Spatio-temporal analysis of the climate impact on rice yield in north-west India

Abstract Background: The number of death children at the international scale are still high, but with proper spatially-targeted health public policies this number could be reduced. In Mexico, children mortality is a particular health concern due to its alarming rate all throughout North America. The aims of this study are i) to model the change of children mortality risk at the municipality level, (ii) to identify municipalities with high, medium and low risk over time and (iii) to ascertain potential high-risk municipalities across time, using local trends of each municipality in Greater Mexico City. Methods: The study uses Bayesian spatio-temporal analysis to control for space-time patterns of data. This allow to model the geographical variation of the municipalities within the time span studied. Results: The analysis shows that most of the high-risk municipalities are in the north, west, and some in the east; some of such municipalities show an increasing children mortality risk over time. The outcomes highlight some municipalities which show a medium risk currently but are likely to become high risk along the study period. Finally, the odds of children mortality risk illustrate a decreasing tendency over the 7-year framework. Conclusions: Identification of high-risk municipalities may provide a useful input to policy-makers seeking out to reduce the incidence of children mortality, since it would provide evidence to support geographical targeting for policy interventions.

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Spatio-temporal analysis of colorectal cancer using a geographic information system in the Iranian military community during the period 2007–2016

BMJ Military Health ◽

10.1136/jramc-2018-001151 ◽

2019 ◽

Vol 166 (E) ◽

pp. e8-e12

Author(s):

Alireza Khoshdel ◽

M Alimohammadi ◽

M Sepandi ◽

Y Alimohamadi ◽

P Jalali ◽

...

Keyword(s):

Colorectal Cancer ◽

Disease Prevention ◽

Temporal Distribution ◽

Temporal Analysis ◽

Individual Risk ◽

Cancer Type ◽

North West ◽

Prevention Programmes ◽

Military Community ◽

Spatio Temporal

IntroductionColorectal cancer (CRC) is one of the most prevalent cancers among Iranian people. The study of spatio-temporal distribution of disease has an important role in the design of disease prevention programmes. The purpose of the current study was to describe the spatio-temporal distribution of CRC in the Iranian military community as a sample of the Iranian population.MethodsIn the current ecological study, all registered cancer cases in the Iranian military community during the period 2007–2016 were considered. To identify hotspots, Getis-Ord Gi statistics were used. All analyses were performed using ArcGIS 10.5 and Excel 2010.ResultsThe highest incidences of CRC in 2007–2008, 2009–2010 and 2011–2012 were recorded in Kermanshah province. The highest incidences of CRC in 2013–2014 were seen in Kermanshah, Ghilan, Tehran and North Khorasan. In 2007–2008 and 2009–2010, hotspots were detected in West Azarbayjan. In 2011–2012, hotspots were detected in Zanjan and Qazvin. In 2013–2014, a hotspot was detected in Qazvin. Finally, West Azerbaijan was the hotspot for CRC in 2015–2016.ConclusionsThe incidence of CRC in men was higher than in women. Also it appeared that North and North West Iran were risk areas for this disease, and so these areas should be considered in the design of disease prevention programme for this cancer type. Additionally, the determination of individual risk factors in the aforementioned geographical areas can play an important role in the prevention of this type of cancer.

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SPATIO-TEMPORAL LAND USE CHANGE ANALYSIS IN DIRECTIONAL ZONES OF LUCKNOW CITY, INDIA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliv-m-3-2021-181-2021 ◽

2021 ◽

Vol XLIV-M-3-2021 ◽

pp. 181-186

Author(s):

R. Verma ◽

P. K. Garg

Keyword(s):

