CO emission datasets and maps from Remote Sensing: spatial and statistical comparison at different levels

2012 ◽  
pp. 69-81
Author(s):  
Federica Migliaccio
Keyword(s):  
Remote Sensing ◽  
Statistical Comparison ◽  
Different Levels ◽  
Co Emission

scholarly journals Monitoring Bemisia tabaci Gennadius (Hemiptera: Aleyrodidae) Infestation in Soybean Using Hyperspectral Remote Sensing

2020 ◽  
Author(s):  
Pedro P. S. Barros ◽  
Inana X. Schutze ◽  
Fernando H. Iost Filho ◽  
Pedro Takao Yamamoto ◽  
Peterson Fiorio ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Bemisia Tabaci ◽  
Insect Pest ◽  
Remote Sensing Data ◽  
Management Program ◽  
Hyperspectral Remote Sensing ◽  
Negative Effects ◽  
Soybean Plants ◽  
Soybean Leaves ◽  
Different Levels

Although monitoring and observing insect pest populations in the fields is essential in crop management, it is still a laborious and sometimes ineffective process. High infestation levels may diminish the photosynthetic activity of soybean plants, affecting their development and reducing the yield. An imprecise decision making in integrated pest management program may lead to an ineffective control in infested areas or the excessive use of insecticides. In order to reach a more efficient control of arthropods population it is important to evaluate the infestation in time to mitigate its negative effects on the crop and remote sensing is an important tool for monitoring. It was proposed that infested soybean areas could be identified, and the arthropods quantified from non-infested areas in a field by hyperspectral remote sensing. Thus, the goals of this study were to investigate and discriminate the reflectance characteristics of soybean non-infested and infested with Bemisia tabaci using hyperspectral remote sensing data. Therefore, samples of infested and non-infested soybean leaves were collected and transported to the laboratory to obtain the hyperspectral curves. The results obtained allowed to discriminate the different levels of infestation and to separate healthy from whitefly infested soybean leaves based on their reflectance.

scholarly journals A Quantitative Validation of Multi-Modal Image Fusion and Segmentation for Object Detection and Tracking

2021 ◽  
Vol 13 (12) ◽  
pp. 2364
Author(s):  
Nicholas LaHaye ◽  
Michael J. Garay ◽  
Brian D. Bue ◽  
Hesham El-Askary ◽  
Erik Linstead
Keyword(s):  
Remote Sensing ◽  
Reference Data ◽  
Deep Belief Networks ◽  
Remotely Sensed Data ◽  
Output Data ◽  
Detection And Tracking ◽  
Multiple Datasets ◽  
Global Coverage ◽  
Quantitative Validation ◽  
Different Levels

In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global coverage and granularity in order to test our models’ capabilities to represent structure at finer and broader scales, using many different kinds of instrumentation, that can be fused when applicable. In all cases tested, our models show a strong ability to segment the objects within input scenes, use multiple datasets fused together where appropriate to improve results, and, at times, outperform the pre-existing datasets. The success here will allow this methodology to be used within use concrete cases and become the basis for future dynamic object tracking across datasets from various remote sensing instruments.

Regional CO emission estimated from ground-based remote sensing at Hefei site, China

2019 ◽  
Vol 222 ◽  
pp. 25-35 ◽  
Author(s):  
Changgong Shan ◽  
Wei Wang ◽  
Cheng Liu ◽  
Youwen Sun ◽  
Qihou Hu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Co Emission

CO Emission vs HI Self-Absorption

1983 ◽  
Vol 5 (2) ◽  
pp. 224-227 ◽  
Author(s):  
William L. Peters ◽  
Frank N. Bash
Keyword(s):  
Atomic Hydrogen ◽  
Molecular Clouds ◽  
Galactic Center ◽  
Galactic Plane ◽  
The Sun ◽  
Statistical Comparison ◽  
Initial Results ◽  
Co Emission

We present the initial results of a statistical comparison of CO emission and H I self-absorption in the galactic plane at large distances from the Sun. Evidence for self-absorption by cold atomic hydrogen (Ts < 60 K) over angular scales of 3 ´-20´ was reported by Baker and Burton (1979). They suggested that this hydrogen was associated with the molecular clouds of the ‘molecular ring’ located between 4 and 8 kpc from the galactic center (Burton and Gordon 1978). Burton, Lizst, and Baker (1978) did find a correspondence between CO emission and H I self-absorption; however, their observations were not extensive enough to prove that the correspondence was statistically significant or to test their prediction that all instances of H I self-absorption are accompanied by CO emission and thus associated with molecular clouds.

scholarly journals Remote sensing and GIS application in assessing the adaptability of some key crops in Dak Nong province

2022 ◽  
Vol 964 (1) ◽  
pp. 012003
Author(s):  
Nguyen Thi Thanh Huong ◽  
Ho Dinh Bao ◽  
Cao Thi Hoai ◽  
Phan Thi Hang ◽  
Ngo The Son ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Scientific Information ◽  
Adaptation Level ◽  
Site Conditions ◽  
Crop Species ◽  
Soil Thickness ◽  
Gis Application ◽  
Rs And Gis ◽  
Natural Factors ◽  
Different Levels

