scholarly journals Synthesis of Vegetation Indices Using Genetic Programming for Soil Erosion Estimation

2019 ◽  
Vol 11 (2) ◽  
pp. 156 ◽  
Author(s):  
Cesar Puente ◽  
Gustavo Olague ◽  
Mattia Trabucchi ◽  
P. Arjona-Villicaña ◽  
Carlos Soubervielle-Montalvo
Keyword(s):  
Genetic Programming ◽  
Vegetation Indices ◽  
Erosion Rates ◽  
Novel Approach ◽  
Erosion Models ◽  
Green Vegetation ◽  
Dead Vegetation ◽  
Computer Optimization ◽  
Factor C ◽  
Spectral Channels

Vegetation Indices (VIs) represent a useful method for extracting vegetation information from satellite images. Erosion models like the Revised Universal Soil Loss Equation (RUSLE), employ VIs as an input to determine the RUSLE soil Cover factor (C). From the standpoint of soil conservation planning, the C factor is one of the most important RUSLE parameters because it measures the combined effect of all interrelated cover and management variables. Despite its importance, the results are generally incomplete because most indices recognize healthy or green vegetation, but not senescent, dry or dead vegetation, which can also be an important contributor to C. The aim of this research is to propose a novel approach for calculating new VIs that are better correlated with C, using field and satellite information. The approach followed by this research is to state the generation of new VIs in terms of a computer optimization problem and then applying a machine learning technique, named Genetic Programming (GP), which builds new indices by iteratively recombining a set of numerical operators and spectral channels until the best composite operator is found. Experimental results illustrate the efficiency and reliability of this approach to estimate the C factor and the erosion rates for two watersheds in Baja California, Mexico, and Zaragoza, Spain. The synthetic indices calculated using this methodology produce better approximation to the C factor from field data, when compared with state-of-the-art indices, like NDVI and EVI.

scholarly journals Object-Based Change Detection in the Cerrado Biome Using Landsat Time Series

2019 ◽  
Vol 11 (5) ◽  
pp. 570 ◽  
Author(s):  
Inacio Bueno ◽  
Fausto Acerbi Júnior ◽  
Eduarda Silveira ◽  
José Mello ◽  
Luís Carvalho ◽  
...  
Keyword(s):  
Time Series ◽  
Change Detection ◽  
Seasonal Changes ◽  
Vegetation Indices ◽  
Detection Methods ◽  
Object Based Image Analysis ◽  
Spectral Bands ◽  
Object Based ◽  
Shortwave Infrared ◽  
Spectral Channels

Change detection methods are often incapable of accurately detecting changes within time series that are heavily influenced by seasonal variations. Techniques for de-seasoning time series or methods that apply the spatial context have been used to improve the results of change detection. However, few studies have explored Landsat’s shortwave infrared channel (SWIR 2) to discriminate between seasonal changes and land use/land cover changes (LULCC). Here, we explored the effectiveness of Operational Land Imager (OLI) spectral bands and vegetation indices for detecting deforestation in highly seasonal areas of Brazilian savannas. We adopted object-based image analysis (OBIA), applying a multidate segmentation to an OLI time series to generate input data for discrimination of deforestation from seasonal changes using the Random Forest (RF) algorithm. We found adequate separability between deforested objects and seasonal changes using SWIR 2. Using spectral indices computed from SWIR 2, the RF algorithm generated a change map with an overall accuracy of 88.3%. For deforestation, the producer’s accuracy was 88.0% and the user’s accuracy was 84.6%. The SWIR 2 channel as well as the mid-infrared burn index presented the highest importance among spectral variables computed by the RF average impurity decrease measure. Our results give support to further change detection studies regarding to suitable spectral channels and provided a useful foundation for savanna change detection using an object-based method applied to Landsat time series.

scholarly journals Computer-aided detection of screening breast cancer: a novel approach based on genetic programming

2012 ◽  
Vol 14 (S1) ◽  
Author(s):  
F Canavan ◽  
S Harding ◽  
L Gustard ◽  
AM Murphy ◽  
JF Miller ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Genetic Programming ◽  
Computer Aided Detection ◽  
Novel Approach ◽  
Computer Aided

