The data set contains All -India Farm holdings details as per 2010-11 Agri Census. The information is categorised by Size of the holdings, social category, gender, Individual/point holding.

Abstract

The current India Agriculture Census with reference year 2010-11 is ninth in the series.

The Department of Agriculture and Cooperation, Ministry of Agriculture, Government of India conducts Agriculture Census, quinquennially, to collect data on operational holdings in the country. The reference period for Agriculture Census is the Agricultural year (July-June). Being the ultimate unit for taking agriculture-related decisions, operational holding has been taken as statistical unit at micro-level for data collection.

The Agriculture Census was conducted in three distinct Phases. The provisional results for first Phase of the current Census were released at State and all India level in October, 2012. After, scrutinizing the results at District/Tehsil level, this database has now been finalized and is being published in the form of an All India Report on number and area of operational holdings.

The main objectives of the Agriculture Census are: i) To describe structure and characteristics of agriculture by providing statistical data on operational holdings, including land utilization, irrigation, source of irrigation, irrigated and unirrigated area under different crops, live-stock, agricultural machinery and implements, use of fertilizers, seeds, agricultural credit etc. ii) To provide benchmark data needed for formulating new agricultural development programmes and for evaluating their progress. iii) To provide basic frame of operational holdings for carrying out future agricultural surveys and, iv) To lay a basis for developing an integrated programme for current agricultural statistics.

Geographic coverage

National

Analysis unit

Agricultural household, individual

Kind of data

Census/enumeration data [cen]

Sampling procedure

The Agriculture Census data is collected following two broad approaches; in States where comprehensive land records exist (Land Record States), for Phase-I of the Census, the data on primary characteristics of operational holdings are collected and compiled on complete enumeration basis through re-tabulation of information available in the Village Land Records. For other States (Non-Land record States), this data is collected on sample basis following household enquiry.

In land record States,data on Agriculture Census is pooled for all the parcels of an operational holding irrespective of its location. However, for operational convenience, the outer limit for pooling is restricted to taluka. This pooling is done for each operational holder in the village of his residence. In the non-land record States, the data is collected through sample survey in 20 per cent of villages in each block. These villages are selected through simple random sampling method and all the operational holdings in the selected villagesare enumerated following household enquiry approach.

In smaller UTs, like Lakshadweep, Daman & Diu etc., no sampling is done. i.e. all holdings in all the villages are surveyed for collection of data.

Mode of data collection

Face-to-face [f2f]

Abstract

The agricultural sector requires reliable and timely information on the activity carried out and changes that have occurred. Regular users of such information include national government agencies, governmental departments (for the formulation of policies and the preparation, monitoring and evaluation of developmental plans and projects), research and teaching institutions, associations of agricultural producers and own producers.

Thus, data provided by an agricultural census will be vital to know the agricultural reality and conditions of a country at a given time, and allow for comparison with previous censuses to examine changes. Undoubtedly, censuses describe a situation but do not explain them. In that sense, a census provides an adequate framework for conducting agricultural surveys which can provide needed explanations. Eleven years after the last agricultural census, it has become necessary to update information on the fundamental characteristics of the agricultural sector, which represents around 10% of the Gross Domestic Product of the country. This was the basis for conducting the 2011 Agricultural Census.

The 2011 Agricultural Census had the following objectives: 1. Provide basic data on the structure of the agricultural sector for the country as a whole, for each department and for small rural areas. 2. Update the sampling frames for the design of specialized agricultural surveys, both continuous and occasional. 3. Provide a base that helps to extend and improve the production of agricultural statistics, with a view to consolidating an Integrated Agricultural Statistical System.

Geographic coverage

National Coverage

Analysis unit

Agricultural holdings

Universe

All agricultural holdings with at least one hectare of land.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The list of farmers and lands from the Agricultural Census (AC), 2000, along with administrative registers, served as a frame for the 2011 census. Also, the population census, 2011 and the AC 2011 used the same cartographic materials. The AC 2011 was conducted using complete enumeration, thus no sampling was used.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

After the data were digitized using optical scanning, an internal consistency procedure of the census data were carried through a programmed application.

Abstract

The 2008 Agriculture Census was carried out during 11th May to 25th May, 2008 on a full count basis. The broad objective of the Agriculture Census, 2008 is to determine the structure and characteristics of agricultural holdings managed by dwelling households.

The specific objectives of the Agriculture Census, 2008 are as follows: a) To determine the number of agricultural holdings, area of holdings, average size of holding etc.; b) To determine the number and distribution of households engaged in agriculture; c) To determine the economic and employment size of the agriculture sector; d) To determine the number of wage labour by gender employed in agriculture sector. e) To determine the irrigated area under different crops; f) To determine the stock of livestock and poultry; g) To measures of the state and changes in attributes relating to the structure of agriculture such as the size and distribution of holding, tenureship, size and type of farming, extent of agriculture resources etc; h) To provide benchmark data for improving current estimates of crop acreage, production and livestock resources. i) To form a basis for the formulation, development and implementation of the programme and policies for agricultural development of the country.

Geographic coverage

National

Analysis unit

Agricultural holders /Farm households

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

A structural questionnaire was designed to collect information on agriculture. The questionnaire was pre-tested at the field level to test the relevance and appropriateness of the survey instruments. The questionnaire was then modified and finalized on the basis of the findings available from the pre-testing.

Statistics Canada conducts the Census of Agriculture every five years at the same time as the Census of Population. The most recent Census of Agriculture was on May 11, 2021. The Census of Agriculture collects and disseminates a wide range of data on the agriculture industry, including the number and type of farms, farm operator characteristics, business operating arrangements, land management practices, crop areas, the number of livestock and poultry, farm capital, total operating expenses and receipts, and farm machinery and equipment. Census data provide a comprehensive picture of the agriculture industry across Canada every five years at the national, provincial and territorial levels, as well as at lower levels of geography. The Census of Agriculture is the cornerstone of Canada's Agriculture Statistics Program. Census of Agriculture data are an indispensable public and private sector tool for analysing important changes in the agriculture and food industries; developing, implementing and evaluating agricultural policies and programs such as farm income safety nets and environmental sustainability; and making production, marketing and investment decisions. Statistics Canada uses the data as benchmarks for its regular surveys on crops, livestock and farm finances between census years. This release contains all farm and farm operator data. For current Census of Agriculture data refer to Statistics Canada.

