In 2022, the union territory of Delhi had the highest urban population density of over 18 thousand persons per square kilometer. While the rural population density was highest in union territory of Puducherry, followed by the state of Bihar.

As of 2019, the south Indian state of Kerala had the highest density of doctors of about ** per ten thousand population in the country. However, Jharkhand had the least density of doctors in the country of about **** doctors per ten thousand people in the state.

This feature layers contain demographics about age, gender, education, employment, assets & amenities as reported by Office of the Registrar General & Census Commissioner, India in the Census 2011. These attributes cover topics such as male and female population counts by age, literacy, occupation, and household characteristics.Census of India counts every resident in India at village level. It is mandated by The Census Act 1948 of the Constitution and takes place every 10 years.Other demographics layers are also available:Country DemographicsDistrict DemographicsSub-district DemographicsVillage DemographicsCombined DemographicsEach layer contains the same set of demographic attributes. Each geography level has a viewing range optimal for the geography size, and the map has increasing detail as you zoom in to smaller areas.Data source: Explore Census DataAdmin boundary source (country, states, and districts): Survey of India, 2020For more information: 2011 Census Demographic ProfileFor feedback please contact: content@esri.inData Processing notes:Country, State and District boundaries are simplified representations offered from the Survey of India database.Sub-districts and village boundaries are developed based on the census provided maps.Field names and aliases are processed by Esri India as created for the ArcGIS Platform.For a list of fields and alias names, access the following excel document.Disclaimer:The boundaries may not be perfectly align with AGOL imagery. The Census PDF maps are georeferenced using Survey of India boundaries and notice alignment issues with AGOL Imagery/ Maps. 33k villages are marked as point location on Census PDFs either because of low scale maps where small villages could not have been drawn or digitization has not been completed. These villages are marked as 100m circular polygons in the data.This web layer is offered by Esri India, for ArcGIS Online subscribers. If you have any questions or comments, please let us know via content@esri.in.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household, enterprise

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: No - Special populations: Persons without any normal residence, foreign nationals, and people in barracks of military and para-military forces, orphanages, rescue homes, ashram and vagrant houses are not covered by survey.

UNIT DESCRIPTIONS: - Households: A group of persons normally living together and taking food from a common kitchen will constitute a household. The members of a household may or may not be related by blood to one another.

Universe

All population in India, except for foreigners, the homeless, or people in barracks of military and para-military forces, orphanages, rescue homes, ashram, and vagrant houses.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Sample Survey Organization, Government of India

SAMPLE DESIGN: Two-stage, stratified samples drawn by the country, coupled with rotation sampling scheme for the central sample. (1) Stage 1: In the central sample, 10,384 first stage units (rural and urban combined) were selected from stratified states in proportion to poluation. Among them, 3,900 of which were revisted. (2) Stage 2: households and enterprises were selected from second-stage strata(hamlet-groups or sub-blocks) by circular systematic sampling with equal probability. (3) Under the rotation sampling scheme which was adopted for the first time in the National Sample Survey, 50% of the sample first stage units in the central sample were revisited in the subsequent three-month period. In state samples, the first stage units were only visited once.

SAMPLE UNIT: Household

SAMPLE FRACTION: .07%

SAMPLE SIZE (person records): 596,688

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form that consists of 8 sections: 1) identification of sample household, 2) household characteristics, 3) demographic and migration particulars, 4) usual principal activity, 5) subsidiary activity, 6) current work activity during the preceding week, 5) follow-up questions for the unemployed, 6) availability for work to working persons, 7) job change of working persons, and 8) questions for females.

Response rate

COVERAGE: 100% of the Indian Union excepting (1) Ladakh and Kargil districts of Jammu and Kashmir, (2) interior villages of Nagaland situated beyond 5 kms. of a bus route, and (3) villages of Andaman and Nicobar Islands remaining inaccessible throughout the year. Also excluded were all the uninhabited villages according to 1991 census.

India population growth rate for 2023 was 0.88%, a 0.09% increase from 2022.

<ul style='margin-top:20px;'>

<li>India population growth rate for 2022 was <strong>0.79%</strong>, a <strong>0.03% decline</strong> from 2021.</li>
<li>India population growth rate for 2021 was <strong>0.82%</strong>, a <strong>0.15% decline</strong> from 2020.</li>
<li>India population growth rate for 2020 was <strong>0.97%</strong>, a <strong>0.07% decline</strong> from 2019.</li>
</ul>Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

As of 2019, the capital Indian territory of Delhi had the highest density of nurses and midwives of about ** per ten thousand people in the country. However, Bihar had the least density of nurses and midwives in the country of about *** per ten thousand people in the state.

This feature layers contain demographics about age, gender, education, employment, assets & amenities as reported by Office of the Registrar General & Census Commissioner, India in the Census 2011. These attributes cover topics such as male and female population counts by age, literacy, occupation, and household characteristics.Census of India counts every resident in India at village level. It is mandated by The Census Act 1948 of the Constitution and takes place every 10 years.Other demographics layers are also available:Country DemographicsState DemographicsSub-district DemographicsVillage DemographicsCombined DemographicsEach layer contains the same set of demographic attributes. Each geography level has a viewing range optimal for the geography size, and the map has increasing detail as you zoom in to smaller areas.Data source: Explore Census DataAdmin boundary source (country, states, and districts): Survey of India, 2020For more information: 2011 Census Demographic ProfileFor feedback please contact: content@esri.inData Processing notes:Country, State and District boundaries are simplified representations offered from the Survey of India database.Sub-districts and village boundaries are developed based on the census provided maps.Field names and aliases are processed by Esri India as created for the ArcGIS Platform.For a list of fields and alias names, access the following excel document.Disclaimer:The boundaries may not be perfectly align with AGOL imagery. The Census PDF maps are georeferenced using Survey of India boundaries and notice alignment issues with AGOL Imagery/ Maps. 33k villages are marked as point location on Census PDFs either because of low scale maps where small villages could not have been drawn or digitization has not been completed. These villages are marked as 100m circular polygons in the data.This web layer is offered by Esri India, for ArcGIS Online subscribers. If you have any questions or comments, please let us know via content@esri.in.

