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Temperature monitoring along the Rhine River based on airborne thermal infrared remote sensing: qualitative results compared to satellite data and validation with in situ measurements

机译:基于机载热红外遥感的莱茵河沿岸温度监测:与卫星数据相比的定性结果,并通过现场测量进行验证

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Water temperature is an important parameter of water quality and influences other physical and chemical parameters. It also directly influences the survival and growth of animal and plant species in river ecosystems. In situ measurements do not allow for a total spatial coverage of water bodies and rivers that is necessary for monitoring and research at the Federal Institute of Hydrology (BfG), Germany. Hence, the ability of different remote sensing products to identify and investigate water inflows and water temperatures in Federal waterways is evaluated within the research project 'Remote sensing of water surface temperature'. The research area for a case study is the Upper and Middle Rhine River from the barrage in Iffezheim to Koblenz. Satellite products (e. g. Landsat and ASTER imagery) can only be used for rivers at least twice as wide as the spatial resolution of the satellite images. They can help to identify different water bodies only at tributaries with larger inflow volume (Main and Mosel) or larger temperature differences between the inflow (e. g. from power plants working with high capacity) and the river water. To identify and investigate also smaller water inflows and temperature differences, thermal data with better ground and thermal resolution is required. An aerial survey of the research area was conducted in late October 2013. Data of the surface was acquired with two camera systems, a digital camera with R, G, B, and Near-IR channels, and a thermal imaging camera measuring the brightness temperature in the 8-12 μm wavelength region (TIR). The resolution of the TIR camera allowed for a ground resolution of 4 m, covering the whole width of the main stream and larger branches. The RGB and NIR data allowed to eliminate land surface temperatures from the analysis and to identify clouds and shadows present during the data acquisition. By degrading the spatial resolution and adding sensor noise, artificial Landsat ETM+ and TIRS datasets were created to evaluate whether the methods applied to the aerial survey data are also applicable for satellite datasets. In situ measurements were obtained from water quality measurement stations and specifically deployed temperature loggers. Two alternative methods to correct for atmospheric influences were evaluated: calibration based on in situ water temperature measurements and atmospheric correction based on atmospheric parameters modelled with MODTRAN®5. Both methods rely on input data, the former on in situ measurements of the water temperature, the latter on data from climate stations. The results are validated by the dataset of independent in situ measurements. The remaining difference of the corrected aerial survey to the in situ measurements could be reduced to 0.0±0.2°C for the calibration and 0.1±0.3°C for the atmospheric correction. The variance of the atmospheric correction proved to be larger than of the in situ calibration method, but still smaller than the variance of atmospherically corrected, real LANDSAT ETM+ data. Inflows with differing water temperatures could be identified successfully with the change point analysis method even for smaller dischargers and the mixing processes of water bodies with different temperatures could be traced into great detail. With decreasing spatial resolution and increasing sensor noise, the ability to detect inflows remained the same, but at the cost of a higher number of 'false positive' change points.
机译:水温是水质的重要参数,会影响其他物理和化学参数。它还直接影响河流生态系统中动植物物种的生存和生长。实地测量不允许对水体和河流进行总的空间覆盖,这是德国联邦水文学研究所(BfG)进行监测和研究所必需的。因此,在“水面温度的遥感”研究项目中评估了不同的遥感产品识别和调查联邦水道中的水流入量和水温的能力。案例研究的研究区域是从伊费兹海姆大坝到科布伦茨的莱茵河中上游。卫星产品(例如Landsat和ASTER影像)只能用于宽度至少是卫星影像空间分辨率两倍的河流。它们仅在流入量较大的支流(主水和Mosel)或流入水量(例如,高容量发电厂的出水量)与河水之间的温差较大时才有助于识别不同的水体。为了识别和研究较小的进水量和温差,需要具有更好地面和热分辨率的热数据。 2013年10月下旬对研究区域进行了一次航空勘测。表面数据是通过两个摄像头系统获取的,其中一个是具有R,G,B和近红外通道的数码相机,另一个是测量亮度温度的热像仪。在8-12μm波长范围(TIR)中。 TIR摄像机的分辨率可实现4 m的地面分辨率,覆盖主流和较大分支的整个宽度。 RGB和NIR数据可以消除分析中的地表温度,并识别数据采集过程中存在的云层和阴影。通过降低空间分辨率并增加传感器噪声,创建了人造Landsat ETM +和TIRS数据集,以评估应用于航空测量数据的方法是否也适用于卫星数据集。从水质测量站和专门配置的温度记录仪获得现场测量结果。评估了两种校正大气影响的替代方法:基于原位水温测量的校准和基于采用MODTRAN®5建模的大气参数的大气校正。两种方法都依赖于输入数据,前者依赖于水温的现场测量,后者依赖于来自气候站的数据。结果由独立的原位测量数据集验证。校正后的航空测量与原位测量的剩余差值可以减少到0.0±0.2°C(用于校准)和0.1±0.3°C(用于大气校正)。事实证明,大气校正的方差大于现场校正方法的方差,但仍小于大气校正的真实LANDSAT ETM +数据的方差。即使对于较小的排放口,也可以使用变化点分析方法成功地识别出具有不同水温的流入,并且可以详细追踪具有不同温度的水体的混合过程。随着空间分辨率的降低和传感器噪声的增加,检测到流量的能力保持不变,但是代价是更多的“误报”变化点。

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