UCD VHSR aerialimagery newly taken in Iran was applied in this study to investigate its potential to measure canopy cover in Zagros woodlands. As these data has very high spatial resolution (0.06 m), it is expected to detect and extract crown boundaries of trees more precisely compared to other high-resolution remote sensing data, available in Iran (e.g. B&W aerial photographs, satellite imagery like IKONOS and Quickbird).
classification was applied in land cover and land use. The main drawback of per-pixel classification in multi-dimensional feature space is that it doesn’t make use of any spatial concept (Blaschke and Strobel, 2001). Object-oriented image processing overcomes these difficulties by segmenting the image into meaningful objects based on both spectral and spatial characteristics. Automatic classification of land cover feature with highresolutionimagery and Lidar based on object-oriented approach was used to detect individual building and tree crown (Sohel Syed et al., 2005). An object-oriented approach for analysing and characterising the urban landscape structure at the parcel level was presented using high-resolution digital aerialimagery and Lidar data for the Baltimore area (Zhou and Troy, 2008). The development overview about OBIA methods was given, which aim to delineate usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way (Blaschke, 2010). High point density Lidar data and colour-infrared orthoimages were applied for the classification of shrubs and trees in a study area in Denmark (Thomas, et al. 2013). A graph based algorithm was promoted, which combines multispectral imagery and airborne Lidar information to completely delineate the building boundaries in urban and densely vegetated area (Gilani et al., 2015). Highresolutionimagery, Lidar datasets and parcel map data have been The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B3, 2016
The shadows in optical remote sensing images are regarded as image nuisances in numerous applications. The classification and interpretation of shadow area in a remote sensing image are a challenge, because of the reduction or total loss of spectral information in those areas. In recent years, airborne multispectral aerial image devices have been developed 12-bit or higher radiometric resolution data, including Leica ADS-40, Intergraph DMC. The increased radiometric resolution of digital imagery provides more radiometric details of potential use in classification or interpretation of land cover of shadow areas. Therefore, the objectives of this study are to analyze the spectral properties of the land cover in the shadow areas by ADS-40 high radiometric resolutionaerial images, and to investigate the spectral and vegetation index differences between the various shadow and non-shadow land covers. According to research findings of spectral analysis of ADS-40 image: (i) The DN values in shadow area are much lower than in nonshadow area; (ii) DN values received from shadowed areas that will also be affected by different land cover, and it shows the possibility of land cover property retrieval as in nonshadow area; (iii) The DN values received from shadowed regions decrease in the visible band from short to long wavelengths due to scattering; (iv) The shadow area NIR of vegetation category also shows a strong reflection; (v) Generally, vegetation indexes (NDVI) still have utility to classify the vegetation and non-vegetation in shadow area. The spectral data of high radiometric resolution images (ADS-40) is potential for the extract land cover information of shadow areas.
Despite the technological advance of remote sensors and the ability to detect finer objects on the ground, higher accuracy is always desirable. Technological restrictions confine satellite design to highresolution but low revisit frequency, or else low resolution and high revisit frequency. A combination of both qualities would be preferable, and therefore, techniques to merge satellite images of different spatial resolutions have been developed.  have used an Intensity-Hue- Saturation (IHS) transformation to merge SPOT (Satellite Pour l’Observation de la Terre) panchromatic and Landsat multispectral satellite images, while  have used the same technique to merge airborne digital data with digitized aerial photography. Other techniques include the Principal Components transformation , and merging of the spatial frequency content . Except for the need for spatial detail, another reason for this merge is that highresolution images are often costly, while low resolution are of low cost, or even are freely distributed. It is possible that remote sensing work can be performed using low-resolution satellite images that are later spatially enhanced using a high spatial resolution image.
