South Africa is the sixth African country with the largest population, counting approximately 60.5 million individuals as of 2021. In 2023, the largest city in South Africa was Cape Town. The capital of Western Cape counted 3.4 million inhabitants, whereas South Africa's second largest city was Durban (eThekwini Municipality), with 3.1 million inhabitants. Note that when observing the number of inhabitants by municipality, Johannesburg is counted as largest city/municipality of South Africa.

From four provinces to nine provinces

Before Nelson Mandela became president in 1994, the country had four provinces, Cape of Good Hope, Natal, Orange Free State, and Transvaal and 10 “homelands” (also called Bantustans). The four larger regions were for the white population while the homelands for its black population. This system was dismantled following the new constitution of South Africa in 1996 and reorganized into nine provinces. Currently, Gauteng is the most populated province with around 15.9 million people residing there, followed by KwaZulu-Natal with 11.68 million inhabiting the province. As of 2022, Black African individuals were almost 81 percent of the total population in the country, while colored citizens followed amounting to around 5.34 million.

A diverse population

Although the majority of South Africans are identified as Black, the country’s population is far from homogenous, with different ethnic groups usually residing in the different “homelands”. This can be recognizable through the various languages used to communicate between the household members and externally. IsiZulu was the most common language of the nation with around a quarter of the population using it in- and outside of households. IsiXhosa and Afrikaans ranked second and third with roughly 15 percent and 12 percent, respectively.

Cairo, in Egypt, ranked as the most populated city in Africa as of 2025, with an estimated population of over 23 million inhabitants living in Greater Cairo. Kinshasa, in Congo, and Lagos, in Nigeria, followed with some 17.8 million and 17.2 million, respectively. Among the 15 largest cities in the continent, another one, Kano, was located in Nigeria, the most populous country in Africa. Population density trends in Africa As of 2023, Africa exhibited a population density of 50.1 individuals per square kilometer. Since 2000, the population density across the continent has been experiencing a consistent annual increment. Projections indicated that the average population residing within each square kilometer would rise to approximately 58.5 by the year 2030. Moreover, Mauritius stood out as the African nation with the most elevated population density, exceeding 627 individuals per square kilometre. Mauritius possesses one of the most compact territories on the continent, a factor that significantly influences its high population density. Urbanization dynamics in Africa The urbanization rate in Africa was anticipated to reach close to 45.5 percent in 2024. Urbanization across the continent has consistently risen since 2000, with urban areas accommodating only around a third of the total population then. This trajectory is projected to continue its rise in the years ahead. Nevertheless, the distribution between rural and urban populations shows remarkable diversity throughout the continent. In 2024, Gabon and Libya stood out as Africa’s most urbanized nations, each surpassing 80 percent urbanization. As of the same year, Africa's population was estimated to expand by 2.27 percent compared to the preceding year. Since 2000, the population growth rate across the continent has consistently exceeded 2.3 percent, reaching its pinnacle at 2.63 percent in 2013. Although the growth rate has experienced a deceleration, Africa's population will persistently grow significantly in the forthcoming years.

Population in largest city in South Africa was reported at 6324351 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. South Africa - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

South Africa ZA: Population in Largest City data was reported at 9,822,625.000 Person in 2017. This records an increase from the previous number of 9,615,976.000 Person for 2016. South Africa ZA: Population in Largest City data is updated yearly, averaging 3,628,124.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 9,822,625.000 Person in 2017 and a record low of 2,136,849.000 Person in 1960. South Africa ZA: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Population in the largest city (% of urban population) in South Africa was reported at 14.26 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. South Africa - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

South Africa ZA: Population in Largest City: as % of Urban Population data was reported at 26.327 % in 2017. This records an increase from the previous number of 26.291 % for 2016. South Africa ZA: Population in Largest City: as % of Urban Population data is updated yearly, averaging 23.218 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 26.327 % in 2017 and a record low of 18.806 % in 1991. South Africa ZA: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted Average;

Johannesburg was the wealthiest city in Africa as of 2021. South Africa's biggest city held *** billion U.S. dollars in private wealth, while Cape Town followed with *** billion U.S. dollars. The country led the ranking of wealthiest nations in Africa. The wealth value referred to assets such as cash, properties, and business interests held by individuals living in each country, less liabilities. Moreover, government funds were excluded.

