webinar cities in transition

15 years M.Sc. Photogrammetry and

GeoinformaticsProf. Dr. Dietrich Schröder

1999

December 31 – The U.S. turns over

complete administration of the Panama

Canal to the Panamanian Government

December 31 – Boris Yeltsin resigns as

President of Russia, leaving Prime Minister

Vladimir Putin as the acting President

The Lecturers The Students

1999

Prof. Dr. Mohl

Prof. Kettemann

Prof. Dr. Hahn

Prof. Dr. Johannsen

Prof. Dr. Behr

Prof. Dr Mönicke

Prof. Dr. Huep

Prof. Dr. Mohr

Prof. Dr. Lehmkühler

Prof. Dr. Schröder

The Lecturers The Students

1999

Prof. Dr. Mohl

Prof. Kettemann

Prof. Dr. Hahn

Prof. Dr. Johansen

Prof. Dr. Behr

Prof. Dr Mönicke

Prof. Dr. Huep

Prof. Dr. Mohr

Prof. Dr. Lehmkühler

Prof. Dr. Schröder

Prehistoric time 1980 – International Advanced Training Centre for Photogrammetry

(IPO ) 1997 - Proposal for M.Sc. developed 11.1998 - DAAD Application for scholarships14.09.1999 - Approval by the Ministry with the conditions:

• 15 to 25 students• above average first degree in a related study program

The start1.10.1999 First batch started:

• 12 students 8 with DAAD scholarship

• Trimester system• program director in charge

Prof. Dr. Hahn• one of the first

post-graduates study programs in Baden-Württemberg Graduation 2001

The past 15 years 01.10.1999 – Start of the first batch01.10.2000 – Entry into the AGEP group01.09.2001 - Program Director in charge Prof. Dr. Dietrich Schröder01.10.2002 - change to semester structure13.12.2002 - Accreditation by ASIIN01.10.2003 – Welcome of the 100th student27.06.2008 – Re-Accreditation 10.12.2008 – AGSE pre-conference in Trivandrum, India24.04.2009 – External Evaluation by DAAD2010-2012 – Fading out of the DAAD support13.07.2009 – Welcome of the 250th student01.09.2009 – First AGSE conference in Stuttgart10.03.2014 - Successful re-application for the DAAD-EPOS program (Development-Related Postgraduate Courses)01.10.2014 – Welcome of the 350th student05.11.2014 – 15th jubilee of the study program and 6th AGSE conference in Stuttgart

Scholarships Development-Related Postgraduate Courses (EPOS)• target Group for Scholarships are foreign Professionals:

• with a first academic degree• at least two years of relevant work experience• with excellent perspectives for professional reintegration upon return to the

home country

• 108 scholarships + 5 Study Scholarships for Graduates of All Disciplines

• support of the study program, e.g. extensive tutor program or establishing an online pre-course

• marketing• intercultural weekend seminar every year• re-invitation program• Carlo-Schmid program

Times are changing…

Changes in content and structure:• new/other software programs• new applications• new sensors• new policies• new standards• …

RADAR RS TerraSAR-x

Hyperspcetral EnMAP

crowdsourcing

participatory approaches

3D City Model

Where are our graduates and students are coming from?

more than 350 graduates and students from 80 different countries

10%3%

5%

4%

2%

20%

1%

25%

2%0.3%

4%

0.3%3%

20%

Germany

Western Europe

Eastern Europe

Near and Middle East

Central Asia

East Asia

South Asia

Indian Subcontinent

Central America

North America

South America

Oceania

North Saharan Africa

South Saharian Africa


3% 15%

5%

5%

6%

8%35%

9%

4% 7%3%

agriculture

civil engineering

envirironmental sciences

forestry

geology

geography

geomatics

information technology

natural science

planning

space science


Where are our graduates and students are going to?

DAAD Survey 2011

The coming 15 years

Will there be a study program like Photogrammetry and Geoinformatics necessary in 2029?• spatial awareness of people will still grow• the spatial dimension of many problems will gain more importance (Poverty reduction programs, disaster management, agriculture, environmental education, sustainable management of natural resources, biodiversity, health and medicine,…)

How will the program look like?• more online and shared modules in a network grid of cooperating

university departments all over the world• more exchange of students and lecturers• more cooperation of private and public institutions with complete

transparency supplemented by participatory and crowdsourcing approaches

Still there will be the need for human interaction and collective training to get a common understanding for the problems of our globalized world!

