scholarly journals Validation of Pleiades Tri-Stereo DSM in Urban Areas

2018 ◽  
Author(s):  
Manolis Panagiotakis ◽  
Nektarios Chrysoulakis ◽  
Vasiliki Charalampopoulou ◽  
Dimitris Poursanidis
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Relevant Literature ◽  
Simulation Models ◽  
Cost Effective ◽  
Stereo Images ◽  
Cost Effective Approach ◽  
Spatial Coverage ◽  
Temporal Coverage

A very high-resolution DSM covering an area of 400km2 over the Athens Metropolitan Area has been produced using Pleiades 1B 0,5m panchromatic tri-stereo images. Applied Remote Sensing and Photogrammetry tools have been used resulted in a 1x1m DSM over the study area. DSM accuracy has been evaluated by comparison with measured elevations with D-GPS and a reference DSM provided by the National Cadaster & Mapping Agency S.A. In addition, different combinations of stereo images have been prepared for further exploitation of the quality of the produced DSM by stereo vs. tri-stereo images. Results show that the produced by the tri-stereo images DSM has an RMSE of 1.17m in elevation (z), which is among the best reported in the relevant literature. Stereo based DSMs from the same sensor have worst performance to this end. Satellite Remote Sensing (SRS) based DSMs over urban areas provide the best cost-effective approach in comparison to airborne-based datasets due to high spatial coverage, lower cost and high temporal coverage. Pleiades-based high-quality DSM products can serve the domains of urban planning/climate, hydrological modelling and natural hazards, as major input for simulation models and morphological analysis at local scale.

A Systematic Planning Tool for Environmental Characterisation

2009 ◽  
Author(s):  
Steven Wilcox ◽  
Richard Wilkins ◽  
Martin Lyons
Keyword(s):  
Best Practice ◽  
Planning Process ◽  
Cost Effective ◽  
Decision Makers ◽  
Performance Criteria ◽  
Final Decision ◽  
Cost Effective Approach ◽  
Systematic Planning ◽  
Sample Plan

Many organisations are currently dealing with long standing legacy issues in clean up, decommissioning and demolition projects. Industry is required to ensure that all bulk articles, substances and waste arisings are adequately characterised and assigned to the correct disposal routes in compliance with UK legislation and best practice. It is essential that data used to support waste sentencing is of the correct type, quality and quantity, and that it is appropriately assessed in order to support defensible, confident decisions that account for inherent uncertainties. AMEC has adopted the Data Quality Objectives (DQO) based methodology and the software package Visual Sample Plan (VSP) to provide a better, faster, and more cost effective approach to meeting regulatory and client requirements, whilst minimising the time spent gathering data and assessing the information. The DQO methodology is based on a scientific approach that requires clear objectives to be established from the outset of a project and that there is a demonstration of acceptability of the results. Through systematic planning, the team develops acceptance or performance criteria for the quality of the data collected and for the confidence in the final decision. The systematic planning process promotes communication between all departments and individuals involved in the decision-making process thus the planning phase gives an open and unambiguous method to support the decisions and enables the decision-makers (technical authorities on the materials of concern) to document all assumptions. The DQO process allows better planning, control and understanding of all the issues. All types of waste can be sentenced under one controllable system providing a more defensible position. This paper will explain that the DQO process consists of seven main steps that lead to a detailed Sampling and Analysis Plan (SAP). The process gives transparency to any assumptions made about the site or material being characterised and identifies individuals involved. The associated calculation effort is reduced using the statistically based sampling models produced with VSP. The first part of this paper explains the DQO based methodology and Visual Sample Plan and the second part shows how the DQO process has been applied in practice.

scholarly journals Leveraging machine learning to produce a cost-effective national building height map of Ireland

2021 ◽  
Author(s):  
Eoghan Keany ◽  
Geoffrey Bessardon ◽  
Emily Gleeson
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
High Resolution ◽  
Land Cover ◽  
Urban Areas ◽  
Cost Effective ◽  
Land Cover Classification ◽  
National Scale ◽  
Building Height ◽  
Height Data