The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updatesTitle: Rio Grande Watershed Ag Census 2018Item Type: CSVSummary:NM Agriculture Census download - Detailed commodity and value information for Rio Grande Watershed in 2018Notes: Highly encouraged to perform your own search on the Quickstats agricultural database: https://quickstats.nass.usda.gov/ which will allow you to query data for sectors (animal and products, crop, demographics, economics), group (further ag categories), commodity (detailed list of commodities), by the geographic location (American Indian Reservation, County, National, Region, state, watershed, zip codes), for various years at the annual or point in time levelPrepared by: Uploaded by EMcRae_NMCDCSource: Agricultural Census https://quickstats.nass.usda.gov/Feature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=44bf4fe6be4040c399788076a754a311#UID: 26Data Requested: Ag CensusMethod of Acquisition: Queried with Search parameters: CENSUS-STATE-NEW MEXICO-2019-ANNUAL-YEAR and downloadedDate Acquired: May 2022Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 8Tags: PENDING

Abstract

There is a long history to the agricultural census in the Netherlands. From 1934 onwards a census has been carried out (almost) every year. In recent years it is no longer purely a statistical project, but serves several purposes: on the one hand production of statistics by Statistics Netherlands and creating a frame for sampling, on the other hand providing data on individual holdings for administrative purposes by the Ministry of Economic Affairs, Agriculture and Innovation (the Ministry). Since the Ministry and Statistics Netherlands have a common interest in the census, it is held as a joint effort. In 1990, it was the last time special meeting days were organised to assess the data from the farmers. On these meeting days, farmers and enumerators jointly filled in the questionnaire manually. In the period 1991 – 1995, these sessions still took place, but the manual procedure was gradually replaced by filling in the information in a computer file. In 1996, the farmer could make a choice between coming to a special meeting place or filling in the survey form himself and returning it by postal mail. From 1997 on, a complete census was organised by postal mail every year. The year 2003 was a pilot year in which respondents had the opportunity to supply the census information through an internet application. In recent years the information is predominantly supplied via the internet. Since the statistical year 2002 the questionnaire of the agricultural census is combined with the application for animal, crop and arable land subsidies (in 2006 also for the single payment scheme). In 2007 data collection for the enforcement of the manure law is also combined in this questionnaire. This is done for efficiency reasons, both for farmers, and for administration and processing of data.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was the agricultural holding, defined as a single unit, both technically and economically, which has a single management and which undertakes agricultural activities listed in Annex Ito the European Parliament and Council Regulation (EC) No. 1166/2008 within the economic territory of the EU, either as its primary or secondary activity.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Frame Statistics Netherlands has a business register of all industrial and non-industrial commercial establishments, but the agricultural holdings are not yet fully covered in this register. The agricultural census therefore relies on the administrative farm register (AFR) of the Ministry held by NSIR, an executive service of the Ministry. By law farmers have to register with NSIR. The AFR contains names, addresses and a few other characteristics of holders or holdings and a unique registration number. With the census information of several years Statistics Netherlands has built up a statistical farm register (SFR). Relevant characteristics from the AFR (a.o. identification number, addresses, legal status) are also stored in the SFR. Changes in addresses are entered into the AFR throughout the year, changes in the SFR of course only once a year. The SFR provides a magnificent basis for stratification and efficient sampling of subsequent agricultural statistics. An annual census may seem expensive (even when only half of the cost is looked upon as expenses for statistics). But the excellent quality of the sample frame allows for relative small samples in related agricultural statistics and thus reduction of costs.

Mode of data collection

Computer Assisted Web Interview (CAWI)

Research instrument

One questionnaire was used, integrating both the 2010 AC and the SAPM, and presented to respondents as a single statistical inquiry. The questionnaire covered all 16 core items recommended in the WCA 2010.

Questionnaire:

1 Work and education 2 Number of animals and housing 3 Horticulture under glass 4 Mushrooms, bulb growing, chicory growing 5 Crops on open land and land use 6 Agricultural land area 7 Subsidies 8 Farm data 9 Livestock manure 10 Excavation notification (WION) 11 Signature

Cleaning operations

a. Data collection and data entry About 85% of the questionnaires was filled in and returned using the web application, which already contained a lotof c hecks and validations. Paper forms were digitized by a data-entry firm and processed by NSIR in the same way as the online questionnaires. There were several quality controls to ensure correct digitization.

b. Data processing, estimation and analysis Data processing, estimation and analysis were performed in two successive stages:

1. Pre-processing at NSIR After data collection and data entry the input data go through an extensive error control phase. In this phase checks are made on missing values, valid values, unlikely values, range checks, checks of correlation in the data, checks of totals and so on. When necessary additional information is collected from the farmers by phone. Data that is checked and accepted by NSIR is forwarded to Statistics Netherlands.

2. Processing at Statistics Netherlands Processing at Statistics Netherlands involves additional error control, enrichment with additional information, such as total SO and typology, imputation for non-response and analysis. Analyses are made at several levels of aggregation and comprise comparison with previous results and agricultural data from other sources.

Data appraisal

Checking the information in the questionnaires took place using a special control programme. Data were checked for hard and soft errors. Hard errors are non-valid values. Soft errors are unlikely values. If necessary, the checking personnel contacted the respondent to correct for errors. Approximately 85 percent of the questionnaires were completed online. The online questionnaire application contained extensive interactive controls and edits.

Dissemination: Dissemination is done via the Statline database, which is available on the Internet (www.cbs.nl ). In this database, Internet users may select their own indicators and information topics. Short publications on specific subjects are presented in the form of newspaper or Internet articles. Safe access to census microdata is also provided.

Abstract

Most people in Lao PDR live in rural areas and make their living from agriculture. The Government needs detailed and up-to-date statistics on agriculture to help develop the agricultural sector and improve the welfare of the people.

The Government already has statistics on the area and production of rice and other major crops, as well as livestock numbers. However, there is little information available on such things as: the different types of rice grown, the number of rice farmers, the area planted to minor crops, the use of different inputs, the use of farm machinery, farm size, farm labour, and the age/sex structure of livestock. The Lao Agricultural Census will provide these and many other data.

The Lao Agricultural Census is part of a world-wide programme of agricultural censuses, which started in the 1930’s. Over 120 countries are now participating in that programme; many of these undertake agricultural censuses every ten years. The Lao agricultural Census is the first such census undertaken in Lao PDR. It is being conducted in all 141 districts and is one of the largest and most important statistical collections ever undertaken in the country.