The availability of space borne images at finer spatial resolutions has opened new vistas in the areas of detailed automated feature extraction. Mapping and extraction of features from satellite imagery is a fundamental operation for updating maps. While road extraction has been performed by digitizing maps, the update and refinement of the road geometry is often based on aerialimagery or highresolution satellite imagery. Automatic road extraction from Remote sensing imagery has attracted much attention for the last few decades. Automatic feature extraction has become a main objective to save time in updating data, and as a result of this, people are changing progressively to new procedures (Kumar2009 a, Jin , 2005. Automated road information extraction from high- resolution images holds great potential for significant reduction of database development cost and turnaround time and vigorous efforts have been made to develop better algorithms and methodologies for this purpose (Mokhtarzade 2008, Mena, 2005).
Strait, M., Rahmani, S., Merkurev, D., 2008. Evaluation of pan- sharpening methods, UCLA Department of Mathematics. Tong, X., Lin, X., Feng, T., Xie, H., Liu, S., Hong, Z., Chen, P., 2013. Use of shadows for detection of earthquake-induced collapsed buildings in high-resolution satellite imagery. ISPRS Journal of Photogrammetry and Remote Sensing 79, 15. Tsai, V.J., 2006. A comparative study on shadow compensation of color aerial images in invariant color models. IEEE Transactions on Geoscience and Remote Sensing 44, 10. Zhan, Q., Shi, W., Xiao, Y., 2005. Quantitative analysis of shadow effects in high-resolution images of urban areas, International Archives of Photogrammetry and Remote Sensing. Zhang, H., Sun, K., Li, W., 2014. Object-Oriented Shadow Detection and Removal From Urban High-Resolution Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing 52, 11.
The combined use of digital imagery and surface models finds mainly applications in automatic object extraction and 3D reconstruction from aerial data or very highresolution satellite sensors (Arefi, 2009, Baltsavias et al., 1995, Jaynes et al. 1996, Paparoditis et al., 1998, Lu et al., 2002, Tao and Yasuoka, 2002, Li et al., 2008). Few works aim at using satellite imagery for DSM enhancement. In (Maire, 2010) user-defined semantic contents (sea, lakes, building, road, etc.) are extracted with a supervised classification in highresolution satellite imagery; then in correspondence of each class the surface is modelled by plane surfaces with geometric constraints given by the topological properties of each class and neighbour regions. This approach was applied, for example, for the enhancement of SRTM-X using a 2.5m ground resolution SPOT-5 scene. The approach proposed by (Kraus and Reinartz, 2010) improves computer vision methods for DSM generation, based on epipolar imagery and dense stereo matching (Scharstein and Szeliski, 2002, Hirschmüller, 2005). One stereo image is segmented and transferred to the disparity map, then for each segment the original disparity map is filled with suitable interpolation of the disparities. A peculiarity of this method is that it does not optimize a DSM using orthoimagery, but starts one step before on the epipolar images during the DSM generation and avoids possible errors contained in orthorectified images.
Nowadays, the unmanned aerial vehicles (UAV) are a valuable source of the graphic data delivered from the low ceiling. The graphic data gained from a low ceiling are widely used in making the stock-taking of the power lines, surveillance, production of high-resolution orthophoto, and in 3D modelling of the building and cities. Thanks to delivering spatial and time highresolution of images, it is also possible to make current and exact map analysis ( Remondino et al., 2011, Saari et al., 2011, Nex and Remondino,2014; Kedzierski and Wierzbicki, 2015; Wischounig-Strucl and Rinner, 2015). In progress of the continuous development of the non-symmetrical digital cameras, miniaturization of the unmanned aerial vehicles, and automatization of making the orthophotos, the photogrammetry of the low ceiling becomes more widely used. Until now, the cadastral application has mainly used the tachymeter and the GNSS receivers. Thanks to the use of those instruments, it is possible to ensure high accuracy and performance in surveying the object points and lines. In contrast to the traditional research methods, until now, the photogrammetry analysis was used in adaptation and update of the maps for larger areas (Manyoky, et al., 2011). However, the traditional aerial photos have limited application in update of the large-scale maps, mainly due to high height of the flight what results in relatively low resolution of the image and high costs. Considering the profitability of making the map analysis and its accuracy for the hundred hectare areas, decidedly better solution seems to be the use of the low ceiling photogrammetry. Update of the detailed maps is
Wastewater and stormwater networks are a perfect example of the mislocalisation of buried utilities both in industrialized and devel- oping countries. Over the past century it was common practice for each service provider and district to install, operate and repair its network separately (Rogers et al., 2012). Maps and databases were often not well archived or centralized and as a result it is dif- ficult nowadays to obtain accurate information on the localization and characteristics of the buried pipes and hydraulic equipment. The manhole covers and inlet grates which are surface elements and thus indicators of the location of these networks, can be ob- served on aerial images. Hence, we can rely on the automatic detection of these objects to provide an estimation of the under- ground utility networks’ position (Pasquet et al., 2016).