<p>To represent surface thermal, turbulent and humidity exchanges, Numerical Weather Prediction (NWP) systems require a land-cover classification map to calculate sur-face parameters used in surface flux estimation. The latest land-cover classification map used in the HARMONIE-AROME configuration of the shared ALADIN-HIRLAMNWP system for operational weather forecasting is ECOCLIMAP-SG (ECO-SG). The first evaluation of ECO-SG over Ireland suggested that sparse urban areas are underestimated and instead appear as vegetation areas (1). While the work of (2) on land-cover classification helps to correct the horizontal extent of urban areas, the method does not provide information on the vertical characteristics of urban areas. ECO-SG urban classification implicitly includes building heights (3), and any improvement to ECO-SG urban area extent requires a complementary building height dataset.</p><p>Openly accessible building height data at a national scale does not exist for the island of Ireland. This work seeks to address this gap in availability by extrapolating the preexisting localised building height data across the entire island. The study utilises information from both the temporal and spatial dimensions by creating band-wise temporal aggregation statistics from morphological operations, for both the Sentinel-1A/B and Sentinel-2A/B constellations (4). The extrapolation uses building height information from the Copernicus Urban Atlas, which contains regional coverage for Dublin at 10 m x10 m resolution (5). Various regression models were then trained on these aggregated statistics to make pixel-wise building height estimates. These model estimates were then evaluated with an adjusted RMSE metric, with the most accurate model chosen to map the entire country. This method relies solely on freely available satellite imagery and open-source software, providing a cost-effective mapping service at a national scale that can be updated more frequently, unlike expensive once-off private mapping services. Furthermore, this process could be applied by these services to reduce costs by taking a small representative sample and extrapolating the rest of the area. This method can be applied beyond national borders providing a uniform map that does not depends on the different private service practices facilitating the updates of global or continental land-cover information used in NWP.</p><p> </p><p>(1) G. Bessardon and E. Gleeson, “Using the best available physiography to improve weather forecasts for Ireland,” in Challenges in High-Resolution Short Range NWP at European level including forecaster-developer cooperation, European Meteorological Society, 2019.</p><p>(2) E. Walsh, et al., “Using machine learning to produce a very high-resolution land-cover map for Ireland, ” Advances in Science and Research,  (accepted for publication).</p><p>(3) CNRM, "Wiki - ECOCLIMAP-SG" https://opensource.umr-cnrm.fr/projects/ecoclimap-sg/wiki</p><p>(4) D. Frantz, et al., “National-scale mapping of building height using sentinel-1 and sentinel-2 time series,” Remote Sensing of Environment, vol. 252, 2021.</p><p>(5) M. Fitrzyk, et al., “Esa Copernicus sentinel-1 exploitation activities,” in IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium, IEEE, 2019.</p>

High-resolution root zone soil moisture-based indices for drought monitoring in the Ebro basin

2021 ◽  
Author(s):  
Vivien-Georgiana Stefan ◽  
Maria-José Escorihuela ◽  
Pere Quintana-Seguí
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
High Resolution ◽  
Root Zone ◽  
Cost Effective ◽  
Strong Relationship ◽  
Drought Indices ◽  
Ebro Basin ◽  
Small Areas ◽  
Cost Effective Approach

