As of 2024, the population of Israel reached about *** million permanent residents in total. About *** million were registered as Jews or other non-Arab populations. Furthermore, some *** million Arabs lived in the country.

Jews were the dominant religious group in the Israel-Palestine region at the beginning of the first millennia CE, and are the dominant religious group there today, however, there was a period of almost 2,000 years where most of the world's Jews were displaced from their spiritual homeland. Antiquity to the 20th century Jewish hegemony in the region began changing after a series of revolts against Roman rule led to mass expulsions and emigration. Roman control saw severe persecution of Jewish and Christian populations, but this changed when the Byzantine Empire adopted Christianity as its official religion in the 4th century. Christianity then dominated until the 7th century, when the Rashidun Caliphate (the first to succeed Muhammad) took control of the Levant. Control of region split between Christians and Muslims intermittently between the 11th and 13th centuries during the Crusades, although the population remained overwhelmingly Muslim. Zionism until today Through the Paris Peace Conference, the British took control of Palestine in 1920. The Jewish population began growing through the Zionist Movement after the 1880s, which sought to establish a Jewish state in Palestine. Rising anti-Semitism in Europe accelerated this in the interwar period, and in the aftermath of the Holocaust, many European Jews chose to leave the continent. The United Nations tried facilitating the foundation of separate Jewish and Arab states, yet neither side was willing to concede territory, leading to a civil war and a joint invasion from seven Arab states. Yet the Jews maintained control of their territory and took large parts of the proposed Arab territory, forming the Jewish-majority state of Israel in 1948, and acheiving a ceasefire the following year. Over 750,000 Palestinians were displaced as a result of this conflict, while most Jews from the Arab eventually fled to Israel. Since this time, Israel has become one of the richest and advanced countries in the world, however, Palestine has been under Israeli military occupation since the 1960s and there are large disparities in living standards between the two regions.

In 2023, Jerusalem was the city with the largest population of Muslim residents in Israel, reaching ******* people. This represented about ** percent of the city's total population. The town with the second-highest number of Muslims was Rahat, with ****** members of the religion. Rahat is a predominantly Bedouin city in southern Israel. Umm al-Fahm and Nazareth, both located in northern Israel, make up a sizeable portion of the Muslim community in Israel.

In 1995, Israel had a Jewish population of approximately 4.5 million people, of whom approximately 1.75 million were born abroad. Over one million of these immigrants were born in Europe, with over 650,000 of these born in the former Soviet Union. Despite Poland having the largest Jewish population in the world in the pre-WWII years, the number of Polish Jewish migrants and descendents in Israel was relatively small in 1995 when compared to the USSR due to the impact of the Holocaust.

Outside of Europe, Morocco had the largest number of Jewish immigrants and descendents in Israel by 1995. Morocco had the largest Jewish population in the Muslim world when Israel was founded in 1948, with over 250,000 people. Many Moroccan Jews sought to emigrate to Israel at this time, but often faced resistance from authorities and local populations who believed the Jews would join in the fight against the Arab forces seeking to establish a Muslim state in Palestine. The government of Morocco then officially prohibited emigration to Israel after gaining independence from France in 1956, however this policy was reversed in 1961 whereby the Moroccan government began facilitating Jewish emigration to Israel in return for payments from Jewish organizations in the U.S. and Israel. By the 1970s, Morocco's Jewish population had fallen to less than 15 percent of its size in 1948.

Between Oct. 14, 2014, and May 21, 2015, Pew Research Center, with generous funding from The Pew Charitable Trusts and the Neubauer Family Foundation, completed 5,601 face-to-face interviews with non-institutionalized adults ages 18 and older living in Israel.

The survey sampling plan was based on six districts defined in the 2008 Israeli census. In addition, Jewish residents of West Bank (Judea and Samaria) were included.

The sample includes interviews with 3,789 respondents defined as Jews, 871 Muslims, 468 Christians and 439 Druze. An additional 34 respondents belong to other religions or are religiously unaffiliated. Five groups were oversampled as part of the survey design: Jews living in the West Bank, Haredim, Christian Arabs, Arabs living in East Jerusalem and Druze.

Interviews were conducted under the direction of Public Opinion and Marketing Research of Israel (PORI). Surveys were administered through face-to-face, paper and pencil interviews conducted at the respondent's place of residence. Sampling was conducted through a multi-stage stratified area probability sampling design based on national population data available through the Israel's Central Bureau of Statistics' 2008 census.

The questionnaire was designed by Pew Research Center staff in consultation with subject matter experts and advisers to the project. The questionnaire was translated into Hebrew, Russian and Arabic, independently verified by professional linguists conversant in regional dialects and pretested prior to fieldwork.

