estimated results of the two models, and the influence of linear and nonlinear edge on the inversion results were compared. The results indicate that: (1) Except that the dry edge and wet edge of OPTRAM models on Landsat 7 and Landsat 8 were non-linear, the other dry and wet edges of pixels in LST-NDVI space and STR-NDVI space are almost linear and enveloped into a trapezoid shape. (2) Compared with the field measurement data, the mean error (ME) of TOTRAM and OPTRAM were 0.009 and 0.045 5, respectively, which indicating that the estimation results of both models were relatively high, but the root mean square error (RMSE) of the OPTRAM model was closer to zero than the TOTRAM model. The value of w estimated by the OPTRAM model is evenly distributed on both sides of the 1∶1 reference line, and the number of points on the reference line is more than that of the TOTRAM model in scatterplots, indicating that the accuracy of OPTRAM is higher than that of the TOTRAM model, moreover, the inversion precision of nonlinear edge is higher than that of linear edge. Thus, in further research, the relationship between the complexity of the dry edge and wet edge and the model’s accuracy improvement should be discussed in the OPTRAM model, and the influences of surrounding environment, rainfall, forest disturbance and NDVI saturation on the estimation accuracy of the two models need to be considered.

相关资源

1. 水质遥感监测的关键要素叶绿素a的反演算法研究进展
2. 基于无人机遥感技术的森林参数获取研究进展
3. 基于无线传感器网络的森林生态系统观测试验平台构建
4. 基于无人机激光雷达的森林冠层高度分析
5. 多源时序国产卫星影像的森林火灾动态监测
6. 基于无人机遥感技术的台风灾害倒伏绿化树木检测

下载说明

·如果您发现该资源不能下载，请通知管理员.gissky@gmail.com

·为确保下载的资源能正常使用，请使用[WinRAR v3.8]或以上版本解压本站资源,缺省解压密码www.gissky.net ，如果是压缩文件为分卷多文件，请依次下载每一个文件，并按照顺序命名为1.rar,2.rar,3.rar...，然后鼠标右击1.rar解压.

·为了保证您快速的下载速度，我们推荐您使用[网际快车]等专业工具下载.

·站内提供的资源纯属学习交流之用,如侵犯您的版权请与我们联系.