Preventing the saturation phenomenon of detectors used in environmental remote sensing

2015 ◽  
Author(s):  
Abdelkrim Kedadra ◽  
Mohammed Traïche
Keyword(s):  
Remote Sensing ◽  
Saturation Phenomenon ◽  
Environmental Remote Sensing

Testbed architecture for rapid prototyping and assessment of environmental remote sensing algorithms

2004 ◽  
Author(s):  
T. Scott Zaccheo ◽  
John Galantowicz ◽  
David B. Hogan ◽  
Edward J. Kennelly ◽  
Hilary E. Snell
Keyword(s):  
Remote Sensing ◽  
Rapid Prototyping ◽  
Environmental Remote Sensing

scholarly journals A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing

2020 ◽  
Vol 32 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Sha Huang ◽  
Lina Tang ◽  
Joseph P. Hupy ◽  
Yang Wang ◽  
Guofan Shao
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Unmanned Aerial Systems ◽  
Atmospheric Effect ◽  
Saturation Phenomenon ◽  
Near Ir ◽  
Critical Problems ◽  
Low Costs ◽  
Aerial Systems

AbstractThe Normalized Difference Vegetation Index (NDVI), one of the earliest remote sensing analytical products used to simplify the complexities of multi-spectral imagery, is now the most popular index used for vegetation assessment. This popularity and widespread use relate to how an NDVI can be calculated with any multispectral sensor with a visible and a near-IR band. Increasingly low costs and weights of multispectral sensors mean they can be mounted on satellite, aerial, and increasingly—Unmanned Aerial Systems (UAS). While studies have found that the NDVI is effective for expressing vegetation status and quantified vegetation attributes, its widespread use and popularity, especially in UAS applications, carry inherent risks of misuse with end users who received little to no remote sensing education. This article summarizes the progress of NDVI acquisition, highlights the areas of NDVI application, and addresses the critical problems and considerations in using NDVI. Detailed discussion mainly covers three aspects: atmospheric effect, saturation phenomenon, and sensor factors. The use of NDVI can be highly effective as long as its limitations and capabilities are understood. This consideration is particularly important to the UAS user community.

Close-range environmental remote sensing with 3D hyperspectral technologies

2016 ◽  
Author(s):  
O. Nevalainen ◽  
E. Honkavaara ◽  
T. Hakala ◽  
Sanna Kaasalainen ◽  
N. Viljanen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Close Range ◽  
Environmental Remote Sensing

Dengue early warning systems using environmental remote sensing data

2020 ◽  
Author(s):  
Zahidur Rahman ◽  
Leonid Roytman ◽  
Abdelhamid Kadik ◽  
Dilara A. Rosy ◽  
Pradipta Nandi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Early Warning ◽  
Remote Sensing Data ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Sensing Data ◽  
Environmental Remote Sensing

scholarly journals Meteorological, environmental remote sensing and neural network analysis of the epidemiology of malaria transmission in Thailand

2006 ◽  
Vol 1 (1) ◽  
pp. 71 ◽  
Author(s):  
Richard Kiang ◽  
Farida Adimi ◽  
Valerii Soika ◽  
Joseph Nigro ◽  
Pratap Singhasivanon ◽  
...  
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Network Analysis ◽  
Malaria Transmission ◽  
Neural Network Analysis ◽  
Environmental Remote Sensing
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