Abstract

The Employment and Unemployment surveys of National sample Survey (NSS) are primary sources of data on various indicators of labour force at National and State levels. These are used for planning, policy formulation, decision support and as input for further statistical exercises by various Government organizations, academicians, researchers and scholars. NSS surveys on employment and un-employment with large sample size of households have been conducted quinquennially from 27th. round(October'1972 - September'1973) onwards. Cotinuing in this series the fourth such all-india survey on the situation of employment and unemployment in India was carried out during the period july 1987 - june 1988 .

The working Group set up for planning of the entire scheme of the survey, among other things, examined also in detail some of the key results generated from the 38th round data and recommended some stream-lining of the 38th round schedule for the use in the 43rd round. Further, it felt no need for changing the engaging the easting conceptual frame work. However, some additional items were recommended to be included in the schedule to obtain the necessary and relevant information for generating results to see the effects on participation rates in view of the ILO suggestions.5.0.1. The NSSO Governing Council approved the recommendations of the working Group and also the schedule of enquiry in its 44th meeting held on 16 January, 1987. In this survey, a nation-wide enquiry was conducted to provide estimates on various characteristics pertaining to employment and unemployment in India and some characteristics associated with them at the national and state levels. Information on various facets of employment and unemployment in India was collected through a schedule of enquiry (schedule 10).

Geographic coverage

The survey covered the whole of Indian Union excepting i) Ladakh and Kargil districts of Jammu & Kashmir ii) Rural areas of Nagaland

Analysis unit

Randomly selected households based on sampling procedure and members of the household

Kind of data

Sample survey data [ssd]

Sampling procedure

It may be mentioned here that in order to net more households of the upper income bracket in the Sample , significant changes have been made in the sample design in this round (compares to the design of the 38th round).

SAMPLE DESIGN AND SAMPLE SIZE The survey had a two-stage stratified design. The first stage units (f.s.u.'s) are villages in the rural sector and urban blocks in the urban sector. The second stage units are households in both the sectors. Sampling frame for f.s.u.'s : The lists of 1981 census villages constituted the sampling frame for rural sector in most districts. But the 1981 census frame could not be used for a few districts because, either the 1981 census was not held there or the list of 1981 census villages could not be obtained or the lists obtained from the census authorities were found to be grossly incomplete. In such cases 1971 census frame were used. In the urban sector , the Urban Frame Survey (U.F.S.) blocks constituted the sampling frame. STRATIFICATION : States were first divided into agro-economic regions which are groups of contiguous districts , similar with respect to population density and crop pattern. In Gujarat, however , some districts have been split for the purpose of region formation In consideration of the location of dry areas and the distribution of the tribal population in the state. The composition of the regions is given in the Appendix. RURAL SECTOR: In the rural sector, within each region, each district with 1981Census rural population less 1.8 million formed a single stratum. Districts with larger population were divided into two or more strata, depending on population, by grouping contiguous tehsils similar, as for as possible, in respect of rural population Density and crop pattern. (In Gujarat, however , in the case of districts extending over more than one region, even if the rural population was less than 1.8 million, the portion of a district falling in each region constituted a separate stratum. Further ,in Assam the old "basic strata" formed on the basis of 1971 census rural population exactly in the above manner, but with cut-off population as 1.5 million have been retained as the strata for rural sampling.) URBAN SECTOR : In the urban sector , strata were formed , again within NSS region , on the basis of the population size class of towns . Each city with population 10 lakhs or more is self-representative , as in the earlier rounds . For the purpose of stratification, in towns with '81 census population 4 lakhs or more , the blocks have been divided into two categories , viz . : One consisting of blocks in areas inhabited by the relatively affluent section of the population and the other consisting of the remaining blocks. The strata within each region were constituted as follows :

Table (1.2) : Composition of urban strata

Stratum population class of town

number

(1) (2)

1 all towns with population less than 50,000 2 -do- 50,000 - 199,999 3 -do- 200,000 - 399,999 4 -do- 400,000 - 999,999 ( affluent area) 5 (other area) 6 a single city with population 1 million and above (affluent area) 7 " (other area) 8 another city with population 1 million and above

9 " (other area)

Note : There is no region with more than one city with population 1 million and above. The stratum number have been retained as above even if in some regions some of the strata are empty. Allocation for first stage units : The total all-India sample size was allocated to the states /U.T.'s proportionate to the strength of central field staff. This was allocated to the rural and urban sectors considering the relative size of the rural and urban population. Now the rural samples were allocated to the rural strata in proportion to rural population. The urban samples were allocated to the urban strata in proportion to urban population with double weight age given to those strata of towns with population 4 lakhs or more which lie in area inhabited by the relatively affluent section. All allocations have been adjusted such that the sample size for stratum was at least a multiple of 4 (preferably multiple of 8) and the total sample size of a region is a multiple of 8 for the rural and urban sectors separately.
Selection of f.s.u.'s : The sample villages have been selected circular systematically with probability proportional to population in the form of two independent interpenetrating sub-samples (IPNS) . The sample blocks have been selected circular systematically with equal probability , also in the form of two IPNS' s. As regards the rural areas of Arunachal Pradesh, the procedure of 'cluster sampling' was:- The field staff will be supplied with a list of the nucleus villages of each cluster and they selected the remaining villages of the cluster according to the procedure described in Section Two. The nucleus villages were selected circular systematically with equal probability, in the form of two IPNS 's. Hamlet-group and sub-blocks : Large villages and blocks were sub- divided into a suitable number of hamlet-groups and sub-blocks respectively having equal population convent and one them was selected at random for surveys. Hamlet-group and sub-blocks : Large villages and blocks were sub- divided into a suitable number of hamlet-groups and sub-blocks respectively having equal population convent and one them was selected at random for surveys. Selection of households : rural : In order to have adequate number of sample households from the affluent section of the society, some new procedures were introduced for selection of sample households, both in the rural and urban sectors. In the rural sector , while listing households, the investigator identified the households in village/ selected hamlet- group which may be considered to be relatively more affluent than the rest. This was done largely on the basis of his own judgment but while exercising his judgment considered factors generally associated with rich people in the localitysuch as : living in large pucca house in well-maintained state, ownership/possession of cultivated/irrigated land in excess of certain norms. ( e.g.20 acres of cultivated land or 10 acres of irrigated land), ownership of motor vehicles and costly consumer durables like T.V. , VCR, VCP AND refrigerator, ownership of large business establishment , etc. Now these "rich" households will form sub-stratum 1. (If the total number of households listed is 80 or more , 10 relatively most affluent households will form sub-stratum 1. If it is below 80, 8 such households will form sub-stratum 1. The remaining households will 'constitute sub-stratum 2. At the time of listing, information relating to each household' s major sources of income will be collected, on the basis of which its means of livelihood will be identified as one of the following : "self-employed in non-agriculture " "rural labour" and "others" (see section Two for definition of these terms) . Also the area of land possessed as on date of survey will be ascertained from all households while listing. Now the households of sub-stratum 2 will be arranged in the order : (1)self-employed in non-agriculture, (2) rural labour, other households, with land possessed (acres) : (3) less than 1.00 (4) 1.00-2.49,(5)2.50-4.99, (6)

