Many studies have been conducted to create building information models (BIMs) or city information models (CIMs) as the digital infrastructure to support various smart city programs. However, ...automatic generation of such models for high-density (HD) urban areas remains a challenge owing to (a) complex topographic conditions and noisy data irrelevant to the buildings, and (b) exponentially growing computational complexity when the task is reconstructing hundreds of buildings at an urban scale. This paper develops a method - multi-Source recTification of gEometric Primitives (mSTEP) - for automatic reconstruction of BIMs in HD urban areas. By retrieving building base, height, and footprint geodata from topographic maps, level of detail 1 (LoD1) BIMs representing buildings with flat roof configuration were first constructed. Geometric primitives were then detected from LiDAR point clouds and rectified using architectural knowledge about building geometries (e.g. a rooftop object would normally be in parallel with the outer edge of the roof). Finally, the rectified primitives were used to refine the LoD1 BIMs to LoD2, which show detailed geometric features of roofs and rooftop objects. A total of 1361 buildings located in a four square kilometer area of Hong Kong Island were selected as the subjects for this study. The evaluation results show that mSTEP is an efficient BIM reconstruction method that can significantly improve the level of automation and decrease the computation time. mSTEP is also well applicable to point clouds of various densities. The research is thus of profound significance; other cities and districts around the world can easily adopt mSTEP to reconstruct their own BIMs/CIMs to support their smart city programs.
•A BIM reconstruction method for high-density urban areas was proposed.•The method takes topographic map, LiDAR data, architectural conventions as inputs.•The outputs of the method are BIMs with detailed rooftop structures.•The method was tested on 1361 buildings in a 4 km2 area of Hong Kong Island.•Benefits of augmenting multi-source data with architectural knowledge for BIM reconstruction were proved.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
T The reed communities along lakeshores are important for preventing shore erosion and enhancing biological production by phytoplankton and benthic invertebrates. However, if reed communities are ...located in inundated areas when the water level rises, they can dam up waste that would otherwise flow downstream. Additionally, unless the reeds are regularly mown and the cut vegetation is removed, the dead reeds can be carried downstream. In Lake Teganuma in Chiba Prefecture, the dead material washed out of the reed beds can stop the operation of the drainage pump station, and it can cause fishery damage if carried downstream into the Tone River. In this study, we used topographic maps and aerial photographs to clarify the formation and mechanisms of reed community development at the mouth of the Ohori River, the inflow river of Teganuma, and we confirmed their present condition through field surveys. The aerial photographs and old topographic maps showed that the field survey sites were located within water bodies from 1947 to 1955 and that the reed colonies were not as dense as they are today. The results of this study indicate that, since the 1960s, the reed colonies at the mouth of the Ohori River have been artificially altered from their natural state to their present form.
Variable rate poultry litter (PL) application can potentially increase cotton yield and reduce environmental degradation risks associated with excess applications. The objective of this study was to ...determine whether applying PL in an inherently variable cotton field as variable-rate based on soil organic matter (SOM, VRo) or elevation (VRe) maps leads to greater yield and production efficiency than applying by the traditional uniform rate (UR). Poultry litter was applied by varying the rate within ±20 % of the target rates (7.9–11.2 Mg ha−1) where the highest elevation or lowest SOM regions received the highest rate, and the lowest elevation or highest SOM regions received the lowest rate. A treatment fertilized with conventional synthetic fertilizers served as the standard control (Std). Cotton fertilized with PL, regardless of the application method, provided greater K, S, and P nutrition and increased lint yield by as much as 30 % relative to the Std treatment. Applying the PL by the VRe method increased the production efficiency (yield per unit applied PL) by nearly 13 % over the UR. The VRo treatment resulted in a yield reduction of up to 11.8 % but the production efficiency was 14.2 % greater than the UR treatment. Variable rate application based on SOM was not as effective as that based on elevation. The results overall show that PL was superior to synthetic fertilizers in this soil and this superiority could further be enhanced by applying the PL as variable rate based on elevation maps.
