GPS raw data (control points and ground control points) from the Liguria Region, Borghetto Santo Spirito, Italy

Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research.

Optimal ground control points for geometric correction using genetic algorithm with glboal accuracy

Establishing the ground control point (GCP) network is a pre-requisite for georeferencing raw image data. Given current typical digital spatial database quality, much interest among users is about the accuracy of the geometric correction model that yields the final product. This paper reports an approach to optimizing GCP assembly using a genetic/evolution algorithm. The paper also suggests an optimal criterion for accuracy assessment through appraisal of global accuracy of the transformation, which is computed at each point of the image space. Experimental results demonstrate that the proposed approach has a great potential for selection of the best GCPs, and considerable improvement to the accuracy of geometric correction models can be expected when it is implemented.

Bundle Block Adjustment of CBERS-2B HRC Imagery Combining Control Points and Lines

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

DIGITAL ELEVATION MODEL VALIDATION WITH NO GROUND CONTROL: APPLICATION TO THE TOPODATA DEM IN BRAZIL

Digital Elevation Model (DEM) validation is often carried out by comparing the data with a set of ground control points. However, the quality of a DEM can also be considered in terms of shape realism. Beyond visual analysis, it can be verified that physical and statistical properties of the terrestrial relief are fulfilled. This approach is applied to an extract of Topodata, a DEM obtained by resampling the SRTM DEM over the Brazilian territory with a geostatistical approach. Several statistical indicators are computed, and they show that the quality of Topodata in terms of shape rendering is improved with regards to SRTM.

Locating control points in aerial images with a multi-scale approach based on terrestrial image patches

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

DSA image registration using non-uniform MRF model and pivotal control points

In order to reduce the motion artifacts in DSA, non-rigid image registration is commonly used before subtracting the mask from the contrast image. Since DSA registration requires a set of spatially non-uniform control points, a conventional MRF model is not very efficient. In this paper, we introduce the concept of pivotal and non-pivotal control points to address this, and propose a non-uniform MRF for DSA registration. We use quad-trees in a novel way to generate the non-uniform grid of control points. Our MRF formulation produces a smooth displacement field and therefore results in better artifact reduction than that of registering the control points independently. We achieve improved computational performance using pivotal control points without compromising on the artifact reduction. We have tested our approach using several clinical data sets, and have presented the results of quantitative analysis, clinical assessment and performance improvement on a GPU. (C) 2013 Elsevier Ltd. All rights reserved.

A survey of process hygiene in the Sri Lankan prawn industry. 3. Critical control points

Of fifteen processing plants surveyed in Sri Lanka, only five were found to have a prawn process which was adequately controlled. Most common process faults were: inadequate chilling of prawns after a wash in 30°C, mains water, the use of large blocks of ice to cool prawns, and high ratios of prawns to ice. There was also ample scope for cross-contamination of the processed prawns.

Strategy to detect ground control in digital images

The identification of ground control on photographs or images is usually carried out by a human operator, who uses his natural skills to make interpretations. In Digital Photogrammetry, which uses techniques of digital image processing extraction of ground control can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features of object space and its homologous in the image space. A build-in self-diagnosis is also used in this method. It is based on implementation of data snooping statistic test in the process of spatial resection using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.

A semi-automatic method for indirect orientation of aerial images using ground control lines extracted from airborne laser scanner data

This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy.

Exterior orientation of CBERS-2B imagery using multi-feature control and orbital data

