scholarly journals Modeling spatiotemporal Aedes aegypti risk in French Guiana using meteorological and remote sensing data

2021 ◽  
Author(s):  
Sarah Bailly ◽  
Vanessa Machault ◽  
Samuel Beneteau ◽  
Philippe Palany ◽  
Romain Girod ◽  
...  
Keyword(s):  
Aedes Aegypti ◽  
Vector Control ◽  
French Guiana ◽  
Meteorological Data ◽  
Remote Sensing Data ◽  
Environmental Data ◽  
Temporal Modeling ◽  
Risk Levels ◽  
Very High Spatial Resolution ◽  
Spatio Temporal

Although the development of vaccines for the prevention of arboviral diseases has been a priority in recent years, prevention strategies continue to depend on vector control. Risk maps at scales appropriate for these strategies can provide valuable information to assess entomological risk levels and guide actions. We used a spatio-temporal modeling approach to predict, at the local scale, the risk of homes potentially harboring Aedes aegypti larvae. The model used integrated larvae risk data collected in the field from September 2011 to February 2013, environmental data obtained from very high spatial resolution Pleiades imagery, and daily meteorological data, collected in the city of Matoury in French Guiana. Various environmental and meteorological conditions were identified as risk or protective factors for the presence of immature stages of Aedes aegypti in homes on a given date and used to produce dynamic maps with high spatial and temporal resolution. Aedes vector risk was modeled between 50 and 200 m, around houses, on a time scale of 3 to 5 days. The resulting model was extrapolated to other municipalities with the same characteristics of urbanization during the 2019-2020 dengue epidemic in French Guiana. This work represents a major opportunity to monitor the evolution of vector risk and constitutes information that could be particularly useful for public health authorities in charge of vector control.

Spatio-temporal variation of net primary productivity in a rapidly expanding artificial woodland area based on remote-sensing data

Erdkunde ◽  
2021 ◽  
Vol 75 (3) ◽  
pp. 191-207
Author(s):  
Qi Yi ◽  
Yuting Gao ◽  
Hongrong Du ◽  
Junxu Chen ◽  
Liang Emlyn Yang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Meteorological Data ◽  
Arable Land ◽  
Remote Sensing Data ◽  
Stand Age ◽  
Sensing Data ◽  
Spatio Temporal

The expansion of artificial woodlands in China has contributed significantly to regional land-cover changes and changes in the regional net primary productivity (NPP). This study used Ximeng County in the Yunnan Province as a case study to investigate the overall changes, associated amplitude, and spatio-temporal distribution of NPP from 2000–2015.The Carnegie-Ames-Stanford approach was used in the rapidly expanding artificial woodland area based on MODIS-NDVI data, meteorological data, and Landsat 5 TM data to calculate the NPP. The results show that (1) artificial woodlands experience a 10fold increase and account for 93 % of the land cover transfer, which was mainly from woodland areas. (2) The NPP was 906.2×109 gC·yr-1 in 2000 and 972.0×109 gC·yr-1 in 2015, presenting a total increase of 65.8×109 gC·yr-1 and a mean increase of 52.4 gC·m-2·yr-1 in Ximeng County. (3) The most notable NPP changes take place in the central and the western border regions, with the increasing NPP of artificial woodlands and arable land offsetting the negative effects of the decrease in woodland NPP. (4) The total NPP in the study area kept increasing, primarily due to the growing area of artificial woodlands as well as the stand age of the woods, whereas the mean value change of the NPP is mostly related to the increasing stand age. (5) The artificial woodlands increase the NPP value more than natural woodlands. While protecting and promoting ecologically valuable natural forests at the same time, it seems quite advantageous to establish regional plantations and coordinate their development on a scientific basis with a view to increasing NPP, economic development, but also the ecological stability of this mountain region. Our study reveals the changes in NPP and its distribution in a rapidly expanding area of artificial woodland in southwest China based on remote-sensing data and the CASA model, providing a decision-making basis for rational land-use management, the optimal utilization of land resources, and a county-scale assessment approach.

