Investigating Error Metrics for Satellite Rainfall Data at Hydrologically Relevant Scales

2008 ◽  
Vol 9 (3) ◽  
pp. 563-575 ◽  
Author(s):  
Faisal Hossain ◽  
George J. Huffman
Keyword(s):  
High Resolution ◽  
Spatial Scales ◽  
The United States ◽  
Space Time ◽  
Probability Of Detection ◽  
Rainfall Data ◽  
True Value ◽  
Error Metrics ◽  
Satellite Rainfall ◽  
New Generation

Abstract This paper addresses the following open question: What set of error metrics for satellite rainfall data can advance the hydrologic application of new-generation, high-resolution rainfall products over land? The authors’ primary aim is to initiate a framework for building metrics that are mutually interpretable by hydrologists (users) and algorithm developers (data producers) and to provide more insightful information on the quality of the satellite estimates. In addition, hydrologists can use the framework to develop a space–time error model for simulating stochastic realizations of satellite estimates for quantification of the implication on hydrologic simulation uncertainty. First, the authors conceptualize the error metrics in three general dimensions: 1) spatial (how does the error vary in space?); 2) retrieval (how “off” is each rainfall estimate from the true value over rainy areas?); and 3) temporal (how does the error vary in time?). They suggest formulations for error metrics specific to each dimension, in addition to ones that are already widely used by the community. They then investigate the behavior of these metrics as a function of spatial scale ranging from 0.04° to 1.0° for the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) geostationary infrared-based algorithm. It is observed that moving to finer space–time scales for satellite rainfall estimation requires explicitly probabilistic measures that are mathematically amenable to space–time stochastic simulation of satellite rainfall data. The probability of detection of rain as a function of ground validation rainfall magnitude is found to be most sensitive to scale followed by the correlation length for detection of rain. Conventional metrics such as the correlation coefficient, frequency bias, false alarm ratio, and equitable threat score are found to be modestly sensitive to scales smaller than 0.24° latitude/longitude. Error metrics that account for an algorithm’s ability to capture rainfall intermittency as a function of space appear useful in identifying the useful spatial scales of application for the hydrologist. It is shown that metrics evolving from the proposed conceptual framework can identify seasonal and regional differences in reliability of four global satellite rainfall products over the United States more clearly than conventional metrics. The proposed framework for building such error metrics can lay a foundation for better interaction between the data-producing community and hydrologists in shaping the new generation of satellite-based, high-resolution rainfall products, including those being developed for the planned Global Precipitation Measurement (GPM) mission.

scholarly journals Flood Risk Assessment and Quantification at the Community and Property Level in the State of Iowa

2021 ◽  
Author(s):  
Enes Yildirim ◽  
Ibrahim Demir
Keyword(s):  
Risk Assessment ◽  
High Resolution ◽  
Flood Risk ◽  
Large Scale ◽  
Spatial Scales ◽  
The United States ◽  
Flood Risk Assessment ◽  
Study Region ◽  
Study Results ◽  
Flood Maps

Flood risk assessment contributes to identifying at-risk communities and supports mitigation decisions to maximize benefits from the investments. Large-scale risk assessments generate invaluable inputs for prioritizing regions for the distribution of limited resources. High-resolution flood maps and accurate parcel information are critical for flood risk analysis to generate reliable outcomes for planning, preparedness, and decision-making applications. Large-scale damage assessment studies in the United States often utilize the National Structure Inventory (NSI) or HAZUS default dataset, which results in inaccurate risk estimates due to the low geospatial accuracy of these datasets. On the other hand, some studies utilize higher resolution datasets, however they are limited to focus on small scales, for example, a city or a Hydrological United Code (HUC)-12 watershed. In this study, we collected extensive detailed flood maps and parcel datasets for many communities in Iowa to carry out a large-scale flood risk assessment. High-resolution flood maps and the most recent parcel information are collected to ensure the accuracy of risk products. The results indicate that the Eastern Iowa communities are prone to a higher risk of direct flood losses. Our model estimates nearly $10 million in average annualized losses, particularly in large communities in the study region. The study highlights that existing risk products based on FEMA's flood risk output underestimate the flood loss, specifically in highly populated urban communities such as Bettendorf, Cedar Falls, Davenport, Dubuque, and Waterloo. Additionally, we propose a flood risk score methodology for two spatial scales (e.g., HUC-12 watershed, property) to prioritize regions and properties for mitigation purposes. Lastly, the watershed-scale study results are shared through a web-based platform to inform the decision-makers and the public.

