The presentation was given by Mr. Bas Kempen and Ms. V.L. Mulder, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
The presentation was given by Mr. Bas Kempen and Ms. V.L. Mulder, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
Soil Organic Carbon mapping by geo- and class- matchingExternalEvents
The presentation was given by Mr. Bas Kempen & Ms. V.L. Mulder, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
A comparison of Land Cover Change in Kaski District, NepalBijesh Mishra
Kaski, one the major cities of Nepal, major tourism place and regional headquarter of Western Development
region, attracts large population from surrounding resulting 36.4% increase in population proportion and thus, land cover
is rapidly changing in the area. The research intended to find land cover change over nine years from 2000 to 2009 as well
as possible reason for the land cover change. Landsat images were obtained from USGS Glovis, National boundary data
was clipped and dissolved selecting study area, and demographic data were obtained from Central Bureau of Statistics,
Nepal for the research. Data was analyzed using Supervised Classification method with maximum likelihood parameter.
From the result, it is concluded that the urban area has increased by 47.86% in study area with the decrease in forest area
by 26.25%. The possible reason for the land cover change can be attributed to rapid increase in population growth and
rapid urbanization. Also, decrease in water resource and barren land can also be accounted to rapid urbanization and
rapid change in land use pattern though research provides sufficient room for further research in this area of study
Spatial analysis for the assessment of the environmental changes in the lands...Universität Salzburg
Presented research is focused on the spatial analysis aimed at the assessment of the environmental changes in the landscapes of Izmir surroundings, Turkey. Methods include Landsat TM images classification using Erdas Imagine, clustering segmentation and classification, verification via the Google Earth and GIS Mapping. Tme span is 13-years (1987-2000). Images were taken from the Global Land Cover Facility (GLCF) Earth Science Data Interface. The selected area of Izmir has the most diverse landscape structure and high heterogeneity of the land cover types. Accuracy results computed. Kappa statistics for the image 2000: 0.7843, for the image 1987: 0.7923. The classification of the image 1987: accuracy 81.25%, 2000: 80,47%. The results indicate changes in land cover types affected by human activities, i.e. increased agricultural areas. Results include following findings. 1987: croplands (wheat) covered 71% of the today’s area (2000): 2382 vs. 3345 ha. Increase in barley cropland areas is noticeable as well: 1149 ha in 1987 vs. 4423 ha in 2000. Sparsely vegetated areas now also occupy more areas : 5914 ha in 2000 against 859 ha in 1987. Natural vegetation, decreased, which can be explained by the expansion of the agricultural lands. 1987: coppice areas covered 5500 ha while later on there are only 700 ha in this land type.
Seismic Risk Assessment and Hazard mapping in NepalPrinceShahabkhan
Assalamualikum
This presentation is about" Seismic Risk Assessment and Hazard mapping in Nepal" and it is related to Hazard and Disaster management Subject.
Introduction to Geographic Information system and Remote Sensing (RS)chala hailu
A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present all types of geographical data
Remote Sensing is Art, science and technology of observing an object, scene or phenomenon by instrument-based techniques without physical contact
Modelled and Analysed the watershed Dynamics in Mahanadi River Basin. Finally came up with watershed Management Plan to minimise the future LUCC in Mahanadi River Basin
GIS and Sensor Based Monitoring and Prediction of Landslides with Landslide M...iosrjce
Monsoon rains affect the Indian subcontinent every year causing devastating floods and deadly
landslides. The worst damages usually are reported in the northern and north-eastern part of India in the
Himalayan region. High risk landslide sites are located across the country, which become dangerous during
rainy season. Hence, monitoring and prediction of landslides in these regions are of utmost importance.
Geographical data management and dissemination for mitigation activities in the event of such disasters can be
handled effectively using GIS technology and physical sensors. With parallel computing power available,
models can be run by varying parameters to simulate different landslide scenarios. This will help in
understanding the landslide precursors, critical parameter values and create awareness among those living on
these slopes on real time.