A novel approach for estimation of solvent activity in polymer solutions using genetic programming

Calphad ◽  
2015 ◽  
Vol 51 ◽  
pp. 35-41 ◽  
Author(s):  
Akbar Asadi Tashvigh ◽  
Farzin Zokaee Ashtiani ◽  
Mohammad Karimi ◽  
Ahmad Okhovat
Keyword(s):  
Genetic Programming ◽  
Polymer Solutions ◽  
Novel Approach ◽  
Solvent Activity

scholarly journals OSL rock surface exposure dating as a novel approach for reconstructing transport histories of coastal boulders over decadal to centennial timescales

2020 ◽  
Author(s):  
Dominik Brill ◽  
Simon Matthias May ◽  
Nadia Mhammdi ◽  
Georgina King ◽  
Christoph Burow ◽  
...  
Keyword(s):  
Local Source ◽  
Rock Surface ◽  
Surface Exposure Dating ◽  
Erosion Rates ◽  
Exposure Dating ◽  
Relative Chronology ◽  
Novel Approach ◽  
Calibration Samples ◽  
Exposure Ages ◽  
Boulder Deposits

Abstract. Wave-transported boulders represent important records of storm and tsunami impact over geological timescales. Their use for hazard assessment requires chronological information that in many cases cannot be achieved by established dating approaches. To fill this gap, this study investigated, for the first time, the potential of optically stimulated luminescence rock surface exposure dating (OSL-RSED) for estimating transport ages of wave-emplaced coastal boulders. The approach was applied to calcarenite clasts at the Rabat coast, Morocco. Calibration of the OSL-RSED model was based on samples with rock surfaces exposed to sunlight for ~ 2 years, and OSL exposure ages were evaluated against age control deduced from satellite images. Our results show that the dating precision is limited for all boulders due to the local source rock lithology which has low amounts of quartz and feldspar. The dating accuracy may be affected by erosion rates on boulder surfaces of 0.06–0.2 mm/year. Nevertheless, we propose a robust relative chronology for boulders that are not affected by significant post-depositional erosion and that share surface angles of inclination with the calibration samples. The relative chronology indicates that (i) most boulders were moved by storm waves; (ii) these storms lifted boulders with masses of up to ~ 40 t; and (iii) the role of storms for the formation of boulder deposits along the Rabat coast is much more significant than previously assumed. Although OSL-RSED cannot provide reliable absolute exposure ages for the coastal boulders in this study, the approach has large potential for boulder deposits composed of rocks with larger amounts of quartz or feldspar, older formation histories and less susceptibility to erosion.

scholarly journals Assessing Drought Vegetation Dynamics in Semiarid Grass- and Shrubland Using MESMA

2021 ◽  
Vol 13 (19) ◽  
pp. 3840
Author(s):  
Rowan L. Converse ◽  
Christopher D. Lippitt ◽  
Caitlin L. Lippitt
Keyword(s):  
New Mexico ◽  
Vegetation Dynamics ◽  
Vegetation Indices ◽  
Model Parameters ◽  
Drought Event ◽  
Soil Fractions ◽  
Western Us ◽  
Green Vegetation ◽  
Historic Data ◽  
Spectral Mixture

Drought intensity and duration are expected to increase over the coming century in the semiarid western United States due to anthropogenic climate change. Historic data indicate that megadroughts in this region have resulted in widespread ecosystem transitions. Landscape-scale monitoring with remote sensing can help land managers to track these changes. However, special considerations are required: traditional vegetation indices such as NDVI often underestimate vegetation cover in semiarid systems due to short and multimodal green pulses, extremely variable rainfall, and high soil fractions. Multi-endmember spectral mixture analysis (MESMA) may be more suitable, as it accounts for both green and non-photosynthetic soil fractions. To determine the suitability of MESMA for assessing drought vegetation dynamics in the western US, we test multiple endmember selection and model parameters for optimizing the classification of fractional cover of green vegetation (GV), non-photosynthetic vegetation (NPV), and soil (S) in semiarid grass- and shrubland in central New Mexico. Field spectra of dominant vegetation species were collected at the Sevilleta National Wildlife Refuge over six field sessions from May–September 2019. Landsat Thematic Mapper imagery from 2009 (two years pre-drought), and Landsat Operational Land Imager imagery from 2014 (final year of drought), and 2019 (five years post-drought) was unmixed. The best fit model had high levels of agreement with reference plots for all three classes, with R2 values of 0.85 (NPV), 0.67 (GV), and 0.74 (S) respectively. Reductions in NPV and increases in GV and S were observed on the landscape after the drought event, that persisted five years after a return to normal rainfall. Results indicate that MESMA can be successfully applied for monitoring changes in relative vegetation fractions in semiarid grass and shrubland systems in New Mexico.

