The global real estate surveying and mapping market is valued at USD XXX million in 2023 and is projected to reach USD XXX million by 2033, exhibiting a CAGR of XX% during the forecast period. The market's growth is attributed to the rising demand for accurate land surveys and maps for real estate development, urban planning, and infrastructure projects. Furthermore, advancements in technology, such as the adoption of drone surveys, laser scanning, and GIS software, are driving market expansion by enhancing surveying and mapping efficiency and accuracy. The real estate surveying and mapping market is segmented by type into land surveying and mapping, house surveying and mapping, and others. Land surveying and mapping account for the largest market share due to the high demand for land surveys for property boundary demarcation, land use planning, and construction projects. The house surveying and mapping segment is also witnessing significant growth due to the increased need for pre-purchase surveys, structural inspections, and property renovations. Key industry players include Morris-Depew Associates, RM Towill Corporation, Trimble, PASCO Corporation, Fugro, AECOM, Stantec, AEI Consultants, Tuofeng Surveying and Mapping, Mucheng Surveying, Nanyang Spatial Mapping, Zhongjiao Road & Bridge, Okay Information Technology, Zhongke Testing Technology, Centre Testing International Group, and TIRAIN Science & Technology.

Uncover historical ownership history and changes over time by performing a reverse Whois lookup for the company J-HOUSE-CONSULTING.

This location is part of the Arizona Mineral Industry Location System (AzMILS), an inventory of mineral occurences, prospects and mine locations in Arizona. Gila380 is located in T7N R15E Sec 15 N2 in the Mcfadden Peak - 15 Min quad. This collection consists of various reports, maps, records and related materials acquired by the Arizona Department of Mines and Mineral Resources regarding mining properties in Arizona. Information was obtained by various means, including the property owners, exploration companies, consultants, verbal interviews, field visits, newspapers and publications. Some sections may be redacted for copyright. Please see the access statement.

Web map used in the Boulder County Greenhouse Gas Inventory project. This is a copy of the web map created by Lotus consultants - https://bouldercounty.maps.arcgis.com/home/item.html?id=43dce4ffec1c43f2af3b02403b173cc2#overview

This location is part of the Arizona Mineral Industry Location System (AzMILS), an inventory of mineral occurences, prospects and mine locations in Arizona. Coconino124 is located in T25N R5E Sec 7 S2 in the Ebert Mtn - 15 Min quad. This collection consists of various reports, maps, records and related materials acquired by the Arizona Department of Mines and Mineral Resources regarding mining properties in Arizona. Information was obtained by various means, including the property owners, exploration companies, consultants, verbal interviews, field visits, newspapers and publications. Some sections may be redacted for copyright. Please see the access statement.

The map of the sectorisation of the public colleges of Hauts-de-Seine allows you to quickly know the sector college associated with a section of road.

In the Versailles Academy, the Yvelines Department and the Val d’Oise Department benefit from a comprehensive mapping solution for managing and consulting the school sectorisation of colleges. This solution, aimed at families and partners, makes it possible to disseminate very widely reliable and accessible information on the sectorisation of colleges, competence of the Departments.

For the Directorate of Education, Citizenship and Colleges (DECC), the challenge of this project was to propose a similar scheme on Hauts-de-Seine within the framework of the Unified Directorate and thus replace the current solution with a complete mapping application. A finer geographical data based on the wireline of roads/streets, a real management mesh of school sectorisation, has been created to visualise and manipulate the data as closely as possible.

The Department’s school sectorisation solution is based on two separate modules:

• A school sector management module for in-house DECC;
• A module to consult the school map of colleges for the general public.

On the basis of the official sectorisation data provided by the DECC (stopped) and the wireline of streets from the IGN topographic database (BD Topo), the SIG and Open data teams, have made the sections of streets reliable in order to assign to each of them its connecting college. They then set up a management web mapping application based on the Department’s GIS solutions. Through it, the DECC can reliable the data and refine the school map according to the evolution of the territory: new college, new neighborhood, evolution of the student population, etc.

The interactive map for the general public exploits all the data thus reliable and refined. This school map of the public colleges of Hauts-de-Seine allows families to quickly and simply know the college of attachment of their children.

Special observations

The map is provided as an indication and only the deliberation voted by the Conseil Départemental des Hauts-de-Seine is enforceable. The information presented relates to the school year 2022-2023. The school map is updated each year according to the evolution of the sectorisations of the colleges.