scholarly journals Multiple insecticide resistance in Aedes aegypti (Diptera: Culicidae) populations compromises the effectiveness of dengue vector control in French Guiana

2011 ◽  
Vol 106 (3) ◽  
pp. 346-352 ◽  
Author(s):  
Isabelle Dusfour ◽  
Véronique Thalmensy ◽  
Pascal Gaborit ◽  
Jean Issaly ◽  
Romuald Carinci ◽  
...  
Keyword(s):  
Aedes Aegypti ◽  
Insecticide Resistance ◽  
Vector Control ◽  
French Guiana ◽  
Dengue Vector ◽  
Dengue Vector Control

scholarly journals Risk factors for Aedes aegypti household pupal persistence in longitudinal entomological household surveys in urban and rural Kenya

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Harun N. Ngugi ◽  
Sindiso Nyathi ◽  
Amy Krystosik ◽  
Bryson Ndenga ◽  
Joel O. Mbakaya ◽  
...  
Keyword(s):  
Risk Factors ◽  
Aedes Aegypti ◽  
Vector Control ◽  
Environmental Data ◽  
Vector Ecology ◽  
Entomological Surveillance ◽  
Public Health Importance ◽  
Tall Grass ◽  
Increased Risk ◽  
Efficient Vector

Abstract Background Aedes aegypti is an efficient vector of several arboviruses of public health importance, including Zika and dengue. Currently vector management is the only available avenue for disease control. Development of efficient vector control strategies requires a thorough understanding of vector ecology. In this study, we identified households that are consistently productive for Ae. aegypti pupae and determined the ecological and socio-demographic factors associated with the persistence and abundance of pupae in households in rural and urban Kenya. Methods We collected socio-demographic, environmental and entomological data monthly from July 2014 to June 2018 from 80 households across four sites in Kenya. Pupae count data were collected via entomological surveillance of households and paired with socio-demographic and environmental data. We calculated pupal persistence within a household as the number of months of pupal presence within a year. We used spatially explicit generalized additive mixed models (GAMMs) to identify the risk factors for pupal abundance, and a logistic regression to identify the risk factors for pupal persistence in households. Results The median number of months of pupal presence observed in households was 4 and ranged from 0 to 35 months. We identified pupal persistence in 85 house-years. The strongest risk factors for high pupal abundance were the presence of bushes or tall grass in the peri-domicile area (OR: 1.60, 95% CI: 1.13–2.28), open eaves (OR: 2.57, 95% CI: 1.33–4.95) and high habitat counts (OR: 1.42, 95% CI: 1.21–1.66). The main risk factors for pupal persistence were the presence of bushes or tall grass in the peri-domicile (OR: 4.20, 95% CI: 1.42–12.46) and high number of breeding sites (OR: 2.17, 95% CI: 1.03–4.58). Conclusions We observed Ae. aegypti pupal persistence at the household level in urban and rural and in coastal and inland Kenya. High counts of potential breeding containers, vegetation in the peri-domicile area and the presence of eaves were strongly associated with increased risk of pupal persistence and abundance. Targeting households that exhibit pupal persistence alongside the risk factors for pupal abundance in vector control interventions may result in more efficient use of limited resources.

scholarly journals Spatiotemporal multiple insecticide resistance in Aedes aegypti populations in French Guiana: need for alternative vector control

2020 ◽  
Vol 115 ◽  
Author(s):  
Amandine Guidez ◽  
Nicolas Pocquet ◽  
Johana Restrepo ◽  
Luana Mathieu ◽  
Pascal Gaborit ◽  
...  
Keyword(s):  
Aedes Aegypti ◽  
Insecticide Resistance ◽  
Vector Control ◽  
French Guiana

scholarly journals Topoclimate Mapping Using Landsat ETM+ Thermal Data: Wolin Island, Poland

2021 ◽  
Vol 13 (14) ◽  
pp. 2712
Author(s):  
Marta Ciazela ◽  
Jakub Ciazela
Keyword(s):  
Land Surface ◽  
Meteorological Data ◽  
Remote Sensing Data ◽  
Animal Husbandry ◽  
Boundary Layer Processes ◽  
Lowland Area ◽  
Agricultural Areas ◽  
Glacial Landforms ◽  
Climatic Pattern