The questionnaire was divided into four sections. All respondents who took the survey in Russian or Hebrew were branched into the Jewish questionnaire (Questionnaire A). Arabic-speaking respondents were branched into the Muslim (Questionnaire B), Christian (Questionnaire C) or Druze questionnaire (D) based on their response to the religious identification question. For the full question wording and exact order of questions, please see the questionnaire.

Note that not all respondents who took the questionnaire in Hebrew or Russian are classified as Jews in this study. For further details on how respondents were classified as Jews, Muslims, Christians and Druze in the study, please see sidebar in the report titled "http://www.pewforum.org/2016/03/08/israels-religiously-divided-society/" Target="_blank">"How Religious are Defined".

Following fieldwork, survey performance was assessed by comparing the results for key demographic variables with population statistics available through the census. Data were weighted to account for different probabilities of selection among respondents. Where appropriate, data also were weighted through an iterative procedure to more closely align the samples with official population figures for gender, age and education. The reported margins of sampling error and the statistical tests of significance used in the analysis take into account the design effects due to weighting and sample design.

In addition to sampling error and other practical difficulties, one should bear in mind that question wording also can have an impact on the findings of opinion polls.

In 2023, the population of Muslims in Israel was estimated at 1.77 million. This marked an increase of 2 percent compared to the previous year. The Muslim community in the country formed the largest religious minority in the country.

Israel's population is aging steadily, with the median age projected to rise from ** years in 2020 to ** years by 2050. This demographic shift reflects global trends of increasing life expectancy and declining birth rates, though Israel maintained a relatively young population compared to many developed nations. The country's unique religious and cultural makeup contributed to regional variations in age distribution, presenting both opportunities and challenges for policymakers. Which region has the oldest population? As of 2023, over a ******* of Israelis were under the age of 14 years. The largest age group in the country being ************** and below. Interestingly, significant regional differences existed within the country when it came to age distribution and aging. While the median age in the Jerusalem district was below **, Tel Aviv was the oldest region with an average age of over ** years, highlighting significant demographic variations across different areas. How does religion influence demographics? Religious affiliation played a role in Israel's age structure and demographics. Muslims are the youngest religious group with a median age of ** years, while Christians of Arab ethnicity are the oldest, at ** years. Jews, the largest religious-ethnic group, had a median age of almost ** years, but within the Jewish demographic, age and fertility varied greatly between people based on religiosity. These differences play a significant role in the country's population and future growth patterns.

The purpose of this study is to examine the attitudes of Jews and Arabs in Israel concerning the role of the police in counterterrorism. The study focuses on the public perception of the effect of the police’s involvement in counterterrorism on their ability to perform traditional police roles; how the police’s role in fighting terrorism affects the relationship between police and the community; and the willingness of Jews and Arabs in Israel to assist the police by reporting crimes and terrorism threats. These questions are asked against the backdrop of majority-minority relations, in which the ways both the majority Jewish population and the minority Arab population in Israel responds are examined. Data included in this study was gathered from a community survey. The computer software “Dvash” and the database “Bezek,” which includes all residents of Israel who have "land" phone lines were used to conduct the survey. The low response rate (58%) of the community survey limits the extent to which the results can be applied to the entire Israeli population. Variables affecting the data gathered include the respondent’s past experiences with the po lice, their religion or ethnicity, their trust in the capabilities of the police, and their views on the consequences of policing terrorism.

Israel Population: 2008 Census: excl Foreign Workers: End Period: Jews and Others data was reported at 7,068.800 Person th in Oct 2018. This records an increase from the previous number of 7,055.800 Person th for Sep 2018. Israel Population: 2008 Census: excl Foreign Workers: End Period: Jews and Others data is updated monthly, averaging 6,446.100 Person th from Jan 2009 (Median) to Oct 2018, with 118 observations. The data reached an all-time high of 7,068.800 Person th in Oct 2018 and a record low of 5,926.300 Person th in Jan 2009. Israel Population: 2008 Census: excl Foreign Workers: End Period: Jews and Others data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G001: Population. The group 'Jews and others' includes Jews, population not classified by religion and non-Arab Christians.

At the end of 2023, the population of Israel reached almost 9.7 million permanent residents. Jewish residents formed the largest religious group, with just over 7.15 million people. The Muslim population in the country, formed the largest religious minority at over 1.7 million individuals. Conversely, the smallest religious group was that of the Druze with about 151,000 people.

