Aguilar Manuel A, Jiménez-Lao Rafael, Nemmaoui Abderrahim, Aguilar Fernando J
Department of Engineering, Research Centre CIAIMBITAL, University of Almeria, Carretera de Sacramento s/n, La Cañada de San Urbano, 04120 Almeria, Spain.
Sensors (Basel). 2020 Dec 18;20(24):7234. doi: 10.3390/s20247234.
Accurate elevation data, which can be extracted from very high-resolution (VHR) satellite images, are vital for many engineering and land planning applications. In this way, the main goal of this work is to evaluate the capabilities of VHR Deimos-2 panchromatic stereo pairs to obtain digital surface models (DSM) over different land covers (bare soil, urban and agricultural greenhouse areas). As a step prior to extracting the DSM, different orientation models based on refined rational polynomial coefficients (RPC) and a variable number of very accurate ground control points (GCPs) were tested. The best sensor orientation model for Deimos-2 L1B satellite images was the RPC model refined by a first-order polynomial adjustment (RPC1) supported on 12 accurate and evenly spatially distributed GCPs. Regarding the Deimos-2 based DSM, its completeness and vertical accuracy were compared with those obtained from a WorldView-2 panchromatic stereo pair by using exactly the same methodology and semiglobal matching (SGM) algorithm. The Deimos-2 showed worse completeness values (about 6% worse) and vertical accuracy results (RMSE 42.4% worse) than those computed from WorldView-2 imagery over the three land covers tested, although only urban areas yielded statistically significant differences ( < 0.05).
可从超高分辨率(VHR)卫星图像中提取的精确高程数据,对许多工程和土地规划应用至关重要。通过这种方式,这项工作的主要目标是评估VHR德米斯-2全色立体像对在不同土地覆盖类型(裸土、城市和农业温室区域)上获取数字表面模型(DSM)的能力。作为提取DSM之前的一个步骤,测试了基于精化有理多项式系数(RPC)和不同数量非常精确的地面控制点(GCP)的不同定向模型。对于德米斯-2 L1B卫星图像,最佳的传感器定向模型是由12个精确且空间分布均匀的GCP支持的一阶多项式调整(RPC1)精化的RPC模型。关于基于德米斯-2的DSM,通过使用完全相同的方法和半全局匹配(SGM)算法,将其完整性和垂直精度与从WorldView-2全色立体像对获得的结果进行了比较。在测试的三种土地覆盖类型上,德米斯-2的完整性值(约低6%)和垂直精度结果(均方根误差低42.4%)比从WorldView-2图像计算得出的结果更差,不过只有城市区域产生了统计学上的显著差异(<0.05)。