•Poultry litter (PL) enhanced cotton K, S, and P nutrition and increased yield by up to 30 %.•Variable rate (VR) PL application based on elevation map (VRe) increased cotton production efficiency by 13 %.•Soil organic matter (SOM)-based VR (VRo) application improved production efficiency by 14.2 % but reduced yield by 11.8 %.•The effectiveness of VRe and the ease to generate elevation maps make it a promising PL application method.•The difficulty to generate accurate SOM maps may preclude the VRo from being a reliable method of PL application.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
4.
A Variational Model for P+XS Image Fusion Ballester, Coloma; Caselles, Vicent; Igual, Laura ...
International journal of computer vision,
8/2006, Volume:
69, Issue:
1
Journal Article
Peer reviewed
Issue Title: Special Issue: Variational Geometric and LS Methods (VLSM 2003) We propose an algorithm to increase the resolution of multispectral satellite images knowing the panchromatic image at ...high resolution and the spectral channels at lower resolution. Our algorithm is based on the assumption that, to a large extent, the geometry of the spectral channels is contained in the topographic map of its panchromatic image. This assumption, together with the relation of the panchromatic image to the spectral channels, and the expression of the low-resolution pixel in terms of the high-resolution pixels given by some convolution kernel followed by subsampling, constitute the elements for constructing an energy functional (with several variants) whose minima will give the reconstructed spectral images at higher resolution. We discuss the validity of the above approach and describe our numerical procedure. Finally, some experiments on a set of multispectral satellite images are displayed.PUBLICATION ABSTRACT
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CEKLJ, DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, SIK, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The main objective of this study is to describe the preparation of topographic maps using the Surfer software. A total of 159 regularly distributed Ground Control Points (GCPs) were collected with ...the use of the Differential Global Positioning System (DGPS). Seven methods (Contour Map, Post Map, 3D Surface Map, 3D Wireframe Maps, Grid Vector-1 Map, Color Relief Map, and Shaded Relief Maps) at the Surfer environment were used to prepare the topographic maps at the Mukhtar Village near the Al-Fallujah City. Contour lines with other features were superimposed on the DEM layer, which refers to the topography of the terrain inside this study area. The accuracy of the database's results was estimated, essential maps were given, and the results were efficient and effective. The most appropriate method to represent topographic maps was proposed, each of these techniques has been enough to provide us with a general understanding of the subject area.
Topographic maps, the systematic spatial ordering of neurons by response tuning, are common across species. In Drosophila, the lobula columnar (LC) neuron types project from the optic lobe to the ...central brain, where each forms a glomerulus in a distinct position. However, the advantages of this glomerular arrangement are unclear. Here, we examine the functional and spatial relationships of 10 glomeruli using single-neuron calcium imaging. We discover novel detectors for objects smaller than the lens resolution (LC18) and for complex line motion (LC25). We find that glomeruli are spatially clustered by selectivity for looming versus drifting object motion and ordered by size tuning to form a topographic visual feature map. Furthermore, connectome analysis shows that downstream neurons integrate from sparse subsets of possible glomeruli combinations, which are biased for glomeruli encoding similar features. LC neurons are thus an explicit example of distinct feature detectors topographically organized to facilitate downstream circuit integration.
•Lobula columnar (LC) neurons are tuned to distinct features of object motion•LC18 detects motion of very small objects by comparing contrast changes in time•LCs project to optic glomeruli that are spatially ordered by visual feature tuning•Downstream neurons integrate from sparse subsets of neighboring glomeruli
By combining calcium imaging and synaptic connectivity analysis, Klapoetke et al. reveal that optic glomeruli in the fly central brain form a topographic visual map, with glomeruli anatomically ordered by visual feature selectivity. Downstream circuits appear to exploit this map by integrating primarily from nearby glomeruli encoding similar features.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•CDB ResU-Net was developed to automate the process of LU map generation.•The proposed neural network has higher accuracy than the existing neural networks.•Addition of building floor data improved ...the accuracy in residential areas.•Combining ancillary data helps to improve the overall accuracy of classification.