A Numerical Study on Erosion Model Selection and Effect of Pump Type and Sand Characters in Electrical Submersible Pumps by Sandy Flow

2019 ◽  
Vol 141 (12) ◽  
Author(s):  
Haiwen Zhu ◽  
Jianjun Zhu ◽  
Risa Rutter ◽  
Hong-Quan Zhang
Keyword(s):  
Particle Density ◽  
Numerical Study ◽  
Petroleum Industry ◽  
Affecting Factors ◽  
Discrete Phase Model ◽  
Erosion Model ◽  
Erosion Rates ◽  
Artificial Lift ◽  
Erosion Models ◽  
Electrical Submersible Pumps

AbstractThe electrical submersible pump (ESP) is one of the most widely used artificial lift methods in the petroleum industry. Although not recommended to be used in sand production well, ESP is still applicable in high producing well with a minimal percentage of solid concentration. Besides, the temporarily produced fracture sand from the proppant backflow can also severely reduce ESP boosting ability in weeks or months. Therefore, it is crucial to study the wear in ESP stages under sandy flow condition. Various erosion equations and models were developed for different materials and affecting factors. However, the predictions of these erosion models in ESPs need to be evaluated to make a proper selection. Comparisons of wear patterns and erosion rates were conducted using the computational fluid dynamics (CFD) software ANSYS. In order to validate the simulation results, an experimental facility was designed and constructed to study the sand erosion process in an ESP. Stages were painted to obtain erosion patterns, and the weight loss was measured. Six erosion models were implemented in the simulations to select the most accurate one in predicting ESP erosion rates. Then, three ESPs, including two mixed-type pumps and one radial-type pump, were modeled to study the effect of pump types with the selected erosion model. Finally, the steady-state discrete phase model (DPM) erosion simulations were carried out to investigate particle density and size effects.

Benchmark Study of CFD-Based Prediction Accuracy of the Models Evaluating Particle and Droplet Induced Erosion for Engineering Applications

2020 ◽  
Author(s):  
Shaoxiang Qian ◽  
Shinichiro Kanamaru
Keyword(s):  
Experimental Data ◽  
Prediction Accuracy ◽  
Erosion Rate ◽  
Solid Particles ◽  
Experimental Results ◽  
Liquid Droplets ◽  
Counter Measures ◽  
Erosion Rates ◽  
Benchmark Study ◽  
Erosion Models

Abstract The particles (including solid particles and liquid droplets) existing in multi-phase flow in process plants can cause erosion due to flow turbulence, and thus, result in pipe wall thinning. Hence, it is important to evaluate erosion rate for determining design margin and finding counter-measures. Many models have been proposed for predicting particles induced erosion rate, but there is significant disparity in their prediction accuracy. The present study aims to verify prediction accuracy of some major erosion models utilizing the published experimental data, for applications to engineering. CFD benchmark study was conducted for three different piping geometries to investigate prediction accuracy of solid particle induced erosion rates for five major erosion models. CFD results show that the erosion rates predicted by Grant & Tabakoff model are closest to the experimental results with acceptable prediction accuracy for applications to engineering. Also, CFD benchmark study was also performed to verify the prediction accuracy of droplet induced erosion rates for three erosion models, utilizing the published experimental data. CFD results show that the erosion rates predicted by Haugen model for all the water impingement velocities are closest to the experimental results with acceptable prediction accuracy for applications to engineering.

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