Application to the whole regional territory over a dense computation grid can aim at the development of a real
time system to generate landslide risk scenarios based on precursor data. The proposed Landslide Monitoring
and Prediction System (LMPS) is based on the principles of landslide physics and hence a sensor-based
monitoring of the precursor variables will lead to an operational landslide monitoring and prediction system,
combining the strengths of mathematical modeling and GIS
GIS and Remote Sensing to study urban-rural transformation during a fifty-yea...Maurizio Pollino
C. R. Fichera, G. Modica, M. Pollino (2011).
Presented at "Computational Science and Its Applications - ICCSA 2011 International Conference", Santander, Spain, June 20-23, 2011.
A relevant issue in Remote Sensing (RS) and GIS is related to the analysis and the characterization of Land Use Land Cover (LULC) changes, very useful for a wide range of environmental applications and to efficiently undertake landscape planning and management policies. The methodology described has been applied to a case-study conducted in the area of the Province of Avellino (Southern Italy). Firstly, aerial photos and Landsat imagery have been classified to produce LULC maps for a fifty-year period (1954÷2004). Then, through a GIS approach, change detection and spatiotemporal analysis has been integrated to characterize LULC dynamics, focusing on the urban-rural gradient. This study has shown that LULC patterns and their changes are linked to both natural and social processes whose driving role has been clearly demonstrated: after the disastrous Irpinia earthquake (1980), local specific zoning laws and urban plans have significantly addressed landscape changes.
Presentation of Four Centennial-long Global Gridded Datasets of the Standardi...Agriculture Journal IJOEAR
Abstract— In this article four global gridded datasets of the Standardized Precipitation Index (SPI) are presented. They are computed from four different data sources: UDEL/GEOG/CCR v3.02, GPCC/ v7.0, NOAA-CIRES 20CR v2c and ECMWF ERA-20C each covering more than a century-long period. The SPI is calculated for the most frequently used time windows of 1, 3, 6, and 12 months. UDEL/GEOG/CCR v3.02 and GPCC/ v7.0 are used in the highest native resolution of 0.5×0.5° whilst NOAA-CIRES 20CR v2c and ECMWF ERA-20C are interpolated at 1.5×1.5° and 0.5×0.5° correspondingly. In contrast to some other indices, for example the popular Palmer Drought Severity Index (PDSI), SPI has significant advantages such as simplicity, suitability on variable time scales and robustness rooted in a solid theoretical development. SPI has been selected by the World Meteorological Organization (WMO) as a key indicator for monitoring drought ('Lincoln declaration'). As a result, drought monitoring centres worldwide are effectively exploiting this index and the National Meteorological and Hydrological Services (NMHSs) are encouraged to use it for monitoring meteorological droughts. These facts and the strong conviction of the authors that the free exchange of data and software services are а basis of effective scientific collaboration, are the main motivators to provide these datasets free of charge at ftp://xeo.cfd.meteo.bg/SPI/. The paper briefly presents some possible applications of the SPI data, revealing its suitability for various objective long-term drought studies at any geographical location.
Metastatistical Extreme Value distributionsRiccardo Rigon
Marco Marani and coworkers rethink the estreme value concepts, observinfg that Pearson's distributions are obtained as a limit of an infinite number of events. He proposed intermediate distribution, when the number of observations is limited. He, they, called these distribution metastistical. This is, I think new insight in old stuff. Pretty much necessary though.
Soil Organic Carbon mapping by geo- and class- matchingExternalEvents
The presentation was given by Mr. Bas Kempen & Ms. V.L. Mulder, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
A comparison of Land Cover Change in Kaski District, NepalBijesh Mishra
Kaski, one the major cities of Nepal, major tourism place and regional headquarter of Western Development
region, attracts large population from surrounding resulting 36.4% increase in population proportion and thus, land cover
is rapidly changing in the area. The research intended to find land cover change over nine years from 2000 to 2009 as well
as possible reason for the land cover change. Landsat images were obtained from USGS Glovis, National boundary data
was clipped and dissolved selecting study area, and demographic data were obtained from Central Bureau of Statistics,
Nepal for the research. Data was analyzed using Supervised Classification method with maximum likelihood parameter.