17

Studienbereich/Absender

Intercultural Weekend Seminar Bad Boll

18


Dr. Michael Kalff, ZNE, 5.11.2014

Dr. Michael KalffZNE – Centre for Sustainable DevelopmentGreat Transition: shifts from industrial to sustainable society Stuttgart, Nov 5th, 2014

19



Engines replace the muscularity of man and beast „Work against money“ instead of self supply Anonymous social security instead of family und guild Democracy, constitutional nations, und competition of

political parties instead of monarchy Nuclear family instead of extended family – urban flats,

nursing homes for the elderly people Labour unions, civil associations, civil code Creation of money by credit and debt, accumulation of

wealth Education for everybody, social mobility Constant growth of GNP, even in spite of two world wars

Industrial Societies: 150 Years of Success

20


Source: NASA Dr. Michael Kalff, ZNE, 5.11.2014

Wage share of German national income 1960-2007

Western Peak of Industrial Society

Olof Palme

21


Source: GENI Dr. Michael Kalff, ZNE, 5.11.2014

22



Physis: The Limits of Planet Earth

23



Polis: The Global Limits of Community People now disappear from production, like horses disappeared

from farming Earned income decreases and is hardly sufficient for living Social security is crashing National democracies are too small for the big problems and

too big for the small problems, political parties are too slow and too inefficient

Patchwork families, birth rate falling Failure of the industrial monetary system Education systems educate for the past, not for the future Growth of GNP doesn‘t work anymore

24


Sources: 1: J.Jahnke, 2: Wikipedia, 3: Wolfgang Heiser, 4: Bund der Steuerzahler Dr. Michael Kalff, ZNE, 5.11.2014

Oikos: The Global Limits of Economy

GNP and Financial Assets Germany National Debt Germany

Capital Income

Efficiency of Labour

Gross Wages per Worker Germany

25

HTWG Konstanz | Welcome to GlobopolisSustainable Development:Successful management of ecological, social and economic transitions towards a global society (Globopolis).

Globopolis integrates theecological, social and economic limits of globeinto it’s subsystems.

26



Physis:Integration of the Earth’s limits into social and economical systems: global management of resources; RE; climate protection; ...Polis:Generation and distribution of income; participative democracy; communities and creation of meaning; cooperation of religions; ...Oikos:Sustainable monetary systems; economy beyond growth; ...

Transition towards Globopolis

27



0

400

800

1200

1600

2000

2400

2800

3200

0 400 800 1200 1600 2000 2400 2800 3200brutto

Steuer

Grundeinkommenbruttonetto

Sustainable Development: Basic income funded by taxes on value creation

Taxes

Basic IncomePre-taxNet

28



Monetary diversity regarding issuer, money creation, backing. Layered money: sectoral/regional – national – global.

Complementary currencies for an expedient decoupling of local production and certain sectors from global markets.

Plain money instead of credit money.Interest rate ladder starts negative.

Sustainable Development: Sustainable monetary system

29



30



Sustainable Development: Reinforcing the third sector

Source: Prof. Dr. Karl Birkhölzer Technet, TU Berlin

World economy

Local economy

1. Private sector

2. Public sector

Third sectorShadow economy

Community economy

Social economy

31



Sustainable Development: Reinforcing the third sector

Source: Prof. Dr. Karl Birkhölzer Technet, TU Berlin

Shadow economy

Social enterprises

Local economy

World economy

Community economy

Social economy

Social welfare associations

Solidarity

Crime

Twilight economy

Family economy Self

help

32

HTWG Konstanz | Welcome to GlobopolisOne Chance Only

"It has often been said that, if the human species fails to make a go of it here on Earth, some other species will take over the running. In the sense of developing high intelligence this is not correct. We have, or soon will have, exhausted the necessary physical prerequisites so far as this planet is concerned. With coal gone, oil gone, high-grade metallic ores gone, no species however competent can make the long climb from primitive conditions to high-level technology. This is a one-shot affair. If we fail, this planetary system fails so far as intelligence is concerned. The same will be true of other planetary systems. On each of them there will be one chance, and one chance only."

Sir Fred Hoyle, "Of Men and Galaxies," 1964

33


Foto: LJR BW Dr. Michael Kalff, ZNE, 5.11.2014

Questions?Protests?Additions?

