This paper focuses on the relationship between remotely-sensed urban site characteristics (USCs) and land surface temperature (LST). Particular emphasis is put on an extensive comparison of ...two-dimensional (2D) and three-dimensional (3D) USCs as potential indicators of the surface urban heat island (UHI) effect and as potential predictors for thermal sharpening applications. Both widely-used as well as more recently proposed metrics of the urban remote sensing literature are investigated within a single experiment. While some of these USCs have already been used earlier, others have never been analyzed before in the context of urban temperature studies. In addition to the comparison of 2D and 3D USCs, the spatio-temporal dependencies of their relation to LST are examined. To this end, the experimental setup of this work includes two study areas, 26 USCs, and 16 LST scenes covering four seasons. Use is made of a comprehensive database compiled for the cities of Berlin and Cologne, Germany. After data preparation, very high resolution (VHR) multi-spectral and height data are employed to map fine-scale urban land cover (LC). The resulting LC maps are then used in conjunction with the height information to compute 2D and 3D USCs. Subsequently, multi-temporal LST images are retrieved from Landsat Enhanced Thematic Mapper Plus (ETM+) scenes. The spatio-temporal investigation of the USC–LST connection constitutes the final stage of the workflow and is achieved in the framework of a dedicated correlation analysis. The results of this study highlight that the linkage between USCs and LST sensed at small scan angles is not stronger when 3D parameters are considered. Even though they may offer more holistic representations of the urban landscape, 3D USCs are consistently outperformed by some of the most widely-used 2D metrics. The analysis of spatial dependencies reveals that the USC–LST interplay does not only differ between, but also within the two test sites. This is due to their distinct geographies, with urban form and compactness, green spaces and street trees, and the structural composition of LC elements being some of the determining factors. The examination of temporal dependencies yielded that the association between USCs and LST is fairly stable over time but can be subject to larger inter- and intra-season variations for different reasons, including the season of acquisition, vegetation phenology, and meteorological conditions. Since previous research was based on the analysis of a single study area, a limited number of (mainly 2D) USCs, and/or only a few LST scenes acquired in specific seasons, it is concluded that the findings of this study provide researchers and practitioners with a more complete picture of the USC–LST relationship.
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•Spatio-temporal analysis of the statistical relationship between 2D/3D USCs and LST•Detailed inspection of 2 study areas, 26 USCs, and 16 LST scenes covering 4 seasons•3D USCs are consistently outperformed by some of the most widely-used 2D indicators.•Correlations are spatially dependent due to the distinct geographies of the cities.•Larger inter-/intra-season variations are mainly driven by environmental conditions.
Low cost UAV systems are a flexible and mobile platform for very detailed spatial high-resolution point cloud and surface height mapping projects. This study investigates the potential of the DJI ...Phantom 4 Pro 3D point clouds and derived crown surface height information in combination with RGB spectral information for mapping of deciduous tree species in the Hainich national park area. RGB image data was captured in August, early October and November 2018 to create a multi seasonal spectral dataset for a 100 ha test area. The flight campaigns were controlled from the Hainich flux tower platform in 40 m height owned and operated by University of Göttingen in the central part of the park area. Absolut georeferencing accuracy of the datasets was improved using 7 DGPS measured control points within the stand structure on small forest clearings. Image files and ground control points were processed to a dense point cloud model with 2.6 billion points (approximately 200k points per tree crown object) using the Agisoft Metashape cluster processing environment. Additionally, a digital surface model and a true ortho image mosaic with 3 cm spatial resolution was generated. For the differentiation of deciduous tree species, a reference data set with coordinates for the tree species Fagus sylvatica (beech), Fraxinus excelsior (ash), Acer pseudoplatanus (sycamore maple), Carpinus betulus (hornbeam) and dead trees and early defoliated trees was defined. The study site is however dominated by Fagus sylvatica and Fraxinus excelsior. We studied two different groups of features: tree crown surface height variability parameters using point cloud densities, point cloud height variance, local standard deviation of gaussian curvature, standard deviation of local point cloud roughness and multi temporal normalised spectral features using multi seasonal uncalibrated UAV RGB data. Analysis of feature separability showed that very high-resolution point cloud surface curvature properties with small neighbourhood radii can differentiate some tree species types but we also found multitemporal spectral ratios based on RGB data to be very successful in differentiating the main tree species.Results of this work show that super fine very dense point cloud models and derived roughness measures of mixed forest stand surfaces hold valuable information for deciduous species discrimination and will likely also be very useful for morphological analysis of tree crown types.