The fastest growing city in Africa is Bujumbura, in Burundi. In 2020, this city had an estimated population of about one million. By 2035, the population of Bujumbura could increase by 123 percent and reach roughly 2.3 million people. Zinder, in Niger, had about half million inhabitants in 2020 and, with a growth rate of 118 percent, is Africa's second fastest growing city. In 2035, Zinder could have over one million residents.

As of 2021, the largest city in whole Africa is Lagos, in Nigeria. Other highly populated cities in Africa are Kinshasa, in Congo, Cairo, and Alexandria, both located in Egypt.

Abstract

The World Values Survey aims to attain a broad understanding of socio-political trends (i.e. perceptions, behaviour and expectations) among adults across the world.

Geographic coverage

National The sample was distributed as follows: 60% metropolitan (large cities with populations of 250 000+); 40% non-metropolitan (including cities, large towns, small towns, villages and rural areas)

Analysis unit

Individual

Universe

The sample included adults 16 years+ in South Africa

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample had to be representative of urban as well as rural populations. Roughly the distribution was as follows: - South Africa: 60% metropolitan (large cities with populations of 250 000+); 40% non-metropolitan (including cities, large towns, small towns, villages and rural areas).

A standard form of sampling instructions was sent to each agency to ensure uniformity in the sampling procedure. Markinor stratified the samples for each country by region, sex and community size. To this end, statistics and figures that were supplied to us by the agencies were used. However, we requested the agencies to revise these where necessary or where alternatives would be more effective. The agencies then supplied the street names for the urban starting points, and made suggestions for sampling procedures in rural areas where neither maps nor street names were available. From sample-point level, the respondent selection was done randomly according to a selection grid used by Markinor (the first two pages of the master questionnaire).

Substitution was permitted after three unsuccessful calls. Six interviews were conducted at each sample point. The male/female split was 50/50. The urban sample included all community sizes greater than 500 and the rural sample all community sizes less than 500. This is the definition of urban and rural used in South Africa.

Remarks about sampling: -Final numbers of clusters or sampling points: 500 -Sample unit from office sampling: Street Names

Mode of data collection

Face-to-face [f2f]

Research instrument

The WVS questionnaire was translated from the English questionnaire by a specialist translator The translated questionnaire was pre-tested. The pre-tests were part of the general pilots. In total 20 pilots were conducted. The English questionnaire from the University of Michigan was used to make the WVS. Extra questions were added at the end of the questionnaire. Also, country specific questions were included at the end of the questionnaire, just before the demographics.The sample was designed to be representative of the entire adult population, i.e. 18 years and older, of your country. The lower age cut-off for the sample was 16 and there was not any upper age cut-off for the sample.

Cleaning operations

Some measures of coding reliability were employed. Each questionnaire is coded against the coding frame. A minimum of 10% of each coders work is checked to ensure consistency in interpretation. If any discrepancies in interpretation are World Values Survey (1999-2004) - South Africa 2001 v.2015.04.18 discovered, a 100% check is carried out on that particular coders work. Errors were corrected individually and automatically.

Sampling error estimates

The error margins for this survey can be calculated by taking the following factors into account: - all samples were random (as opposed to quota-controlled) - the sample size per country (or segment being analysed) - the substitution rate per country (or segment being analysed) - the rates were recorded on CARD 1; col. 805 of the questionnaire. From the substitution rate, the response rate can be calculated.

South Africa is the southernmost country in Africa. It covers an area of 1,221,037 square kilometres (471,445 square miles). South Africa has three capital cities: executive Pretoria, judicial Bloemfontein and legislative Cape Town. The largest city is Johannesburg. About 80% of South Africans are of Black African ancestry, divided among a variety of ethnic groups speaking different African languages. The remaining population consists of Africa's largest communities of European (White South Africans), Asian (Indian South Africans and Chinese South Africans), and Multiracial (Coloured South Africans) ancestry.