The history of research into automatic individual tree detection from digital imagery dates back to the mid-1980s. One of the earliest examples was the research which was presented by Pinz (Pinz, 1991) using the Vision Expert to locate the center of a crown and estimate the crown radius by searching for local brightness maxima in smoothed aerial images with a 10 cm pixel size. In the mid-1990s, (Gougeon, 1995a) presented a valley-following and rule-based algorithm to delineate fully coniferous tree crowns by following valleys of shadows between tree crowns using 36 cm ground sampled distance (GSD) digital aerialimagery (Ke et al., 2011). In the same period of time, multiple scale analysis was applied on higher resolutionimagery to estimate tree-crown area (Brandtberg, 1998), and model-based template matching techniques were introduced to recognize individual trees (Pollock, 1996). Later, methods such as Multidimentional Temporal Feature Space Analysis, Composite Analysis, Image Differencing, Image Rationing, Change Vector Analysis, Image Regression, multi temporal Biomass Index were introduced for change detection purposes. However, the methods reported are different in terms of the type of algorithms which is used, the conditions of specific study area, the types of applicable imagery and the accuracy of the evaluation methods considered (Culvenor, 2002). Additionally, the increased speed found in modern computer systems has facilitated, the development of digital image analysis for automated recognition of specific object characteristics (Ke et al., 2011). Different object based change detection methods presented in the figure 2.
This study was using three highresolution satellite imagery to estimate bathymetric condition at shallow water coral reef environment around Pulau Panggang, Jakarta. The Worldview 2 supply 2 m spasial resolution with 8 spectral band, whereas Quickbird 2 produce 2.44 m spatial resolution in 4 spectral band and ALOS produce 10 m spasial resolution with also 4 spectral band. Red band of ALOS and Quickbird have high correlation with sand depth and the lowest are blue bands. Among this bands, Quickbird red band is the highest and its blue band is the lowest. Worldview visible bands may have low sand depth correlation because of noise from ripple wave during acquisition. This study shown that, Quickbird image is proven able to map water depth variation up to 8 metre at reef flat and lagoon area of Panggang island, Jakarta with RMSe is 1.1 metre. The result also shown an opportunity to implement this approach to bathymetric mapping of shallow water area at remote small islands.
Accurate bathymetric measurements are considered of fundamental importance towards monitoring sea bottom and producing nautical charts in support of marine navigation. Until recently, bathymetric surveying of shallow sea water has been mainly based on conventional ship-borne echo sounding operations. However, this technique demands cost and time, particularly in shallow waters, where a dense network of measured points is required. Taking all these under consideration, during the last decades remotely sensed data have provided a cost- and time-effective solution to accurate depth estimation (Lyzenga, 1985; Stumpf et al., 2003; Su et al., 2008). The initial attempts for automatic estimation of water depth were based on the combination of aerial multispectral data and radiometric techniques (Lyzenga, 1978). With the advent of Landsat images, the methods of monitoring sea floor were increased and ameliorated, so as to be efficiently applied on optical satellite images (Lyzenga, 1981; Spitzer and Dirks, 1987; Philpot, 1989; Van Hengel and Spitzer, 1991). In the following years, the advance of remote sensing technology expanded the use of these methodologies to data with improved spatial and spectral resolution, i.e. Ikonos (Stumpf et al., 2003; Mishra et al. 2006; Su et al., 2008), Quickbird (Conger et al., 2006; Lyons et al., 2011) and Worldview-2 data (Kerr, 2010, Bramante et al. 2010). The main hindrances while applying these processes were reflectance penetration and water turbidity (Conger et al., 2006; Su et al., 2008). However, the bathymetric approaches involving satellite imagery data are regarded as a fast and economically advantageous solution to automatic water depth calculation in shallow water (Stumpf et al., 2003; Su et al., 2008).
