scholarly journals Modeling and Characterization of Vegetation, Aquatic and Mineral Surfaces Using the Theory of Plausible and Paradoxical Reasoning from Satellite Images: Case of the Toumodi-Yamoussoukro-Tiébissou Zone in V Baoulé (Côte d’Ivoire)

2017 ◽  
Vol 07 (10) ◽  
pp. 520-536
Author(s):  
Jean-Claude Okaingni ◽  
Sié Ouattara ◽  
Adles Kouassi ◽  
Wognin J. Vangah ◽  
Aubin K. Koffi ◽  
...  
Keyword(s):  
Satellite Images ◽  
Mineral Surfaces

scholarly journals Uso de Técnicas de Geoprocessamento para Estudo da Erosão Hídrica Laminar em Bacia Hidrográfica do Sudoeste do Paraná.

2020 ◽  
Vol 13 (3) ◽  
pp. 1117
Author(s):  
Julio Caetano Tomazoni ◽  
Ana Paula Vansan
Keyword(s):  
Soil Erosion ◽  
Soil Conservation ◽  
Soil Loss ◽  
Satellite Images ◽  
Water Erosion ◽  
Soil Samples ◽  
Universal Equation ◽  
Erosion Rates ◽  
Loss Estimate

Este trabalho tem como objetivo avaliar a erosão hídrica laminar do solo, por meio da Equação Universal de Perdas de Solos Revisada (RUSLE) na bacia hidrográfica do rio São José, localizada no município de Francisco Beltrão (PR).  A perda de solo média anual (A) foi determinada através da RUSLE para os anos 2000, 2005, 2009, 2015 e 2017 utilizando-se técnicas de geoprocessamento com o auxílio do software ArcGis 10.0. O fator erosividade da chuva (R) foi determinado utilizando-se dados pluviométricos correspondentes ao período de 1974 a 2016. O fator erodibilidade do solo (K) foi obtido através da análise de amostras de solo coletadas in loco. O fator topográfico (LS) foi estimado por meio dos dados altimétricos e hidrográficos da bacia. Os fatores de uso e manejo do solo (C) e de práticas conservacionistas do solo (P) foram determinados por meio da caracterização multitemporal do uso e ocupação do solo, através de imagens de satélite. O potencial natural de erosão (PNE) foi determinado pela multiplicação dos fatores R, K e LS.A estimativa de perda de solo (A) foi determinada pela multiplicação do PNE pelos fatores C e P.  Use of Geoprocessing Techniques to Study Laminar Water Erosion in Watershed of Southwest Paraná A B S T R A C TThe objective of this work is evaluate the soil erosion by the Universal Equation of Soil Losses Revised (RUSLE) in the São José river basin, located in the municipality of Francisco Beltrão (PR). The average annual soil loss (A) was determined through RUSLE for the years 2000, 2005, 2009, 2015 and 2017 using geoprocessing techniques with ArcGis 10.0 software. Rainfallerosivity (R) was determined using rainfall data from 1974 to 2016, being determined at 11521.26 11521,26 MJ.mm.ha-1.h-1.year-1. The soil erodibility factor (K) was obtained through the analysis of soil samples collected on the spot (0,03018 t.ha.h/ha.MJ.mm, 0,02771 t.ha.h/ha.MJ.mm e 0,02342 t.ha.h/ha.MJ.mm). The topographic factor (LS) was estimated by the altimetric and hydrographic data of the basin. Soil use and management (C) and soil conservation (P) were determined through multitemporal characterization of land use and occupation, using satellite images. The natural erosion potential (NEP) was determined by multiplying the R, K and LS factors, with more than half of the total area of the watershed with very strong PNE. The soil loss estimate (A) was determined by multiplying the NEP by factors C and P with predominance of the class called low (0 to 10 t/ha/year) denoting the reduction of erosion rates through factors C and P, helping to protect the soil from the erosion process.Key words: Soil Erosion; Watershed, Revised Universal Soil Loss Equation, Geoprocessing, Software.

Heterogeneous Oxidation and Precipitation of Aqueous Mn(II) at the Goethite Surface: A SPM Study

1998 ◽  
Vol 4 (S2) ◽  
pp. 600-601
Author(s):  
John Rakovan ◽  
F. Hochella Michael
Keyword(s):  
Lateral Force ◽  
Atomic Scale ◽  
Scanning Tunneling ◽  
Mineral Surfaces ◽  
Tunneling Microscopy ◽  
Heterogeneous Oxidation ◽  
Force Microscopy ◽  
Solution Interface ◽  
Atomic Force

Since its invention inl982 scanning probe microscopy (SPM) has become an important analytical tool in every branch of physical science. The two most widely used types of SPM are atomic force Microscopy (AFM) and scanning tunneling microscopy (STM). Both AFM and STM allow measurement of the microtopography of a surface down to the atomic scale. Many spin-off applications such as lateral force and magnetic force allow measurement of a variety of the physical properties of a surface while imaging its microtopography. SPM can be done in both air and liquid and hence can be used to observe the interactions that take place at a solid-solution interface.SPM has been used in mineralogy and geochemistry since 1989. Here as in other applications the great strength of SPM is in the characterization of the heterogeneous nature of mineral surfaces and the ability to observe many geochemical processes in real time.

Characterization of Submesoscale Turbulence in the East/Japan Sea Using Geostationary Ocean Color Satellite Images

2019 ◽  
Vol 46 (14) ◽  
pp. 8214-8223 ◽  
Author(s):  
J. Choi ◽  
Y.‐G. Park ◽  
W. Kim ◽  
Y. H. Kim
Keyword(s):  
Satellite Images ◽  
Ocean Color ◽  
Japan Sea

scholarly journals Fine-Grained Large-Scale Vulnerable Communities Mapping via Satellite Imagery and Population Census Using Deep Learning

2021 ◽  
Vol 13 (18) ◽  
pp. 3603
Author(s):  
Joaquín Salas ◽  
Pablo Vera ◽  
Marivel Zea-Ortiz ◽  
Elio-Atenogenes Villaseñor ◽  
Dagoberto Pulido ◽  
...  
Keyword(s):  
Large Scale ◽  
Satellite Images ◽  
Census Data ◽  
Population Census ◽  
Fine Grained ◽  
Vulnerable Communities ◽  
Landsat 7 ◽  
Block Level ◽  
Definition Of

One of the challenges in the fight against poverty is the precise localization and assessment of vulnerable communities’ sprawl. The characterization of vulnerability is traditionally accomplished using nationwide census exercises, a burdensome process that requires field visits by trained personnel. Unfortunately, most countrywide censuses exercises are conducted only sporadically, making it difficult to track the short-term effect of policies to reduce poverty. This paper introduces a definition of vulnerability following UN-Habitat criteria, assesses different CNN machine learning architectures, and establishes a mapping between satellite images and survey data. Starting with the information corresponding to the 2,178,508 residential blocks recorded in the 2010 Mexican census and multispectral Landsat-7 images, multiple CNN architectures are explored. The best performance is obtained with EfficientNet-B3 achieving an area under the ROC and Precision-Recall curves of 0.9421 and 0.9457, respectively. This article shows that publicly available information, in the form of census data and satellite images, along with standard CNN architectures, may be employed as a stepping stone for the countrywide characterization of vulnerability at the residential block level.

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