AGSE 2014 3 – 7 Nov 2014 HfT-Stuttgart A.P.Pradeepkumar

l Big Data Analytics in Disaster Management

l A.P.Pradeepkumarl University of Kerala, India


•Prevention/Mitigation•Preparedness

•Response •Recovery

Disaster


l Reference mapsl Pre-disaster situation maps

l Reference maps

l Disaster response maps

l Reference mapsl Post-disaster situation maps


l Disaster Tweeting


l Disaster Tweeting

l Unknown Source – verified location using iPhone

l Video stream situational information


l Social Media Messa

ge

l Volunteer

Crisis Team

l Local EMA

l Crisis Response Map


l Disaster & Emergency alerts

l Transportation/Vehicular Networks l Sensor Networks

l Networked Mobile Societies Everywhere, Anytime


l The Internet as a Lifeline - Person Finder (Google)


•Copernicus is faced with big data issues :• acquisition and management of an extremely large and

growing volume of Earth observation data• long term series analysis

• challenge to produce service information from heterogeneous datasets with a diversity of formats and

metadata• interoperability issues between systems

• variety of access rights, intellectual property protection

Copernicus – new name for GMES – Global Monitoring for Environement and Security


Volcano Eyjafjallajökull plume


Efficient use of large amounts of scientific dataOpen access for reliable scientific and commercial use

Long term preservation for re-use, re-analysis, verification or validationCreate trust in data, information and systems


l Disaster Prediction & Detection


l Red Cross study on Potential Uѕе οf Social Media іn Disaster

• About half of the respondents are willing to sign up for email, text alerts to receive news regarding an

emergency

• About half of the respondents would mention a particular emergency on their social media channel

75% choose Facebook as the most used platform for respondents to post eyewitness information during an

emergency or newsworthy event. • 22% Blogs / 22% Twitter

• Vast majority will choose Facebook as the platform of choice when it comes to posting about their safety


Public behavior response analysis in disaster events utilizing visual analytics of microblog dataJunghoon Chae, Dennis Thom et al.

For emergency and disaster management, analysis of publicbehavior, such as how people prepare and respond to disasters, is important for evacuation planning.

Social media has played a pervasive role in the way people think, act, and react to the world (more than 40 million Americans use social media web sites multiple times a day

Social media is changing the way people communicate not only in their daily lives, but also during abnormal events, such as natural disasters.


Interactive analysis scheme for public behavior analysis using social media data


Spatial user-based Tweet distribution in the Manhattan area in New York City during 4 h after the evacuation order on 28 Oct 2014


Twitter user distribution on the eastern coast area in New Jersey, after the hurricane passed over the area on October 31st (Right).

Previous distribution on October24th (left)


Distribution of Twitter users of each consecutive date (October 26–30, 2012), who post hurricane related Tweets on the southeastern (1 and 2) and northeastern coast (3, 4, and 5) area of the United States. Note the variance of Twitter user reactions along the track of the hurricane center locations.


Topic cloud: Topics from Tweets within the selected area ordered by their abnormality scores.


Temporal analysis for public behaviors during the disaster event, Sandy. Number of Twitter users within the selected region including a supermarket in in 4 h intervals is shown. Many people went to the supermarket right after the evacuation order.


Residents in Zone A (red) faced the highest risk of flooding, Zone B (yellow) and Zone C (green) are moderate and low respectively.

Visualization for spatiotemporal social media data (Left). A hexagon represents the spatial (position) and temporal (color) information of a Tweet. Hurricaneevacuation map (Right).


Social Media MiningSocial Data scientist

Big Data Paradox Obtaining Sufficient Samples

Noise Removal Fallacy Evaluation Dilemma

Apache Hadoop

MapReduce NoSQL databases


Big Data need not be Big Noise

Thank you

Poverty Situation : A Comparison of Different Countries

Dr. Vinita YadavPh.D. , Master’s in Urban Planning, M.B.A (Financial Management), Master’s in GeographyUrban Planner and Governance SpecialistFaculty, Department of Regional PlanningSchool of Planning and Architecture, New DelhiE Mail id. [email protected]

AGSE 2014Stuttgart

Scheme of PresentationEvolution of Poverty LineMillennium Development Goals

(MDGs)Difference in Level of PovertyInter-Country Comparison of

Poverty Line Poverty Status

05/01/2023Poverty Situation: A Comparison of Different Countries 80

Poverty Line 1990 World Development Report: $ 1 per day (Ravallion and Others 1991) 1990: assess poverty in the world as a whole by the standards of what

poverty means in the poorest countries

2005 : $1.25 as extreme Poverty and $2.50 per day as moderate poverty 2005 : Defined by mean of the indicators found in the poorest 15 countries in

terms of consumption per capita

Debate: Revising the poverty line

05/01/2023Poverty Situation: A Comparison of

Different Countries 81

Millennium Development Goals Achieving 1990 $1 a day:

reducing it by half by 2015

28.3 percent of all people living in low and middle income economies to 14.2 per cent.