Related links

Link to the general public web application of the school map School map of public colleges

Related data

Link to College Dataset Public and Private Colleges

Abstract

The survey of the Pemba was an attempt to reach all households in Kenya with links to Pemba in Tanzania. It was conducted in the two counties of Kilifi and Kwale on the coast, north and south of Mombasa, respectively. According to information from village elders familiar with the Pemba community in Kenya, most of the Pemba population resides in these two counties. While there are some Pemba residents in Lamu, the security situation prevented data collection there. Further, a few Pemba are believed to live in the city of Mombasa and elsewhere in the country. But due to lack of further information, no data were collected in Mombasa or elsewhere. The objectives of the full survey, conducted in August 2016, were: 1. To establish the number and characteristics of the Pemba living in Kenya, including their arrival period in Kenya, nationality and their problems; 2. To make recommendations for the issuance of the documentation that is required for those who apply for citizenshiop by registration

Geographic coverage

Kwale and Kilifi counties, Kenya.

Analysis unit

Households, individuals

Universe

The total number of households with links to Pemba in Tanzania, in Kilifi and Kwale counties.

Kind of data

Census/enumeration data [cen]

Sampling procedure

A household mapping exercise was conducted in Kilifi and Kwale to identify Pemba households and to make it easier to locate them on the ground. The mapping was done from 4 to 12 August 2016 by a team from UNHCR Kenya office and KNBS. The mapping in each village commenced with a visit to the chief's office, who put the team in touch with the village chair. The team explained the purpose of its visit to the village chair and began the mapping exercise. The importance of involving the chiefs and village chairpersons is that they are well connected, recognised and trusted by residents in their communities. The same procedure is followed by KNBS when they are mapping for sample surveys and censuses. The team established physical boundaries of the area to be mapped, located the boundaries on the map and then identified and listed the Pemba households within the enumeration boundary. A Pemba household, in this context, is one identified by the informants as having at least one person with origins or links to Pemba. The links may include a person's spouse, parents or grandparents, who migrated to Kenya from Pemba or where a person has migrated from Pemba to Kenya. The mapping team was followed by the village chair to the Pemba households, where the UNHCR and Haki Centre staff listed number of persons in each, while the KNBS staff marked the location of the household on the map. The entrances of identified Pemba households were marked in chalk with the letters HCR and a number starting at 001 to make it easier to find the houses during the enumeration. Since it seems to be generally well known where the Pemba live it was not considered stigmatising to mark their doors. During the feedback forums with the Pemba after the survey, there was no mention of stigmatization due to marking the door with chalk. The maps were from the 2009 national housing and population census, purchased from KNBS. The team made lists with information about the location, number and size of each household. The mapping team visited 17 villages in Kilifi and Kwale (see Table 1 in Section 2.7). All villages visited were identified before the mapping exercise by key informants as locations being home to the Pemba of Kenya. The key informants were Pemba elders in different sub-counties previously identified for providing background information on the Pemba arrival and history in Kenya. In each sub-country, the chief, the assistant chief or the village chair also accompanied the team. In Kwale, 358 households were identified with 2,220 persons, and in Kilifi, 86 households with 558 persons.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was developed before the pilot survey and revised during and after the pilot survey, based on the experience gained. The pilot survey was used to test the questions and to check for inconsistences and misinterpretations due to unclear concepts and definitions. The testing process also revealed some important themes that had been left out. The structure of the questionnaire was altered, including the order of the questions and the introductory pages, to facilitate administration of the questionnaire. Finally, the questionnaire was translated into Swahili. Both the English and Swahili versions were used in the survey, even though the English version was preferred by almost all interviewers. The two versions of the questionnaire are attached in Annex 4 and 5. Enumerators used the English questionnaire to frame the questions in the local and less academic version of Swahili.

Cleaning operations

The data were imported into a Statistics Analysis Software (SAS) file and validated. Several errors were identified during the validation process, both on how the data had been recorded by the interviewers in the field and how the data had been entered by the clerks. There were particularly many errors in the entry of the variable “Relation to the household head” (Q.2). There were also many errors in the entry of the age of the household head, which was mostly due to errors in recording the right codes. A substantial amount of time was spent cleaning the data after the data had been entered, which included consulting many paper questionnaires. The quality of the survey data was significantly improved after the data entry revision. The data were analysed using both SAS software and Excel spreadsheets.

Response rate

The rate of non-response was low. Of the 452 households visited, visits to only 23 households can be categorised as non-response. A lot of effort was made to revisit non-responding households, using interviewers living nearby. Out of the 23 non-responsive households, 12 were not at home or there was no adult at home. There were 2 interrupted interviews, 7 refusals and 2 with no links to Pemba. In one household the respondent was not mentally stable enough to be interviewed, according to the enumerator.

