A remote sensing satellite observation scheme evaluation method based on granular computing of intuitionistic linguistic preference relation

2021 ◽  
Author(s):  
Xiaoxuan Hu ◽  
Yanjun Wang ◽  
Haiquan Sun ◽  
Peng Jin
Keyword(s):  
Remote Sensing ◽  
Granular Computing ◽  
Evaluation Method ◽  
Preference Relation ◽  
Satellite Observation ◽  
Linguistic Preference Relation ◽  
Remote Sensing Satellite ◽  
Scheme Evaluation ◽  
Observation Scheme

Remote sensing in coastal water monitoring: Applications in the eastern Mediterranean Sea (IUPAC Technical Report)

2011 ◽  
Vol 84 (2) ◽  
pp. 335-375 ◽  
Author(s):  
Manos Dassenakis ◽  
Vasiliki Paraskevopoulou ◽  
Constantinos Cartalis ◽  
Nektaria Adaktilou ◽  
Katerina Katsiabani
Keyword(s):  
Remote Sensing ◽  
Mediterranean Sea ◽  
Forest Fires ◽  
Land Surface ◽  
Oil Spills ◽  
Environmental Concern ◽  
Eastern Mediterranean ◽  
Satellite Observation ◽  
Habitat Destruction ◽  
Remote Sensing Satellite

Remote sensing/satellite observation of land and oceans is a field of research that was developed during the second half of the 20th century, and its importance is widely recognised because of the amount of information it can provide to the scientific community and the general public. The outcomes of remote sensing/satellite observation can be used to address and study significant aspects of environmental concern, such as habitat destruction, environmental degradation, forest fires, oil spills, and climate change. There is continuous improvement of the methods and means of remote sensing observations in order to achieve more accurate and useful information. The main advantage is the possibility of observing large areas, and the main disadvantage is that it can observe only the water and land surface. The present paper is an effort to review the technologies used in remote sensing and the general applications in a comprehensive manner addressed to scientists who do not specialize in this area of research. Furthermore, this paper reviews case studies/applications in the Mediterranean Sea, an area affected by various polluting activities (industrial cities, agriculture, shipping, etc.) that should be continuously monitored so that the coastal countries are able to successfully manage this sensitive environment.

Expected consistency-based model and multiplicative DEA cross-efficiency for group decision-making with incomplete distribution linguistic preference relations

2021 ◽  
pp. 1-21
Author(s):  
Jinpei Liu ◽  
Longlong Shao ◽  
Ligang Zhou ◽  
Feifei Jin
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Optimization Model ◽  
Group Decision ◽  
Preference Relation ◽  
Preference Relations ◽  
Priority Vector ◽  
Linguistic Preference Relation ◽  
Multiplicative Preference Relations ◽  
High Consistency

Faced with complex decision problems, Distribution linguistic preference relation (DLPR) is an effective way for decision-makers (DMs) to express preference information. However, due to the complexity of the decision-making environment, DMs may not be able to provide complete linguistic distribution for all linguistic terms in DLPRs, which results in incomplete DLPRs. Therefore, in order to solve group decision-making (GDM) with incomplete DLPRs, this paper proposes expected consistency-based model and multiplicative DEA cross-efficiency. For a given incomplete DLPRs, we first propose an optimization model to obtain complete DLPR. This optimization model can evaluate the missing linguistic distribution and ensure that the obtained DLPR has a high consistency level. And then, we develop a transformation function that can transform DLPRs into multiplicative preference relations (MPRs). Furthermore, we design an improved multiplicative DEA model to obtain the priority vector of MPR for ranking all alternatives. Finally, a numerical example is provided to show the rationality and applicability of the proposed GDM method.

scholarly journals Modeling and Simulation of Mission Planning Problem for Remote Sensing Satellite Imaging

2018 ◽  
Vol 179 ◽  
pp. 03024 ◽  
Author(s):  
Yao Pan ◽  
Zhong Ming Chi ◽  
Qi Long Rao ◽  
Kai Peng Sun ◽  
Yi Nan Liu
Keyword(s):  
Remote Sensing ◽  
Time Window ◽  
Constraint Satisfaction Problem ◽  
Optimal Path ◽  
Time Constraint ◽  
Mission Planning ◽  
Planning Problem ◽  
Satellite Imaging ◽  
Problem Model ◽  
Remote Sensing Satellite

Mission planning problem for remote sensing satellite imaging is studied. Firstly, the time constraint satisfaction problem model is presented after analyzing the characteristic of time constraint. Then, An optimal path searching algorithm based on the discrete time window is proposed according to the non-uniqueness for satellite to mission in the visible time window. Simulation results verify the efficiency of the model and algorithm.

scholarly journals Observation of Oceanic Eddy in the Northeastern Arabian Sea Using Multisensor Remote Sensing Data

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
R. K. Sarangi
Keyword(s):  
Remote Sensing ◽  
Arabian Sea ◽  
Chlorophyll Concentration ◽  
Climatic Conditions ◽  
Late Winter ◽  
Surrounding Water ◽  
Noaa Avhrr ◽  
Oceanic Eddy ◽  
Remote Sensing Satellite ◽  
Cold Core

An oceanic eddy of size about 150 kilometer diameter observed in the northeastern Arabian Sea using remote sensing satellite sensors; IRS-P4 OCM, NOAA-AVHRR and NASA Quickscat Scatterometer data. The eddy was detected in the 2nd week of February in Indian Remote Sensing satellite (IRS-P4) Ocean Color Monitor (OCM) sensor retrieved chlorophyll image on 10th February 2002, between latitude 16°90′–18°50′N and longitude 66°05′–67°60′E. The chlorophyll concentration was higher in the central part of eddy (~1.5 mg/m3) than the peripheral water (~0.8 mg/m3). The eddy lasted till 10th March 2002. NOAA-AVHRR sea surface temperature (SST) images generated during 15th February-15th March 2002. The SST in the eddy’s center (~23°C) was lesser than the surrounding water (~24.5°C). The eddy was of cold core type with the warmer water in periphery. Quickscat Scatterometer retrieved wind speed was 8–10 m/sec. The eddy movement observed southeast to southwest direction and might helped in churning. The eddy seemed evident due to convective processes in water column. The processes like detrainment and entrainment play role in bringing up the cooler water and the bottom nutrient to surface and hence the algal blooming. This type of cold core/anti-cyclonic eddy is likely to occur during late winter/spring as a result of the prevailing climatic conditions.

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