05/01/2023Poverty Situation: A Comparison of Different

Countries 82

DIFFERENCE IN LEVEL OF POVERTY



Poverty Situation: A Comparison of Different Countries

Description World map showing % of population living on less than $1.25 (PPP) per day for 2000-2006.

Date 1 May 2009Source UN Human Development statistics 2008

PERCENTAGE OF POPULATION LIVING IN POVERTY IN WORLD

05/01/2023 85


05/01/2023 86

Per Capita Income

DIFFERENCE IN DEFINING POVERTY



United States of America Poverty defined in absolute term since 1960.

Measure of poverty in US is the poverty threshold.

threshold below which the families and individuals are considered to be lacking the resources to meets the basic needs for the healthy living ; having the insufficient income to provide the foods, shelter and clothing needed to preserve health.

For the individual who do not live with family members their own income is compared with appropriate threshold.

U.S. Census Bureau determines poverty status by comparing pre-tax cash income against a threshold that is set at three times the cost of a minimum food diet in 1963, updated annually for inflation using the Consumer Price Index, and adjusted for family size, composition, and age of householder. 05/01/2023

Poverty Situation: A Comparison of Different Countries 88

The Paradox ‘The typical American defined as poor by the

government has a car, air conditioning, a refrigerator, a stove, a clothes washer and dryer, and a microwave. He has two colour televisions, cable or satellite TV reception, a VCR or DVD player, and a stereo. He is able to obtain medical care. His home is in good repair and is not overcrowded. By his own report, his family is not hungry, and he had sufficient funds in the past year to meet his family’s essential needs. While this individual’s life is not opulent, it is equally far from the popular images of dire poverty conveyed by the press, liberal activists, and politicians’ (Rector and Johnson, 2004:1)



Europe defined in relation to the distribution of income within

each of 56 country in Europe. 1984 European Council Decision states: poor are

persons, families and groups of persons where resources (material, cultural and social) are so limited as to exclude them from a minimum acceptable way of life in the Member States in which they live (European Commission 1985, see Meijer 1999).

individuals living in households where the equivalised income is below the threshold of 60 % of the national equivalised median income (According to Euro stat's)

income deprivation within European countries leaves income gaps between countries.

distribution of poverty across Europe ranging from 4 percent poverty rate in Lithunia to a 35% rate in Ukraine.



People Below Poverty Line and Global Bank

• Highest levels of human poverty are registered in southern Europe, in particular in Portugal, Spain, Italy, Greece and Malta.

• Lowest levels of human poverty can be found in highly, moderately and less developed Member States – in particular in the Czech Republic, Sweden, Germany, Slovenia and Slovakia.

• Group of high development and low poverty includes particular in Germany, Austria, Finland and Sweden, Belgium, Denmark, France Netherland, UK etc.



Russia

Poverty line defined by those households whose adult income is less than 5497 Roubles i.e.$110/month.



Australia does not have an official poverty line, either absolute or relative as it

has a very high development index, but it is measured by certain private organizations in the country.

For September 2011 poverty line for Australia set Inclusive of housing costs, is $863.68 per week for a family comprising two adults, one of whom is working, and two dependent children.

decrease of $18.15 over the poverty line for the previous quarter (June 2011)




South-East Asia*poverty level is defined on the basis of world

bank’s definition taking into account the people who live in less than 2 US dollar a day or 1 US dollar a day.

ranks second after sub-saharan Africa in terms of percentage of its people who live in poverty.

1.3 billion people live on less than $2 US per day which shows that about 37 percent of South East Asia’s population is surviving on less than $1 a day (World Bank, Poverty Net Overview 2006). *Includes countries i.e. Cambodia, Laos, Myanmar, Thailand, Vietnam, Malaysia, East Timor, Indonesia, Philippines and Singapore

94

China people whose income is less than $1.25 per day set by

World Bank measured in 2 ways◦ Food Poverty Line

China in order to set a poverty line has chosen a calorie level i.e. intake of nutrition equivalent to 2100 calories per person per day.