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones. The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

India

Analysis unit

Household Individual

Universe

National Population, Both sexes,18 and more years

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 2002

As part of the India component of the World Values Survey, it was decided to conduct 2000 face-toface interviews. A rigorous scientific method was employed to generate the target sample for the study. The survey was conducted in 18 states of India, which covered nearly 97 % of the nations population.

40 districts in the country were identified for the purpose of the survey (a little less than 1/10 of the districts in the country: 466 districts as per 1991 census). The 40 districts were spread across the 18 states, in which the survey was conducted keeping in mind the population of the states, even while ensuring that the survey was conducted in at least one district in each of the sampled states.

Within each state, the district/s in which the survey was to be conducted was selected by circular sampling (PPS: Probability Proportion to Size). Once all the 40 districts were selected, the Lok Sabha (Lower House of the Indian Parliament)constituency that covered the district was identified. If the sampled district had more than one Lok Sabha constituency, the one, which had a larger proportion of the districts electorate, was selected.

The next stage in the sampling process was the selection of 2 State Assembly (Lower House of the State Legislature) constituencies in each of the sampled 40 Lok Sabha constituencies. Circular Sampling (PPS: Probability Proportion to Size) was once again employed. Thus, 80 Assembly Constituencies in 40 Lok Sabha constituencies (in 40 districts) were selected. Subsequently, a polling booth area in each of the 80 sampled Assembly constituencies was selected by simple circular sampling method.

The number of respondents to be interviewed in each state was determined on the basis of the proportion of the states share in the national population. This was equally divided among the polling booth areas that were sampled in a state. The number of respondents in the polling booth area was the same within a state, but varied from state to state. In a polling booth area, the respondents were selected from the electoral rolls (voters list) by circular sampling with a random first number.

While drawing up the random list of respondents to be interviewed in every sampled polling booth area, the number of target respondents was increased by nearly 20 %. This was done in view of the fact that the field investigators were required to interview only those respondents whose names were included in the sample list. No replacements or alteration in the list of sampled respondents was permitted. Previous survey experience has shown that it has never been possible for the investigator to interview all those included in the list of sampled respondents. A wide range of factors is responsible for the same. The investigators were told to make every effort to interview all those included in the list of respondents. In the event of the investigator not being able to complete an interview, they were asked to record the reason for the same. Such a rigorous method of sampling was followed in order to obtain as representative a national sample as possible. The analysis of the sample profile clearly indicates that the detailed and objective criteria employed has eminently served its purpose as the sample mirrors the nations social, economic, political, cultural and religious diversity.

Remarks about sampling: - Final numbers of clusters or sampling points: No clusters - Sample unit from office sampling: Named individual

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was translated into ten Indian languages by a specialist translator. A few modifications were undertaken in response categories for the scale answer questions. It was then back-translated to English. For each of the 10 languages the pre test was done on a sample of 5 each. There were several concepts and questions difficult to translate: more specifically v75/76/v103/v175/v208/v212/v229/. These problems were solved by developing new phrases close to the original statement or using it in the context of social reality The sample was designed to be representative of the entire adult population, i.e. 18 years and older, of your country. The lower age cut-off for the sample was 18 and there was not any upper age cut-off for the sample.

Response rate

The following table presents completion rate results: - Total number of starting names/addresses 2354 - Addresses which could not be traced at all 56 - Addresses established as empty, demolished or containing no private dwellings 39 - Selected respondent too sick/incapacitated to participate 29 - Selected respondent away during survey period 62 - Selected respondent had inadequate understanding of language of survey 27 - No contact at selected address 76 - No contact with selected person 31 - Refusal at selected address 34 - Full productive interviews 2002

Sampling error estimates

Estimated Error: 2,2

Data set of a community based cross-sectional survey done to find the prevalence , its correlates and patterns in a population of a district in southern Kerala, IndiaBackground: Multi-morbidity is the coexistence of multiple chronic conditions in the same individual. With advancing epidemiological and demographic transitions, the burden of multi-morbidity is expected to increase India. The state of Kerala in India is also in an advanced phase of epidemiological transition. However, very limited data on prevalence of multi-morbidity are available in the Kerala population.

Methods: A cross sectional survey was conducted among 410 participants in the age group of 30-69 years. A multi-stage cluster sampling method was employed to identify the study participants. Every eligible participant in the household were interviewed to assess the household prevalence. A structured interview schedule was used to assess socio-demographic variables, behavioral risk factors and prevailing clinical conditions, PHQ-9 questionnaire for screening of depression and active measurement of blood sugar and blood pressure. Co-existence of two or more conditions out of 11 was used as multi-morbidity case definition. Bivariate analyses were done to understand the association between socio-demographic factors and multi-morbidity. Logistic regression analyses were performed to estimate the effect size of these variables on multi-morbidity.

Results: Overall, the prevalence of multi-morbidity was 45.4% (95% CI: 40.5-50.3%). Nearly a quarter of study participants (25.4%) reported only one chronic condition (21.3-29.9%). Further, 30.7% (26.3-35.5), 10.7% (7.9-14.2), 3.7% (2.1-6.0) and 0.2% reported two, three, four and five chronic conditions, respectively. Nearly seven out of ten households (72%, 95%CI: 65-78%) had at least one person in the household with multi-morbidity and one in five households (22%, 95%CI: 16.7-28.9%) had more than one person with multi-morbidity. With every year increase in age, the propensity for multi-morbidity increased by 10 percent (OR=1.1; 95% CI: 1.1-1.2). Males and participants with low levels of education were less likely to suffer from multi-morbidity while unemployed and who do recommended level of physical activity were significantly more likely to suffer from multi-morbidity. Diabetes and hypertension was the most frequent dyad.