<h3>Agriculture is an important factor on water resources, given the constant population growth and the strong relationship between water availability and food production. In this context, root zone soil moisture (RZSM) measurements are used by modern irrigators in order to detect the onset of crop water stress and to trigger irrigations. Unfortunately, in situ RZSM measurements are costly; combined with the fact they are available only over small areas and that they might not be representative at the field scale, remote sensing is a cost-effective approach for mapping and monitoring extended areas. A recursive formulation of an exponential filter was used in order to derive 1 km resolution RZSM estimates from SMAP (Soil Moisture Active Passive) surface soil moisture (SSM) over the Ebro basin. The SMAP SSM was disaggregated to a 1 km resolution by using the DISPATCH (DISaggregation based on a Physical And Theoretical scale CHange) algorithm. The pseudodiffusivity parameter of the exponential filter was calibrated per land cover type, by using ISBA-DIF (Interaction Soil Biosphere Atmosphere) surface and root zone soil moisture data as an intermediary step. The daily 1 km RZSM estimates were then used to derive 1 km drought indices such as soil moisture anomalies and soil moisture deficit indices (SMDI), on a weekly time-scale, covering the entire 2020 year. Results show that both drought indices are able to capture rainfall and drying events, with the weekly anomaly being more responsive to sudden events such as heavy rainfalls, while the SMDI is slower to react do the inherent inertia it has. Moreover, a quantitative comparison with drought indices derived from a model-based RZSM estimates has also been performed, with results showing a strong correspondence between the different indices. For comparison purposes, the weekly soil moisture anomalies and SMDI derived using 1 km SMAP-derived SSM were also estimated. The analysis shows that the anomalies and SMDI based on the RZSM are more representative of the hydric stress level of the plants, given that the RZSM is better suited than the SSM to describe the moisture conditions at the deeper layers, which are the ones used by plants during growth and development.</h3><h3>The study provides an insight into obtaining robust, high-resolution remote-sensing derived drought indices based on remote-sensing derived RZSM estimates. The 1 km resolution proves an improvement from other currently available drought indices, such as the European Drought Observatory’s 5 km resolution drought index, which is not able to capture as well the spatial variability present within heterogeneous areas. Moreover, the SSM-derived drought indices are currently used in a drought observatory project, covering a region in the Tarragona province of Catalonia, Spain. The project aims at offering irrigation recommendations to water agencies, and the introduction of RZSM-derived drought indices will further improve such advice.</h3>

Estimating Area Coverage and Volume of Hot Lava by Integrating Multiple Satellite Remote Sensing Techniques

2021 ◽  
Author(s):  
Ninad Bhagwat ◽  
Xiaobing Zhou ◽  
Jiaqing Miao
Keyword(s):  
Remote Sensing ◽  
Rift Zone ◽  
Cost Effective ◽  
Interferometric Synthetic Aperture Radar ◽  
Areal Coverage ◽  
Volcanic Processes ◽  
Distribution Index ◽  
Remote Sensing Techniques ◽  
Temporal Coverage ◽  
Area And Volume

<p>Monitoring the regions that are prone to natural hazards is essential in disaster management, since early warnings can be issued. Airborne and space-borne remote sensing techniques are cost-effective in accomplishing the task. Estimating the area and volume of erupted lava can help researchers understand the volcanic processes and impact on land use and land cover. In this study, we developed a new algorithm to estimate areal coverage and volume of exposed hot lava by integrating the space-borne Interferometric Synthetic Aperture Radar (InSAR), thermal infrared, and Normalized Vegetation Distribution Index (NDVI) techniques. We applied this algorithm to the eruption of the East Rift Zone (ERZ) of the Kilauea volcano took place between May and August 2018 and estimated the areal coverage and volume of lava erupted. We compared the results of InSAR to those derived from airborne Light Detection and Ranging (LiDAR), and found that although air-borne LiDAR provides data with higher resolution and accuracy, InSAR is almost as good as LiDAR in monitoring deformed areas and has larger spatial and temporal coverage.</p>

scholarly journals Integrating Satellite-Derived Data as Spatial Predictors in Multiple Regression Models to Enhance the Knowledge of Air Temperature Patterns

Urban Science ◽  
2019 ◽  
Vol 3 (4) ◽  
pp. 101 ◽  
Author(s):  
Lucille Alonso ◽  
Florent Renard
Keyword(s):  
Remote Sensing ◽  
Air Temperature ◽  
Urban Areas ◽  
Land Development ◽  
Explanatory Variables ◽  
Dense Networks ◽  
Urban Heat ◽  
Derived Data ◽  
Computer Resources