From the result, it is concluded that the urban area has increased by 47.86% in study area with the decrease in forest area
by 26.25%. The possible reason for the land cover change can be attributed to rapid increase in population growth and
rapid urbanization. Also, decrease in water resource and barren land can also be accounted to rapid urbanization and
rapid change in land use pattern though research provides sufficient room for further research in this area of study
Spatial analysis for the assessment of the environmental changes in the lands...Universität Salzburg
Presented research is focused on the spatial analysis aimed at the assessment of the environmental changes in the landscapes of Izmir surroundings, Turkey. Methods include Landsat TM images classification using Erdas Imagine, clustering segmentation and classification, verification via the Google Earth and GIS Mapping. Tme span is 13-years (1987-2000). Images were taken from the Global Land Cover Facility (GLCF) Earth Science Data Interface. The selected area of Izmir has the most diverse landscape structure and high heterogeneity of the land cover types. Accuracy results computed. Kappa statistics for the image 2000: 0.7843, for the image 1987: 0.7923. The classification of the image 1987: accuracy 81.25%, 2000: 80,47%. The results indicate changes in land cover types affected by human activities, i.e. increased agricultural areas. Results include following findings. 1987: croplands (wheat) covered 71% of the today’s area (2000): 2382 vs. 3345 ha. Increase in barley cropland areas is noticeable as well: 1149 ha in 1987 vs. 4423 ha in 2000. Sparsely vegetated areas now also occupy more areas : 5914 ha in 2000 against 859 ha in 1987. Natural vegetation, decreased, which can be explained by the expansion of the agricultural lands. 1987: coppice areas covered 5500 ha while later on there are only 700 ha in this land type.
Seismic Risk Assessment and Hazard mapping in NepalPrinceShahabkhan
Assalamualikum
This presentation is about" Seismic Risk Assessment and Hazard mapping in Nepal" and it is related to Hazard and Disaster management Subject.
Introduction to Geographic Information system and Remote Sensing (RS)chala hailu
A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present all types of geographical data
Remote Sensing is Art, science and technology of observing an object, scene or phenomenon by instrument-based techniques without physical contact
Modelled and Analysed the watershed Dynamics in Mahanadi River Basin. Finally came up with watershed Management Plan to minimise the future LUCC in Mahanadi River Basin
GIS and Sensor Based Monitoring and Prediction of Landslides with Landslide M...iosrjce
Monsoon rains affect the Indian subcontinent every year causing devastating floods and deadly
landslides. The worst damages usually are reported in the northern and north-eastern part of India in the
Himalayan region. High risk landslide sites are located across the country, which become dangerous during
rainy season. Hence, monitoring and prediction of landslides in these regions are of utmost importance.
Geographical data management and dissemination for mitigation activities in the event of such disasters can be
handled effectively using GIS technology and physical sensors. With parallel computing power available,
models can be run by varying parameters to simulate different landslide scenarios. This will help in
understanding the landslide precursors, critical parameter values and create awareness among those living on
these slopes on real time.
Application to the whole regional territory over a dense computation grid can aim at the development of a real
time system to generate landslide risk scenarios based on precursor data. The proposed Landslide Monitoring
and Prediction System (LMPS) is based on the principles of landslide physics and hence a sensor-based
monitoring of the precursor variables will lead to an operational landslide monitoring and prediction system,
combining the strengths of mathematical modeling and GIS
GIS and Remote Sensing to study urban-rural transformation during a fifty-yea...Maurizio Pollino
C. R. Fichera, G. Modica, M. Pollino (2011).
Presented at "Computational Science and Its Applications - ICCSA 2011 International Conference", Santander, Spain, June 20-23, 2011.