The census was developed based on the guidelines given in FAO Statistical Development Series No.5: Programme for the World Census of Agriculture 2000 (FAO 1996), taking into account the circumstances in Lao PDR. Extra emphasis was given to data on rice, because of its importance in Lao agriculture.

One of the keys to running an agricultural census is defining a suitable "farm" unit. In the Lao Agricultural Census, the farm unit used was the agricultural holding, defined as an economic unit of agricultural production under single management, comprising all livestock raised and all agricultural land operated, regardless of ownership. An agricultural holding is sometimes referred to as a "holding" or a "farm household".

Only household units were included in the census; that is, agricultural activities of businesses, government organisations, etc. were excluded. Usually, an agricultural holding is the same as a household, but sometimes it consists of two or more households operating as a partnership.

The Lao Agricultural Census covered only those units that either: - operated 0.02 ha or more of agricultural land in the 2010 wet season or the 2010/11 dry season; or - were raising 2 or more cattle or buffaloes, 5 or more pigs or goats, or 20 or more poultry at the time of the census.

An agricultural holding can be a land holding or a livestock holding. A land holding is one that operated 0.02 ha or more of agricultural land in 2010/11. A livestock holding is an agricultural holding that is not a land holding.

One of the interesting features of the agricultural sector as the market system develops is measuring the extent to which farmers participate in the market economy. In the census, information was collected for each agricultural holding on: - the main purpose of production on the holding in 2010/11; - whether, in 2010/11, any production by the holding was sold, whether any was exchanged for other produce, and whether any was used for home consumption.

Geographic coverage

National

Analysis unit

Agricultural holdings - Land holding - Livestock holding

Universe

The Lao Census of Agriculture 2010/11 covered the whole of Lao PDR, including urban areas in Vientiane and elsewhere. The census covered private households only. Agricultural activities of institutional units such as government farms, private companies and schools were excluded.

The Lao Agricultural Census covered only those units that either: - operated 0.02 ha or more of agricultural land in the 2010 wet season or the 2010/11 dry season; or - were raising 2 or more cattle or buffaloes, 5 or more pigs or goats, or 20 or more poultry at the time of the census.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The sample for the sample farm household component was selected using two-stage sampling: a sample of villages was first selected, and then a sample of farm households was selected in each sample village.

In most districts, a sample of between 16 and 22 villages was selected, with 16 farm households selected in each sample village; that is, a sample of between 256 and 352 sample farm households in each district. The more villages or farm households in a district, the bigger the sample that was taken. A smaller sample was taken in districts containing few villages or households and in urban areas.

In each district, the sample of villages was selected using stratified systematic probability proportional to size (PPS) sampling. A list of all villages in Lao PDR was prepared. Villages were divided into urban and rural strata, with rural strata being sampled more heavily than urban strata because of their agricultural importance. The estimated number of households in each village was used as the size measure for PPS sampling.

The sample of farm households in each sample village was selected using stratified systematic random sampling based on a list of all farm households in each village prepared following the household component of the census.

Altogether, 2,620 villages and 41,660 farm households formed the sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire has 4 forms: Form 1: Household listing Form 3: Village Form 4: Households (short) Form 5: Sample household (long)

Cleaning operations

Errors to be corrected during the data entry: "Fatal" error; that is, the data are wrong and should be corrected in the editing process (not during the data entry). "Query" error; that is, the data might be wrong and should be checked during the editing process (not during the data entry).

Sampling error estimates

Not computed

Abstract

The Government of Liberia and its Development Partners recognized agriculture as a pivotal sector in fostering economic growth, reducing poverty, and achieving food security. Since post-war, the Government in collaboration with development partners, has made substantial investments to develop and expand the agriculture sector. Over the years, policymakers and data users in the agriculture sector have experienced significant challenges in obtaining the requisite data needed to monitor and evaluate these interventions and make informed decisions on new interventions. To address these challenges, the Liberia Institute of Statistics and Geo-Information Services (LISGIS) and the Ministry of Agriculture (MoA) conducted several ad hoc agricultural surveys. While valuable, these surveys have often been limited in scope and unable to provide the comprehensive data needed for effective policymaking and planning. To support the sector more robustly, the government decided to undertake a comprehensive agricultural census. The Liberia Agriculture Census 2024, the second agricultural census in Liberia since 1971 and the first to be conducted digitally, aimed to collect structural and reliable data on various aspects of the agricultural sector.

The main objectives of the LAC-2024 was to: · Reduce the existing data gap in Liberia's agriculture sector. · Provide comprehensive data on the agriculture sector for policy formulation and evaluation of existing programs. · Enable LISGIS to establish an agriculture master sampling frame for the conduct of future agricultural surveys and research. · Identify the structural changes in the agriculture sector over time. · Provide information on crop, livestock, poultry, and aquaculture activities. · Determine the size, composition, practices and related characteristics of Liberia's agricultural holdings. · Generate disaggregated agriculture statistics. · Provide statistics for advocacy in Liberia's agriculture sector. · Identify agricultural practices and constraints at the community level.

To achieve these objectives, the LAC-2024 was designed to collect structural data at the household, non-household and community levels. The data collected at these three levels provide a wealth of information for understanding the state of agriculture in Liberia. This documentation provides a catalogue of information necessary for understanding how data was collected at the community level. The documentation also provides useful information for understanding the community anonymized dataset.

Geographic coverage

National Coverage

Analysis unit

Agricultural Communities:

Universe

The universe for the Liberia Agriculture Census 2024 community operations is: All communities (localities) in Liberia that are located within an agricultural enumeration area.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Focus group interviews were conducted in communities attached to the EAs selected for the sample census of farming households. A sampled community had the same probability of selection and sample weight of the EA to which it was attached. In case a community was linked to many EAs in the sampling frame of EAs, additional adjustment for multiplicity would be performed. The LAC-2024 community operations engaged 61,600 respondents across 7,193 sampled communities. Nationally, the distribution of respondents shows that males represented 66.1% of the total 61,600 participants, while females accounted for 33.9%. For more details on the sampling procedure, please see the Liberia Agriculture Census 2024 Community Report.