A comprehensive analysis of LiDAR DEMs, aerial images, and digital maps of Mt. Umyeon was performed to make geomorphic comparisons of the study area before and after the debris flow event. The landslide and debris flow behaviors were assessed for the watershed that incurred the most damage. To quantify the geomorphic changes induced by the event, the flow paths before and after the event were determined (Figure 7), and longitudinal and cross-sectional profiles were extracted (Figure 8). The longitudinal run of the debris flow path was observed at 20 m intervals from the initiation point to the watershed exit, and the cross-sectional features were observed at 1 m intervals The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B8, 2016
The availability of new highresolution radar spaceborne sensors offers new interesting potentialities for the geomatics application: spatial and temporal change detection, features extraction, generation of Digital Surface (DSMs). As regards the DSMs generation from new highresolution data (as SpotLight imagery), the development and the accuracy assessment of method based on radargrammetric approach are topics of great interest and relevance. The aim of this investigation is the DSM generation from a COSMO-SkyMed Spotlight stereo pair with the radargrammetric technique. DSM generation procedure consists of two basic steps: the stereo pair orientation and the image matching. The suite for radargrammetric approach has been implemented in SISAR (Software per Immagini Satellitari ad Alta Risoluzione), a scientific software developed at the Geodesy and Geomatic Institute of the University of Rome “La Sapienza”. As regard the image matching the critical issue is the definition of a strategy to search the corresponding points; in SISAR software, an original matching procedure has been developed, based on a coarse-to-fine hierarchical solution with an effective combination of geometrical constrains and an Area Base Matching (ABM) algorithm.
Later a layer of complexity was added with ice processes, following ideas such as Rutledge and Hobbs (1983) to repre- sent the initiation and growth of ice crystals, aggregation into snow particles, and their fall and melting terms. Dudhia (1989) adapted these for a mesoscale model (MM4) to obtain impor- tant tropical stratiform processes, and later recognized the im- portance of ice-crystal fall-speed for multi-day simulations to not overestimate ice cloud coverage. This need becomes even more clear in regional climate applications when verified against outgoing longwave radiation (OLR) that is dominated by the cirrus extent. With ice saturation being lower than water saturation, various methodologies were adopted to handle sat- uration processes below freezing, sometimes with a weighted saturation level between that of water and ice based on either temperature or species present. Dudhia (1989) preferred the ice particles to respond only to ice saturation levels, however, and this approach has been carried through to many current micro- physics schemes. Verifications of relative humidity in meso- scale models indicated the necessity of ice-phase processes in preventing high biases in the upper troposphere. Another aspect of this mesoscale ice approach was to carry only three variables, vapour, ice/cloud, and snow/rain, to reduce advection cost. Below the freezing level, only water processes were handled, while above was ice, enforcing freezing/melting for transport or fall at the freezing level. While efficient, this 3- class approach cannot be used at higher resolution because supercooled water and gradual melting were precluded. Later so-called mixed-phase 5-class schemes added the extra ad- vected variables (Hong et al ., 1998; Reisner et al ., 1998; Hong et al ., 2004). Mesoscale models typically have long time steps for 10 km grids and fine vertical resolutions, perhaps 100 m, for the surface and boundary-layer processes. When precipi- tating species such as rain are explicitly carried, their fall terms may have to be treated on split sub-steps, or use Lagrangian methods (e.g., Juang and Hong, 2010), for numerical stability
Pb-Free (RoHS) TAOS’ terms Lead-Free or Pb-Free mean semiconductor products that are compatible with the current RoHS requirements for all 6 substances, including the requirement that lead not exceed 0.1% by weight in homogeneous materials. Where designed to be soldered at high temperatures, TAOS Pb-Free products are suitable for use in specified lead-free processes.