A relevant issue in Remote Sensing (RS) and GIS is related to the analysis and the characterization of Land Use Land Cover (LULC) changes, very useful for a wide range of environmental applications and to efficiently undertake landscape planning and management policies. The methodology described has been applied to a case-study conducted in the area of the Province of Avellino (Southern Italy). Firstly, aerial photos and Landsat imagery have been classified to produce LULC maps for a fifty-year period (1954÷2004). Then, through a GIS approach, change detection and spatiotemporal analysis has been integrated to characterize LULC dynamics, focusing on the urban-rural gradient. This study has shown that LULC patterns and their changes are linked to both natural and social processes whose driving role has been clearly demonstrated: after the disastrous Irpinia earthquake (1980), local specific zoning laws and urban plans have significantly addressed landscape changes.
Presentation of Four Centennial-long Global Gridded Datasets of the Standardi...Agriculture Journal IJOEAR
Abstract— In this article four global gridded datasets of the Standardized Precipitation Index (SPI) are presented. They are computed from four different data sources: UDEL/GEOG/CCR v3.02, GPCC/ v7.0, NOAA-CIRES 20CR v2c and ECMWF ERA-20C each covering more than a century-long period. The SPI is calculated for the most frequently used time windows of 1, 3, 6, and 12 months. UDEL/GEOG/CCR v3.02 and GPCC/ v7.0 are used in the highest native resolution of 0.5×0.5° whilst NOAA-CIRES 20CR v2c and ECMWF ERA-20C are interpolated at 1.5×1.5° and 0.5×0.5° correspondingly. In contrast to some other indices, for example the popular Palmer Drought Severity Index (PDSI), SPI has significant advantages such as simplicity, suitability on variable time scales and robustness rooted in a solid theoretical development. SPI has been selected by the World Meteorological Organization (WMO) as a key indicator for monitoring drought ('Lincoln declaration'). As a result, drought monitoring centres worldwide are effectively exploiting this index and the National Meteorological and Hydrological Services (NMHSs) are encouraged to use it for monitoring meteorological droughts. These facts and the strong conviction of the authors that the free exchange of data and software services are а basis of effective scientific collaboration, are the main motivators to provide these datasets free of charge at ftp://xeo.cfd.meteo.bg/SPI/. The paper briefly presents some possible applications of the SPI data, revealing its suitability for various objective long-term drought studies at any geographical location.
Metastatistical Extreme Value distributionsRiccardo Rigon
Marco Marani and coworkers rethink the estreme value concepts, observinfg that Pearson's distributions are obtained as a limit of an infinite number of events. He proposed intermediate distribution, when the number of observations is limited. He, they, called these distribution metastistical. This is, I think new insight in old stuff. Pretty much necessary though.
Geostatistical analysis of rainfall variability on the plateau of Allada in S...IJERA Editor
The goal of this survey is to contribute to a better understanding of the distribution of the rainfall on the plateau
of Allada in Benin. The plateau of Allada is the garner ofCotonou and vicinities. The food production is over
62% rainfed.Then, it imports to analyze the way how rains are spatially distributed on the area in order to deduct
the potential rainfall. To achieve this goal, rainfall data of 28 stations have been used. Three sub-periods have
been identified: 1996-2000, 2001-2005 and 2006-2010. The distribution of rainfall has been established with
Thiessen and kriging methods. On average, 1117mm of rain fell on the study area per year. But three tendencies
were shown: the less rainy zones, the fairly rainy zones, and the greatly rainy zones. All the rainfall zones knew
an increase of the precipitations except Abomey-Calavi and Niaouli. But the variations are not significant. While
analyzing the spatial structure for the kriging of precipitations, it was revealed a power model of variogram. The
direction of the rainfall gradient is oriented southeast - northwest during the three sub-periods. Abomey-Calavi
recorded the weakest precipitations. The strongest values are interchanged between Toffo and Sékou, OuidahNorth
and Ouidah-City.