Planning done on the basis of a food basket.◦ General Poverty Line◦ This looks as the issue of determining basic non-food

expenditure so as to obtain a general poverty line and are divided into two:

Direct: To calculate the cost of various non-food items such as clothing, housing, energy consumption etc

Indirect: Setting the basic non-food expenditure at a level just consistent with maintaining the food expenditure at the basic level



India: Evolution of Poverty line In 1962 the devised poverty line was a minimum consumer

expenditure of Rs. 20 per capita per month In 1979, Task Force under Dr Y. K. Alagh defined the

poverty line as “per capita consumption expenditure level, which meets the average per capita daily calorie requirement of 2400 kcal in rural areas and 2100 kcal in urban areas along with the expenditure on non-food items such as clothing, shelter, transport, education, health care, etc.”

In 1993, an Expert Group under the chairmanship of professor D. T. Lakdawala recommended to calculate state specific poverty lines taking the earlier 1973-74 price level as the base line.

In 2009, the Planning Commission set up another expert group under the chairmanship of Professor Suresh Tendulkar. A rural urban specific, state specific, weighted aggregate for different base years are calculated for the national aggregate poverty line.



IndiaA minimum level of living necessary for physical and

social development of a person.Estimated as: total consumption expenditure level that

meets energy (calorie) need of an average person.comprises of both food and non-food components of

consumption. Considers non-food expenditure actually incurred

corresponding to this total expenditure. Difficult to consider minimum non-food needs entirely

on an objective basis


“What changes when poverty is measured differently is not the actual number of poor in the country but the way the poverty line is defined.”

05/01/2023Poverty Situation: A Comparison of Different

Countries 98

DIFFERENCE IN LEVELS OF POVERTY



Official U.S. Poverty Rates


Different Countries

• In 2011, poverty threshold for a family of four with two children was $22,811.

• national poverty rate was 15.0 percent. • 46.2 million people in poverty.

%

100

% of People Below Poverty Line in Europe


Different Countries

Country Name

Population below poverty line (in %)

Year of Estimate

Global Rank

Ukraine 35 2009 Not available Macedonia 29 2008 Not available Belarus 27 2003 76 Moldova 26 2009 Not available Romania 25 2005 87 Bulgaria 22 2008 97 Slovakia 21 2002 98 Bosnia and Herzegovina

19 2007 Not available

Portugal 18 2006 109 Turkey 17 2008 111 Poland 17 2003 113 Croatia 17 2008 114 Ireland 6 2009 148 Lithuania 4 2003 149

Country Name

Population below Poverty Line (in%)

Year of Estimates

Global Bank

Germany 16 2010 119 Belgium 15 2007 120 United Kingdom

14 2006 124

Hungary 14 2010 Not available

Albania 13 2008 Not available

Slovenia 12 2008 98 Denmark 12 2007 130 Netherlands 11 2005 Not

available Serbia 9 2010 Not

available Montenegro 7 2007 Not

available Switzerland 7 2010 145 France 6 2004 146 Austria 6 2008 147 10

1

Russia People living in poverty declined from 33.5% in 1992 to

24.7% in 1995. Despite drop in poverty in 2003, 60% of its youth (30

million children) are in poor mental and physical health. In 2008-09, number of household below poverty line

decreased from 38% (1998) to 3% (2009) (Jeni Klugman).

Surge of poverty again became a problem between 2009-10, because of recession and rise in all prices.



Poverty Lines in Australia, September Quarter, 2011


Different Countries

Income Unit Including Housing($ Per Week )

Excluding Housing($ Per Week )

Couple Couple plus 1Couple plus 2Couple plus 3 Couple plus 4 Single person Single parent

plus 1 Single parent

plus 2Single parent

plus 3 Single parent

plus 4

615.12739.40 863.68987.97 1,112.25459.83590.33714.53 838.81963.09

449.89559.24668.58 777.92 886.05 309.46 425.02 534.36643.70 753.05 Source: The Melbourne Institute of Applied Economic and Social Research, 2012

103

Africa In Sub-Saharan Africa extreme poverty went up from 41

percent in 1981 to 46 percent in 2001, which combined with growing population increased the number of people living in extreme poverty from 231 million to 318 million.

nearly half of the population on the African continent remains poor and jobless despite significant improvement in economic growth (UN 2006).