Mode of data collection

Focus Group [foc]

Research instrument

The LAC-2024 employed three questionnaires: the Household Questionnaire, the Community Questionnaire and the Non-Household Questionnaire. These three questionnaires were based on the 50x2030 Initiative standard model questionnaires. The Liberia Agriculture Census Technical Working Group (LAC-TWG), comprising technical staff from LISGIS,Ministry of Agriculture (MOA), National Fishery and Aquaculture Authority (NaFAA), Cooperative Development Agency (CDA) and the Ministry of Internal Affairs (MIA) worked with technicians from the 50x2030 Initiative to adapt the questionnaires to Liberia's context and realities. Suggestions and inputs were solicited from various stakeholders representing government ministries, commissions and agencies (MACs), nongovernmental and international organizations as well as accademic institutions involved with agriculture issues. All questionnaires were finalized in English. Some questions in the questionnaires were translated into simple Liberian English, for the purpose of easy administration. The community questionnaire include the following sections: 1-respondents characteristics; 2- production and processing activities in the community; 3- land characteristics and irrigation in the community; 4- markets to sell agriculture products; 5- access to agricultural inputs, services and credits in the community; 6- social cohesion; 7- difficulties in agricultural activities; 8- livestock and Poultry Production; 9- environment; 10- disasters and Shocks; 11- community infrastructure and transportation; 12- community organizations; 13- community resource management; 14- land prices and credit; 15- community key events; 16- labor and producer prices.

Cleaning operations

The data was edited using CSpro programs, version 7.7.3. The appropriate edit rules were established by programmers and subject matter specialists at LISGIS and MOA. In few cases, manual editing techniques were applied to recode responses generated from "Other specify" options. The SPSS software was used for this purpose.

Response rate

100%.

The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updatesTitle: Ag Census by NM Tribal Lands, 2017Item Type: CSVSummary: NM Agriculture Census download - Detailed commodity and value information for all Tribal Lands in the US Ag Census.Notes: Highly encouraged to perform your own search on the Quickstats agricultural database: https://quickstats.nass.usda.gov/ which will allow you to query data for sectors (animal and products, crop, demographics, economics), group (further ag categories), commodity (detailed list of commodities), by the geographic location (American Indian Reservation, County, National, Region, state, watershed, zip codes), for various years at the annual or point in time levelPrepared by: Uploaded by EMcRae_NMCDCSource: Agricultural Census https://quickstats.nass.usda.gov/Feature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=9d74679671bd48c0bb06ba73299b0194#UID: 26Data Requested: Ag CensusMethod of Acquisition: Queried on source websiteDate Acquired: May 2022Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 8Tags: PENDING

Abstract

Importance of Agriculture Census (AC)

Agriculture is the predominant activity in the Kingdom of Tonga's economy, contributing more than 17% to the Gross Domestic Product (GDP) in 2012 - 2013. The first ever Agriculture Census of the Kingdom was conducted in 1985. The second Census was conducted in 2001, focusing on land tenure, land utilization, area and production of principal crops, livestock, agricultural implements and equipment, use of fertilizers, etc. including the various agricultural activities in which most of the households were engaged in. Although agriculture is the main factor in the economy of the Kingdom of Tonga, the database in this sector seems to be inadequate. There were quite several surveys conducted for this sector, however, an updated frame (list of holdings/parcels and its characteristics) is needed so these surveys will obtain more reliable estimates. There were important developments in agriculture within the fourteen-year period from the last census that should be captured like the use of forest trees within the farming system to enhance productivity and information on fisheries, which is becoming a very important sector of the Kingdom's economy. Considering the above issues, there is a great need to update the statistics on agriculture in order to determine its present situation and to use it for economic planning and policy-making.

Objectives.

In support of the strategic plans and programmes of the Kingdom of Tonga on agriculture, the Government has decided to conduct the Agriculture Census (AC). This census is envisioned to: a) Provide benchmark or basic data on structure of agricultural holdings and their main characteristics; b) Use this information to develop a regular system of agricultural statistics; c) Build up some important village level statistics; d) Establish a technical and organizational foundation on which to build up a comprehensive and integrated system of food and agricultural statistics; and e) Provide a frame from which samples can be drawn to study certain aspects of agricultural activities in greater depth. f) Provide information on community (village) statistics.

Authority for Undertaking the AC 2015 The AC 2015 is conducted jointly by the Ministry of Agriculture and Food, Forests and Fisheries and the Statistic Department. Authority for the census rest with the Government Statistician who has the legal power to collect such information under the Statistics Act 1978.

Geographic coverage

It was a National coverage, as the Agriculture Census covers the whole of the Kingdom of Tonga which includes the five districts of enumeration:

1. Tongatapu
2. Vavau
3. Ha'apai
4. Eua
5. Niua

Analysis unit

• Individuals in a private household dwelling.
• Households
• Communities like cooperatives, religious groups, companies, semi-government and joint operations

Universe

The Census covers all individuals and households.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed in collaboration between FAO, Ministry of Agriculture and the TNSO. It was designed in such a way that data items were efficiently encoded and processed using the software package CSPro.

The questionnaire was developed in English, but enumerators were specifically trained to be able to clearly translate these questions to other languages and dialect used in the country.

The questionnaires were designed in 13 sub-sections which are:

A. Identification particulars B. Household demographic and economic information C. Household engagement in agricultural subsectors D. Usage of land E. Food crops F. Agricultural practices G. Livestock H. Fisheries I. Forestry J. Handicrafts K. Labour L. Machinery and equipment M. Agricultural income and loan for all subsectors

Information collected for each sub-sections:

Section A: This section basically include the IDs for the households and include: - Village number - Census block - Household number - Sample - Type of holding

Section B: - name - relationship - sex - age - economic activity - educational attainment

Section D: - Bush allotment - Town allotment

Section E: - Exisiting crops - Crops harvested

Section F: - Fertilizer - Pesticides - Irrigation - Community farming

Section G: - Beef cattle - Dairy cattle - Pig - Horse - Sheep - Goat - Chicken - Duck - Dog / Cat - Veterinary services

Section H: - Fishing type - Fish income / sales - Purpose of fishing

Section I: - Number of trees - uses of trees

Section J: - Handicraft materials - Handicrafts sold - Value of handicrafts

Section K / L - Number of laborers - Days worked - Hours worked - Machinery used

Section M: - Income from agriculture - Loans - Drawbacks

Cleaning operations

VERIFICATION AND CODING

The data editing process begins when the completed questionnaires were returned to the national statistics office (NSO) for checking by the coders. This include checking that all fields are correctly filled, skipped pattern are properly followed, missing fields and so forth. Once the questionnaires are verified to be correct, then coding begins where certain variables are coded to their respective codes for capturing in the data entry screen - codes include Village code, Crops and Tress codes.