Source: Objaverse 1.0 / Sketchfab

In 2024, Pietermaritzburg in South Africa ranked first in the crime index among African cities, scoring **** index points. The six most dangerous areas on the continent were South African cities. Furthermore, Pretoria and Johannesburg followed, with a score of **** and **** points, respectively. The index estimates the overall level of crime in a specific territory. According to the score, crime levels are classified as very high (over 80), high (60-80), moderate (40-60), low (20-40), and very low (below 20). Contact crimes are common in South Africa Contact crimes in South Africa include violent crimes such as murder, attempted murder, and sexual offenses, as well as common assault and robbery. In fiscal year 2022/2023, the suburb of Johannesburg Central in the Gauteng province of South Africa had the highest number of contact crime incidents. Common assault was the main contributing type of offense to the overall number of contact crimes. Household robberies peak in certain months In South Africa, June, July, and December experienced the highest number of household robberies in 2023. June and July are the months that provide the most hours of darkness, thus allowing criminals more time to break in and enter homes without being detected easily. In December, most South Africans decide to go away on holiday, leaving their homes at risk for a potential break-in. On the other hand, only around ** percent of households affected by robbery reported it to the police in the fiscal year 2022/2023.

As of 2023, South Africa's population increased and counted approximately 62.3 million inhabitants in total, of which the majority inhabited Gauteng, KwaZulu-Natal, and the Western-Eastern Cape. Gauteng (includes Johannesburg) is the smallest province in South Africa, though highly urbanized with a population of over 16 million people according to the estimates. Cape Town, on the other hand, is the largest city in South Africa with nearly 3.43 million inhabitants in the same year, whereas Durban counted 3.12 million citizens. However, looking at cities including municipalities, Johannesburg ranks first. High rate of young population South Africa has a substantial population of young people. In 2024, approximately 34.3 percent of the people were aged 19 years or younger. Those aged 60 or older, on the other hand, made-up over 10 percent of the total population. Distributing South African citizens by marital status, approximately half of the males and females were classified as single in 2021. Furthermore, 29.1 percent of the men were registered as married, whereas nearly 27 percent of the women walked down the aisle. Youth unemployment Youth unemployment fluctuated heavily between 2003 and 2022. In 2003, the unemployment rate stood at 36 percent, followed by a significant increase to 45.5 percent in 2010. However, it fluctuated again and as of 2022, over 51 percent of the youth were registered as unemployed. Furthermore, based on a survey conducted on the worries of South Africans, some 64 percent reported being worried about employment and the job market situation.

Background: To optimally allocate limited health resources in responding to the HIV epidemic, South Africa has undertaken to generate local epidemiological profiles identifying high disease burden areas. Central to achieving this, is the need for readily available quality health data linked to both large and small geographic areas. South Africa has relied on national population-based surveys: the Household HIV Survey and the National Antenatal Sentinel HIV and Syphilis Prevalence Survey (ANC) amongst others for such data for informing policy decisions. However, these surveys are conducted approximately every 2 and 3 years creating a gap in data and evidence required for policy. At subnational levels, timely decisions are required with frequent course corrections in the interim. Routinely collected HIV testing data at public health facilities have the potential to provide this much needed information, as a proxy measure of HIV prevalence in the population, when survey data is not available. The South African District health information system (DHIS) contains aggregated routine health data from public health facilities which is used in this article.Methods: Using spatial interpolation methods we combine three “types” of data: (1) 2015 gridded high-resolution population data, (2) age-structure data as defined in South Africa mid-year population estimates, 2015; and (3) georeferenced health facilities HIV-testing data from DHIS for individuals (15–49 years old) who tested in health care facilities in the district in 2015 to delineate high HIV disease burden areas using density surface of either HIV positivity and/or number of people living with HIV (PLHIV). For validation, we extracted interpolated values at the facility locations and compared with the real observed values calculating the residuals. Lower residuals means the Inverse Weighted Distance (IDW) interpolator provided reliable prediction at unknown locations. Results were adjusted to provincial published HIV estimates and aggregated to municipalities. Uncertainty measures map at municipalities is provided. Data on major cities and roads networks was only included for orientation and better visualization of the high burden areas.Results: Results shows the HIV burden at local municipality level, with high disease burden in municipalities in eThekwini, iLembe and uMngundgudlovu; and around major cities and national routes.Conclusion: The methods provide accurate estimates of the local HIV burden at the municipality level. Areas with high population density have high numbers of PLHIV. The analysis puts into the hand of decision makers a tool that they can use to generate evidence for HIV programming. The method allows decision makers to routinely update and use facility level data in understanding the local epidemic.