Over the period 1960-2000, Africa’s population-weighted per capita annual growth of GDP was a mere 0.1%. Between 1980 and2000 the annual rate of divergence was an astounding 5%.




South-East Asia Poverty (% by using national poverty line)

05/01/2023 105

COUNTRIES TOTAL RURAL URBANCambodia 35.9 18.2 40.1Indonesia 18.2 14.5 21.1Lao PDR 38.6 26.9 41.0Malaysia 7.5 3.4 12.4Myanmar 22.9 23.9 22.4

Philippines 34.0 20.4 47.4Thailand 9.8 4.0 12.6Vietnam 28.9 6.6 35.6


South-East AsiaMalaysia and Singapore have healthy

economies and low poverty rates (Szczepanski, 2005).

Thailand and Philippines are on their way to recovery after severe set-backs during the disastrous Asian Financial Crisis of 1998 when the corporate culture of banks and governments could not deal with global capital flows.

Nations such as Cambodia, Laos, Burma, and East Timor rank near the bottom of global development lists.

05/01/2023 106

China China’s poverty research has so far been confined

to the rural areas. This can be explained by the following two points. ◦ For a long time a strict household registration

system was used, which restricted the influx of rural population into urban areas

◦ The cities had a comparatively perfect system of employment and social security.

urban poverty had not become as serious as its rural poverty.


CAUSES OF POVERTY: DIFFERENT FOR DIFFERENT NATIONS



USA◦ Loss of a job: nearly 20 percent of people enter poverty when the

head of household loses a job.◦ Decline in earnings: half of poverty spells begin with the

household experiences a decline in earnings.◦ No high school degree: households headed by someone without a

high school degree have a high likelihood of entering poverty.◦ Female-headed household: When a two-adult household becomes

a female-headed household 20.1 percent entered poverty.◦ Having children: 8.6 percent of poverty entries happen when a

child is born into a household.◦ Disability: when a head of household becomes disabled, 6.5

percent of households enter poverty.◦ Child poverty: low level of parental work and high numbers of

single-parent families” (Rector and Johnson, 2004, p.16).



Europe Europe appears to be uniformly highly developed. A wide variety of human development levels emerge

across and within European countries most European face challenges of human development or poverty.

fight against poverty has a long history in the EU, starting as early as the 1970s.

In recent decades, the issue of the ‘working poor’ slowly entered the public debate in the EU

In the past, having a job would successfully protect someone from the risk of poverty.

Due to changes in the labour market such as the development of a low-paid services sector, as well as in private life and family structures like growing number of single parents, work and poverty were no longer self-exclusive.



Russia Soviet Union broke apart in 1991, the transition has been

difficult for many Russians. With the sudden shift in its economy and privatization in

public enterprises, tones of industries collapsed leading to unemployment and loss of social assistance and wages.

Socialism in Russia was able to keep the poverty levels low. However, after 1991, one third of Russians lived below poverty line.

By 1994, real income had fallen by 60% from1991 Tregional differentiation of welfare indicators increased

dramatically between 1992 and 1994.



Who are Russia’s Poor Households with unemployed members are found to

be four times poorer than those with jobs (1992). Household with women population are 3.7 times

poorer. households with population under the age of 64 are

1.7times poorer. Those with high school or less level of education are

3.2 times poorer than those with high school plus education.

60% of poor households fall within the age group of 18-64 and has no surplus income.

Working poor also predominates Russia.



Africa: Impact of Poverty About 50 % of the African population lives in slums.

◦ From the outskirts of Johannesburg in South Africa to the Interior of Kibera (Africa’s largest and worst slum) in Kenya.

Three-fourths of the poor population in Western and Central Africa are subsistence farmers.

A child dies every three seconds from AIDS and due to extreme poverty before their fifth birthday.

More than 50 percent of Africans suffer from water-related diseases.

57% of African children are enrolled in primary education, and one in three of those does not complete school.

64% of children in Sub-Saharan Africa do not have adequate sanitation.

2,00,000 child slaves are sold every year in Africa. an estimated 8,000 girl-slaves in West Africa alone.



South-East AsiaHigh incidence of rural poverty incidence of poverty in rural areas can be

five times as high as that in urban areas. For example, in Vietnam, the incidence of

poverty in rural areas stands at 36 per cent versus 7 per cent for urban areas.

