scholarly journals Spatio-Temporal Coverage Enhancement in Drive-By Sensing Through Utility-Aware Mobile Agent Selection

Author(s):  
Navid Hashemi Tonekaboni ◽  
Lakshmish Ramaswamy ◽  
Deepak Mishra ◽  
Omid Setayeshfar ◽  
Sorush Omidvar
2021 ◽  
Vol 12 (4) ◽  
pp. 14-20
Author(s):  
Jianhua Yin ◽  
Feiyue Mao ◽  
Lin Zang ◽  
Jiangping Chen ◽  
Xin Lu ◽  
...  

2020 ◽  
Author(s):  
Laia Comas-Bru ◽  
Kira Rehfeld ◽  
Carla Roesch ◽  
Sahar Amirnezhad-Mozhdehi ◽  
Sandy P. Harrison ◽  
...  

Abstract. Characterising the temporal uncertainty in palaeoclimate records is crucial for analysing past climate change, for correlating climate events between records, for assessing climate periodicities, identifying potential triggers, and to evaluate climate model simulations. The first global compilation of speleothem isotope records by the SISAL (Speleothem Isotope Synthesis and Analysis) Working Group showed that age-model uncertainties are not systematically reported in the published literature and these are only available for a limited number of records (ca. 15 %, n = 107/691). To improve the usefulness of the SISAL database, we have (i) improved the database’s spatio-temporal coverage and (ii) created new chronologies using seven different approaches for age-depth modelling. We have applied these alternative chronologies to the records from the first version of the SISAL database (SISALv1) and to new records compiled since the release of SISALv1. This paper documents the necessary changes in the structure of the SISAL database to accommodate the inclusion of the new age-models and their uncertainties as well as the expansion of the database to include new records and the quality-control measures applied. This paper also documents the age-depth model approaches used to calculate the new chronologies. The updated version of the SISAL database (SISALv2) contains isotopic data from 691 speleothem records from 294 cave sites and new age-depth models, including age-depth temporal uncertainties for 512 speleothems. SISALv2 is available at https://doi.org/10.17864/1947.242 (Comas-Bru et al., 2020).


2014 ◽  
Vol 24 (12) ◽  
pp. 2117-2131 ◽  
Author(s):  
Alessandro Redondi ◽  
Dujdow Buranapanichkit ◽  
Matteo Cesana ◽  
Marco Tagliasacchi ◽  
Yiannis Andreopoulos

2021 ◽  
Vol 9 ◽  
Author(s):  
Nitu Ojha ◽  
Olivier Merlin ◽  
Christophe Suere ◽  
Maria José Escorihuela

DISPATCH is a disaggregation algorithm of the low-resolution soil moisture (SM) estimates derived from passive microwave observations. It provides disaggregated SM data at typically 1 km resolution by using the soil evaporative efficiency (SEE) estimated from optical/thermal data collected around solar noon. DISPATCH is based on the relationship between the evapo-transpiration rate and the surface SM under non-energy-limited conditions and hence is well adapted for semi-arid regions with generally low cloud cover and sparse vegetation. The objective of this paper is to extend the spatio-temporal coverage of DISPATCH data by 1) including more densely vegetated areas and 2) assessing the usefulness of thermal data collected earlier in the morning. Especially, we evaluate the performance of the Temperature Vegetation Dryness Index (TVDI) instead of SEE in the DISPATCH algorithm over vegetated areas (called vegetation-extended DISPATCH) and we quantify the increase in coverage using Sentinel-3 (overpass at around 09:30 am) instead of MODIS (overpass at around 10:30 am and 1:30 pm for Terra and Aqua, respectively) data. In this study, DISPATCH is applied to 36 km resolution Soil Moisture Active and Passive SM data over three 50 km by 50 km areas in Spain and France to assess the effectiveness of the approach over temperate and semi-arid regions. The use of TVDI within DISPATCH increases the coverage of disaggregated images by 9 and 14% over the temperate and semi-arid sites, respectively. Moreover, including the vegetated pixels in the validation areas increases the overall correlation between satellite and in situ SM from 0.36 to 0.43 and from 0.41 to 0.79 for the temperate and semi-arid regions, respectively. The use of Sentinel-3 can increase the spatio-temporal coverage by up to 44% over the considered MODIS tile, while the overlapping disaggregated data sets derived from Sentinel-3 and MODIS land surface temperature data are strongly correlated (around 0.7). Additionally, the correlation between satellite and in situ SM is significantly better for DISPATCH (0.39–0.80) than for the Copernicus Sentinel-1-based (−0.03 to 0.69) and SMAP/S1 (0.37–0.74) product over the three studies (temperate and semi-arid) areas, with an increase in yearly valid retrievals for the vegetation-extended DISPATCH algorithm.


Author(s):  
Cha-Hwa Lin ◽  
Jin-Fu Wang

Mobile agent planning (MAP) is one of the most important techniques in the mobile computing paradigm to complete a given task in the most efficient manner. To tackle this challenging NP-hard problem, Hopfield-Tank neural network is modified to provide a dynamic approach which not only optimizes the cost of mobile agents in a spatio-temporal computing environment, but also satisfies the location-based constraints such as the starting and ending nodes of the routing sequence which must be the home site of the traveling mobile agent. Meanwhile, the energy function is reformulated into a Lyapunov function to guarantee the convergence to a stable state and the existence of valid solutions. Moreover, the objective function is designed to estimate the completion time of a valid solution and to predict the optimal routing path. This method can produce solutions rapidly that are very close to the minimum cost of the location-based and time-constrained distributed MAP problem.


2014 ◽  
Vol 94 (7) ◽  
pp. 1401-1408 ◽  
Author(s):  
Stephen K. Pikesley ◽  
Brendan J. Godley ◽  
Sue Ranger ◽  
Peter B. Richardson ◽  
Matthew J. Witt

Concern has been expressed over future biogeographical expansion and habitat capitalization by species of the phylum Cnidaria, as this may have negative implications on human activities and ecosystems. There is, however, a paucity of knowledge and understanding of jellyfish ecology, in particular species distribution and seasonality. Recent studies in the UK have principally focused on the Celtic, Irish and North Seas, but all in isolation. In this study we analyse data from a publicly-driven sightings scheme across UK coastal waters (2003–2011; 9 years), with the aim of increasing knowledge on spatial and temporal patterns and trends. We describe inter-annual variability, seasonality and patterns of spatial distribution, and compare these with existing historic literature. Although incidentally-collected data lack quantification of effort, we suggest that with appropriate data management and interpretation, publicly-driven, citizen-science-based, recording schemes can provide for large-scale (spatial and temporal) coverage that would otherwise be logistically and financially unattainable. These schemes may also contribute to baseline data from which future changes in patterns or trends might be identified. We further suggest that findings from such schemes may be strengthened by the inclusion of some element of effort-corrected data collection.


Sign in / Sign up

Export Citation Format

Share Document