Abstract

The Human Sciences Research Council (HSRC) carried out the Migration and Remittances Survey in South Africa for the World Bank in collaboration with the African Development Bank. The primary mandate of the HSRC in this project was to come up with a migration database that includes both immigrants and emigrants. The specific activities included: · A household survey with a view of producing a detailed demographic/economic database of immigrants, emigrants and non migrants · The collation and preparation of a data set based on the survey · The production of basic primary statistics for the analysis of migration and remittance behaviour in South Africa.

Like many other African countries, South Africa lacks reliable census or other data on migrants (immigrants and emigrants), and on flows of resources that accompanies movement of people. This is so because a large proportion of African immigrants are in the country undocumented. A special effort was therefore made to design a household survey that would cover sufficient numbers and proportions of immigrants, and still conform to the principles of probability sampling. The approach that was followed gives a representative picture of migration in 2 provinces, Limpopo and Gauteng, which should be reflective of migration behaviour and its impacts in South Africa.

Geographic coverage

Two provinces: Gauteng and Limpopo

Limpopo is the main corridor for migration from African countries to the north of South Africa while Gauteng is the main port of entry as it has the largest airport in Africa. Gauteng is a destination for internal and international migrants because it has three large metropolitan cities with a great economic potential and reputation for offering employment, accommodations and access to many different opportunities within a distance of 56 km. These two provinces therefore were expected to accommodate most African migrants in South Africa, co-existing with a large host population.

Analysis unit

• Household
• Individual

Universe

The target group consists of households in all communities. The survey will be conducted among metro and non-metro households. Non-metro households include those in: - small towns, - secondary cities, - peri-urban settlements and - deep rural areas. From each selected household, one adult respondent will be selected to participate in the study.

Kind of data

Sample survey data [ssd]

Sampling procedure

Migration data for South Africa are available for 2007 only at the level of local governments or municipalities from the 2007 Census; for smaller areas called "sub places" (SPs) only as recently as the 2001 census, and for the desired EAs only back so far as the Census of 1996. In sum, there was no single source that provided recent data on the five types of migrants of principal interest at the level of the Enumeration Area, which was the area for which data were needed to draw the sample since it was going to be necessary to identify migrant and non-migrant households in the sample areas in order to oversample those with migrants for interview.

In an attempt to overcome the data limitations referred to above, it was necessary to adopt a novel approach to the design of the sample for the World Bank's household migration survey in South Africa, to identify EAs with a high probability of finding immigrants and those with a low probability. This required the combined use of the three sources of data described above. The starting point was the CS 2007 survey, which provided data on migration at a local government level, classifying each local government cluster in terms of migration level, taking into account the types of migrants identified. The researchers then spatially zoomed in from these clusters to the so-called sub-places (SPs) from the 2001 Census to classifying SP clusters by migration level. Finally, the 1996 Census data were used to zoom in even further down to the EA level, using the 1996 census data on migration levels of various typed, to identify the final level of clusters for the survey, namely the spatially small EAs (each typically containing about 200 households, and hence amenable to the listing operation in the field).

A higher score or weight was attached to the 2007 Community Survey municipality-level (MN) data than to the Census 2001 sub-place (SP) data, which in turn was given a greater weight than the 1996 enumerator area (EA) data. The latter was derived exclusively from the Census 1996 EA data, but has then been reallocated to the 2001 EAs proportional to geographical size. Although these weights are purely arbitrary since it was composed from different sources, they give an indication of the relevant importance attached to the different migrant categories. These weighted migrant proportions (secondary strata), therefore constituted the second level of clusters for sampling purposes.

In addition, a system of weighting or scoring the different persons by migrant type was applied to ensure that the likelihood of finding migrants would be optimised. As part of this procedure, recent migrants (who had migrated in the preceding five years) received a higher score than lifetime migrants (who had not migrated during the preceding five years). Similarly, a higher score was attached to international immigrants (both recent and lifetime, who had come to SA from abroad) than to internal migrants (who had only moved within SA's borders). A greater weight also applied to inter-provincial (internal) than to intra-provincial migrants (who only moved within the same South African province).