Conclusion: One of two participants in the productive age group of 30-69 years report multi-morbidity. Further, seven of ten households have at least one person with multi-morbidity. Preventive and management guidelines for chronic non-communicable conditions should focus on multi-morbidity especially in the older age group. Health-care systems that function within the limits of vertical disease management and episodic care (e.g., maternal health, tuberculosis, malaria, cardiovascular disease, mental health etc.) require optimal re-organization and horizontal integration of care across disease domains in managing people with multiple chronic conditions.

Key words: Multi-morbidity, cross-sectional, household, active measurement, rural, India, pattern

This feature layers contain demographics about age, gender, education, employment, assets & amenities as reported by Office of the Registrar General & Census Commissioner, India in the Census 2011. These attributes cover topics such as male and female population counts by age, literacy, occupation, and household characteristics.Census of India counts every resident in India at village level. It is mandated by The Census Act 1948 of the Constitution and takes place every 10 years.Other demographics layers are also available:Country DemographicsState DemographicsDistrict DemographicsSub-district DemographicsCombined DemographicsEach layer contains the same set of demographic attributes. Each geography level has a viewing range optimal for the geography size, and the map has increasing detail as you zoom in to smaller areas.Data source: Explore Census DataAdmin boundary source (country, states, and districts): Survey of India, 2020For more information: 2011 Census Demographic ProfileFor feedback please contact: content@esri.inData Processing notes:Country, State and District boundaries are simplified representations offered from the Survey of India database.Sub-districts and village boundaries are developed based on the census provided maps.Field names and aliases are processed by Esri India as created for the ArcGIS Platform.For a list of fields and alias names, access the following excel document.Disclaimer:The boundaries may not be perfectly align with AGOL imagery. The Census PDF maps are georeferenced using Survey of India boundaries and notice alignment issues with AGOL Imagery/ Maps. 33k villages are marked as point location on Census PDFs either because of low scale maps where small villages could not have been drawn or digitization has not been completed. These villages are marked as 100m circular polygons in the data.This web layer is offered by Esri India, for ArcGIS Online subscribers. If you have any questions or comments, please let us know via content@esri.in.

The statistic shows the total population of India from 2019 to 2029. In 2023, the estimated total population in India amounted to approximately 1.43 billion people.

Total population in India

India currently has the second-largest population in the world and is projected to overtake top-ranking China within forty years. Its residents comprise more than one-seventh of the entire world’s population, and despite a slowly decreasing fertility rate (which still exceeds the replacement rate and keeps the median age of the population relatively low), an increasing life expectancy adds to an expanding population. In comparison with other countries whose populations are decreasing, such as Japan, India has a relatively small share of aged population, which indicates the probability of lower death rates and higher retention of the existing population.

With a land mass of less than half that of the United States and a population almost four times greater, India has recognized potential problems of its growing population. Government attempts to implement family planning programs have achieved varying degrees of success. Initiatives such as sterilization programs in the 1970s have been blamed for creating general antipathy to family planning, but the combined efforts of various family planning and contraception programs have helped halve fertility rates since the 1960s. The population growth rate has correspondingly shrunk as well, but has not yet reached less than one percent growth per year.

As home to thousands of ethnic groups, hundreds of languages, and numerous religions, a cohesive and broadly-supported effort to reduce population growth is difficult to create. Despite that, India is one country to watch in coming years. It is also a growing economic power; among other measures, its GDP per capita was expected to triple between 2003 and 2013 and was listed as the third-ranked country for its share of the global gross domestic product.

India's population demographics - total population, growth rate, age-wise and state-wise population, languages spoken, and religion.

India birth rate for 2025 is 16.55, a 1.19% decline from 2024.

<ul style='margin-top:20px;'>

<li>India birth rate for 2024 was <strong>16.75</strong>, a <strong>3.74% increase</strong> from 2023.</li>
<li>India birth rate for 2023 was <strong>16.15</strong>, a <strong>1.16% decline</strong> from 2022.</li>
<li>India birth rate for 2022 was <strong>16.34</strong>, a <strong>0.94% decline</strong> from 2021.</li>
</ul>Crude birth rate indicates the number of live births occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.

The North-Eastern region (NER) of India, comprising of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland and Tripura, is a hot spot for genetic diversity and the most probable origin of rice. North-east rice collections are known to possess various agronomically important traits like biotic and abiotic stress tolerance, unique grain and cooking quality. The genetic diversity and associated population structure of 6,984 rice accessions, originating from NER, were assessed using 36 genome wide unlinked single nucleotide polymorphism (SNP) markers distributed across the 12 rice chromosomes. All of the 36 SNP loci were polymorphic and bi-allelic, contained five types of base substitutions and together produced nine types of alleles. The polymorphic information content (PIC) ranged from 0.004 for Tripura to 0.375 for Manipur and major allele frequency ranged from 0.50 for Assam to 0.99 for Tripura. Heterozygosity ranged from 0.002 in Nagaland to 0.42 in Mizoram and gene diversity ranged from 0.006 in Arunachal Pradesh to 0.50 in Manipur. The genetic relatedness among the rice accessions was evaluated using an unrooted phylogenetic tree analysis, which grouped all accessions into three major clusters. For determining population structure, populations K = 1 to K = 20 were tested and population K = 3 was present in all the states, with the exception of Meghalaya and Manipur where, K = 5 and K = 4 populations were present, respectively. Principal Coordinate Analysis (PCoA) showed that accessions were distributed according to their population structure. AMOVA analysis showed that, maximum diversity was partitioned at the individual accession level (73% for Nagaland, 58% for Arunachal Pradesh and 57% for Tripura). Using POWERCORE software, a core set of 701 accessions was obtained, which accounted for approximately 10% of the total NE India collections, representing 99.9% of the allelic diversity. The rice core set developed will be a valuable resource for future genomic studies and crop improvement strategies.