Abstract Remote sensing (RS) and Geographic information system (GIS) is widely applied in the world and gradually affirms its role in Vietnam in managing agricultural and forest resources. This application is highly effective, providing information timely for managers to make decisions and build development strategies. In this study, RS and GIS were integrated to assess suitability for key crop species in Dak Nong province including coffee, rubber, cashew, and durian based on their suitability to site conditions such as soil (soil type, soil texture, soil thickness), topography (elevation, slope) and climate (temperature, precipitation). Using the restrictive method and overlapping map layers of natural factors, classified into adaptive levels according to FAO (1976). Results show that most land areas in Dak Nong province have different levels of potential suitability for key crop species ranging from non-adaptive to lesst-adaptive and moderately adaptive. However, most suitable areas for key crops are only at low (accounting for a large proportion) and the average adaptation level. The findings from the study are the scientific information for managers to make decisions regarding the structure of major crops in the province.

scholarly journals Multi-Granularity Mission Negotiation for a Decentralized Remote Sensing Satellite Cluster

2020 ◽  
Vol 12 (21) ◽  
pp. 3595
Author(s):  
Xuelei Deng ◽  
Yunfeng Dong ◽  
Shucong Xie
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Lower Cost ◽  
Multi Agent System ◽  
Cost Effectiveness Ratio ◽  
Multi Agent ◽  
New Challenges ◽  
Decentralized Architecture ◽  
Different Levels

Satellite remote sensing is developing towards the micro-satellite cluster, which brings new challenges to mission assignment and planning for the cluster. A multi-agent system (MAS) is used, but the time delay caused by communication and computation is rarely considered. To solve the problem, a neural-network-based multi-granularity negotiation method under decentralized architecture is proposed. Firstly, we divided negotiation into three levels of granularity, and they work in different modes. Secondly, a neural network was trained to help the satellite select the best level in real-time. Through experiments, we compared the satellites working in three different levels of granularity, in which a multi-granularity decision was used. As a result of our experiments, a lower cost-effectiveness ratio was obtained, which proved that the multi-granularity negotiation method proposed in this paper is practical.

scholarly journals Lidar Observations in South America. Part I - Mesosphere and Stratosphere

2020 ◽  
Author(s):  
Eduardo Landulfo ◽  
Alexandre Cacheffo ◽  
Alexandre Calzavara Yoshida ◽  
Antonio Arleques Gomes ◽  
Fábio Juliano da Silva Lopes ◽  
...  
Keyword(s):  
Remote Sensing ◽  
South America ◽  
Latin American ◽  
Earth Science ◽  
Large Area ◽  
Developing Area ◽  
Lidar Observations ◽  
Different Levels ◽  
Laser Remote Sensing

South America covers a large area of the globe and plays a fundamental function in its climate change, geographical features, and natural resources. However, it still is a developing area, and natural resource management and energy production are far from a sustainable framework, impacting the air quality of the area and needs much improvement in monitoring. There are significant activities regarding laser remote sensing of the atmosphere at different levels for different purposes. Among these activities, we can mention the mesospheric probing of sodium measurements and stratospheric monitoring of ozone, and the study of wind and gravity waves. Some of these activities are long-lasting and count on the support from the Latin American Lidar Network (LALINET). We intend to pinpoint the most significant scientific achievements and show the potential of carrying out remote sensing activities in the continent and show its correlations with other earth science connections and synergies. In Part I of this chapter, we will present an overview and significant results of lidar observations in the mesosphere and stratosphere. Part II will be dedicated to tropospheric observations.

scholarly journals What contributions of Artificial Intelligence in Innovation?

2021 ◽  
Vol 234 ◽  
pp. 00105
Author(s):  
Yassine Barakat ◽  
Salmane Bourekkadi ◽  
Samira Khoulji ◽  
Mohamed Larbi Kerkeb
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Sustainable Development ◽  
Critical Point ◽  
Robot Control ◽  
Medical Diagnostics ◽  
Review Article ◽  
Point Of View ◽  
The Sustainable Development ◽  
Different Levels

Artificial intelligence has proven its effectiveness through many applications in society: medical diagnostics, e-commerce, robot control and remote sensing. It has been able to advance many fields and industries including finance, education, transportation and others. In this review article, the method adopted consists first of all in collecting and analyzing all the data making it possible to certify the existence of a varying impact of artificial intelligence on the environment and the sustainable development, through the description of the contributions of AI at the level of several approaches carried out and projects carried out recently. Secondly, we drew from the different levels of differential paradigms cited in the first part, a synthesis, a critical point of view, as well as the perspectives that the feedbacks to the various points raised in the critical vision create, in particular those related to the limits of artificial intelligence and its implications for sustainable development.

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