ObjectiveDiabetes mellitus is an emerging epidemic in the Arab world. Although high diabetes prevalence is documented in Israeli Arabs, information from cohort studies is scant.MethodsThis is a population study, based on information derived between 2007–2011, from the electronic database of the largest health fund in Israel, among Arabs and Jews. Prevalence, 4-year-incidence and diabetes hazard ratios [HRs], adjusted for sex and the metabolic-syndrome [MetS]-components, were determined in 3 age groups (

Background and Aims: Scientific evidence regarding protective factors that contribute to healthy weight in childhood is limited and is particularly scarce in lower socio-economic populations in different ethnic groups. This study aimed to assess the prevalence of biological, behavioral and psychosocial factors for child overweight/obesity in Jewish and Arab population groups in Israel, and to compare their associations with child overweight/obesity in the two groups.Methods: Children aged 5–6 years were randomly selected from 20 Mother and Child Health clinics in towns and villages of lowest socio-economic ranking in Northern Israel. Children and mothers were invited for a special “One Stop Shop–Preparation for School” visit which included growth measurements. Questionnaires were distributed to mothers for self-report on biological, SES, psychological and lifestyle factors. Perinatal and early nutritional data were retrieved from clinic records. Multivariate analyses using logistic regression models predicting child overweight/obesity were conducted separately for Jewish (N = 371) and Arab (N = 575) children.Results: Overweight/obesity (BMI ≥85th centile) rates were higher in Jewish (25%) than Arab (19%) children. In both Jewish and Arab groups, respectively, maternal BMI (OR = 1.10 [95%CI = 1.04, 1.17]; OR = 1.08 [95%CI = 1.04, 1.13]), and child birthweight (OR = 1.33 [95%CI = 1.04, 1.71]; OR = 1.39 [95%CI = 1.11, 1.73]) were significant risk factors for overweight/obesity, and maternal self-efficacy regarding child's lifestyle was significantly protective (OR = 0.49 [95%CI = 0.28, 0.85]; OR = 0.54 [95%CI = 0.34, 0.85]). Additionally, four other maternal psychological and child behaviors were significantly associated with overweight/obesity in the Jewish group and two child lifestyle behavior factors in the Arab group. Moreover, significant interactions indicating moderation effects were found only in the Jewish group: maternal education and maternal age moderated the effect of maternal BMI on child overweight/obesity. No other moderation of risk factors was found.Discussion: In this study of children from low SES families, protective factors contributed to healthy child weight alongside risk factors for overweight/obesity. They differed between the population groups, and fewer variables explained overweight/obesity in Arab children. Although further expansion of these findings is required they point at the relevance of protective factors, maternal self-efficacy in particular, for understanding childhood obesity in specific ethnic contexts and for planning culturally adapted prevention programs in disadvantaged populations.

In 2024, nearly ** percent of the Arab population in Israel lived in a home that they owned themselves. Just over ** percent of this segment of the Israeli population lived in rented housing. There were no records of older members of this segment of society living in assisted living facilities.

Seroprevalence and univariate logistic regression analysis of associated possible correlates for West Nile virus in subjects in Israel.

Israel IL: Refugee Population: by Country or Territory of Origin data was reported at 459.000 Person in 2017. This records a decrease from the previous number of 495.000 Person for 2016. Israel IL: Refugee Population: by Country or Territory of Origin data is updated yearly, averaging 818.500 Person from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 1,541.000 Person in 2007 and a record low of 16.000 Person in 1990. Israel IL: Refugee Population: by Country or Territory of Origin data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Israel – Table IL.World Bank: Population and Urbanization Statistics. Refugees are people who are recognized as refugees under the 1951 Convention Relating to the Status of Refugees or its 1967 Protocol, the 1969 Organization of African Unity Convention Governing the Specific Aspects of Refugee Problems in Africa, people recognized as refugees in accordance with the UNHCR statute, people granted refugee-like humanitarian status, and people provided temporary protection. Asylum seekers--people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers--are excluded. Palestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict. Country of origin generally refers to the nationality or country of citizenship of a claimant.; ; United Nations High Commissioner for Refugees (UNHCR), Statistics Database, Statistical Yearbook and data files, complemented by statistics on Palestinian refugees under the mandate of the UNRWA as published on its website. Data from UNHCR are available online at: www.unhcr.org/en-us/figures-at-a-glance.html.; Sum;

In a survey conducted in Israel in 2021, ** percent of Jewish respondents stated that they saw India as a friendly country. The same share of Arab respondents found India to be a friendly state to Israel. India was the only country in the survey labeled as favorable at the same rate by both population groups.

Overview

This dataset is the repository for the following paper submitted to Data in Brief:

Kempf, M. A dataset to model Levantine landcover and land-use change connected to climate change, the Arab Spring and COVID-19. Data in Brief (submitted: December 2023).