This feature layers contain demographics about age, gender, education, employment, assets & amenities as reported by Office of the Registrar General & Census Commissioner, India in the Census 2011. These attributes cover topics such as male and female population counts by age, literacy, occupation, and household characteristics.Census of India counts every resident in India at village level. It is mandated by The Census Act 1948 of the Constitution and takes place every 10 years.Other demographics layers are also available:Country DemographicsState DemographicsDistrict DemographicsVillage DemographicsCombined DemographicsEach layer contains the same set of demographic attributes. Each geography level has a viewing range optimal for the geography size, and the map has increasing detail as you zoom in to smaller areas.Data source: Explore Census DataAdmin boundary source (country, states, and districts): Survey of India, 2020For more information: 2011 Census Demographic ProfileFor feedback please contact: content@esri.inData Processing notes:Country, State and District boundaries are simplified representations offered from the Survey of India database.Sub-districts and village boundaries are developed based on the census provided maps.Field names and aliases are processed by Esri India as created for the ArcGIS Platform.For a list of fields and alias names, access the following excel document.Disclaimer:The boundaries may not be perfectly align with AGOL imagery. The Census PDF maps are georeferenced using Survey of India boundaries and notice alignment issues with AGOL Imagery/ Maps. 33k villages are marked as point location on Census PDFs either because of low scale maps where small villages could not have been drawn or digitization has not been completed. These villages are marked as 100m circular polygons in the data.This web layer is offered by Esri India, for ArcGIS Online subscribers. If you have any questions or comments, please let us know

Geographic coverage

The survey covered the whole of the Indian Union except (i) Leh (Ladakh) and Kargil districts of Jammu & Kashmir, (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Analysis unit

Household, Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design Outline of sample design: A stratified multi-stage design has been adopted for the 60th round survey. The first stage units (FSU) will be the 1991 census villages in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units (USU) will be households in both the sectors. In case of large villages/blocks requiring hamlet-group (hg)/sub-block (sb) formation, one intermediate stage will be the selection of two hgs/sbs from each FSU.

Sampling Frame for First Stage Units: For the rural sector, the list of Census 1991 villages (panchayat wards for Kerala) and Census 1981 villages for J & K will constitute the sampling frame. For the urban sector, the list of latest available Urban Frame Survey (UFS) blocks will be considered as the sampling frame.

Stratification Rural sector: Two special strata will be formed at the State/ UT level, viz.

Stratum 1: all FSUs with population between 0 to 50 and Stratum 2: FSUs with population more than 15,000.

Special stratum 1 will be formed if at least 50 such FSUs are found in a State/UT. Similarly, special stratum 2 will be formed if at least 4 such FSUs are found in a State/UT. Otherwise, such FSUs will be merged with the general strata.

From FSUs other than those covered under special strata 1 and 2, general strata will be formed and its numbering will start from 3. Each district of a State/UT will normally be treated as a separate stratum. However, if the census rural population of the district is greater than or equal to 2.5 million as per population census 2001 or 2 million as per population census 1991, the district will be split into two or more strata, by grouping contiguous tehsils to form strata. However, in Gujarat, some districts are not wholly included in an NSS region. In such cases, the part of the district falling in an NSS region will constitute a separate stratum.

Urban sector: In the urban sector, strata will be formed within each NSS region on the basis of size class of towns as per Population Census 2001. The stratum numbers and their composition (within each region) are given below.

stratum 1: all towns with population less than 50,000 stratum 2: all towns with population 50,000 or more but less than 2 lakhs stratum 3: all towns with population 2 lakhs or more but less than 10 lakhs stratum 4, 5, 6,...: each town with population 10 lakhs or more

The stratum numbers will remain as above even if, in some regions, some of the strata are not formed.

Total sample size (FSUs): 7612 FSUs have been allocated at all-India level on the basis of investigator strength in different States/UTs for central sample and 8260 for state sample.

Allocation of total sample to States and UTs: The total number of sample FSUs is allocated to the States and UTs in proportion to provisional population as per Census 2001 subject to the availability of investigators ensuring more or less uniform work-load.

Allocation of State/UT level sample to rural and urban sectors: State/UT level sample is allocated between two sectors in proportion to provisional population as per Census 2001 with 1.5 weightage to urban sector subject to the restriction that urban sample size for bigger states like Maharashtra, Tamil Nadu etc. should not exceed the rural sample size. Earlier practice of giving double weightage to urban sector has been modified considering the fact that there has been considerable growth in urban population. A minimum of 8 FSUs will be allocated to each state/UT separately for rural and urban areas.

Allocation to strata: Within each sector of a State/UT, the respective sample size will be allocated to the different strata in proportion to the stratum population as per census 2001. Allocations at stratum level will be adjusted to a multiple of 4 with a minimum sample size of 4.

Selection of FSUs: FSUs will be selected with Probability Proportional to Size With Replacement (PPSWR), size being the population as per Population Census 1991 in all the strata for rural sector except for stratum 1. In stratum 1 of rural sector and in all the strata of urban sector, selection will be done using Simple Random Sampling Without Replacement (SRSWOR). Within each stratum, samples will be drawn in the form of two independent sub-samples in both the rural and urban sectors.

Note: Detail sampling procedure is provided as external resource.

Mode of data collection

Face-to-face [f2f]

Research instrument

Schedule 10: Employment and Unemployment

Block 0- Descriptive identification of sample household: This block is meant for recording descriptive identification particulars of the sample household and the sample village/block to which the sample household belongs.

Block 1- Identification of sample household: The identification particulars of the sample household are to be recorded against items 1, 5 to 15.

Block 2- Particulars of field operation: The identity of the Investigator, Assistant Superintendent and Superintendent associated, date of survey/inspection/scrutiny of Schedules, despatch, etc., will be recorded in this block against the appropriate items in the relevant columns.

Block 3- Household characteristics: Certain household characteristics, such as, household size, household type, religion, social-group, household industry, household occupation, monthly household consumer expenditure, land possessed as on the date of survey (code) etc., will be recorded in this block.

Block 4- Demographic and usual activity particulars of household members: This block is meant to record the demographic particulars like sex, age, marital status, educational level etc. and usual principal activity and usual subsidiary activity particulars of all the household members.

Block 5- Time disposition of members during the week: This block is meant for recording the time disposition for all the 7 days preceding the date of survey, the current weekly status based on the 7 days time disposition, wage and salary earnings during the week, etc.

Block 6- Follow-up questions for persons unemployed on all the seven days of the week: This block is meant for collecting information on persons who are found to be unemployed on all the seven days of the week preceding the date of survey.

Block 7- Particulars of vocational training received by household members: Particulars of formal vocational training received will be collected in respect of all the household members who are in the age group 15-29 with minimum general education level middle and above but below graduate (i.e with codes 05 to 08 in column 7, block 4) and for those who are graduate in vocational courses within the age group 15-29.

