Monitoring of selected soil contaminants using proximal and remote sensing techniques: Background, state-of-the-art and future perspectives

2018 ◽  
Vol 48 (3) ◽  
pp. 243-278 ◽  
Author(s):  
Asa Gholizadeh ◽  
Mohammadmehdi Saberioon ◽  
Eyal Ben-Dor ◽  
Luboš Borůvka
2018 ◽  
Vol 216 ◽  
pp. 105-121 ◽  
Author(s):  
Sander Veraverbeke ◽  
Philip Dennison ◽  
Ioannis Gitas ◽  
Glynn Hulley ◽  
Olga Kalashnikova ◽  
...  

1972 ◽  
Vol 1 (13) ◽  
pp. 112
Author(s):  
Donald B. Stafford

aerial remote sensing techniques and provides a current state of the art summary of the utilization of aerial remote sensors in coastal engineering studies. The sensors' discussed include conventional black and white aerial photographs, black and white infrared aerial photographs, color and color infrared aerial photographs, multispectral aerial photographs, satellite photographs, infrared imagery, multispectral imagery, and radar imagery. The field of coastal engineering is considered in a broad context to include all important applications of aerial remote sensing that relate to coastal engineering problems. The use of remote sensors to monitor coastal changes, study coastal landforms, examine storm effects, map coastal areas, determine nearshore hydrography, and monitor the environmental effects of coastal engineering projects, a topic of considerable current concern, is described. The important characteristics of the various aerial remote sensors are described briefly. The advantages and limitations of the aerial remote sensing techniques for different coastal engineering studies are noted. The review and state of the art summary of the applications of the aerial remote sensors can be used by coastal engineers as guidelines in employing the sensors in future coastal engineering investigations.


Author(s):  
Cristiano Capellani Quaresma ◽  
Edson Aparecida de Araujo Querido Oliveira

The article starts from the premise that cities are constituted in complex systems, so that its study, through the systemic approach, encounters three difficulties. Among these, the availability of technological instrumentation applied to research and which favors the obtaining and analysis of reality data stands out. In this context, remote sensing techniques are inserted, which have been increasingly applied in urban studies. Thus, the present article aims to present the state of the art of the use of remote sensing in urban studies, having the phenomenon of the Heat Island and the monitoring of water quality as thematic focus. In methodological terms, this article is a narrative, non-systematic and qualitative review, carried out based on the analysis of the literature, from books and articles in international journals. It is expected that the present material will contribute to the updating of knowledge, as well as to highlight the importance of the topic addressed in the academic environment.


Author(s):  
Pedro Perez Cutillas ◽  
Gonzalo G. Barberá ◽  
Carmelo Conesa García

El objetivo principal de este trabajo se centra en la determinación y análisis de las variables ambientales que influyen en las divergencias de las estimaciones de erosionabilidad a partir de dos métodos, aplicando tres algoritmos de estimación del Factor K. La exploración de esta información permite conocer el peso que ejerce el origen de los datos de entrada a los modelos en el cómputo de erosionabilidad y qué importancia tiene en función del algoritmo elegido para la estimación del Factor K. Los resultados muestran que las pendientes, así como los índices de vegetación (NDVI) y de composición mineralógico (IOI) obtenidos mediantes técnicas de teledetección han   mostrado los valores de asociación más elevados entre ambos métodos.The main goal of this work is to determine and analyze the influence of environmental variables on the changes of two erodibility methods, through the application of three estimation algorithms of K Factor. The analysis of this information allows knowing the significance of the input data to the models in the erodibility estimation, and likewise the consequence of the algorithm selected for the estimation of K Factor. The results show that the slopes, as well as the vegetation index (NDVI) and the mineralogical composition index (IOI), generated both by remote sensing techniques, have shown the highest values of association between methods.


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