scholarly journals Evaluation of High-resolution Satellite Rainfall Data over Singapore

2016 ◽  
Vol 154 ◽  
pp. 158-167 ◽  
Author(s):  
Jina Hur ◽  
Srivatsan V. Raghavan ◽  
Ngoc Son Nguyen ◽  
Shie-Yui Liong
Keyword(s):  
High Resolution ◽  
Rainfall Data ◽  
Satellite Rainfall

scholarly journals Accuracy Analysis of IMERG Satellite Rainfall Data and Its Application in Long-term Runoff Simulation

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2177
Author(s):  
Chongxun Mo ◽  
Mingshan Zhang ◽  
Yuli Ruan ◽  
Junkai Qin ◽  
Yafang Wang ◽  
...  
Keyword(s):  
Swat Model ◽  
Probability Of Detection ◽  
Rainfall Data ◽  
Karst Area ◽  
Efficiency Coefficient ◽  
Accuracy Analysis ◽  
Runoff Simulation ◽  
Satellite Rainfall ◽  
Simulation Results

Frequent flood disasters have caused serious damage to karst areas with insufficient measured rainfall data, and the analysis of the applicability of satellite rainfall data in runoff simulation is helpful to the local water management. Therefore, the purpose of this study is to analyze the accuracy of IMERG satellite rainfall data and apply it to long-term runoff simulations in a karst area—the Xiajia River basin, China. First, R (correlation coefficient) and POD (probability of detection) are applied to analyze the accuracy of the IMERG data, and the SWAT model is used for runoff simulation. The results show that the accuracy of the original IMERG data is poor (R range from 0.412 to 0.884 and POD range from 47.33 to 100), and the simulation results are “Unsatisfactory” (NSE (Nash-Sutcliffe efficiency coefficient) ranged from 0.17 to 0.32 and RSR (root mean square standard deviation ratio) ranged from 0.81 to 0.92). Therefore, the GDA correction method is used to correct the original IMERG data, and then the accuracy analysis and runoff simulation are carried out. The results show that the accuracy of the corrected IMERG data is better than that of the original data (R range from 0.886 to 0.987 and POD range from 94.08 to 100), and the simulation results of the corrected IMERG data are “Satisfactory” (NSE is over 0.55 and RSR is approximately 0.65). Therefore, the corrected data have a certain applicability in long-term continuous runoff simulations.

scholarly journals How Has Malaysia Benefited from the High-Resolution Satellite Rainfall? Trends, Gaps and Further Research Opportunities

2019 ◽  
Vol 12 ◽  
pp. 1-11
Author(s):  
Mohd. Rizaludin Mahmud
Keyword(s):  
High Resolution ◽  
Environmental Sustainability ◽  
Rainfall Data ◽  
Tropical Country ◽  
Scientific Review ◽  
Scientific Databases ◽  
Rainfall Trends ◽  
Present Information ◽  
The Status ◽  
Satellite Rainfall

This paper presents a scientific review on how Malaysia has benefited from the high-resolution satellite rainfall since its first launch in 1998. As a tropical country in which the environment is highly characterised by rainfall dynamics, public domain access of high-resolution satellite rainfall data could be very useful to support the hydrologic and related environmental studies. The scope of this paper includes achievements, the trend of studies, as well as gaps and future opportunities for scientific research. Examining this element is crucial in determining the present information on the status quo of the applications of space-based technology to Malaysian hydrologic research. Furthermore, this information is critical to charter the future action for the policymakers and revision of respective disciplines, including climate change, environmental sustainability, disaster resilience, food security, and education. Based on the search throughout the largest scientific databases of Web of Science and Scopus, five major trends have been identified. Those trends were ranked based on the number of research, 1) Satellite rainfall data performance and quality evaluation (40%), 2) Satellite rainfall data as input to environmental modelling (27%), 3) Rain fade & telecommunication (16%), 4) Satellite rainfall data quality improvement (7%), and 5) Rainfall studies. These trends were identified about 11 years after the satellite rainfall project started in 1998. The major achievement till now is validating the accuracy of the satellite rainfall and also downscaling it for local application.