Block 8- Household consumer expenditure: This block is meant for collecting household consumer expenditure information which is the sum total of monetary values of all goods and services consumed (out of purchase or procured otherwise) by the household on domestic account during a specific reference period.

Block 9- Remarks by investigator: Any remark which is considered necessary for explaining any peculiarity in the consumption pattern of the household or any other item-specific unusual feature of the household or of any member thereof will be noted here.

Block 10- Comments by supervisory officer(s): The supervisory officers should note their views on any aspect pertaining to the characteristics under enquiry in this schedule relating to the household or any member thereof.

Abstract

The 61st round of the Nationbal Sample Survey was conducted during July, 2004 to June, 2005. The survey was spread over 7,999 villages and 4,602 urban blocks covering 1,24,680 households (79,306 in rural areas and 45,374 in urban areas) and enumerating 6,02,833 persons (3,98,025 in rural areas and 2,04,808 in urban areas). Employment and unemployment were measured with three different approaches, viz. usual status with a reference period of one year, current weekly status with one week reference period and current daily status based on the daily activity pursued during each day of the reference week. Unless otherwise stated, ‘all’ usual status workers will mean all workers taking into consideration the usual principal and subsidiary status taken together.

Geographic coverage

The survey covered the whole of the Indian Union except (i) Leh (Ladakh) and Kargil districts of Jammu & Kashmir, (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Analysis unit

Household, individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Outline of sample design: A stratified multi-stage design has been adopted for the 61st round survey. The first stage units (FSU) are the 2001 census villages in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units (USU) are households in both the sectors. In the case of large villages/blocks requiring hamlet-group (hg)/sub-block (sb) formation, one intermediate stage is the selection of two hgs/sbs from each FSU.

Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the list of latest available Urban Frame Survey (UFS) blocks has been considered as the sampling frame.

Stratification: Within each district of a State/UT, two basic strata have been formed: i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, if there are one or more towns with population 10 lakhs or more as per population census 2001 in a district, each of them will also form a separate basic stratum and the remaining urban areas of the district will be considered as another basic stratum. There are 27 towns with population 10 lakhs or more at all-India level as per census 2001.

Sub-stratification:

• Rural sector: If 'r' be the sample size allocated for a rural stratum, the number of sub-strata formed is 'r/2'. The villages within a district as per frame have been first arranged in ascending order of population. Then sub-strata 1 to 'r/2' have been demarcated in such a way that each sub-stratum comprises a group of villages of the arranged frame and has more or less equal population.

• Urban sector: If 'u' be the sample size for a urban stratum, 'u/2' number of sub-strata have been formed. The towns within a district, except those with population 10 lakhs or more, have been first arranged in ascending order of population. Next, UFS blocks of each town have been arranged by IV unit no. × block no. in ascending order. From this arranged frame of UFS blocks of all the towns, 'u/2' number of sub-strata has been formed in such a way that each sub-stratum has more or less equal number of UFS blocks.

For towns with population 10 lakhs or more, the urban blocks have been first arranged by IV unit no. × block no. in ascending order. Then 'u/2' number of sub-strata has been formed in such a way that each sub-stratum has more or less equal number of blocks.

Total sample size (FSUs): 12784 FSUs have been allocated at all-India level on the basis of investigator strength in different States/UTs for central sample and 14992 for state sample.

Allocation of total sample to States and UTs: The total number of sample FSUs is allocated to the States and UTs in proportion to population as per census 2001 subject to the availability of investigators ensuring more or less uniform work-load.

Allocation of State/UT level sample to rural and urban sectors: State/UT level sample size is allocated between two sectors in proportion to population as per census 2001 with 1.5 weightage to urban sector subject to the restriction that urban sample size for bigger states like Maharashtra, Tamil Nadu etc. should not exceed the rural sample size. A minimum of 8 FSUs has been allocated to each state/UT separately for rural and urban areas.

Allocation to strata: Within each sector of a State/UT, the respective sample size is allocated to the different strata in proportion to the stratum population as per census 2001. Allocations at stratum level have been adjusted to a multiple of 4 with a minimum sample size of 4.

Selection of FSUs: Two FSUs have been selected from each sub-stratum of a district of rural sector with Probability Proportional to Size With Replacement (PPSWR), size being the population as per Population Census 2001. For urban sector, two FSUs have been selected from each sub-stratum by using Simple Random Sampling Without Replacement (SRSWOR). Within each sub-stratum, samples have been drawn in the form of two independent sub-samples in both the rural and urban sectors.

Selection of hamlet-groups/sub-blocks/households - important steps

Criterion for hamlet-group/sub-block formation: Large villages/blocks having approximate present population of 1200 or more will be divided into a suitable number (say, D) of 'hamlet-groups' in the rural sector and 'sub-blocks' in the urban sector as stated below.

approximate present population of the sample village/block / no. of hgs/sbs to be formed (D)

less than 1200 (no hamlet-groups/sub-blocks): 1
1200 to 1799: 3 1800 to 2399: 4 2400 to 2999: 5 3000 to 3599: 6 …..and so on

For rural areas of Himachal Pradesh, Sikkim and Poonch, Rajouri, Udhampur, Doda districts of Jammu and Kashmir and Idukki district of Kerala, the number of hamlet-groups formed is as follows.

approximate present population of the sample village / no. of hgs to be formed

less than 600 (no hamlet-groups): 1
600 to 899: 3
900 to 1199: 4
1200 to 1499: 5 …..and so on

Two hamlet-groups/sub-blocks are selected from a large village/UFS block wherever hamlet-groups/sub-blocks have been formed, by SRSWOR. Listing and selection of the households are done independently in the two selected hamlet-groups/sub-blocks. In case hamlet-groups/sub-blocks are to be formed in the sample FSU, the same would be done by more or less equalizing population.

Formation of Second Stage Strata and allocation of households

For both Schedule 1.0 and Schedule 10, households listed in the selected village/block/ hamlet-groups/sub-blocks are stratified into three second stage strata (SSS) as given below.