The major contribution of this paper relates to the practical advantages of combining Ground Control Points (GCPs), Ground Control Lines (GCLs) and orbital data to estimate the exterior orientation parameters of images collected by CBERS-2B (China-Brazil Earth Resources Satellite) HRC (High-resolution Camera) and CCD (High-resolution CCD Camera) sensors. Although the CBERS-2B is no longer operational, its images are still being used in Brazil, and the next generations of the CBERS satellite will have sensors with similar technical features, which motivates the study presented in this paper. The mathematical models that relate the object and image spaces are based on collinearity (for points) and coplanarity (for lines) conditions. These models were created in an in-house developed software package called TMS (Triangulation with Multiple Sensors) with multi-feature control (GCPs and GCLs). Experiments on a block of four CBERS-2B HRC images and on one CBERS-2B CCD image were performed using both models. It was observed that the combination of GCPs and GCLs provided better bundle block adjustment results than conventional bundle adjustment using only GCPs. The results also demonstrate the advantages of using primarily orbital data when the number of control entities is reduced. © 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Critical Control Points for Profitability in the Cow-Calf Enterprise

Financial, economic, and biological data collected from cow-calf producers who participated in the Illinois and Iowa Standardized Performance Analysis (SPA) programs were used in this study. Data used were collected for the 1996 through 1999 calendar years, with each herd within year representing one observation. This resulted in a final database of 225 observations (117 from Iowa and 108 from Illinois) from commercial herds with a range in size from 20 to 373 cows. Two analyses were conducted, one utilizing financial cost of production data, the other economic cost of production data. Each observation was analyzed as the difference from the mean for that given year. The independent variable utilized in both the financial and economic models as an indicator of profit was return to unpaid labor and management per cow (RLM). Used as dependent variables were the five factors that make up total annual cow cost: feed cost, operating cost, depreciation cost, capital charge, and hired labor, all on an annual cost per cow basis. In the economic analysis, family labor was also included. Production factors evaluated as dependent variables in both models were calf weight, calf price, cull weight, cull price, weaning percentage, and calving distribution. Herd size and investment were also analyzed. All financial factors analyzed were significantly correlated to RLM (P < .10) except cull weight, and cull price. All economic factors analyzed were significantly correlated to RLM (P < .10) except calf weight, cull weight and cull price. Results of the financial prediction equation indicate that there are eight measurements capable of explaining over 82 percent of the farm-to-farm variation in RLM. Feed cost is the overriding factor driving RLM in both the financial and economic stepwise regression analyses. In both analyses over 50 percent of the herd-to-herd variation in RLM could be explained by feed cost. Financial feed cost is correlated (P < .001) to operating cost, depreciation cost, and investment. Economic feed cost is correlated (P < .001) with investment and operating cost, as well as capital charge. Operating cost, depreciation, and capital charge were all negatively correlated (P < .10) to herd size, and positively correlated (P < .01) to feed cost in both analyses. Operating costs were positively correlated with capital charge and investment (P < .01) in both analyses. In the financial regression model, depreciation cost was the second critical factor explaining almost 9 percent of the herd-to-herd variation in RLM followed by operating cost (5 percent). Calf weight had a greater impact than calf price on RLM in both the financial and economic regression models. Calf weight was the fourth indicator of RLM in the financial model and was similar in magnitude to operating cost. Investment was not a significant variable in either regression model; however, it was highly correlated to a number of the significant cost variables including feed cost, depreciation cost, and operating cost (P < .001, financial; P < .10, economic). Cost factors were far more influential in driving RLM than production, reproduction, or producer controlled marketing factors. Of these cost factors, feed cost had by far the largest impact. As producers focus attention on factors that affect the profitability of the operation, feed cost is the most critical control point because it was responsible for over 50 percent of the herd-to-herd variation in profit.

Calcareous nannofossil datums and control points for the TCMS age model of ODP Site 175-1085

An astronomically calibrated age model for the Pliocene section of Ocean Drilling Program Leg 175 Cape Basin Site 1085 based on magnetic susceptibility data was developed using shipboard biostratigraphic datums. The composite core magnetic susceptibility record was compiled using shipboard correlations between Holes 1085A and 1085B and then tuned to the record of orbital variations in eccentricity to generate an orbitally tuned age model. Magnetic susceptibility apparently records climate variations in the Cape Basin. Strong power spectra values at the 100- and 400-k.y. frequency suggest an orbital control on the beat of Pliocene climate change in the Cape Basin.