This location is part of the Arizona Mineral Industry Location System (AzMILS), an inventory of mineral occurences, prospects and mine locations in Arizona. Yavapai1085B is located in T12.5N R1W Sec 27 NW in the Poland Junction - 7.5 Min quad. This collection consists of various reports, maps, records and related materials acquired by the Arizona Department of Mines and Mineral Resources regarding mining properties in Arizona. Information was obtained by various means, including the property owners, exploration companies, consultants, verbal interviews, field visits, newspapers and publications. Some sections may be redacted for copyright. Please see the access statement.

This location is part of the Arizona Mineral Industry Location System (AzMILS), an inventory of mineral occurences, prospects and mine locations in Arizona. Mohave232A is located in T32N R11W Sec 2 SE in the Yellow John Mountain - 7.5 Min quad. This collection consists of various reports, maps, records and related materials acquired by the Arizona Department of Mines and Mineral Resources regarding mining properties in Arizona. Information was obtained by various means, including the property owners, exploration companies, consultants, verbal interviews, field visits, newspapers and publications. Some sections may be redacted for copyright. Please see the access statement.

The U.S. Bureau of Reclamation (Reclamation) reported a violation of the Archaeological Resources Protection Act (ARPA) in April 2003 when a petroglyph boulder was removed from Reclamation land. The boulder was located on a terrace edge overlooking the Agua Fria River north of Lake Pleasant, within archaeological site AZ T:4:157(ASM). A criminal investigation followed. The petroglyph boulder was recovered in September 2003. Subsequent to the investigation, Mr. Jon Czaplicki, Reclamation Archaeologist, requested that Archaeological Consulting Services, Ltd. (ACS) relocate the petroglyphs that were originally mapped when the site was recorded in 1996, remap their locations using a Global Positioning System (GPS) unit, and assess whether additional petroglyph boulders had been removed from AZ T:4:157(ASM) and/or adjacent site AZ T:4:156(ASM). The project also included relocation and mapping of the original datum stakes; mapping of natural and modern features such as terrace edges, drainages, and fences; and mapping of other selected archaeological features indicated as landmarks on CAD maps of the sites that were created in 1999. This letter report describes ACS' work to mitigate the damage to the site(s) and to protect the existing cultural resources. It also includes updated site maps. Select photos from this project can be found at https://core.tdar.org/image/391350. The photo log can be found at https://core.tdar.org/document/391349.

Abstract

The harmonized data set on health, created and published by the ERF, is a subset of Iraq Household Socio Economic Survey (IHSES) 2012. It was derived from the household, individual and health modules, collected in the context of the above mentioned survey. The sample was then used to create a harmonized health survey, comparable with the Iraq Household Socio Economic Survey (IHSES) 2007 micro data set.

----> Overview of the Iraq Household Socio Economic Survey (IHSES) 2012:

Iraq is considered a leader in household expenditure and income surveys where the first was conducted in 1946 followed by surveys in 1954 and 1961. After the establishment of Central Statistical Organization, household expenditure and income surveys were carried out every 3-5 years in (1971/ 1972, 1976, 1979, 1984/ 1985, 1988, 1993, 2002 / 2007). Implementing the cooperation between CSO and WB, Central Statistical Organization (CSO) and Kurdistan Region Statistics Office (KRSO) launched fieldwork on IHSES on 1/1/2012. The survey was carried out over a full year covering all governorates including those in Kurdistan Region.

The survey has six main objectives. These objectives are:

1. Provide data for poverty analysis and measurement and monitor, evaluate and update the implementation Poverty Reduction National Strategy issued in 2009.
2. Provide comprehensive data system to assess household social and economic conditions and prepare the indicators related to the human development.
3. Provide data that meet the needs and requirements of national accounts.
4. Provide detailed indicators on consumption expenditure that serve making decision related to production, consumption, export and import.
5. Provide detailed indicators on the sources of households and individuals income.
6. Provide data necessary for formulation of a new consumer price index number.

The raw survey data provided by the Statistical Office were then harmonized by the Economic Research Forum, to create a comparable version with the 2006/2007 Household Socio Economic Survey in Iraq. Harmonization at this stage only included unifying variables' names, labels and some definitions. See: Iraq 2007 & 2012- Variables Mapping & Availability Matrix.pdf provided in the external resources for further information on the mapping of the original variables on the harmonized ones, in addition to more indications on the variables' availability in both survey years and relevant comments.