Rural: The three second-stage-strata (SSS) in the rural sector are formed in the following order:

SSS 1: relatively affluent households
SSS 2: from the remaining households, households having principal earning from non- agricultural activity
SSS 3: other households

Urban: In the urban sector, the three second-stage strata (SSS) are formed as under:

Two cut-off points, say 'A' and 'B', based on MPCE of NSS 55th round, have been determined at NSS Region level in such a way that top 10% of households have MPCE more than 'A' and bottom 30% have MPCE less than 'B'. Then three second-stage-strata (SSS) are formed in the urban sector in the following order:

SSS 1: households with MPCE more than A (i.e. MPCE > A)
SSS 2: households with MPCE equal to or less than A but equal to or more than B ( i.e. B = MPCE = A)
SSS 3: households with MPCE less than B (i.e. MPCE < B)

The number of households to be surveyed in each FSU is 10 for each of the schedules 1.0 and 10. C

Selection of households for Schedules 1.0 and 10: From each SSS the sample households for both the schedules are selected by SRSWOR. If a household is selected both for schedule 1.0 and schedule 10, only schedule 1.0 would be canvassed in that household and the sample household for schedule 10 would be replaced by next household in the frame for schedule 10.

Mode of data collection

Face-to-face [f2f]

Research instrument

In the present round, Schedule 10 on employment-unemployment consists of 16 blocks.

The first three blocks, viz. Blocks 0, 1 and 2, are used to record identification of sample households and particulars of field operations, as is the common practice in usual NSS rounds. Similarly, the last two blocks, viz., Blocks 10 & 11, are again the usual blocks to record the remarks of investigator and comments by supervisory officer(s), respectively. Block 3 will be for recording the household characteristics like household size, religion, social group, land possessed and cultivated, monthly per capita consumer expenditure, etc., and Block 3.1 for recording particulars of indebtedness of rural labour households.

Block 4 is used for recording the demographic particulars and attendance in educational institutions of all the household members. Particulars of vocational training receiving/received by the household members will also be collected in block 4.

In Block 5.1, particulars of usual principal activity of all the household members will be recorded along with some particulars of the enterprises in which the usual status workers (excluding those in crop and plantation activities) are engaged. Information on informal employment will also be collected in block 5.1. Similarly, the particulars of one subsidiary economic activity of the household members along with some

PerCapita_CO2_Footprint_InDioceses_FULLBurhans, Molly A., Cheney, David M., Gerlt, R.. . “PerCapita_CO2_Footprint_InDioceses_FULL”. Scale not given. Version 1.0. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.MethodologyThis is the first global Carbon footprint of the Catholic population. We will continue to improve and develop these data with our research partners over the coming years. While it is helpful, it should also be viewed and used as a "beta" prototype that we and our research partners will build from and improve. The years of carbon data are (2010) and (2015 - SHOWN). The year of Catholic data is 2018. The year of population data is 2016. Care should be taken during future developments to harmonize the years used for catholic, population, and CO2 data.1. Zonal Statistics: Esri Population Data and Dioceses --> Population per dioceses, non Vatican based numbers2. Zonal Statistics: FFDAS and Dioceses and Population dataset --> Mean CO2 per Diocese3. Field Calculation: Population per Diocese and Mean CO2 per diocese --> CO2 per Capita4. Field Calculation: CO2 per Capita * Catholic Population --> Catholic Carbon FootprintAssumption: PerCapita CO2Deriving per-capita CO2 from mean CO2 in a geography assumes that people's footprint accounts for their personal lifestyle and involvement in local business and industries that are contribute CO2. Catholic CO2Assumes that Catholics and non-Catholic have similar CO2 footprints from their lifestyles.Derived from:A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of resultshttp://ffdas.rc.nau.edu/About.htmlRayner et al., JGR, 2010 - The is the first FFDAS paper describing the version 1.0 methods and results published in the Journal of Geophysical Research.Asefi et al., 2014 - This is the paper describing the methods and results of the FFDAS version 2.0 published in the Journal of Geophysical Research.Readme version 2.2 - A simple readme file to assist in using the 10 km x 10 km, hourly gridded Vulcan version 2.2 results.Liu et al., 2017 - A paper exploring the carbon cycle response to the 2015-2016 El Nino through the use of carbon cycle data assimilation with FFDAS as the boundary condition for FFCO2."S. Asefi‐Najafabady P. J. Rayner K. R. Gurney A. McRobert Y. Song K. Coltin J. Huang C. Elvidge K. BaughFirst published: 10 September 2014 https://doi.org/10.1002/2013JD021296 Cited by: 30Link to FFDAS data retrieval and visualization: http://hpcg.purdue.edu/FFDAS/index.phpAbstractHigh‐resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high‐resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long‐term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long‐term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter‐term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set."Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/Esri Gridded Population Data 2016DescriptionThis layer is a global estimate of human population for 2016. Esri created this estimate by modeling a footprint of where people live as a dasymetric settlement likelihood surface, and then assigned 2016 population estimates stored on polygons of the finest level of geography available onto the settlement surface. Where people live means where their homes are, as in where people sleep most of the time, and this is opposed to where they work. Another way to think of this estimate is a night-time estimate, as opposed to a day-time estimate.Knowledge of population distribution helps us understand how humans affect the natural world and how natural events such as storms and earthquakes, and other phenomena affect humans. This layer represents the footprint of where people live, and how many people live there.Dataset SummaryEach cell in this layer has an integer value with the estimated number of people likely to live in the geographic region represented by that cell. Esri additionally produced several additional layers World Population Estimate Confidence 2016: the confidence level (1-5) per cell for the probability of people being located and estimated correctly. World Population Density Estimate 2016: this layer is represented as population density in units of persons per square kilometer.World Settlement Score 2016: the dasymetric likelihood surface used to create this layer by apportioning population from census polygons to the settlement score raster.To use this layer in analysis, there are several properties or geoprocessing environment settings that should be used:Coordinate system: WGS_1984. This service and its underlying data are WGS_1984. We do this because projecting population count data actually will change the populations due to resampling and either collapsing or splitting cells to fit into another coordinate system. Cell Size: 0.0013474728 degrees (approximately 150-meters) at the equator. No Data: -1Bit Depth: 32-bit signedThis layer has query, identify, pixel, and export image functions enabled, and is restricted to a maximum analysis size of 30,000 x 30,000 pixels - an area about the size of Africa.Frye, C. et al., (2018). Using Classified and Unclassified Land Cover Data to Estimate the Footprint of Human Settlement. Data Science Journal. 17, p.20. DOI: http://doi.org/10.5334/dsj-2018-020.What can you do with this layer?This layer is unsuitable for mapping or cartographic use, and thus it does not include a convenient legend. Instead, this layer is useful for analysis, particularly for estimating counts of people living within watersheds, coastal areas, and other areas that do not have standard boundaries. Esri recommends using the Zonal Statistics tool or the Zonal Statistics to Table tool where you provide input zones as either polygons, or raster data, and the tool will summarize the count of population within those zones. https://www.esri.com/arcgis-blog/products/arcgis-living-atlas/data-management/2016-world-population-estimate-services-are-now-available/