IN-BUILT EDITING

The data entry application for the 2015 Agriculture Census was designed using the software package CSPro where all necessary checks were incorporated to allow the Data Entry Operators (DEO) to verify data while doing data entry. With all the in-built checks, this ensures capturing good quality data efficiently and effectively. The in-built checks include range checks, skip and filtering questions and consistent and logic checks. Withe these in-built checks ensures good quality data is captured while entering and this greatly helps in the final batch editing.

SECONDARY EDITING

After the completion of the data entry, the final editing process was done. This include verification of questionnaires that all are captured and the actual running of the batch editing program on the whole data. Since most of the checks were done during the data entry phase, the batch editing process mostly involves verifying those errors that were missed or could not be solved during data entry, checking on those responses which have been coded 'missing' and trying to impute or verify by referring to the respective questionnaire and fixing 'outliers' responses. Frequencies on each variable were also checked to verify any inconsistencies between variables. The batch editing logic program was ren twice when it was decided to finalize the data. Some missing values were not fixed as they were not able to be verified, examples of these are mostly on money values and number of crops/trees.

Response rate

The final national response rate was 89% with 16,122 households enumerated out of the 18,043 total households.

Data appraisal

A Pilot Census was conducted which the questionnaires received were used to test the data entry application. This allowed to redefine the questionnaires as well as the data entry application to ensure that it everything was efficiently designed to capture reliable data.

Like any other census, the 2015 Agriculture Census (AGC) has its own limitations. These are summarized as follows:

• The 2015 AGC only covered 89% of the total households in Tonga; 11% of the households were not enumerated.
• The 2015 AGC took place at the aftermath of Cyclone Ian which had destroyed a large part of the agriculture sector and the infrastructure for the Ha'apai Region.
• The 2015 AGC Questionnaire design meant that some of the data was not comparable to 2001. For example, the levels of agriculture activities (subsistence, semi-subsistence and commercial) and the way they were described.
• The 2015 AGC took place between April and June 2015 whereas the 2001 AGC took place between October and December 2001, therefore there is variation in the data due to seasonality of some of the agriculture activities, such as cropping and fishing.
• In the 2001 AGC the size of agricultural holding, to be considered as an agricultural holder was more than 1/8 of an acre. The 2015 AGC included town allotments below 1/8 of an acre. This was done so that agriculture activities in the town allotment could be accounted for.
• Questions on the use of fertilizers were answerable only by "Yes" or "No" and questions on agricultural chemicals asked only for the name of the chemical and the crops they were used on. Quantities of these agricultural inputs were not gathered.
• In the 2015 AGC, the question on the level of agriculture activities was only asked for the fisheries sub-sector and not for the other sub-sectors. Therefore, these were determined by the size of the land cultivated, the numbers of livestock kept, the number of forest trees grown, and the amount of handicrafts made and sold.
• The time allowed for data processing, editing and verification was rather limited and did not allow sufficient time for thorough and in-depth checking of the data.

A report presenting results of the Lao Census of Agriculture 2010/11. The census involved 1) surveying all villages in the country to collect data on rural infrastructure and services; 2) surveying all households for basic data on crops and livestock; and 3) a sample survey of 41,660 farm households to collect data on agricultural production activities. The report highlights major findings, featuring commentary and graphical presentations, as well as some summary tables. Results are shown for each province.

Agriculture Census: Average Size of Operational Land Holdings: Maharashtra: Size Group: 1 to 2 Hectares data was reported at 1.330 ha in 2016. This records a decrease from the previous number of 1.420 ha for 2011. Agriculture Census: Average Size of Operational Land Holdings: Maharashtra: Size Group: 1 to 2 Hectares data is updated yearly, averaging 1.375 ha from Jun 2001 (Median) to 2016, with 4 observations. The data reached an all-time high of 1.420 ha in 2011 and a record low of 1.260 ha in 2006. Agriculture Census: Average Size of Operational Land Holdings: Maharashtra: Size Group: 1 to 2 Hectares data remains active status in CEIC and is reported by Directorate of Economics and Statistics, Department of Agriculture and Farmers Welfare. The data is categorized under India Premium Database’s Agriculture Sector – Table IN.RIK003: Agriculture Census: Average Size of Operational Land Holdings: by Size Group.

Abstract

The Ministry of Agriculture and Forestry (MAF) was entrusted with the responsibility to lead the implementation of the agricultural census project with the assistance of the Statistics Department (SD). The Census was conducted under the National Statistics Act 1978 which provides for obligation of the citizens to provide information, confidentiality of information provided and the duties of the census staff. A National Agriculture Census Committee was constituted to guide and supervise the entire census exercise. Technical and financial assistance for undertaking the census was provided by the FAO of the UN.

The undertaking of the AC 2001 was envisioned to: 1. provide benchmark or basic data on the structure of agricultural holdings and their main characteristics; 2. use this information to develop a regular system of agricultural statistics; 3. build up some important village and regional level statistics; 4. establish a technical and organizational foundation on which to build up a comprehensive and integrated system of food and agricultural statistics; and 5. provide a frame from which samples can be drawn to study certain aspects of agricultural activities in greater depth.

Geographic coverage

National

Analysis unit

• Household
• Agricultural Holding

Universe

The Agricultural Census 2001 was conducted at the household level and a complete enumeration of all households residing in Tonga during the period of the census enumeration. However, households that left for abroad and came back after the period of the census taking and those that were permanently living in other countries were no longer included.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

Considerable time was spent in designing the census questionnaires. The census questionnaires were in three forms, namely, AC Form 1 – Household Questionnaire, AC Form 2 – Holding Questionnaire and AC Form 3 – Parcel Questionnaire.

The draft questionnaires were presented first to the Working Committee then to the User–Producer Consultation Meeting which was held on September 24, 2001. Afterwards these were tested in the field from August 27-31, 2001. From the results of the field test, the census questionnaires were finalized for printing.