Evaluating Satellite Precipitation Error Propagation in Runoff Simulations of...Yiwen Mei
This study investigates the error characteristics of six quasi-global satellite precipitation products and associated error propagation in flow simulations for 16 mountainous basin scales (areas ranging from 255 to 6967 km2) and two different periods (May-Aug & Sep-Nov) in northeast Italy. The satellite products used in this study are 3B42-CCA, 3B42-V7, CMORPH and PERSIANN with their respect gauge-adjusted products. To evaluate the error propagation in flood simulations satellite precipitation datasets were used to force a gauge-calibrated hydrologic model to simulate runoff for the 16 basins, and comparing them to the gauge-driven simulated hydrographs for a range of moderate to high flood events spanning a nine-year period (2002 to 2009). Statistics describing the systematic and random error, the temporal similarity and error ratios between precipitation and runoff are presented.
data-driven approach to identifying key regions of change associated with fut...Zachary Labe
Labe, Z.M., T.L. Delworth, N.C. Johnson, and W.F. Cooke. A data-driven approach to identifying key regions of change associated with future climate scenarios, 23rd Conference on Artificial Intelligence for Environmental Science, Baltimore, MD (Jan 2024). https://ams.confex.com/ams/104ANNUAL/meetingapp.cgi/Paper/431300
Satellite based observations of the time-variation of urban pattern morpholog...Beniamino Murgante
Satellite based observations of the time-variation of urban pattern morphology using geospatial analysis
Gabriele Nolè, Rosa Lasaponara - Institute of Methodologies for Environmental Analysis, National Research Council, Italy
CLIMATE CHANGE AND ITS IMPACT ON GROUNDWATER TABLE FLUCTUATION IN PRECAMBRIAN...IAEME Publication
The study area falls within the semiarid region and frequently facing water scarcity problems. Rain is a form of precipitation, snow, sleet, hail and dew. The precipitation occurs when separate drops of waterfalls on the earth’s surface from clouds. Not all rain reaches the surface, however; some evaporates while falling through dry air, a type of precipitation called Virga. The precipitated water percolates to deeper zones to be stored as groundwater. The present study generates the primary data to map the groundwater table fluctuation in hard rock terrain of Chitradurga District
through Geomatics technique. Efforts have been made to evaluate a total of 20 representative rain gauge station samples and analyzed the season rainfall variation over a period of 31 years (1981- 2011). 47 representative well samples are collected to study the season-wise groundwater fluctuation of about 11 years (2000-2011). Rain gauge stations are plotted on a base map with their respective amount of rainfall.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
"Protectable subject matters, Protection in biotechnology, Protection of othe...
Climate Change and Armed Conflict
1. Spatio-temporal analyses of the relationship
between armed conflict and climate change
in Eastern Africa
Riazuddin Kawsar
MScGT Program
Supervisor Co-Supervisor Co-Supervisor Co-Supervisor
Edzer Pebesma Jorge Mateu Pedro Cabral Mário Caetano
IFGI, WWU LSI, UJI ISEGI, UNL ISEGI, UNL
2. Climate and armed conflict
?
• Higher temperature, droughts, poverty and Armed Conflict (Burke et al.
2009, 2010);
• Recent empirical works have been concerned about the link between the
economic shocks and conflict (Miguel et all. 2004; Ciccone 2011);
• Rainfall variations as predictor for changes in GDP growth in sub-Saharan
Africa (SSA);
• SSA is heavily dependent on rain fed agriculture;
• Cross country evidence is found;
Variation in annual average precipitation and temperature has impact on
GDP by means of Agricultural growth but there are disagreement too
(Buhaug 2010)
2
3. Conflict and development
?