How the three data sources were combined to provide overall scores for EA can be briefly described. First, in each of the two provinces, all local government units were given migration scores according to the numbers or relative proportions of the population classified in the various categories of migrants (with non-migrants given a score of 1.0. Migrants were assigned higher scores according to their priority, with international migrants given higher scores than internal migrants and recent migrants higher scores than lifetime migrants. Then within the local governments, sub-places were assigned scores assigned on the basis of inter vs. intra-provincial migrants using the 2001 census data. Each SP area in a local government was thus assigned a value which was the product of its local government score (the same for all SPs in the local government) and its own SP score. The third and final stage was to develop relative migration scores for all the EAs from the 1996 census by similarly weighting the proportions of migrants (and non-migrants, assigned always 1.0) of each type. The the final migration score for an EA is the product of its own EA score from 1996, the SP score of which it is a part (assigned to all the EAs within the SP), and the local government score from the 2007 survey.

Based on all the above principles the set of weights or scores was developed.

In sum, we multiplied the proportion of populations of each migrant type, or their incidence, by the appropriate final corresponding EA scores for persons of each type in the EA (based on multiplying the three weights together), to obtain the overall score for each EA. This takes into account the distribution of persons in the EA according to migration status in 1996, the SP score of the EA in 2001, and the local government score (in which the EA is located) from 2007. Finally, all EAs in each province were then classified into quartiles, prior to sampling from the quartiles.

From the EAs so classified, the sampling took the form of selecting EAs, i.e., primary sampling units (PSUs, which in this case are also Ultimate Sampling Units, since this is a single stage sample), according to their classification into quartiles. The proportions selected from each quartile are based on the range of EA-level scores which are assumed to reflect weighted probabilities of finding desired migrants in each EA. To enhance the likelihood of finding migrants, much higher proportions of EAs were selected into the sample from the quartiles with the higher scores compared to the lower scores (disproportionate sampling). The decision on the most appropriate categorisations was informed by the observed migration levels in the two provinces of the study area during 2007, 2001 and 1996, analysed at the lowest spatial level for which migration data was available in each case.

Because of the differences in their characteristics it was decided that the provinces of Gauteng and Limpopo should each be regarded as an explicit stratum for sampling purposes. These two provinces therefore represented the primary explicit strata. It was decided to select an equal number of EAs from these two primary strata.

The migration-level categories referred to above were treated as secondary explicit strata to ensure optimal coverage of each in the sample. The distribution of migration levels was then used to draw EAs in such a way that greater preference could be given to areas with higher proportions of migrants in general, but especially immigrants (note the relative scores assigned to each type of person above). The proportion of EAs selected into the sample from the quartiles draws upon the relative mean weighted migrant scores (referred to as proportions) found below the table, but this is a coincidence and not necessary, as any disproportionate sampling of EAs from the quartiles could be done, since it would be rectified in the weighting at the end for the analysis.

The resultant proportions of migrants then led to the following proportional allocation of sampled EAs (Quartile 1: 5 per cent (instead of 25% as in an equal distribution), Quartile 2: 15 per cent (instead

Nigeria has the largest population in Africa. As of 2025, the country counted over 237.5 million individuals, whereas Ethiopia, which ranked second, has around 135.5 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 118.4 million people. In terms of inhabitants per square kilometer, Nigeria only ranked seventh, while Mauritius had the highest population density on the whole African continent in 2023. The fastest-growing world region Africa is the second most populous continent in the world, after Asia. Nevertheless, Africa records the highest growth rate worldwide, with figures rising by over two percent every year. In some countries, such as Chad, South Sudan, Somalia, and the Central African Republic, the population increase peaks at over 3.4 percent. With so many births, Africa is also the youngest continent in the world. However, this coincides with a low life expectancy. African cities on the rise The last decades have seen high urbanization rates in Asia, mainly in China and India. African cities are also growing at large rates. Indeed, the continent has three megacities and is expected to add four more by 2050. Furthermore, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria, by 2035.

