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Background Evidence on the association between greenness and adiposity in children and adolescents is inconsistent and mostly from developed countries. Relatively limited evidence is from China. Objective To assess the association between greenness and adiposity in children and adolescents based on satellite remote sensing data. Methods From 2016 to 2018, a cross-sectional study was conducted among 52316 children and adolescents aged 5-18 years in three cities in the Pearl River Delta region of China. Basic sociological and demographic characteristics of the population and adiposity levels were collected through questionnaires. Land Remote-Sensing Satellite (Landsat) data and moderate-resolution imaging spectroradiometer (MODIS) products were used to quantify the greenness around the schools and homes, including normalized difference vegetation index (NDVI), vegetation continuous field (VCF), soil-adjusted vegetation index (SAVI), and enhanced vegetation index (EVI) calculated within 500 m and 1000 m buffers centered around the participants' homes or schools. A restricted cubic spline function was used to assess the exposure-response relationship. After categorizing greenness levels into quartiles with the first quartile as the reference, two-level generalized linear models were applied to assess the change in body mass index z-scores (zBMI) and the risk of overweight of children and adolescents in higher quartiles relative to the lowest quartile. In addition, counterfactual framework modelling was applied to assess the potential mediation effects of PM2.5 and NO2, and physical activity levels on the associations between greenness and adiposity levels. Results Of the 52316 children included, 8406 (16.1%) were overweight. A non-linear negative association of the level of greenness around the homes or schools and zBMI was found, with a significant lower zBMI in children and adolescents when a certain level of greenness was reached. After adjusting for confounders, the participants in the highest quartile had a significantly lower level of zBMI and a significantly lower risk of overweight compared with those in the lowest quartile of NDVI500 m and VCF500 m. The estimate change (\begin{document}$b$\end{document}) for zBMI was −0.07 (95%CI: −0.10-−0.04) and the odds ratio (OR) for overweight was 0.92 (95%CI: 0.85-0.99) for the students in the highest NDVI500 m quartile based on home address compared to those in the lowest quartile. Significant negative associations were also observed when 1000 m buffer, SAVI, and EVI were used. The mediation analysis showed that PM2.5 and NO2 partially mediated the negative association of NDVI500 m with zBMI , and the proportions of mediation were 50% (95%CI: 20%-80%) and 90% (95%CI: 50%-160%), respectively while no significant mediation effect was observed for physical activity level. Conclusion Higher levels of greenness surrounding homes or schools may be associated with a reduced risk of overweight and decreased zBMI in children and adolescents, and such associations may be partially mediated by reducing air pollutant concentrations.
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Introduction: Land Surface Temperature (LST) is a significant climatic variable and defined as how hot the "surface" of the Earth would feel to the physical touch in a particular location. A spatial analysis of the land surface temperature with respect to different land use/cover changes is vital to evaluate the hydrological processes. Methods: The objective of this paper is to assess the spatial variation of land surface temperature derived from thermal bands of the Landsat 8 Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) by using split window algorithm. Place and Data: The study was conducted in Lalgudi block of Trichy District, Tamil Nadu, India. The block has diverse environment like forest area, barren land, river sand bed, water bodies, dry vegetation, cultivated areas (paddy, sugarcane, banana etc.) and settlements. Landsat 8 satellite images for four selected scenes (December 2014 & January 2015 and December 2017 & January 2018) were used to estimate the LST. Results: The spatial and temporal variation of Normalized Difference Vegetation Index (NDVI) and LST were estimated. The average NDVI values of cropped fields varied from 0.3 to 0.5 in all the scenes. The maximum value of LST ranging from 35 to 40°C was recorded in river sand bed. Subsequently, semi-urban settlements in the central part of Lalgudi block exhibited higher temperature ranging from 28 – 30°C. The LST of paddy crop and sugarcane was in the range of 23 to 25°C. The water bodies exhibited LST around 20°C. The coconut plantations, forest area and Prosopis juliflora showed LST value ranging from 24 – 29°C. This kind of block level monitoring studies helps in adopting suitable policies to overcome or minimize the problems triggered by increase in land surface temperature.