• 127 civil wars in 73 states with over 16 millions deaths (1994-
1999);
• Enormous human cost but also economic cost: 8% of the world GDP
(Hess 2003);
• Around 58% of these conflicts were in Sub-Saharan Africa;
• One of the main obstacles to development in this continent (i.e.,
Angola, Sudan);
Understanding the determinants is the key for development policy
3
4. This study
?
• A step further to understand the relationship between climate change
and armed conflict by taking the analyses to a different scale
– Geographical disaggregation: 55 x 55 km subnational “cells”
– Temporal disaggregation: yearly climate variations
– Rich detailed geo-referenced datasets (1991-2000)
• Various approaches to model the relationship between armed
conflict and climate change
4
5. Study area
?
• 1991-2000(data availability)
• About 8,719,926 km2
• Area: 30 % of the Africa
Continent
• number of armed conflict
(AC): 3,289
• region experienced highest
number of AC (31 % )
• Efficient data processing
and analyses
Fig 1 the distribution of the Armed Conflict in Africa
5
6. Our contributions
?
• Methodology
– Disaggregated level of analysis in space, space and time;
– Point Process Modelling approach;
– Careful modelling of spatial dependence, spatial and temporal
autocorrelation (using Spatial autoregressive Models)
• Focus on climate within the cell (spatial and temporal fashion)
– Identify cell specific yearly climate variation;
– More closely linked to agriculture then aggregated index;
• New climate indicator
– Weighted Anomaly Soil Water Index (WASWI): captures
variation of precipitation + evaporation + temperature.
6
7. Estimation strategies (1/3)
?
• Grid approach (cell and cell/year panel)
• Main dependent variable
– Events: the number of conflicts related episode a cell
experienced during the year (GED, UCDP, Version 1.5)
• Independent Variables
– Soil Water Index (SWI) (TWIN)
– WASWI (dimensionless measure of the relative severity of SWI surplus or deficit)
– Standardized Precipitation Index (SPI) (GPCC)
– Population (GPW, version 3)
7
8. Estimation strategies (2/3)
?
• WASWI preparation (Lyon and Barnston 2005)
𝑁
(𝑠𝑤𝑖 𝑖 − 𝑠𝑤𝑖 𝑖 ) 𝑠𝑤𝑖 𝑖
𝑊𝐴𝑆𝑊𝐼 𝑁 =
𝜎𝑖 𝑠𝑤𝑖 𝐴
𝑖=1
• 𝑠𝑤𝑖 𝑖 = is the observed value of SWI for the ith month
• 𝑠𝑤𝑖 𝑖 = represents long term (1991-2000) mean of monthly SWI for the ith
month
• 𝜎 𝑖 = standard deviation of the anomalies of monthly SWI for the ith month
• 𝑠𝑤𝑖 𝐴 = mean annual SWI
𝑠𝑤𝑖 𝑖
• = Weighting factor representing the monthly fraction of annual SWI*
𝑠𝑤𝑖 𝐴
*to reduce large standardized SWI anomalies that might result from small precipitation amounts or higher
temperature and evaporation, occurring near the start or end of dry seasons and to emphasize anomalies during
the heart of rainy seasons. 8
9. Estimation strategies (3/3)
?
Fig 2 space-time plot of Soil Water Index (SWI)
Fig 3 space-time plot of WASWI Fig 4 average of yearly WASWI (1991-2000)
9
10. Point process modelling (1/3)
(with aggregated data)
?
Fig 5 area−interaction process
(adopted from Baddeley 2010)
Fig 6 Point wise critical envelopes for inhomogeneous version of the L-
function in Inhomogeneous area-interaction process
Table 1 Fitted coefficients for trend formula using non-stationary area-interaction process
(Intercept) Population WASWI SPI
-16.30236 0.00044 -0.16475 0.87916
10
11. Point process modelling (2/3)
(for disaggregated data)
?
