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Simulating the directional, spectral and textural properties of a large-scale scene at high resolution using a MODIS BRDF product

机译：使用MODIS BRDF产品模拟高分辨率大规模场景的方向，光谱和纹理特性

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Many remote sensing applications rely on simulated scenes to perform complex interaction and sensitivity studies that are not possible with real-world scenes. These applications include the development and validation of new and existing algorithms, understanding of the sensor's performance prior to launch, and trade studies to determine ideal sensor configurations. The accuracy of these applications is dependent on the realism of the modeled scenes and sensors. The Digital Image and Remote Sensing Image Generation (DIRSIG) tool has been used extensively to model the complex spectral and spatial texture variation expected in large city-scale scenes and natural biomes. In the past, material properties that were used to represent targets in the simulated scenes were often assumed to be Lambertian in the absence of hand-measured directional data. However, this assumption presents a limitation for new algorithms that need to recognize the anisotropic behavior of targets. We have developed a new method to model and simulate large-scale high-resolution terrestrial scenes by combining bi-directional reflectance distribution function (BRDF) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data, high spatial resolution data, and hyperspectral data. The high spatial resolution data is used to separate materials and add textural variations to the scene, and the directional hemispherical reflectance from the hyperspectral data is used to adjust the magnitude of the MODIS BRDF. In this method, the shape of the BRDF is preserved since it changes very slowly, but its magnitude is varied based on the high resolution texture and hyperspectral data. In addition to the MODIS derived BRDF, target/class specific BRDF values or functions can also be applied to features of specific interest. The purpose of this paper is to discuss the techniques and the methodology used to model a forest region at a high resolution. The simulated scenes using this method for varying view angles show the expected variations in the reflectance due to the BRDF effects of the Harvard forest. The effectiveness of this technique to simulate real sensor data is evaluated by comparing the simulated data with the Landsat 8 Operational Land Image (OLI) data over the Harvard forest. Regions of interest were selected from the simulated and the real data for different targets and their Top-of-Atmospheric (TOA) radiance were compared. After adjusting for scaling correction due to the difference in atmospheric conditions between the simulated and the real data, the TOA radiance is found to agree within 5 ％ in the NIR band and 10 ％ in the visible bands for forest targets under similar illumination conditions. The technique presented in this paper can be extended for other biomes (e.g. desert regions and agricultural regions) by using the appropriate geographic regions. Since the entire scene is constructed in a simulated environment, parameters such as BRDF or its effects can be analyzed for general or target specific algorithm improvements. Also, the modeling and simulation techniques can be used as a baseline for the development and comparison of new sensor designs and to investigate the operational and environmental factors that affects the sensor constellations such as Sentinel and Landsat missions.
机译：许多遥感应用程序依赖于模拟场景，以执行现实世界场景不可能的复杂交互和敏感性研究。这些应用包括新的和现有算法的开发和验证，在发布之前了解传感器的性能，以及贸易研究以确定理想的传感器配置。这些应用程序的准确性取决于所建模场景和传感器的现实主义。数字图像和遥感图像生成（DIRSIG）工具已广泛用于模拟大城市尺度场景和天然生物群中预期的复杂光谱和空间纹理变化。过去，用于表示模拟场景中的目标的材料特性通常被认为是兰伯语在没有手动测量的方向数据。然而，这种假设呈现了需要识别目标各向异性行为的新算法的限制。我们开发了一种通过将双向反射率分布函数（BRDF）产品组合起作用的模拟和模拟大规模高分辨率地面场景的新方法，从中等分辨率成像分光镜（MODIS）数据，高空间分辨率数据和高光谱数据。高空间分辨率数据用于分离材料并向场景添加纹理变化，并且来自高光谱数据的定向半球形反射率用于调整MODIS BRDF的大小。在这种方法中，保留了BRDF的形状，因为它变化得非常缓慢，但是基于高分辨率纹理和高光谱数据来改变其幅度。除了MODIS派生BRDF之外，目标/类特定的BRDF值或功能也可以应用于特定兴趣的特征。本文的目的是讨论以高分辨率模拟森林区域的技术和方法。使用该方法进行不同视角的模拟场景显示了由于哈佛林的BRDF效果导致的反射率的预期变化。通过将模拟数据与哈佛林上的Landsat 8运行陆地图像（OLI）数据进行比较来评估该技术模拟实际传感器数据的有效性。从模拟和实际数据中选择了感兴趣的区域，并比较了它们的顶部大气压（TOA）光线。在调整缩放校正后由于模拟和实际数据之间的大气条件差异，发现TOA辐射在类似的照明条件下，在NIR带中的5％中达到5％，在类似的照明条件下的森林靶标中的可见带中的10％。本文呈现的技术可以通过使用适当的地理区域延长其他生物群（例如沙漠地区和农业区域）。由于整个场景在模拟环境中构建，因此可以针对一般或目标特定算法改进分析诸如BRDF或其效果的参数。此外，建模和仿真技术可以用作新传感器设计的开发和比较的基线，并调查影响传感器星座的操作和环境因素，例如哨兵和山地驻地特派团。

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