Data appraisal

Data Limitation The AC 2001, as stated in one of its objectives, provides basic information on the structure of agricultural holdings in the Kingdom and its characteristics that do not change over a certain period of time. Like any other census and surveys, it has limitations which are enumerated in the following: 1. No data on crop production was included in this census since this information would be better asked in a follow up survey specifically designed for major crops. 2. The level of agricultural activity of a household was determined only through its involvement in the cultivation/growing of crops and size of its agricultural land which should be more than 1/8 of an acre. A household having only livestock or poultry was not considered to have an agricultural holding for this census. 3. The size of the agricultural holding, to be considered as an agricultural holder, was more than 1/8 of an acre. 4. The economic characteristics of the household members were asked for member 15 years old and over as recommended and being done internationally and in other local surveys. 5. Apart from Livestock animals, only information on dogs was included in the Livestock Section of this census. Other domesticated animals such as cats and birds like parrots were excluded. 6. Fisheries Section was asked for only few data items such as main purpose of fishing, type of fishing method engaged in, use of fishing boats and proportion of fish/other sea products sold. 7. The holding and parcels included only those agricultural lands cultivated by the holder whether owned or leased from other households. On the other hand, all lands owned by the holder but rented out to other households whether for a fee or for free were excluded in the Holding Questionnaire and Parcel Questionnaire. 8. Sections on Agricultural Income and Loan, Agro-Forestry on the Holding and Handicraft Making were asked only for agriculturally active households. The nonagricultural and minor agricultural households did not have such information. 9. Questions on the use of fertilizers were answerable only by “Yes” or “No” and questions on agricultural chemicals were the name of chemical and crops it was used on. Quantities on these agricultural inputs were not taken for it is best to include these items in a follow-up survey. 10. Small implements such as knife, spade and other gardening tools were not included in this census since it is assumed that almost all agriculturally active households owned and used such small tools. 11. The section on Agro-forestry was limited to the name of the trees/shrubs and its uses, not on the number of trees for this would create problems on data processing. Hence, a follow-up survey using this information as a frame can be done to get additional information on agro-forestry. 12. The section on Crops Planted and Already Harvested of the Parcel Questionnaire was supposed to be answered by all agricultural holders who answered the section on Parcel Details of the Holding Questionnaire. However, due to memory recall of the respondents, information on this section might have been under reported. 13. The quality of the data collected can be affected by many factors. For example, the complete enumeration and coverage limits the completeness of data, the concepts and interpretation of questionnaires may not be fully understood by enumerators, inadequate supervision and others.

The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updatesTitle: Ag Census by NM Zip Codes, 2017Item Type: CSVSummary: NM Agriculture Census download- by zip codes for 2017Notes: Highly encouraged to perform your own search on the Quickstats agricultural database: https://quickstats.nass.usda.gov/ which will allow you to query data for sectors (animal and products, crop, demographics, economics), group (further ag categories), commodity (detailed list of commodities), by the geographic location (American Indian Reservation, County, National, Region, state, watershed, zip codes), for various years at the annual or point in time levelPrepared by: Uploaded by EMcRae_NMCDCSource: Agricultural Census https://quickstats.nass.usda.gov/Feature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=c227b162226a4766b47cfb005c08d368#UID: 26Data Requested: Ag CensusMethod of Acquisition: Queried with Search parameters: CENSUS-STATE-NEW MEXICO-2019-ANNUAL-YEAR and downloadedDate Acquired: May 2022Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 8Tags: PENDING

Abstract

Since the 1990s the Government of the Gambia has been committed to sustainable human development and improved living standards of the people of the country, During this period, the Government has established a number of strategies and approaches to achieve these overarching objectives, including: a Vision 2020, Millennium Development Goals, Poverty Reduction Strategies, and very recently a Programme for Accelerated Growth and Employment. Each of these strategies recognized the major roles and contributions of the Agriculture and Natural Resources (ANR) Sector in achieving their respective objectives. Although the sector made impressive growth performances during the past two decades, there were indications more could be achieved from it, especially because of the increasing demands being placed on it to meet changing circumstances in the global economy, from climate change occurrences the national macro-economic environment.

The long-term objectives of The Gambia Census of Agriculture 20011/12 were: a. Improvement of the capacity and capability in the to implement an agriculture census and thereby provide agricultural statistical data within the overall integrated agricultural statistical system; b. Provision of national agricultural statistical indicators for assessing and monitoring of the implementation of agricultural development programmes and interventions; c. Monitoring progress towards the Millennium Development Goals (MDGs); d. Poverty alleviation

The more specific objectives were: a. Establishment of a viable sampling frames for agricultural surveys and censuses; b. Development and implementation of a national programme for an agricultural census and an annual crop and livestock surveys to collect Food and Agricultural statistics; c. Improvement of skills and knowledge of field staff in agricultural statistical data collection and compilation techniques and thereby develop the capability for undertaking agricultural censuses and surveys as well as compile relevant indicators; d. Collection and accumulation of annual agricultural statistics; e. Establishment of an agricultural data bank; f. To provide data on the structure of agriculture, especially for small administrative units, and to enable detailed cross tabulations and g. To provide data to use as benchmarks for current agricultural statistics

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was the agricultural holding, defined as a technical or operational unit of agricultural production comprising all land used wholly or partly for agricultural production purposes, under single management exercised by one person alone or with others, without regard to title, legal form, size or location.

Kind of data

Census/enumeration data [cen]

Sampling procedure

i. Methodological modality for conducting the census The AC was a sample-based census. A community survey was conducted jointly with the AC.

ii. Frame The EAs defined by the GBoS for the 2003 Population Census (PCs) were used for the AC as PSUs. Complete and/or sample enumeration methods The 2011/2012 AC was conducted using sample enumeration.

iii. Sample design Two-stage sample design was applied, the PSUs being the EAs. The sample of EAs was selected from each district with PPS (the number of households was used as a measure of size). The SSUs were the agricultural holdings. The SSUs within the EAs were selected using systematic random sampling (SRS). During the first stage, 400 EAs were selected, while 2 000 agricultural holdings were selected during the second stage. The AC covered approximately 15 percent of the EAs and 4 percent of all households enumerated in the 2003 PC.

iv. Sampling Size Background information from the 2011 Agricultural Census programme had indicated the sampling error obtained for the early millet crop acreage was determined to be 12%. For a country like The Gambia, experience has shown that if the number of households in the sample is increased to about 2000 households or 4% of the total households in the country, this would result in an acceptable sampling error of 2%. Consequently, out of the total number of 2434 rural EAs in the country, four hundred (400 or 15%) were sampled. Such a sample was considered to be adequate for providing regional estimates with a reasonable degree of precision. Additionally, it was known from experience of the last agricultural census conducted in 2003 and the subsequent annual sample surveys that by providing adequate logistics (transportation facilities and incentive allowances), an enumerator workload that could be handled was about six EAs.