The Data in Brief article contains the supplement information and is the related data paper to:

Kempf, M. Climate change, the Arab Spring, and COVID-19 - Impacts on landcover transformations in the Levant. Journal of Arid Environments (revision submitted: December 2023).

Description/abstract

The Levant region is highly vulnerable to climate change, experiencing prolonged heat waves that have led to societal crises and population displacement. Since 2010, the area has been marked by socio-political turmoil, including the Syrian civil war and currently the escalation of the so-called Israeli-Palestinian Conflict, which strained neighbouring countries like Jordan due to the influx of Syrian refugees and increases population vulnerability to governmental decision-making. Jordan, in particular, has seen rapid population growth and significant changes in land-use and infrastructure, leading to over-exploitation of the landscape through irrigation and construction. This dataset uses climate data, satellite imagery, and land cover information to illustrate the substantial increase in construction activity and highlights the intricate relationship between climate change predictions and current socio-political developments in the Levant.

Folder structure

The main folder after download contains all data, in which the following subfolders are stored are stored as zipped files:

“code” stores the above described 9 code chunks to read, extract, process, analyse, and visualize the data.

“MODIS_merged” contains the 16-days, 250 m resolution NDVI imagery merged from three tiles (h20v05, h21v05, h21v06) and cropped to the study area, n=510, covering January 2001 to December 2022 and including January and February 2023.

“mask” contains a single shapefile, which is the merged product of administrative boundaries, including Jordan, Lebanon, Israel, Syria, and Palestine (“MERGED_LEVANT.shp”).

“yield_productivity” contains .csv files of yield information for all countries listed above.

“population” contains two files with the same name but different format. The .csv file is for processing and plotting in R. The .ods file is for enhanced visualization of population dynamics in the Levant (Socio_cultural_political_development_database_FAO2023.ods).

“GLDAS” stores the raw data of the NASA Global Land Data Assimilation System datasets that can be read, extracted (variable name), and processed using code “8_GLDAS_read_extract_trend” from the respective folder. One folder contains data from 1975-2022 and a second the additional January and February 2023 data.

“built_up” contains the landcover and built-up change data from 1975 to 2022. This folder is subdivided into two subfolder which contain the raw data and the already processed data. “raw_data” contains the unprocessed datasets and “derived_data” stores the cropped built_up datasets at 5 year intervals, e.g., “Levant_built_up_1975.tif”.

Code structure

1_MODIS_NDVI_hdf_file_extraction.R

This is the first code chunk that refers to the extraction of MODIS data from .hdf file format. The following packages must be installed and the raw data must be downloaded using a simple mass downloader, e.g., from google chrome. Packages: terra. Download MODIS data from after registration from: https://lpdaac.usgs.gov/products/mod13q1v061/ or https://search.earthdata.nasa.gov/search (MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V061, last accessed, 09th of October 2023). The code reads a list of files, extracts the NDVI, and saves each file to a single .tif-file with the indication “NDVI”. Because the study area is quite large, we have to load three different (spatially) time series and merge them later. Note that the time series are temporally consistent.

2_MERGE_MODIS_tiles.R

In this code, we load and merge the three different stacks to produce large and consistent time series of NDVI imagery across the study area. We further use the package gtools to load the files in (1, 2, 3, 4, 5, 6, etc.). Here, we have three stacks from which we merge the first two (stack 1, stack 2) and store them. We then merge this stack with stack 3. We produce single files named NDVI_final_*consecutivenumber*.tif. Before saving the final output of single merged files, create a folder called “merged” and set the working directory to this folder, e.g., setwd("your directory_MODIS/merged").

3_CROP_MODIS_merged_tiles.R

Now we want to crop the derived MODIS tiles to our study area. We are using a mask, which is provided as .shp file in the repository, named "MERGED_LEVANT.shp". We load the merged .tif files and crop the stack with the vector. Saving to individual files, we name them “NDVI_merged_clip_*consecutivenumber*.tif. We now produced single cropped NDVI time series data from MODIS.
The repository provides the already clipped and merged NDVI datasets.

4_TREND_analysis_NDVI.R

Now, we want to perform trend analysis from the derived data. The data we load is tricky as it contains 16-days return period across a year for the period of 22 years. Growing season sums contain MAM (March-May), JJA (June-August), and SON (September-November). December is represented as a single file, which means that the period DJF (December-February) is represented by 5 images instead of 6. For the last DJF period (December 2022), the data from January and February 2023 can be added. The code selects the respective images from the stack, depending on which period is under consideration. From these stacks, individual annually resolved growing season sums are generated and the slope is calculated. We can then extract the p-values of the trend and characterize all values with high confidence level (0.05). Using the ggplot2 package and the melt function from reshape2 package, we can create a plot of the reclassified NDVI trends together with a local smoother (LOESS) of value 0.3.
To increase comparability and understand the amplitude of the trends, z-scores were calculated and plotted, which show the deviation of the values from the mean. This has been done for the NDVI values as well as the GLDAS climate variables as a normalization technique.