Abstract

The 44th round started from July 1988. The survey period of this round was July 1988 to June 1989. This round has been devoted to mainly three enquiries. First and foremost, there has been an enquiry on the living condition of the tribal population. Of the other two, one is concerned with the housing condition of the general population and the other is a survey on current building construction activity. For the purpose of this enquiry, “tribal population” mean the members of the Scheduled Tribes declared under the Article 342 of the Constitution of India. They are known to be the descendants of the earliest inhabitants of India (hence called “Adivasis”). At present, in most parts of India, they form one of the economically weakest sections of the society. So far there has not been any systematic study of their living conditions covering the whole country. Whatever data are available are derived from the decennial censuses, apart from some micro studies carried out by social anthropologists. In the NSS the tribal population has always been covered as part of the general population. In NSS 32nd and 33rd rounds special surveys had been carried out through an integrated schedule (schedule 16.4) in the North-Eastern region. The survey was conducted in the rural areas of the following States:- 32nd round : Arunachal Pradesh, Assam (N. Cachar and Karbi Anglong districts only), Manipur, Meghalaya and Tripura; 33rd round: In addition to the above States, Mizoram also. Even though this covered many aspects specially related to the life of the people of this region (who are mostly tribals), no such survey has so far been undertaken about the life of the tribals living in the main tribal belt stretching from West Bengal through Bihar, Orissa, Madhya Pradesh to Gujarat and Rajasthan. The scope of the enquiry is to understand the living condition of the tribals living in the main tribal belt stretching from West Bengal through Bihar, Orissa, Madhya Pradesh to Gujarat and Rajasthan.) The object of the enquiry in the this round is to throw light on as many aspects as possible of the tribal population of this country. This relates to aspects of their “level of the living” including demographic and activity particulars, family expenditure etc. as well as to their entrepreneurial activities.

Geographic coverage

The survey covered the whole of Indian Union except Ladakh and Kargil districts of Jammu and Kashmir state. The rural areas of Nagaland, so far outside NSS coverage up to the 43rd round, have also been brought in this round.

Analysis unit

Randomly selected households based on sampling procedure and members of the household

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design is stratified two-stage with the census village as the first stage unit in the rural sector and UFS block as the first stage unit in the urban sector. The second stage units are households.

The sample design in the rural sector has been decided with a view to providing good estimates for the tribal enquiry. Except in the north-eastern region, the tribal population is concentrated in some districts within the states having considerable tribal population and even in those districts they are found to be unevenly distributed geographically. Therefore special stratification and selection procedures have been adopted not only to net sufficient number of tribal households in the sample but also to improve the design in general for the tribal enquiry.

While the rural design is oriented towards the tribal enquiry, the urban design is oriented towards the enquiry on construction. As building construction activity is found to be concentrated in some areas in the urban sector, attempts have been made in urban design to demarcate such areas in larger towns as separate strata. Detailed description of the rural and urban sample designs are as follows:

SAMPLE DESIGN : RURAL

Sampling frame of villages: The list of 1981 census villages constitute the sampling frame for selection of villages in most districts. However in Assam (where '81 census was not done) and a few districts of some other states (where the available lists of villages were not satisfactory), 1971 census village lists have been used as frame.

Stratification :
In Haryana, Jammu & Kashmir, Punjab, Chandigarh, Delhi, Goa, Daman & Diu and Pondicherry where there are practically no tribal population, the strata used in NSS 43rd round were retained. In Meghalaya, Mizoram, Nagaland, Arunachal Pradesh, Sikkim, Dadra and Nagar Haveli and Lakshadweep also the strata of 43rd round were retained because of the high percentage of ST population in these States/U.T.'s. (The strata of 43rd round have been retained in the case of Sikkim as the distribution of tribal population is more or less uniform over all the districts). In the remaining states fresh stratification was carried out as described below.

In these states all districts accounting for the bulk of the state's tribal population were selected for formation of strata with concentration of tribal population. Besides these districts, tribal concentration strata have been demarcated also in some other districts with relatively small tribal population in order to ensure coverage of as many different ethnic groups as possible.

Within each district so identified for formation of tribal concentration strata, the tehsils with relatively high concentration of tribal population, together constituted one stratum. These tehsils were selected in such a way that together they accounted for the bulk (70% or more) of the district tribal population and the proportion of tribal to total population in this stratum was significantly greater than that of the district as a whole. The strata so formed were not always geographically contiguous. These tribal concentration strata are called STRATUM TYPE -1. Further, all the strata of Meghalaya, Mizoram, Nagaland, Arunachal Pradesh, Dadra & Nagar Haveli, Lakshadweep and Sikkim are also considered as stratum type-1. All the remaining strata in the rural sector (in any State/U.T.) are called stratum type -2.

Sampling deviation

There was no deviation from the original sampling design.

Mode of data collection

Face-to-face [f2f]

Research instrument

NSS Round 44 Schedule 29.2 consists of 17 blocks as enumerated below:

Block 1: identification of sample household Block 2: particulars of field operations Block 3: remarks by investigator Block 4: remarks by supervisory officer (s) Block 5: household characteristics Block 6: demographic particulars of household members Block 7: particulars of assistance received by the household during last 3 years Block 8: particulars of land owned and possessed Block 9: particulars of disposal of land during last 5 years Block 10: information on input items for cultivation during 1987-88 Block 11: particulars of crops produced during 1987-88 Block 12: particulars of wage employment in forest and forestry operation
Block 13: particulars of forest produce collected, consumed at home and sold by household members during last 30 days as self-employed Block 14: particulars of household enterprise (other than cultivation) during last 30 days Block 15: particulars of products (other than forest products) marketed during last 30 days Block 16 : inventory of assets owned on the date of survey Block 17 : cash dues and grain & other commodity dues payable by the household as on the date of survey and particulars of transaction of loans during last 365 days