Mode of data collection

Face-to-face [f2f]

Research instrument

Detailed census data were collected using seven questionnaire forms:

· Form 1 - Listing questionnaire, used to list all households in a sampled EA, to identify those engaged in agricultural activities (that is, the agricultural holdings) · Form 2 - Holding questionnaire, used to collect data on the demographic characteristics of household members, as well as some data on the agricultural holding · Form 3 - Field questionnaire · Form 4 - Yield plot questionnaire, used for recording harvest from yield plots · Form 5 - Village questionnaire, designed to collect community- level data · Form 6 - Groundnut questionnaire · Form 7 - Mango questionnaire

The questionnaires covered 11 of the 16 core items recommended by the WCA 2010. All questionnaires are attached to the external materials section.

Cleaning operations

1. DATA PROCESSING AND ARCHIVING The main programs for data entry, batch edit/validation and tabulations were developed using CSPro. Error controls were built into every stage of the data processing cycle. Two IBM 120-GB external mass storage devices were used for weekly backups of the census data. STATA was used to calculate standard errors and coefficients of variation for the census estimates. CSPro was used to produce most of the tables according to the tabulation plan designed by the Census Technical Committee. In some cases, Microsoft Excel was used to generate data charts.

2. CENSUS DATA QUALITY CSPro data verification techniques were used to control the quality of the census data. In this process, data were keyed again and compared with the value currently in the data file. The system would flag errors in case of discrepancies between the item in the file and the keyed item.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit of the CA is the agricultural holding - an agricultural production unit, which includes all agricultural activities run under a single management. This unit is managed by the members of one or more households (natural persons) or by a company or a public institution (legal entity).

Kind of data

Census/enumeration data [cen]

Sampling procedure

(a) The Modular approach - In the Census of Agriculture in 2014 , the enumerators referred to all the households in rural and urban areas and completed the frame list for all of the holders and then filled in a holding questionnaire for each holding.

(b) Frame - The frame used for rural areas in the Census of Agriculture in 2014 was the list of villages based on the latest geographical divisions and the frame used for the urban areas was the comprehensive list of urban blocks map.

(c) Complete or Sample Enumeration Methods - Complete enumeration method was used. - List of agriculture holdings in metropolises and large villages was used for direct interviewing methods.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four types of listing forms (specific for different types of units) were used to identify the holdings. Two census questionnaires were used to collect census data:

(i) the holding questionnaire (ii) the village questionnaire

The CA 2014 covered 11 of the 16 core items recommended by FAO for the WCA 2010. The following core items were not covered by the CA 2014: (i) "Household size" (ii) "Main purpose of production of the holding" (iii) "Land tenure types on the holding"; (iv) "Presence of forest and other wood land on the holding"; (V) "Other economic production activities of the holding's enterprise".

See questionnaire in external materials.

Cleaning operations

(a) Data processing and archiving - Data entry and editing in Tablets (done by the enumerators) - Data editing in web-based system (done by the experts) - The SCI conducted a general assessment of the data and and also conducted some imputations on them.

(b) Census data quality - The SCI monitored all phases of the Census such as implementation and data processing - Experts of the SCI and experts in the provinces checked the gathered data after the Census ended. - The SCI also conducted post enumeration

Abstract

The 2004 Georgia Agriculture Census is the first National Agricultural Census conducted in Georgia.

The necessity of conducting the agricultural census was due, on the one hand, to fundamental changes in the structure of land tenure, land use, agricultural producers and production that took place in Georgia since independence, and on the other hand to the fact that Georgia has joined the FAO Programme of Word Census of Agriculture 1996-2005. The census has been conducted by Department of Statistics under Ministry of Economic Development of Georgia with close cooperation with Ministry of Agriculture. Due to financial restrictions the census was conducted in two stages: from 25 September to 4 October 2004 in the rural area and from14 to 23 April 2005 in district centers and small towns. 5 large cities of Georgia (Tbilisi, Kutaisi, Batumi, Rustavi and Poti) were not covered by the census, as well as the uncontrolled territory of Abkhazia (except Kodori gorge) and Tskhinvali Region (Former South Ossetia).

Geographic coverage

The census did not cover 5 big cities of Georgia (Tbilisi, Kutaisi, Batumi, Rustavi, Poti) not constituting part of any district. Uncontrolled territories of Georgia were not covered as well: Abkhazia completely (except Kodori gorge), present-day Java district completely, those parts of the present-day Gori, Kareli,, Sachkhere, Oni districts which earlier were parts of the former South Ossetian Autonomous Area, as well as a small part of Akhalgori district (see the map of the present-day administrative and territorial division of Georgia).

Analysis unit

• Agricultural Holding and Holders

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire has the following sections: 1. Holding location 2. Holder type 3. Ownership form of the holding 4. Information about the holder 5. Household composition 6. Total area of the holding in parcels 7. Total area of the holding and its structure 8. Numbers of fruit and citrus trees 9. Numbers of vines by species 10. Livestock 11. Agricultural machinery used in the holding 12. Agricultural production used 13. Food security of the household

Share of total agricultural land under dry season sugar cane(Refers to the dry season 2010/11)Data Source: Lao Agriculture Census 2011Contact: Ministry of Agriculture and Forestry (MAF) URL: www.maf.gov.la Tel: 021-412345 Fax: 021-412344 E-mail: maf.infro@gmail.com P.O.BOX: 811ແບ່ງປັນເນື້ອທີ່ດິນກະສິກຳ ທັງໝົດ ພາຍໃຕ້ອ້ອຍໃນລະດູແລ້ງ (ອີງຕາມລະດູແລ້ງ 2010/11)ການສຳຫລວດກະສີກຳ 2011ກະຊວງກະສີກຳ ແລະ ປ່າໄມ້ URL: www.maf.gov.la Tel: 021-412345 Fax: 021-412344 E-mail: maf.infro@gmail.com P.O.BOX: 811

Abstract

The Fiji National Agricultural Census 2009 is the fourth agricultural census. After a lapse of 18 years, National Agricultural Census 2009 was carried out in Fiji beginning in October 2009; data collection was interrupted by two cyclones and not completed until March of 2010.

The Agriculture Census is a national obligation conducted by the country to provide benchmark data for planning and policy decisions in sustainable agricultural and rural development; and to strengthen and improve the ongoing Fiji Agriculture Statistics System (FASS) to generate key agricultural data on a regular basis using the results of the 2009 NAC as the benchmark and the dissemination of this statistical information in the form of regular reports.