With the phenomenon of urban heat island and thermal discomfort felt in urban areas, exacerbated by climate change, it is necessary to best estimate the air temperature in every part of an area, especially in the context of the on-going rationalization weather stations network. In addition, the comprehension of air temperature patterns is essential for multiple applications in the fields of agriculture, hydrology, land development or public health. Thus, this study proposes to estimate the air temperature from 28 explanatory variables, using multiple linear regressions. The innovation of this study is to integrate variables from remote sensing into the model in addition to the variables traditionally used like the ones from the Land Use Land Cover. The contribution of spectral indices is significant and makes it possible to improve the quality of the prediction model. However, modeling errors are still present. Their locations and magnitudes are analyzed. However, although the results provided by modelling are of good quality in most cases, particularly thanks to the introduction of explanatory variables from remote sensing, this can never replace dense networks of ground-based measurements. Nevertheless, the methodology presented, applicable to any territory and not requiring specific computer resources, can be highly useful in many fields, particularly for urban planners.

scholarly journals Detection of Urban Areas using Genetic Algorithms and Kohonen Maps on Multispectral images

2018 ◽  
Vol 8 (1) ◽  
pp. 46-62 ◽  
Author(s):  
Djelloul Mokadem ◽  
Abdelmalek Amine ◽  
Zakaria Elberrichi ◽  
David Helbert
Keyword(s):  
Remote Sensing ◽  
Genetic Algorithms ◽  
Urban Areas ◽  
Satellite Image ◽  
Initial Population ◽  
Landsat Images ◽  
Kohonen Maps ◽  
Multispectral Satellite Image

In this article, the detection of urban areas on satellite multispectral Landsat images. The goal is to improve the visual interpretations of images from remote sensing experts who often remain subjective. Interpretations depend deeply on the quality of segmentation which itself depends on the quality of samples. A remote sensing expert must actually prepare these samples. To enhance the segmentation process, this article proposes to use genetic algorithms to evolve the initial population of samples picked manually and get the most optimal samples. These samples will be used to train the Kohonen maps for further classification of a multispectral satellite image. Results are obtained by injecting genetic algorithms in sampling phase and this paper proves the effectiveness of the proposed approach.

Efficacy of slow-release system for improving the quality of water in streams affected by mining activities

2020 ◽  
Author(s):  
Eung Seok Lee ◽  
Ryan Wolbert
Keyword(s):  
Mine Drainage ◽  
Slow Release ◽  
Cost Effective ◽  
Ecological Impacts ◽  
Polluted Water ◽  
Narrow Channels ◽  
Quality Of Water ◽  
Cost Effective Approach ◽  
Effective Manner

<p>Acid mine drainage (AMD) is considered as one of the most prevalent environmental problems worldwide and remediation of AMD-affected streams remains a major challenge due to the large affected areas, large volume of polluted water, poor accessibility, and lack of financial supports. Advanced oxidation processes (AOPs) have been widely investigated as potential remedial options for contaminated water bodies of variety of settings, such as groundwater and waste discharges. This study presents a novel cost-effective approach for utilizing AOPs on improving quality of AMD-affected streams. Slow-release cylinders and pellets were created using polymeric binder and reagent salts that release strong oxidant and alkalinity upon dissolution in water. Results of column tests demonstrated that release durations were over 29 days and up to 100% iron removal was achieved within 20 minutes. Field-scale slow-release forms were manufactured and applied to an AMD site in southeast Ohio, USA for a 29-day demonstration study. Narrow channels were constructed for installation of slow-release forms and characterization of quality and flow of mine seeps and AMD stream during low subsurface flow periods. Results of field investigations suggest that the slow-release forms can be used to rapidly remove metals from AMD, as well as improve water parameters such as pH and minimize ecological impacts of remediation within the system in cost-effective manner.</p><p> </p>

scholarly journals Endoscopy of Nasopharyngeal Cancer

1994 ◽  
Vol 1 (2) ◽  
pp. 63-68 ◽  
Author(s):  
Brian B. Burkey ◽  
Robert H. Ossoff
Keyword(s):  
Quality Of Life ◽  
High Risk ◽  
High Resolution ◽  
Local Anesthesia ◽  
Nasopharyngeal Cancer ◽  
Cost Effective ◽  
Cost Effective Approach ◽  
The World