Land Use ◽

Nearest Neighbor ◽

Urban Expansion ◽

Temporal Analysis ◽

Shape Index ◽

Change Analysis ◽

Aggregation Index ◽

North West ◽

North East ◽

Spatio Temporal

Abstract. Dynamic changes in urbanisation of a city is best analyzed through spatio-temporal analysis of classified data. Decadal Land use data for India for years 1985, 1995 and 2005 and Copernicus Global Land service Dynamic Land Cover layers (CGLS-LC100 products) for year 2015 have been used to conduct analysis for multi-temporal analysis of urban expansion and its dynamics using Landscape Metrics by FRAGSTATS and Shannon’s Entropy Values (Hn) over the 4 directional zones of Lucknow city namely North-East (NE), South-East (SE), South-West (SW) and North-West (NW). The metrics used to find characteristics of urbanisation are Landscape Shape Index (LSI), Largest Patch Index (LPI), Mean Euclidean Nearest Neighbor Distance (ENN_MN) and Aggregation Index (AI). Results showed the increase in LSI for Built-up patches over the years from 1985 to 2015, explaining the increase in complexity of shapes of Built-up patches in all zones. The increase in LPI indicates the increase of Built-up land use class over the years but also the convergence of urbanisation in the study area as indicated by lower entropy values. NW zone of Lucknow city area being poor in Vegetation is having highest ENN_MN which is decreasing over the years indicating more centrality. AI is same for Built-up patches from 1985 to 2015 which is due to either edge-filling or outlying urban growth in study area in all 3 change durations 1985-1995, 1995–2005 and 2005–2015. Among all 4 zones of Lucknow city, decrease in vegetation is major factor to urbanisation in city over the years.

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Spatio-temporal Analysis of Ground Movement Susceptibility in the Kef Area (North West Tunisia)

Recent Advances in Environmental Science from the Euro-Mediterranean and Surrounding Regions - Advances in Science, Technology & Innovation ◽

10.1007/978-3-319-70548-4_533 ◽

2018 ◽

pp. 1841-1843

Author(s):

Radhia Mansour ◽

Nouha Brachen ◽

Abdesselem ElGhali

Keyword(s):

Temporal Analysis ◽

Ground Movement ◽

North West ◽

Spatio Temporal ◽

Area North

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Spatio-temporal analysis identifies hotspots of marine mammal strandings along the Indian coastline: implications for developing a National Marine Mammal Stranding Response and Management policy

10.1101/2021.01.20.427409 ◽

2021 ◽

Author(s):

Sohini Dudhat ◽

Anant Pande ◽

Aditi Nair ◽

Indranil Mondal ◽

Kuppusamy Sivakumar

Keyword(s):

West Coast ◽

Marine Mammal ◽

Life Histories ◽

East Coast ◽

Temporal Analysis ◽

Management Policy ◽

Hotspot Analysis ◽

North West ◽

Mobile Species ◽

Spatio Temporal

AbstractMarine mammal strandings provide vital information on their life histories, population health and status of marine ecosystems. Opportunistic reporting of strandings serve as a potent low-cost tool for conservation monitoring of these highly mobile species. We present the results of spatio-temporal analyses of marine mammal stranding events to identify hotpots along Indian coastline. We collated data over a long-time frame (~270 years) available from various open access databases, reports and publications. Given the inadequacy in data collection over these years, we grouped data into four major groups viz. baleen whales, toothed whales, small cetaceans and dugongs. Further, we described the trends in data for marine mammal sightings, incidental mortalities, induced mortalities and stranding events using the last group for spatio-temporal analysis. Annual strandings along the Indian coast has increased considerably in the recent years (11.25 ± 9.10 strandings/ year), peaking in the last two years (2015-17, mean = 27.66±12.03 strandings /year). We found that number of strandings spiked in June- September along the west coast and December- January along the east coast. We identified several sections of coastline which have consistently received comparatively higher number of stranded animals (0.38 - 1.82 strandings/km) throughout the study period. Use of novel geospatial tool ‘Emerging Hotspot Analysis’ revealed new and consecutive hotspots along the north-west coast, and sporadic hotspots along the south-east coast. Despite the challenges of working with an opportunistic database, this study highlights critical areas to be prioritized for monitoring marine mammal strandings in the country. We recommend establishing regional marine mammal stranding response centres at the identified hotspots coordinated by a National Stranding Monitoring Centre with adequate funding support. Regular conduct of stranding response programs for field veterinarians, frontline personnel focused around identified stranding hotspots would help develop a comprehensive picture of marine mammal populations in Indian waters.

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