In this paper, the new data source of China (ZY3/GF1) was selected in inland-lake monitoring and protection. With these high spatial resolution satellite imagery, the object-oriented analysis method is applied in inland-lakes boundary extraction by the object-oriented classification in eCognition. Based on the ZY-3 imagery captured in April 2012, the classification map of Xiwanhu Lake is produced, and based on the imagery between April 2012 (ZY-3) and April 2013 (GF-1), the water surface change thematic map of Tangxunhu Lake in Wuhan is also be obtained efficiently and clearly. While the important point should be noted is that although the change area were found by satellite imagery, while the detailed reason for the change of water surface should be validated and checked by the field survey and investigation. some change maybe the false change for the spectral difference cause by the weather or other factors. With the rapid development in Wuhan, especially in establishing the experimental zone 'Wuhan 1+8 city cluster', many lakes are changed from water surface to land surface, and this situation is really a challenges for water resource management in Wuhan. While the rapid developing remote sensing technology in China shown as the improvement in the spatial/temporal resolution, satellite imagery could be a kind of new data source or solution in water resource management. The works in this paper illustrates this point in certain extent.
This OGC Engineering Report describes the high-resolution flood information scenario carried out under the Urban Climate Resilience Thread of the Testbed 11 Initiative. The scenario was developed for two areas of interest: the San Francisco Bay Area and in Mozambique. The scenarios for these two locations demonstrate the interoperation and capabilities of open geospatial standards in supporting data and processing services. The prototype HighResolution Flood Information System addresses access and control of simulation models and high-resolution data in an open, worldwide, collaborative Web environment. The scenarios were designed to help testbed participants examine the feasibility and capability of using existing OGC geospatial Web Service standards in supporting the on-demand, dynamic serving of flood information from models with forecasting capacity. Change requests to OGC standards have also been identified through the Testbed activity.
Buildings change detection has the ability to quantify the temporal effect, on urban area, for urban evolution study or damage assessment in disaster cases. In this context, changes analysis might involve the utilization of the available satellite images with different resolutions for quick responses. In this paper, to avoid using traditional method with image resampling outcomes and salt- pepper effect, building change detection based on shape matching is proposed for multi-resolution remote sensing images. Since the object ’ s shape can be extracted from remote sensing imagery and the shapes of corresponding objects in multi-scale images are similar, it is practical for detecting buildings changes in multi-scale imagery using shape analysis. Therefore, the proposed methodology can deal with different pixel size for identifying new and demolished buildings in urban area using geometric properties of objects of interest. After rectifying the desired multi-dates and multi-resolutions images, by image to image registration with optimal RMS value, objects based image classification is performed to extract buildings shape from the images. Next, Centroid- Coincident Matching is conducted, on the extracted building shapes, based on the Euclidean distance measurement between shapes centroid (from shape T 0 to shape T 1 and vice versa), in order to define corresponding building objects. Then, New and Demolished
Highresolution optical satellite, playing an important role in Earth Observation System, can obtain the imagery covering the surface of the Earth with ground sampling distance (GSD) of several meters and even less than 1 m. Worldview-3/4, launched in 2014 and 2016 respectively, have reached 0.3 m GSD. Gaofen- 2, one of the optical satellites of Chinese HighResolution Observation System, also can obtain imagery with sub-meter GSD. When the spatial resolution is improved higher, the imaging rang will be smaller than before. To improve the imaging efficiency, increasing the imaging width is a direct and effective method, which can obtain a larger imaging range at one time. However, wider imaging swath leads to an exponential increase in the amount of imaging data, which not only brings pressure to data transmission, but also reduces the efficiency of data processing and application, especially for the rapid emergency response applications, such as monitoring of earthquake area, dynamic monitoring of time sensitive target. So region of interest (ROI)-oriented data processing, which can obtain data and information quickly and efficiently, is a useful strategy for emergency situation in both ground processing system and on-board processing system.