Unlike land classification maps, it is difficult to automate the generation of land use (LU) maps. The deep learning approach is a state-of-the-art methodology that can expedite the creation of LU maps. However, as the deep learning output depends on the training input, it is critical to decide upon the input that should be selected. In this study, a method for securing accurate LU information is established and used for ground truthing, using data on the number of building floors extracted from a digital topographic map and a 51 cm resolution aerial orthoimages as inputs. To this end, we developed a Conv-Depth Block (CDB) ResU-Net architecture. To verify the versatility of the proposed network, our neural network was applied to three complex metropolitan areas with different LU characteristics in Korea. The accuracy of LU maps for these cities was improved by combining convolution layers and depth-wise separable convolution as well as by including numerical building floor data. The proposed CDB ResU-Net achieved an overall accuracy of 83.7 % for the test samples. Our network exhibited an improved performance compared to Deeplab v3+, ResUnet, ResASPP-Unet, and context-based ResU-Net in classifying residential classes, which is crucial for estimating the degree of exposure in urban risk analyses.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Visual perception and behavior are mediated by cortical areas that have been distinguished using architectonic and retinotopic criteria. We employed fluorescence imaging and GCaMP6 reporter mice to ...generate retinotopic maps, revealing additional regions of retinotopic organization that extend into barrel and retrosplenial cortices. Aligning retinotopic maps to architectonic borders, we found a mismatch in border location, indicating that architectonic borders are not aligned with the retinotopic transition at the vertical meridian. We also assessed the representation of visual space within each region, finding that four visual areas bordering V1 (LM, P, PM and RL) display complementary representations, with overlap primarily at the central hemifield. Our results extend our understanding of the organization of mouse cortex to include up to 16 distinct retinotopically organized regions.
ABSTRACT
Regeneration after peripheral nerve damage requires that axons re-grow to the correct target tissues in a process called target-specific regeneration. Although much is known about the ...mechanisms that promote axon re-growth, re-growing axons often fail to reach the correct targets, resulting in impaired nerve function. We know very little about how axons achieve target-specific regeneration, particularly in branched nerves that require distinct targeting decisions at branch points. The zebrafish vagus motor nerve is a branched nerve with a well-defined topographic organization. Here, we track regeneration of individual vagus axons after whole-nerve laser severing and find a robust capacity for target-specific, functional re-growth. We then develop a new single-cell chimera injury model for precise manipulation of axon-environment interactions and find that (1) the guidance mechanism used during regeneration is distinct from the nerve's developmental guidance mechanism, (2) target selection is specified by neurons' intrinsic memory of their position within the brain, and (3) targeting to a branch requires its pre-existing innervation. This work establishes the zebrafish vagus nerve as a tractable regeneration model and reveals the mechanistic basis of target-specific regeneration.
Point symbols on a scanned topographic map (STM) provide crucial geographic information. However, point symbol recognition entails high complexity and uncertainty owing to the stickiness of map ...elements and singularity of symbol structures. Therefore, extracting point symbols from STMs is challenging. Currently, point symbol recognition is performed primarily through pattern recognition methods that have low accuracy and efficiency. To address this problem, we investigated the potential of a deep learning-based method for point symbol recognition and proposed a deep convolutional neural network (DCNN)-based model for this task. We created point symbol datasets from different sources for training and prediction models. Within this framework, atrous spatial pyramid pooling (ASPP) was adopted to handle the recognition difficulty owing to the differences between point symbols and natural objects. To increase the positioning accuracy, the k-means++ clustering method was used to generate anchor boxes that were more suitable for our point symbol datasets. Additionally, to improve the generalization ability of the model, we designed two data augmentation methods to adapt to symbol recognition. Experiments demonstrated that the deep learning method considerably improved the recognition accuracy and efficiency compared with classical algorithms. The introduction of ASPP in the object detection algorithm resulted in higher mean average precision and intersection over union values, indicating a higher recognition accuracy. It is also demonstrated that data augmentation methods can alleviate the cross-domain problem and improve the rotation robustness. This study contributes to the development of algorithms and the evaluation of geographic elements extracted from STMs.
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