The 2009 National Agriculture Census (NAC) is the first census programme to be conducted in the country using Multiple Sample Frame (MSF) as the main methodology. Given the experiences of the previous census programmes in terms of funding and availability of resources, the 2009 agriculture census programme provides a platform for more diversification and improvement programmes within the agriculture sector thus ensuring compatible foreign exchange earnings as well as uplifting the living standards of rural populace.

Geographic coverage

National

Analysis unit

• Agricultural Holding and Holders

Kind of data

Census/enumeration data [cen]

Sampling procedure

The survey design used the multiple sampling frame methodology. This methodology combines the advantages of an area frame (complete coverage) and a list frame (rare commodities and large and special farms). In the 2009 NAC, it was expected to provide reliable results at district level for most tables, although results for smaller districts might not be possible. In addition, a small island strategy (SIS) was used where complete enumeration of villages occurred within some districts.

The underlying basis for an area frame sample is to select small areas (in this case, one square kilometer - 100 hectares) that represent the entire area of interest. To improve the efficiency of the sample, the entire country was stratified (or characterized) by the intensity of agriculture. The stratification split the country into areas of high intensity agriculture, medium intensity agriculture, low intensity agriculture, forest areas, peri-urban areas and urban areas/non agricultural areas. The overall sample size was limited by the resources available; it was determined to use a ten percent sample of "agricultural land" as determined during the stratification process.

Initially the Fiji Bureau of Statistics (FIBOS) enumeration areas (EAs) for the 2007 Population and Housing Census were used for stratum identification. Subsequently it was determined that re- stratification of whole EAs and subdivision of other EAs would be more efficient. In many of the FIBOS EAs, farms were present only in small pockets; the uniformity of agriculture in the EA, one of the strengths of the stratification, did not exist. These EAs were, first, reviewed for the presence of natural pine forest and natural reserves. After these areas were removed, the remainder of the EA was divided into one square kilometer grids before the sampling process occurred. After the grids were selected, the Land Use Section of the DOA prepared maps using detectable boundaries "around the grid". It was not possible for segments to retain the gridlines as boundaries because they seldom were along recognizable boundaries; however, it was possible to approximate 100 hectares in that general area.

A farm can consist of land areas that are separated by physical boundaries or by land use patterns; these are called tracts. The method of data collection was to account for each tract inside the segment, but, also to collect information about areas outside the segment for farms with tracts both inside and outside. If a segment boundary splits an existing tract, it is divided into one tract inside the segment and one tract outside the segment. The percentage of the farmland inside the segment is used as a weighting factor for the farm in the expansions.

One of the limitations of area frame samples is the accurate expansion of rare or concentrated (non- uniform) variables - such as poultry houses or large dairy or beef farms. The list frame sample, developed from the knowledge and experience of DOA Animal Health and Production Division and Extension Division staff, was expanded as data collection occurred and there was better awareness of large and specialized farms. Data were collected from all of these farms. It should be noted that shortly before the beginning of data collection, a severe outbreak of brucellosis occurred and some culling took place.

Three levels of data presentation were identified for tabulation of the data of the National Agriculture Census 2009 (NAC 2009). The first is tables and expansions at district level; the second is tables and expansions at provincial and national level; the third is tables and (estimates) for special variables.

The census data were collected at farm level, at tract level, at crop level and at animal/poultry level. Information about households and their demographics were also collected. One priority area has been the role of gender in agriculture in Fiji. A special section of the census questionnaire was targeted at identifying these roles and highlighting any special differences. These data also have been broken out by age group.

Accurate land stratification for the 2009 NAC was essential; it was necessary to estimate the percentage of agriculture land use. Initially the stratification was made for each of the Fiji Islands Bureau of Statistics (FIBOS) enumeration areas (EAs).

The census estimates were requested at national, divisional, provincial and also tikina levels. The 15 provinces including Rotuma Island were the main focus of the tabulation. Consequently, the entire country was divided into strata according to the intensity of land use for agriculture. They were further subdivided into sub-strata according to specific land use. This sub-stratification technique guaranteed the sample allocation for priority and special crops. Another stratum was created for special farms including large commercial and freehold farms.

A total of 1,602 existing EAs from the 2007 population census were overlaid on the ASF topographic maps scale 1:50,000 in preparation for stratification activities according to land use. Each EA was classified into one of the strata keeping the same geographical identification codes as those used in the population census. The percentage of area under crops, pastures, forest, etc. (land use) of each EA was estimated by field observation to check that each EA was classified in the right stratum and sub-stratum.

The sampling procedures are more fully described in "National Agricultural Census 2009 - Final Report" pp.7-13.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two questionnaires, NAC 1 and NAC 3, were used to record information about the segments from the sample. The NAC 1 itemized all tracts inside the segment and all associated farm tracts outside the segments. The NAC 3 documented the nonfarm tracts inside the segment. Enumerators were required to fill out these questionnaires; during the interview process the main questionnaire (NAC 2) was used. Neither the NAC 1 nor NAC 3 was necessary for List Frame farms.

The questionnaire was designed and tested by the staff of the Agricultural Statistics Unit and training manuals were prepared for supervisors and enumerators. A Pilot Census was carried out in several locations to evaluate the content and layout of the questionnaires and the completeness of the census documents. The questionnaire and training materials were updated as the result of the Pilot Census.

Cleaning operations

After a prioritized order of data collection from the provinces, the questionnaires were received at the Agricultural Statistics Unit in batches. Unique questionnaire numbers were assigned by the data processing administrator and recorded in a management system designed to prevent duplicate numbers and to coordinate the collection and processing of the three types of questionnaires. The questionnaire numbers consisted of province, district and a sequence number starting with an initial value assigned previously to each of the segments.

The editing and coding process for a total of 9,341 NAC 2 questionnaires containing farm data started in mid November 2009. Four persons managed the archives of census materials (questionnaires, cartography and photo-enlargements, etc.). Eleven coders were contracted and trained using the Field Team Manual and the Coding, Editing and Data Processing Manual. One table head checked the manual editing and coding. Data entry activities were conducted by ten data entry operators beginning in early December.

Consistency checks were also carried out in the ACCESS databases. Queries were designed to identify data entry and coding errors. Data were entered into 15 provincial databases (including Rotuma Island) which were combined into four divisional databases. The LSF database was kept separate, but combined in SPSS for tabulation and analysis.