5_BUILT_UP_change_raster.R

Let us look at the landcover changes now. We are working with the terra package and get raster data from here: https://ghsl.jrc.ec.europa.eu/download.php?ds=bu (last accessed 03. March 2023, 100 m resolution, global coverage). Here, one can download the temporal coverage that is aimed for and reclassify it using the code after cropping to the individual study area. Here, I summed up different raster to characterize the built-up change in continuous values between 1975 and 2022.

6_POPULATION_numbers_plot.R

For this plot, one needs to load the .csv-file “Socio_cultural_political_development_database_FAO2023.csv” from the repository. The ggplot script provided produces the desired plot with all countries under consideration.

7_YIELD_plot.R

In this section, we are using the country productivity from the supplement in the repository “yield_productivity” (e.g., "Jordan_yield.csv". Each of the single country yield datasets is plotted in a ggplot and combined using the patchwork package in R.

8_GLDAS_read_extract_trend

The last code provides the basis for the trend analysis of the climate variables used in the paper. The raw data can be accessed https://disc.gsfc.nasa.gov/datasets?keywords=GLDAS%20Noah%20Land%20Surface%20Model%20L4%20monthly&page=1 (last accessed 9th of October 2023). The raw data comes in .nc file format and various variables can be extracted using the [“^a variable name”] command from the spatraster collection. Each time you run the code, this variable name must be adjusted to meet the requirements for the variables (see this link for abbreviations: https://disc.gsfc.nasa.gov/datasets/GLDAS_CLSM025_D_2.0/summary, last accessed 09th of October 2023; or the respective code chunk when reading a .nc file with the ncdf4 package in R) or run print(nc) from the code or use names(the spatraster collection).
Choosing one variable, the code uses the MERGED_LEVANT.shp mask from the repository to crop and mask the data to the outline of the study area.
From the processed data, trend analysis are conducted and z-scores were calculated following the code described above. However, annual trends require the frequency of the time series analysis to be set to value = 12. Regarding, e.g., rainfall, which is measured as annual sums and not means, the chunk r.sum=r.sum/12 has to be removed or set to r.sum=r.sum/1 to avoid calculating annual mean values (see other variables). Seasonal subset can be calculated as described in the code. Here, 3-month subsets were chosen for growing seasons, e.g. March-May (MAM), June-July (JJA), September-November (SON), and DJF (December-February, including Jan/Feb of the consecutive year).
From the data, mean values of 48 consecutive years are calculated and trend analysis are performed as describe above. In the same way, p-values are extracted and 95 % confidence level values are marked with dots on the raster plot. This analysis can be performed with a much longer time series, other variables, ad different spatial extent across the globe due to the availability of the GLDAS variables.

Population: 2008 Census: excl Foreign Workers: End Period: Jews and Others: ow Jews data was reported at 6,646.100 Person th in Oct 2018. This records an increase from the previous number of 6,635.400 Person th for Sep 2018. Population: 2008 Census: excl Foreign Workers: End Period: Jews and Others: ow Jews data is updated monthly, averaging 6,099.800 Person th from Jan 2009 (Median) to Oct 2018, with 118 observations. The data reached an all-time high of 6,646.100 Person th in Oct 2018 and a record low of 5,616.100 Person th in Jan 2009. Population: 2008 Census: excl Foreign Workers: End Period: Jews and Others: ow Jews data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G001: Population. The group 'Jews and others' includes Jews, population not classified by religion and non-Arab Christians.

Standardized and age-specific prevalence and weighted cumulative 4-yr incidence per 100 persons of diabetes (95% confidence interval)*.

The dataset includes detailed information from Israel's 2013 and 2018 local elections, covering 2520 electoral lists across 193 municipalities. It contains data on each list's official name, election results, mayoral candidacy, national-party linkage, relative size, and vote share in the city. Additionally, it includes comprehensive municipal data such as registered voter numbers, socioeconomic ranking, geographic region, city type (Jewish or Arab), and demographics of the elderly and youth populations. The authors made two Freedom of Information requests, one on November 26, 2020, and another on November 19, 2022. Adv. Elad Mann assisted the authors after the Ministry of Interior rejected their requests. This approach helped us to collect a unique dataset, making it the first comprehensive resource for Israeli local elections.