The Contribution of Intermediate-Voltage, High-Resolution Electron Microscopy In Materials Science: An Appraisal

1990 ◽  
Vol 48 (1) ◽  
pp. 478-479
Author(s):  
John L. Hutchison
Keyword(s):  
High Resolution ◽  
Materials Science ◽  
High Resolution Electron Microscopy ◽  
Optical Diffraction ◽  
The Past ◽  
Resolution Electron ◽  
Extreme Sensitivity ◽  
Electron Microscopes ◽  
New Generation ◽  
Small Metal Particles

Over the past five years or so the development of a new generation of high resolution electron microscopes operating routinely in the 300-400 kilovolt range has produced a dramatic increase in resolution, to around 1.6 Å for “structure resolution” and approaching 1.2 Å for information limits. With a large number of such instruments now in operation it is timely to assess their impact in the various areas of materials science where they are now being used. Are they falling short of the early expectations? Generally, the manufacturers’ claims regarding resolution are being met, but one unexpected factor which has emerged is the extreme sensitivity of these instruments to both floor-borne and acoustic vibrations. Successful measures to counteract these disturbances may require the use of special anti-vibration blocks, or even simple oil-filled dampers together with springs, with heavy curtaining around the microscope room to reduce noise levels. In assessing performance levels, optical diffraction analysis is becoming the accepted method, with rotational averaging useful for obtaining a good measure of information limits. It is worth noting here that microscope alignment becomes very critical for the highest resolution.In attempting an appraisal of the contributions of intermediate voltage HREMs to materials science we will outline a few of the areas where they are most widely used. These include semiconductors, oxides, and small metal particles, in addition to metals and minerals.

scholarly journals Object Oriented Classification for Mapping Mixed and Pure Forest Stands Using Very-High Resolution Imagery

2021 ◽  
Vol 13 (13) ◽  
pp. 2508
Author(s):  
Loredana Oreti ◽  
Diego Giuliarelli ◽  
Antonio Tomao ◽  
Anna Barbati
Keyword(s):  
High Resolution ◽  
Spatial Scales ◽  
Parametric Method ◽  
Mixed Forest ◽  
Mixed Stands ◽  
Mapping Unit ◽  
Mixed Forests ◽  
High Resolution Imagery ◽  
Very High Resolution Imagery ◽  
Very High

The importance of mixed forests is increasingly recognized on a scientific level, due to their greater productivity and efficiency in resource use, compared to pure stands. However, a reliable quantification of the actual spatial extent of mixed stands on a fine spatial scale is still lacking. Indeed, classification and mapping of mixed populations, especially with semi-automatic procedures, has been a challenging issue up to date. The main objective of this study is to evaluate the potential of Object-Based Image Analysis (OBIA) and Very-High-Resolution imagery (VHR) to detect and map mixed forests of broadleaves and coniferous trees with a Minimum Mapping Unit (MMU) of 500 m2. This study evaluates segmentation-based classification paired with non-parametric method K- nearest-neighbors (K-NN), trained with a dataset independent from the validation one. The forest area mapped as mixed forest canopies in the study area amounts to 11%, with an overall accuracy being equal to 85% and K of 0.78. Better levels of user and producer accuracies (85–93%) are reached in conifer and broadleaved dominated stands. The study findings demonstrate that the very high resolution images (0.20 m of spatial resolutions) can be reliably used to detect the fine-grained pattern of rare mixed forests, thus supporting the monitoring and management of forest resources also on fine spatial scales.

Validation of EMAT ILI for Management of Stress Corrosion Cracking in Natural Gas Pipelines

2014 ◽  
Author(s):  
Toby Fore ◽  
Stefan Klein ◽  
Chris Yoxall ◽  
Stan Cone
Keyword(s):  
High Resolution ◽  
Natural Gas ◽  
Stress Corrosion ◽  
Stress Corrosion Cracking ◽  
Corrosion Cracking ◽  
Probability Of Detection ◽  
Gas Pipelines ◽  
Line Pipe ◽  
Natural Gas Pipelines ◽  
Electro Magnetic

Managing the threat of Stress Corrosion Cracking (SCC) in natural gas pipelines continues to be an area of focus for many operating companies with potentially susceptible pipelines. This paper describes the validation process of the high-resolution Electro-Magnetic Acoustical Transducer (EMAT) In-Line Inspection (ILI) technology for detection of SCC prior to scheduled pressure tests of inspected line pipe valve sections. The validation of the EMAT technology covered the application of high-resolution EMAT ILI and determining the Probability Of Detection (POD) and Identification (POI). The ILI verification process is in accordance to a API 1163 Level 3 validation. It is described in detail for 30″ and 36″ pipeline segments. Both segments are known to have an SCC history. Correlation of EMAT ILI calls to manual non-destructive measurements and destructively tested SCC samples lead to a comprehensive understanding of the capabilities of the EMAT technology and the associated process for managing the SCC threat. Based on the data gathered, the dimensional tool tolerances in terms of length and depth are derived.

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