Fig 7 year 1999 (with covariates Fig 8 year 1999 (with covariates Fig 9 year 1999 (with covariates
of the year 1999) of the year 1998) of the year 1997)
Fig 10 year 1997 (with Fig 11 year 1997 (with Fig 12 year 1997 (with
covariates of the year 1997) covariates of the year 1996) covariates of the year 1995)
11
12. Point process modelling (3/3)
(with disaggregated data)
?
Fig 13 Standardized fitted coefficients for Inhomogeneous cluster point process model
12
13. Space-time point process modelling (1/2)
(with disaggregated data)
?
Fig 14 Image of spatial Fig 15 3-30 𝐾 𝑆𝑇 𝑢, 𝑣 − 𝜋𝑢2 𝑣 with various distance and time sequence for the
intensity based on kernel case events without covariates
Fig 16 Image of spatial Fig 17 𝐾 𝑆𝑇 𝑢, 𝑣 − 𝜋𝑢2 𝑣 with small u (up to 440 km) and v (up to 20
intensity based on covariates days) for the case events with covariates 13
14. Space-time point process modelling (2/2)
(with disaggregated data)
?
Fig 18 Superimposed events (red) with simulated Fig 19 Superimposed events (red) with simulated
(black) realization of point process using kernel (black) realization of point process using covariates
>.001 >.001
>.005 >.005
<.01 <.01
Fig 20 P-value for 𝐾 𝑆𝑇 𝑢, 𝑣 − 𝜋𝑢2 𝑣 for the Fig 21 P-value for 𝐾 𝑆𝑇 𝑢, 𝑣 − 𝜋𝑢2 𝑣 for the
case events without covariates from 100 case events with covariates from 100
simulation simulation
14
15. Spatial cross sectional models
(with aggregated data )
?
Table 2 Spatial autoregressive model output for the aggregated data (year 1991 to 2000)
15
16. Impacts in spatial durbin model
?
j1 j2 j3
Spillover Effect
Lesage and Pace (2007) j8 i j4
Feedback Effect
j7 j6 j5
Table 3 impacts in SDM output for the aggregated data for the year 1991 to 2000
Direct impact: fitted coefficient + additional feedback impact
Indirect impact: spillover impact (neighboring impact)
Total impact: Direct impact + indirect impact
16
17. Spatio-temporal SAR models
?
Fig 21 Neighbors addressed for of temporally lagged SAR model (left), model 2 (middle) and model 3 (right).
This figure is adopted from Espindola, Pebesma, et al. (2011)
17
18. Spatio-temporal SAR models
?
Table 4 Spatio-temporal autoregressive model (SAR) output from the disaggregated data for the year 1991 to 2000
18
19. Findings
• Local level negative relationship between conflict and climate change
– change in WASWI impact change in AC by -0.1981 or -0.1657
– Conflicts are clustered up to 200 km
• Spatio-temporal spillover
– Conflict in the own cell associated to a (0.3651) increase in the
probability of conflict of the following year
• Climate change indicator: long term WASWI measured at the cell level are
strong local conflict predictor
So…
Climate measures of a particular year don’t have significant effect on armed
conflict outbreak of the following year but Climate Change (long term
measure) has significant effect on Armed Conflict outbreak
19
20. Conclusion
• Sub national disaggregated studies may provide more support for the
resource conflict nexus. Further study for the whole continent is
recommended
• Our findings also gave an indication of acceptance of such hypothesis, that
in future the conflict situation is going to be worse due to climate change
(temperature increase, decrease in precipitation, results less water in soil
can trigger more conflict outbreak)
• Incising the temporal resolution (seasonal level) we can get a more clear
picture
• Separating the spatial and temporal factors can take us another step forward
in understanding the determinants which is the key for development policy.
20
21. Linking climate change and armed conflict,
we can answer tomorrow’s World Peace
today
Thank you
21