06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
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Item Open Access Crop water productivity mapping and benchmarking using remote sensing and Google Earth Engine cloud computing(2022) Ghorbanpour, Ali Karbalaye; Kisekka, Isaya; Afshar, Abbas; Hessels, Tim; Taraghi, Mahdi; Hessari, Behzad; Tourian, Mohammad J.; Duan, ZhengScarce water resources present a major hindrance to ensuring food security. Crop water productivity (WP), embraced as one of the Sustainable Development Goals (SDGs), is playing an integral role in the performance-based evaluation of agricultural systems and securing sustainable food production. This study aims at developing a cloud-based model within the Google Earth Engine (GEE) based on Landsat -7 and -8 satellite imagery to facilitate WP mapping at regional scales (30-m resolution) and analyzing the state of the water use efficiency and productivity of the agricultural sector as a means of benchmarking its WP and defining local gaps and targets at spatiotemporal scales. The model was tested in three major agricultural districts in the Lake Urmia Basin (LUB) with respect to five crop types, including irrigated wheat, rainfed wheat, apples, grapes, alfalfa, and sugar beets as the major grown crops. The actual evapotranspiration (ET) was estimated using geeSEBAL based on the Surface Energy Balance Algorithm for Land (SEBAL) methodology, while for crop yield estimations Monteith’s Light Use Efficiency model (LUE) was employed. The results indicate that the WP in the LUB is below its optimum targets, revealing that there is a significant degree of work necessary to ameliorate the WP in the LUB. The WP varies between 0.49-0.55 (kg/m3) for irrigated wheat, 0.27-0.34 for rainfed wheat, 1.7-2.2 for apples, 1.2-1.7 for grapes, 5.5-6.2 for sugar beets, and 0.67-1.08 for alfalfa, which could be potentially increased up to 80%, 150%, 76%, 83%, 55%, and 48%, respectively. The spatial variation of the WP and crop yield makes it feasible to detect the areas with the best and poorest on-farm practices, thereby facilitating the better targeting of resources to bridge the WP gap through water management practices. This study provides important insights into the status and potential of WP with possible worldwide applications at both farm and government levels for policymakers, practitioners, and growers to adopt effective policy guidelines and improve on-farm practices.Item Open Access Analysis of the technical biases of meteor video cameras used in the CILBO system(2017) Albin, Thomas; Koschny, Detlef; Molau, Sirko; Srama, Ralf; Poppe, BjörnIn this paper, we analyse the technical biases of two intensified video cameras, ICC7 and ICC9, of the double-station meteor camera system CILBO (Canary Island Long-Baseline Observatory). This is done to thoroughly understand the effects of the camera systems on the scientific data analysis. We expect a number of errors or biases that come from the system: instrumental errors, algorithmic errors and statistical errors. We analyse different observational properties, in particular the detected meteor magnitudes, apparent velocities, estimated goodness-of-fit of the astrometric measurements with respect to a great circle and the distortion of the camera. We find that, due to a loss of sensitivity towards the edges, the cameras detect only about 55 % of the meteors it could detect if it had a constant sensitivity. This detection efficiency is a function of the apparent meteor velocity. We analyse the optical distortion of the system and the "goodness-of-fit" of individual meteor position measurements relative to a fitted great circle. The astrometric error is dominated by uncertainties in the measurement of the meteor attributed to blooming, distortion of the meteor image and the development of a wake for some meteors. The distortion of the video images can be neglected. We compare the results of the two identical camera systems and find systematic differences. For example, the peak magnitude distribution for ICC9 is shifted by about 0.2–0.4 mag towards fainter magnitudes. This can be explained by the different pointing directions of the cameras. Since both cameras monitor the same volume in the atmosphere roughly between the two islands of Tenerife and La Palma, one camera (ICC7) points towards the west, the other one (ICC9) to the east. In particular, in the morning hours the apex source is close to the field-of-view of ICC9. Thus, these meteors appear slower, increasing the dwell time on a pixel. This is favourable for the detection of a meteor of a given magnitude.Item Open Access Forecasting next year's global land water storage using GRACE data(2024) Li, Fupeng; Kusche, Jürgen; Sneeuw, Nico; Siebert, Stefan; Gerdener, Helena; Wang, Zhengtao; Chao, Nengfang; Chen, Gang; Tian, KunjunExisting approaches for predicting total water storage (TWS) rely on land surface or hydrological models using meteorological forcing data. Yet, such models are more adept at predicting specific water compartments, such as soil moisture, rather than others, which consequently impedes accurately forecasting of TWS. Here we show that machine learning can be used to uncover relations between nonseasonal terms of Gravity Recovery and Climate Experiment (GRACE) derived total water storage and the preceding hydrometeorological drivers, and these relations can subsequently be used to predict water storage up to 12 months ahead, and even exceptional droughts on the basis of near real‐time observational forcing data. Validation by actual GRACE observations suggests that the method developed here has the capability to forecast trends in global land water storage for the following year. If applied in early warning systems, these predictions would better inform decision‐makers to improve current drought and water resource management.Item Open Access Low temperature oxidation of cyclohexane: uncertainty of important thermo-chemical properties(2018) Abbasi, Mehdi; Slavinskaya, Nadezda; Riedel, UweThe study of the standard formation enthalpy, entropy, and heat capacity for key species relevant to the low-temperature combustion of cyclohexane has been performed by applying the group additivity method of Benson. The properties of 18 Benson groups (8 of them for the first time), and 10 ring correction factors for cyclic species were estimated through different empirical and semi-empirical methods. The method validation proceeded through comparison of predicted values for certain number of newly estimated groups and available literature data derived from quantum chemistry estimations. Further validations of the estimated properties of groups have been provided by comparing estimated properties of test species with data in literature and kinetic databases. Also the standard deviation between prediction and reported values has been evaluated for each validation case. A similar approach has been applied for validation of the estimated ring correction groups. For selected well-studied cyclic molecules the predicted values and the literature data have been compared with each other, and the standard deviations have been also reported. The evaluated properties of the cyclohexane relevant species were also compared with similar ones available in other kinetic models and in databases. At the end the estimated properties have been presented in a tabulated form of NASA polynomial coefficients with extrapolation up to 3500 K.