OTF (Off The Shelf) quadro copter systems provide a cost effective (below 2000 Euro), flexible and mobile platform for high resolution point cloud mapping. Various studies showed the full potential ...of these small and flexible platforms. Especially in very tight and complex 3D environments the automatic obstacle avoidance, low copter weight, long flight times and precise maneuvering are important advantages of these small OTS systems in comparison with larger octocopter systems. This study examines the potential of the DJI Phantom 4 pro series and the Phantom 3A series for within-stand and forest tree crown 3D point cloud mapping using both within stand oblique imaging in different altitude levels and data captured from a nadir perspective. On a test site in Brandenburg/Germany a beach crown was selected and measured with 3 different altitude levels in Point Of Interest (POI) mode with oblique data capturing and deriving one nadir mosaic created with 85/85 % overlap using Drone Deploy automatic mapping software. Three different flight campaigns were performed, one in September 2016 (leaf-on), one in March 2017 (leaf-off) and one in May 2017 (leaf-on) to derive point clouds from different crown structure and phenological situations – covering the leaf-on and leafoff status of the tree crown. After height correction, the point clouds where used with GPS geo referencing to calculate voxel based densities on 50 × 10 × 10 cm voxel definitions using a topological network of chessboard image objects in 0,5 m height steps in an object based image processing environment. Comparison between leaf-off and leaf-on status was done on volume pixel definitions comparing the attributed point densities per volume and plotting the resulting values as a function of distance to the crown center. In the leaf-off status SFM (structure from motion) algorithms clearly identified the central stem and also secondary branch systems. While the penetration into the crown structure is limited in the leaf-on status (the point cloud is a mainly a description of the interpolated crown surface) – the visibility of the internal crown structure in leaf-off status allows to map also the internal tree structure up to and stopping at the secondary branch level system. When combined the leaf-on and leaf-off point clouds generate a comprehensive tree crown structure description that allows a low cost and detailed 3D crown structure mapping and potentially precise biomass mapping and/or internal structural differentiation of deciduous tree species types. Compared to TLS (Terrestrial Laser Scanning) based measurements the costs are neglectable and in the range of 1500–2500 €. This suggests the approach for low cost but fine scale in-situ applications and/or projects where TLS measurements cannot be derived and for less dense forest stands where POI flights can be performed. This study used the in-copter GPS measurements for geo referencing. Better absolute geo referencing results will be obtained with DGPS reference points. The study however clearly demonstrates the potential of OTS very low cost copter systems and the image attributed GPS measurements of the copter for the automatic calculation of complex 3D point clouds in a multi temporal tree crown mapping context.
The energy gap of correlated Hubbard clusters is well studied for one‐dimensional systems using analytical methods and density‐matrix‐renormalization‐group (DMRG) simulations. Beyond 1D, however, ...exact results are available only for small systems by quantum Monte Carlo. For this reason and, due to the problems of DMRG in simulating 2D and 3D systems, alternative methods such as Green functions combined with many‐body approximations (GFMBA), that do not have this restriction, are highly important. However, it has remained open whether the approximate character of GFMBA simulations prevents the computation of the Hubbard gap. Here we present new GFMBA results that demonstrate that GFMBA simulations are capable of producing reliable data for the gap which agrees well with the DMRG benchmarks in 1D. An interesting observation is that the accuracy of the gap can be significantly increased when the simulations give up certain symmetry restriction of the exact system, such as spin symmetry and spatial homogeneity. This is seen as manifestation and generalization of the “symmetry dilemma” introduced by Löwdin for Hartree–Fock wave function calculations.
Remote sensing of penguins gives a unique opportunity to observe ecosystem changes in the Antarctic and the Southern Ocean at a continent-wide scale. The extent of guano is the best proxy to the size ...of penguin populations but frequent cloud cover limits the number of available images. This study focuses on the correlation between guano coverage visible in aerial and satellite images and breeding pair numbers in the course of the breeding seasons 2016/17 and 2017/18 in a colony of Pygocelid penguins on Ardley Island (South Shetland Islands, Antarctica). Multitemporal UAV (Unmanned Aerial Vehicle) orthomosaics and high-resolution satellite images were collected of Ardley Island as well as data on breeding phenology, weather conditions and snow coverage. “Fresh” guano stains were classified using different methods of Geographical Object-based Image Analysis (GEOBIA) and differentiated from weathered guano stains. Analysis of this data shows that guano stains in an Antarctic Pygoscelid penguin colony undergo significant intraseasonal changes in extent, texture and spectral signature. Hence, the timing of image acquisition and the advance of snow melt during Antarctic spring matter when determining penguin populations and should be considered during the analysis. Our results show changes of up to 25 % of the total guano covered surface due to individual weather events and changes up to 80 % in the time between the peak of egg laying and the occurrence of the first crèche.
This paper presents a method for the classification of satellite images into multiple predefined land cover classes. The proposed approach results in a fully automatic segmentation and classification ...of each pixel, using a small amount of training data. Therefore, semantic segmentation techniques are used, which are already successful applied to other computer vision tasks like facade recognition. We explain some simple modifications made to the method for the adaption of remote sensing data. Besides local features, the proposed method also includes contextual properties of multiple classes. Our method is flexible and can be extended for any amount of channels and combinations of those. Furthermore, it is possible to adapt the approach to several scenarios, different image scales, or other earth observation applications, using spatially resolved data. However, the focus of the current work is on high resolution satellite images of urban areas. Experiments on a QuickBird-image and LiDAR data of the city of Rostock show the flexibility of the method. A significant better accuracy can be achieved using contextual features.
The arctic regions are highly vulnerable to climate change. Climate models predict an increase in global mean temperatures for the upcoming century. The arctic environment is subject to significant ...changes of the land surface. Especially the changes of vegetation pattern and the phenological cycle in the taiga-tundra transition area are of high importance in climate change research. This study focuses on time series and trend analysis of land surface temperature, albedo, snow water equivalent, and normalized difference vegetation index information in the time period of 1982-2005 for northern Siberia. The findings show strong dependencies between these parameters and their inter-annual dynamics, which indicate changes in vegetation growing period. We found a strong negative correlation between land surface temperature and albedo conditions for the beginning (60-90%) of the growing season for selected hot spot trend regions in northern Siberia.
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