Variations in climatic pattern due to boundary layer processes at the topoclimatic scale are critical for ecosystems and human activity, including agriculture, fruit harvesting, and animal husbandry. Here, a new method for topoclimate mapping based on land surface temperature (LST) computed from the brightness temperature of Landsat ETM+ thermal bands (band6) is presented. The study was conducted in a coastal lowland area with glacial landforms (Wolin Island). The method presented is universal for various areas, and is based on freely available remote sensing data. The topoclimatic typology obtained was compared to the classical one based on meteorological data. It was proven to show a good sensitivity to changes in topoclimatic conditions (demonstrated by changes in LST distribution) even in flat, agricultural areas with only small variations in topography. The technique will hopefully prove to be a convenient and relatively fast tool that can improve the topoclimatic classification of other regions. It could be applied by local authorities and farmer associations for optimizing agricultural production.

scholarly journals Pyramidal Framework: Guidance for the Next Generation of GIS Spatial-Temporal Models

2021 ◽  
Vol 10 (3) ◽  
pp. 188
Author(s):  
Cyril Carré ◽  
Younes Hamdani
Keyword(s):  
Conceptual Models ◽  
Future Generations ◽  
Temporal Data ◽  
Temporal Modeling ◽  
Temporal Models ◽  
Gis Data ◽  
Spatio Temporal ◽  
New Interpretation ◽  
Conventional Literature

Over the last decade, innovative computer technologies and the multiplication of geospatial data acquisition solutions have transformed the geographic information systems (GIS) landscape and opened up new opportunities to close the gap between GIS and the dynamics of geographic phenomena. There is a demand to further develop spatio-temporal conceptual models to comprehensively represent the nature of the evolution of geographic objects. The latter involves a set of considerations like those related to managing changes and object identities, modeling possible causal relations, and integrating multiple interpretations. While conventional literature generally presents these concepts separately and rarely approaches them from a holistic perspective, they are in fact interrelated. Therefore, we believe that the semantics of modeling would be improved by considering these concepts jointly. In this work, we propose to represent these interrelationships in the form of a hierarchical pyramidal framework and to further explore this set of concepts. The objective of this framework is to provide a guideline to orient the design of future generations of GIS data models, enabling them to achieve a better representation of available spatio-temporal data. In addition, this framework aims at providing keys for a new interpretation and classification of spatio-temporal conceptual models. This work can be beneficial for researchers, students, and developers interested in advanced spatio-temporal modeling.

scholarly journals A Spatio-Temporal Local Association Query Algorithm for Multi-Source Remote Sensing Big Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2333
Author(s):  
Lilu Zhu ◽  
Xiaolu Su ◽  
Yanfeng Hu ◽  
Xianqing Tai ◽  
Kun Fu
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Temporal Correlation ◽  
Local Association ◽  
Sensing Data ◽  
Multi Scale ◽  
Correlation Networks ◽  
Efficient Integration ◽  
Spatio Temporal ◽  
Query Algorithm

It is extremely important to extract valuable information and achieve efficient integration of remote sensing data. The multi-source and heterogeneous nature of remote sensing data leads to the increasing complexity of these relationships, and means that the processing mode based on data ontology cannot meet requirements any more. On the other hand, the multi-dimensional features of remote sensing data bring more difficulties in data query and analysis, especially for datasets with a lot of noise. Therefore, data quality has become the bottleneck of data value discovery, and a single batch query is not enough to support the optimal combination of global data resources. In this paper, we propose a spatio-temporal local association query algorithm for remote sensing data (STLAQ). Firstly, we design a spatio-temporal data model and a bottom-up spatio-temporal correlation network. Then, we use the method of partition-based clustering and the method of spectral clustering to measure the correlation between spatio-temporal correlation networks. Finally, we construct a spatio-temporal index to provide joint query capabilities. We carry out local association query efficiency experiments to verify the feasibility of STLAQ on multi-scale datasets. The results show that the STLAQ weakens the barriers between remote sensing data, and improves their application value effectively.