Only Myanmar registers an incidence of poverty that is higher in urban areas than in rural areas

05/01/2023 114

China China has maintained a high growth rate for more than

30 years since the beginning of economic reform in 1978 leading to huge increase in average living standard.

As per the World Bank’s Household survey in China, the poverty rate in China in 1981 was 64% of the population. This rate declined to 10% in 2004, indicating that about 500 million people have climbed out of poverty during this period.

From 1981 to 2007, fall in the poverty head count from 18.5 percent to less than 2 percent

China has undoubtedly made the largest single contribution to global poverty reduction of any country in the last 20 years.



Irony of Indian Poor Using the same distribution of consumption expenditure

from the National Sample Survey Organisation for the same year, 2004-05 poverty estimates ranges from ◦ Single digits by Surjit Bhalla, ◦ 26% according to the Lakdawala committee ◦ 37% by the Suresh Tendulkar committee ◦ 42% by the World Bank ◦ 77% by the Arjun Sengupta committee and ◦ Around 80% by Utsa Patnaik using the calorie measure.

05/01/2023Poverty Situation: A Comparison of Different Countries

“The extent of confusion that has been created due to lack of clarity on the basic conceptual underpinnings especially with respect to the identification of the poor undoubtedly inspired awe and wonder both locally as well as globally.”

-- Bandopadhyay, 2010 p. 23

116


ConclusionBenchmark by way of poverty

line doesn’t give an insight into the real situation

Varied estimates of the number of urban poor by different institutions

Patronage Received by Poor: Does it help?

Amenities vs. Affordability05/01/2023 11

7


Way AheadInclusive PlanningParticipatory PlanningEquity Affordable Service DeliveryEquitable Distribution of

Resources

05/01/2023 118


THANK YOU

05/01/2023 119

Poverty Mapping techniqes in India

Presented bySatyendra Singh

Geospatial Consultant, Architect and Environment PlannerEmail: [email protected]

Poverty Map of India

(Urban and Rural)

Map of world poverty by country, showing percentage of population living under $2 (PPP) a day. As per 2009 UN Human Development

Report.

What is Poverty?considerable debate on how to best define the term

Poor Economic conditionLack of basic necessitiesUrban and Rural Poverty

Poverty in Indiadebate on existing methodology for estimating poverty

Source: Times of India survey 2014

Tendulkar methodology ( 2011-12) the poverty

line was Rs 816($15) /month in rural areas and Rs

1,000( $18) /month in urban areas

Rangarajan Methodology the

poverty line should be Rs 972($18) /month in

rural areas and Rs 1,407($26) /month in

urban areas

Poverty in IndiaEstimation of number of poor (in Million)

Source: Times of India survey 2014

29.5% of the India population lives below the poverty line as defined by the Rangarajan committee, as against

21.9% according to Tendulkar

125

India Administrative Hierarchy Country

State (36)

District Admin. Division(676)

Sub-district (5,767) C D Block (7,933)

Town (5,161)Village (0.6 million)

Ward

State of the art for Poverty Mapping in India

126

Census Mapping 20112.7 million Enumerators were deployed for 2011 Census

Before census, a complete list of administrative units (e.g., state, district, sub-district, towns and villages) is finalized to

ensure full coverage ( freeze admin boundary) Population was classified according to gender, religion, education and

occupation

Unique Permanent Location Code Number (PLCN) assigned to each and every village in the country for the first time in

2001 Census

2001 Census: Notable work for Geographic reference

Unique code is allotted to each state, district, sub-district, town, village

State/UT …. 2 digits (within the country)District …. 2 digits (within the state/UT)

Sub-district …. 4 digits (within the district)Village …. 8 digits (within the state/UT)Town …. 8 digits (within the district)

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Thematic maps portraying census and house listing ( at country, state, district, sub-

district level )

Census Mapping 2011

Map showing state-wise

poverty percentage

(Rural, Urban, Combined)

Source: www.mapsofindia.com

Poverty Map of India(Urban and Rural)

Andaman & Nicobar 0.4 0.3 0.4Andhra Pradesh 22.8 17.7 21.1Arunachal Pradesh 26.2 24.9

25.9Assam 39.9 26.1 37.9Bihar 55.3 39.4 53.5Chandigarh 10.3 9.2 9.2

Chhattisgarh 56.1 23.8 48.7Dadra and Nagar 55.9 17.7 39.1Daman and Diu 34.2 33 33.3Delhi 7.7 14.4 14.2Goa 11.5 6.9 8.7Gujarat 26.7 17.9 23