Nasopharyngeal cancer (NPC) is a unique disease with increasing interest for many physicians due to its unusual etiology, histology, and epidemiology. The recent era of fiberoptic endoscopy now provides the clinician with better tools for the screening, diagnosis, staging, and follow-up of NPC. The use of high resolution flexible and rigid nasopharyngoscopy gives the physician an opportunity for a more sensitive examination in a higher proportion of patients. Ultimately, this will allow for earlier diagnosis of NPC, and improved prognosis and better quality of life for the patients with this disease. Also, by allowing the clinician to perform directed biopsies of the nasopharynx under local anesthesia, fiberoptic nasopharyngoscopy allows a less morbid and more cost-effective approach towards this disease, including screening protocols in certain high risk regions of the world.

scholarly journals A REVIEW ON SPATIAL QUALITY ASSESSMENT METHODS FOR EVALUATION OF PAN-SHARPENED SATELLITE IMAGERY

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 255-261
Author(s):  
F. Dadras Javan ◽  
F. Samadzadegan ◽  
S. Mehravar ◽  
A. Toosi
Keyword(s):  
Remote Sensing ◽  
Quality Assessment ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Large Scale ◽  
Spatial Distortion ◽  
Sensing Applications ◽  
Fused Image ◽  
Spatial Quality

Abstract. Nowadays, high-resolution fused satellite imagery is widely used in multiple remote sensing applications. Although the spectral quality of pan-sharpened images plays an important role in many applications, spatial quality becomes more important in numerous cases. The high spatial quality of the fused image is essential for extraction, identification and reconstruction of significant image objects, and will result in producing high-quality large scale maps especially in the urban areas. This paper introduces the most sensitive and effective methods in detecting the spatial distortion of fused images by implementing a number of spatial quality assessment indices that are utilized in the field of remote sensing and image processing. In this regard, in order to recognize the ability of quality assessment indices for detecting the spatial distortion quantity of fused images, input images of the fusion process are affected by some intentional spatial distortions based on non-registration error. The capabilities of the investigated metrics are evaluated on four different fused images derived from Ikonos and WorldView-2 initial images. Achieved results obviously explicate that two methods namely Edge Variance Distortion and the spatial component of QNR metric called Ds are more sensitive and responsive to the imported errors.

scholarly journals Carnivore occurrence: do interview-based surveys produce unreliable results?

Oryx ◽  
2016 ◽  
Vol 51 (2) ◽  
pp. 240-245 ◽  
Author(s):  
N. Caruso ◽  
E. Luengos Vidal ◽  
M. Guerisoli ◽  
M. Lucherini
Keyword(s):  
Puma Concolor ◽  
Cost Effective ◽  
Camera Traps ◽  
Local People ◽  
Wildlife Ecology ◽  
Cost Effective Approach ◽  
Elusive Species ◽  
Different Characteristics ◽  
High Degree

AbstractInterviews with local people have been widely used by biologists as a cost-effective approach to studying certain topics in wildlife ecology and conservation. However, doubts still exist about the validity and quality of the information gathered, especially in studies targeting cryptic or elusive species, such as carnivores. We assessed the reliability of interviews (n = 155) in detecting the presence of three species of carnivores with different characteristics, by comparing interview results with data obtained through camera trapping surveys at 52 sites in central Argentina. The degree of concordance between methods was low for Geoffroy's cat Leopardus geoffroyi and especially for the puma Puma concolor. However, Geoffroy's cats were detected more frequently by camera traps than interviews, whereas the opposite was true for pumas. For the pampas fox Pseudalopex gymnocercus, a less elusive species, we observed a high degree of concordance and a similar probability of occurrence between methods. Our results indicate that data obtained by interviewing local inhabitants should be used with caution because the information about species presence provided by local people may be inaccurate and biased.

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