scholarly journals First Assessment of the Benthic Meiofauna Sensitivity to Low Human-Impacted Mangroves in French Guiana

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 338
Author(s):  
Claire Michelet ◽  
Daniela Zeppilli ◽  
Cédric Hubas ◽  
Elisa Baldrighi ◽  
Philippe Cuny ◽  
...  
Keyword(s):  
South America ◽  
French Guiana ◽  
Ecological Status ◽  
Organic Enrichment ◽  
Strongly Correlated ◽  
Trophic Groups ◽  
Ecological State ◽  
Spatio Temporal ◽  
De Man ◽  
Main City

Bioindicators assess the mangroves ecological state according to the types of pressures but they differ with the ecosystem’s specificities. We investigated benthic meiofauna diversity and structure within the low human-impacted mangroves in French Guiana (South America) in response to sediment variables with various distances to the main city. Contaminant’s concentrations differed among the stations, but they remained below toxicity guidelines. Meiofauna structure (Foraminifera, Kinorhyncha, Nematoda) however varied accordingly. Nematode’s identification brought details on the sediment’s quality. The opportunistic genus Paraethmolaimus (Jensen, 1994) strongly correlated to the higher concentrations of Hg, Pb. Anoxic sediments were marked by organic enrichment in pesticides, PCB, and mangrove litter products and dominance of two tolerant genus, Terschellingia (de Man, 1888) and Spirinia (Gerlach, 1963). In each of these two stations, we found many Desmodora individuals (de Man, 1889) with the presence of epibionts highlighting the nematodes decreased fitness and defenses. Oxic sediments without contaminants were distinguished by the sensitive genera Pseudocella (Filipjev, 1927) and a higher diversity of trophic groups. Our results suggested a nematodes sensitivity to low contaminants concentrations. Further investigations at different spatio-temporal scales and levels of deterioration, would be necessary to use of this group as bioindicator of the mangroves’ ecological status.

Implementation of a proactive system to monitor Aedes aegypti populations using open access historical and forecasted meteorological data

2021 ◽  
pp. 101351
Author(s):  
Exequiel Aguirre ◽  
Verónica Andreo ◽  
Ximena Porcasi ◽  
Laura Lopez ◽  
Claudio Guzman ◽  
...  
Keyword(s):  
Open Access ◽  
Aedes Aegypti ◽  
Meteorological Data

scholarly journals Predicting Aedes aegypti infestation using landscape and thermal features

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Camila Lorenz ◽  
Marcia C. Castro ◽  
Patricia M. P. Trindade ◽  
Maurício L. Nogueira ◽  
Mariana de Oliveira Lage ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Aedes Aegypti ◽  
Vector Control ◽  
Land Surface ◽  
Urban Areas ◽  
Negative Binomial ◽  
Control Strategies ◽  
Winter Season ◽  
Landsat 8 ◽  
Thermal Features

AbstractIdentifying Aedes aegypti breeding hotspots in urban areas is crucial for the design of effective vector control strategies. Remote sensing techniques offer valuable tools for mapping habitat suitability. In this study, we evaluated the association between urban landscape, thermal features, and mosquito infestations. Entomological surveys were conducted between 2016 and 2019 in Vila Toninho, a neighborhood of São José do Rio Preto, São Paulo, Brazil, in which the numbers of adult female Ae. aegypti were recorded monthly and grouped by season for three years. We used data from 2016 to 2018 to build the model and data from summer of 2019 to validate it. WorldView-3 satellite images were used to extract land cover classes, and land surface temperature data were obtained using the Landsat-8 Thermal Infrared Sensor (TIRS). A multilevel negative binomial model was fitted to the data, which showed that the winter season has the greatest influence on decreases in mosquito abundance. Green areas and pavements were negatively associated, and a higher cover of asbestos roofs and exposed soil was positively associated with the presence of adult females. These features are related to socio-economic factors but also provide favorable breeding conditions for mosquitos. The application of remote sensing technologies has significant potential for optimizing vector control strategies, future mosquito suppression, and outbreak prediction.

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