Haryana 18.6 23 20.1Himachal Pradesh 9.1 12.6

9.5Jammu & Kashmir 8.1 12.8

9.4Jharkhand 41.6 31.1 39.1Karnataka 26.1 19.6 23.6Kerala 12 12.1 12Lakshwadeep 22.2 1.7 6.8

Madhya Pradesh 42 22.9 36.7Maharashtra 29.5 18.3 24.5Manipur 47.4 46.4 47.1Meghalaya 15.3 24.1 17.1Mizoram 31.1 11.5 21.1Nagaland 19.3 25 20.9Orissa 39.2 25.9 37Puducherry 0.2 1.6 1.2

Punjab 14.6 18.1 15.9Rajasthan 26.4 19.9 24.8Sikkim 15.5 5 13.1Tamil Nadu 21.2 12.8 17.1Tripura 19.8 10 17.4Uttar Pradesh 39.4 31.7 37.7Uttarakhand 14.9 25.2 18

West Bengal 28.8 22 26.7

Total 33.8 20.9 29.8

Source: www.pinterest.com

Map showing District-

wise % of population

living Below

Poverty Line (BPL)

Source: www.datastories.in

Map showing % Households with no Census Assets

Census Assets= Phone, TV or radio,

Vehicle

Map showing District-wise % of population living Below Poverty

Line (BPL)

Map showing % Households with no Census Assets

Poverty Mapping : Comparision of techniques

Poverty Mapping : Indicators in Census

Houselistings

Source: www.wikipedia.org

Poverty Mapping : Indicators in Census

Source: www.wikipedia.org

Population enumeration

National Population Register

Poverty Mapped ?Not really?

Poor Economic condition=done?Lack of basic necessities= done?

Urban and Rural Poverty ?What about use of GIS?

Urban Poverty Mapping using GIS (Mapping Slums)

Level 3:Carry out household Sample Survey and Analyze the data after integrating spatial and socio-economic data along with HH sample data using different techniques( Small

area estimation, regression etc)

Level 2:Link Spatial Data to census information with focus on

Economic Condition(socio-economic data that is collected includes employment, caste, education and family size..) as well as access to basic necessities (information about

infrastructure and access to facilities such as toilets, water,education..) etc.

Level 1:Create critical spatial data of slums graphically overlaid onto the remote sensing image or extract missing data

from ImageValidate the data with existing map in the city to get a

slum-wide or city-wide view of the data

Urban Poverty Mapping using GIS (Mapping Slums)

Level 1:Create critical spatial data

of slums ( Example of Ahmedabad City) , 1998-

2005

Effort to estimateurban poverty under

SJSRY .The 32% of the slum dwellers in the

city occupy 8% of the total residential land.

Slum Networking Project with focus on improving Physical

Environment and Community Developmen

Source: Ahmedabad Municipal

Corporation Map

Level 2:Link Spatial Data to census/HH Survey

information

Effort to estimate state of the art for Water Supply at Gandhinagar slum in Pune

A detailed map of each settlement, showing every house, manhole,

water point, electric pole etc

Source: http://shelter-associates.org/gis-remote-sensing

Query results: for provision of water standposts

Thematic Maps with linked information for Water Supply

Level 3:Poverty Analysisto

present disaggregated information to capture

heterogeneity( Small area estimation)

These Situations where household surveys are too small to be representative at levels of disaggregation, and most census data do not contain the required information to calculate

poverty.Step 1: consists in the estimation of regressions that model expenditure

or consumption using a set of explanatory variables that are common to both the HH survey

and the census (e.g. household size, education, housing and

infrastructure characteristics and demographic variables)

Source: http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTPOVERTY/

Object-oriented mapping of urban poverty and deprivation.

Step2: Estimated coefficients from these regressions to

predict expenditure or consumption for every

household in the census on the basis of the explanatory

variables that are common to the census and the survey.

These household-unit data are then used to compute poverty

estimates for small areas.

•Inter-departmental synergy•Data Mapping techniques•Land Mafia occupying lands•Multiple spatial data models•Multiple systems using GIS•Multiple departments building GIS applications from scratch•Redundant data across multiple systems with no clear system of record (metadata)•Lack of integration between spatial and MIS data

Challenges ahead

Thank You