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Objective With Landsat TM remote sensing images,snail habitats in Poyang Lake region were identified,using two indices:the modified normalized difference water index (MNDWI) and the normalized difference vegetation index (NDVI).Methods Two Remote sensing images of both wet and drought seasons in Poyang Lake region were obtained.MNDWI and NDVI were extracted from the images respectively,to present the regions of “water in summer and land in winter” and the coverage of vegetation.By overlaying those two regions,the areas of potential snail habitats were drawn.Finally,sensitivities and specificities of the recommended methods were assessed and compared to that of the traditional methods for the sake of extracting the areas of snail habitats.Results The threshold values of MNDWI for the wet and drought seasons were 0.34 and 0.58,respectively and the threshold value for NDVI of the drought season was 0.02.Sensitivity and specificity of our method were 95％ and 100％,respectively,higher than the conventional approach (se.=75％,sp.=100％ ).Conclusion Joint application of MNDWI and NDVI seemed a better method to detect the snail habitats and could be used for the quantitative and automatic surveillance program on snails.
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Objective To detect the snail habitats from the marshland of Eastern Dongting Lake Area, using the Remote Sensing (RS) and Geographic Information System (GIS) technology based on the China-Brazil Earth Resources Satellite-02B (CBERS-02B) CCD images. Methods According to the two typical traits of snail habitats in marshland including "water in summer and land in winter" and "no grass, no snails" , the "water in summer and land in winter" region and the vegetation coverage region were calculated by RS image processing respectively. The two regions mentioned above were then overlapped to confirm the snail habitats through comparing with the data from field survey under spatial overlapping of Arcgis as the last step. Results In Eastern Dongting Lake area, the "water in summer and land in winter" region and vegetation coverage region were predicted based on the formula normalized difference water index (NDWI) >0.01 and normalized difference vegetation index (NDVI) >0.36, respectively. The snail habitat was determined by theme overlay of the two regions said above.The agreement rate between the prediction and the geospatial data of field survey was 93.55% , which demonstrated the final results were credible and reliable. Conclusion CBERS-02B image could be used to detect the snail habitats and to monitor the changes of them, so as to find out the characteristics of distribution and the trends of diffusion. The snail index (discriminant 1 and 2) seemed to be suitable for the detection of snail habitats in the marshland of Lake area and used for the programs of snail control.
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A fim de avaliar os padrões de resposta de áreas cultivadas com cereais de estação fria destinados para pastagens e para produção de grãos em imagens de satélite, foram analisados perfis temporais de índice de vegetação por diferença normalizada (NDVI), adquiridos em 29 áreas cultivadas com trigo e azevém anual, nos Estados do Rio Grande do Sul e Paraná. Para cada área foi informada a espécie cultivada (trigo ou azevém anual) e a coordenada do ponto central da área adquirido por meio do Global Positioning System (GPS). Foram usadas as imagens do sensor MODIS (Moderate Resolution Imaging Spectroradiometer), com resolução espacial de 250 metros, sobre cada área monitorada, de onde os valores de NDVI foram extraídos. Os perfis temporais de NDVI mostraram que os cultivos de produção de grãos têm um comportamento espectral típico de cultivos agrícolas, enquanto que, nas áreas cultivadas para a produção de pastagem, não foi observado esse mesmo padrão. As diferenças nos padrões temporais observadas se devem a modificações que o pastoreio impõe na fenologia e na morfologia dessas plantas.
In order to evaluate the satellite image patterns between such cool season cereals cultivated areas intended for grazing or grain production, Normalized Difference Vegetation Index (NDVI) temporal profiles were analyzed. This data was acquired from twenty nine wheat and annual ryegrass cultivated areas in the states of Rio Grande do Sul and Paraná. For each area, the cultivated species (wheat or ryegrass), as well as the respective central point coordinates, acquired via Global Positioning System (GPS) was informed. NDVI values were extracted over each monitored area from MODIS (Moderate Resolution Imaging Spectroradiometer) sensor images, with spatial resolution of 250 meters. The NDVI temporal profiles showed that grain production areas have a typical agricultural field spectral pattern. The same pattern was not observed for the grazing pasture areas. The differences observed in these temporal patterns are defined by the changes that grazing has imposed on the phenology and morphology of these plants.