Geographic coverage

National coverage: Covering a sample of urban, rural and metropolitan areas in all the governorates including those in Kurdistan Region.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey was carried out over a full year covering all governorates including those in Kurdistan Region.

Kind of data

Sample survey data [ssd]

Sampling procedure

----> Design:

Sample size was (25488) household for the whole Iraq, 216 households for each district of 118 districts, 2832 clusters each of which includes 9 households distributed on districts and governorates for rural and urban.

----> Sample frame:

Listing and numbering results of 2009-2010 Population and Housing Survey were adopted in all the governorates including Kurdistan Region as a frame to select households, the sample was selected in two stages: Stage 1: Primary sampling unit (blocks) within each stratum (district) for urban and rural were systematically selected with probability proportional to size to reach 2832 units (cluster). Stage two: 9 households from each primary sampling unit were selected to create a cluster, thus the sample size of total survey clusters was 25488 households distributed on the governorates, 216 households in each district.

----> Sampling Stages:

In each district, the sample was selected in two stages: Stage 1: based on 2010 listing and numbering frame 24 sample points were selected within each stratum through systematic sampling with probability proportional to size, in addition to the implicit breakdown urban and rural and geographic breakdown (sub-district, quarter, street, county, village and block). Stage 2: Using households as secondary sampling units, 9 households were selected from each sample point using systematic equal probability sampling. Sampling frames of each stages can be developed based on 2010 building listing and numbering without updating household lists. In some small districts, random selection processes of primary sampling may lead to select less than 24 units therefore a sampling unit is selected more than once , the selection may reach two cluster or more from the same enumeration unit when it is necessary.

Mode of data collection

Face-to-face [f2f]

Research instrument

----> Preparation:

The questionnaire of 2006 survey was adopted in designing the questionnaire of 2012 survey on which many revisions were made. Two rounds of pre-test were carried out. Revision were made based on the feedback of field work team, World Bank consultants and others, other revisions were made before final version was implemented in a pilot survey in September 2011. After the pilot survey implemented, other revisions were made in based on the challenges and feedbacks emerged during the implementation to implement the final version in the actual survey.

----> Questionnaire Parts:

The questionnaire consists of four parts each with several sections: Part 1: Socio – Economic Data: - Section 1: Household Roster - Section 2: Emigration - Section 3: Food Rations - Section 4: housing - Section 5: education - Section 6: health - Section 7: Physical measurements - Section 8: job seeking and previous job

Part 2: Monthly, Quarterly and Annual Expenditures: - Section 9: Expenditures on Non – Food Commodities and Services (past 30 days). - Section 10 : Expenditures on Non – Food Commodities and Services (past 90 days). - Section 11: Expenditures on Non – Food Commodities and Services (past 12 months). - Section 12: Expenditures on Non-food Frequent Food Stuff and Commodities (7 days). - Section 12, Table 1: Meals Had Within the Residential Unit. - Section 12, table 2: Number of Persons Participate in the Meals within Household Expenditure Other Than its Members.

Part 3: Income and Other Data: - Section 13: Job - Section 14: paid jobs - Section 15: Agriculture, forestry and fishing - Section 16: Household non – agricultural projects - Section 17: Income from ownership and transfers - Section 18: Durable goods - Section 19: Loans, advances and subsidies - Section 20: Shocks and strategy of dealing in the households - Section 21: Time use - Section 22: Justice - Section 23: Satisfaction in life - Section 24: Food consumption during past 7 days

Part 4: Diary of Daily Expenditures: Diary of expenditure is an essential component of this survey. It is left at the household to record all the daily purchases such as expenditures on food and frequent non-food items such as gasoline, newspapers…etc. during 7 days. Two pages were allocated for recording the expenditures of each day, thus the roster will be consists of 14 pages.

Cleaning operations

----> Raw Data:

Data Editing and Processing: To ensure accuracy and consistency, the data were edited at the following stages: 1. Interviewer: Checks all answers on the household questionnaire, confirming that they are clear and correct. 2. Local Supervisor: Checks to make sure that questions has been correctly completed. 3. Statistical analysis: After exporting data files from excel to SPSS, the Statistical Analysis Unit uses program commands to identify irregular or non-logical values in addition to auditing some variables. 4. World Bank consultants in coordination with the CSO data management team: the World Bank technical consultants use additional programs in SPSS and STAT to examine and correct remaining inconsistencies within the data files. The software detects errors by analyzing questionnaire items according to the expected parameter for each variable.

----> Harmonized Data:

• The SPSS package is used to harmonize the Iraq Household Socio Economic Survey (IHSES) 2007 with Iraq Household Socio Economic Survey (IHSES) 2012.
• The harmonization process starts with raw data files received from the Statistical Office.
• A program is generated for each dataset to create harmonized variables.
• Data is saved on the household and individual level, in SPSS and then converted to STATA, to be disseminated.

Response rate

Iraq Household Socio Economic Survey (IHSES) reached a total of 25488 households. Number of households refused to response was 305, response rate was 98.6%. The highest interview rates were in Ninevah and Muthanna (100%) while the lowest rates were in Sulaimaniya (92%).

Global Insurtech Market was valued at $5.48 Billion in 2022, and Projected to $146.43 Billion by 2030, CAGR of 50.78% from 2023 to 2030.

The Bureau of Reclamation (Reclamation) partnered with the Fort McDowell Indian Community (FMIC) on the FMIC Irrigated Farmland Development Project to develop new agricultural fields in accordance with the stipulations set forth in the Fort McDowell Indian Community Water Rights Settlement Act (Public Law 101-628).

At the request of Reclamation, Archaeological Consulting Services, Ltd. (ACS) conducted survey of approximately 400 acres, mapping, photographing, and limited testing of cultural resources on the Fort McDowell Indian Reservation. The survey and mapping were performed to record and determine the extent of prehistoric agricultural rockpile features at AZ U:6:81(ASM) and U:6:239(ASM) that will be impacted by agricultural development. Subsurface testing at AZ U:6:87(ASM) was conducted to identify the nature and extent of subsurface cultural resources at the site that will be impacted by road widening. All three sites have previously been determined to be eligible for inclusion on the National Register of Historic Places (NRHP). Further inspection of a possible historic site on Rattlesnake Point was undertaken and determined to date to the 1960s, and was therefore, not considered eligible for inclusion in the NRHP.

This location is part of the Arizona Mineral Industry Location System (AzMILS), an inventory of mineral occurences, prospects and mine locations in Arizona. Pima703 is located in T14S R4W Sec 2 C in the Mt Ajo - 15 Min quad. This collection consists of various reports, maps, records and related materials acquired by the Arizona Department of Mines and Mineral Resources regarding mining properties in Arizona. Information was obtained by various means, including the property owners, exploration companies, consultants, verbal interviews, field visits, newspapers and publications. Some sections may be redacted for copyright. Please see the access statement.

This location is part of the Arizona Mineral Industry Location System (AzMILS), an inventory of mineral occurences, prospects and mine locations in Arizona. Coconino284B is located in T19N R1E Sec 10 SE in the Matterhorn - 7.5 Min quad. This collection consists of various reports, maps, records and related materials acquired by the Arizona Department of Mines and Mineral Resources regarding mining properties in Arizona. Information was obtained by various means, including the property owners, exploration companies, consultants, verbal interviews, field visits, newspapers and publications. Some sections may be redacted for copyright. Please see the access statement.

This location is part of the Arizona Mineral Industry Location System (AzMILS), an inventory of mineral occurences, prospects and mine locations in Arizona. Mohave18B is located in T19N R20W Sec 7 SE in the Oatman - 7.5 Min quad. This collection consists of various reports, maps, records and related materials acquired by the Arizona Department of Mines and Mineral Resources regarding mining properties in Arizona. Information was obtained by various means, including the property owners, exploration companies, consultants, verbal interviews, field visits, newspapers and publications. Some sections may be redacted for copyright. Please see the access statement.

The Significant Geothermal Feature data is a combination of information digitised in-house, and data received from Wildlands Consultants regarding vegetation and other sources regarding geophysical aspects of Significant Geothermal Features. This particular layer represents Significant Geothermal Features as in the Regional Plan Geothermal module. December 2006: Some boundaries have changed; the features are based on Wildlands 2004 work that was reflected in the Decisions version and the recent fieldwork undertaken by Wildlands in late 2006. Changes were made ONLY where boundaries could be reduced in specific area, to satisfy Environment Court requirement that only areas notified publicly be shown. April 2011: Some boundaries have been changed, and maps for Tokaanu and Atiamuri added. Hydrothermal eruption craters on the Horohoro map have been added. Some warm streams have been added.For further metadata please see feature WRP_GEOTHERMAL_FEATURE in dataset Waikato Regional Plan Significant Geothermal Feature