The South African data center construction market is projected to grow at a CAGR of 10.27% during the forecast period (2025-2033), reaching a market size of $1.31 million by 2033. The growth of the market is attributed to the increasing demand for data storage and processing services, driven by the adoption of cloud computing and big data analytics. Moreover, the presence of several major financial institutions and telecommunication companies in the country has further fueled the demand for data center infrastructure. The major drivers of the market include the rising demand for cloud computing, big data analytics, and artificial intelligence applications, which require significant data storage and processing capabilities. Additionally, the increasing need for data security and compliance has led to the adoption of tier 3 and tier 4 data centers, driving the growth of the market. However, the market also faces challenges such as rising construction costs and the shortage of skilled professionals, which may restrain its growth to some extent. Recent developments include: February 2024: Equinix Inc. decided to invest USD 390 million in Africa over the next five years. The investment will focus on constructing new data centers and bolstering its existing operations, primarily in South Africa and the western regions of the continent.January 2023: Africa Data Centres, a subsidiary of Cassava Technologies, a prominent pan-African technology conglomerate, revealed plans for its second data center in Cape Town. Positioned in the northern region of the city, this new facility is set to accommodate an IT load of 20 MW. With construction already in progress, the center is slated for completion and operational status by 2024.. Key drivers for this market are: 4., Government Support for Data Center Development4.; Advent of Cloud, Big Data, and IoT Technologies Driving Investments. Potential restraints include: 4., Government Support for Data Center Development4.; Advent of Cloud, Big Data, and IoT Technologies Driving Investments. Notable trends are: Tier 3 Data Centers Holding Significant Market Share.

Nigeria has the largest population in Africa. As of 2024, the country counted over 232.6 million individuals, whereas Ethiopia, which ranked second, has around 132 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 116 million people. In terms of inhabitants per square kilometer, Nigeria only ranks seventh, while Mauritius has the highest population density on the whole African continent. The fastest-growing world region Africa is the second most populous continent in the world, after Asia. Nevertheless, Africa records the highest growth rate worldwide, with figures rising by over two percent every year. In some countries, such as Niger, the Democratic Republic of Congo, and Chad, the population increase peaks at over three percent. With so many births, Africa is also the youngest continent in the world. However, this coincides with a low life expectancy. African cities on the rise The last decades have seen high urbanization rates in Asia, mainly in China and India. However, African cities are currently growing at larger rates. Indeed, most of the fastest-growing cities in the world are located in Sub-Saharan Africa. Gwagwalada, in Nigeria, and Kabinda, in the Democratic Republic of the Congo, ranked first worldwide. By 2035, instead, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria.

EGYPT @ CROCODILE DELIGHT IN BIODIVERSITY HERITAGE SITE OF AFRICA IS AFRICAN SAFARI DELIGHTJewel and Jenita mol Mango plant for this International Day of Biological & Biodiversity on May 22 ,THE KING CROCODILE OF EGYPT LIVED IN THE NILE RIVER BIODIVERSITY SITES EGYPT IS CROCODILE GOD'S OWN COUNTRYEGYPT BIODIVERSITY AND ECOSYSTEM IS MAKING THE COUNTRY A CROCODILE GOD'S OWN COUNTRY, NILE CROCODILE SITES & CROCODILE SPACE ECOSYSTEM IS THE E@ CROCODILE IN THE BIODIVERSITY HERITAGE SITE OF AFRICAN CONTINENT WHERE E IS EGYPT COUNTRYTHE E@ CROCODILE IN THE BIODIVERSITY HERITAGE SITE OF AFRICAN CONTINENT WHERE E IS EGYPT COUNTRY EGYPT IS CROCODILE GOD'S OWN COUNTRY IS THE STORY - E@ CROCODILE IN THE BIODIVERSITY HERITAGE SITE & ECOSYSTEM WHERE E @ IS EGYPT COUNTRYSOBEK CROCODILE THE KING OF NILE RIVER & NILE RIVER THE GIFT OF EGYPT BIODIVERSITY & ECOSYSTEM HAD KOM OMBO TEMPLE, CROCODILE CITY ARISINOEThe NUBIANS , NILOTIC, FELLAH, URBAN People in the Egyptian Community Worshiped Crocodile in the the city of Faiyum in Egypt is known as the "Crocodile City" because it was the center of the ancient Egyptian crocodile god, Sobek. The city is located in the Faiyum Oasis, which was a major center for the worship of Sobek and in temple. The crocodile cult at Fayoum in Egypt, centered around the city of Crocodilopolis (Arsinoe), further emphasizes the cultural importance of these creatures in ancient Egypt. Crocodiles were regarded as sacred beings, with temples and rituals dedicated to their worship . E @ Crocodile Biodiversity & Ecosystem where E is ENTRY OF TWO CROCODILE TRESPASSERS IN CROCODILE TERRITORY The Temple of Kom Ombo in Egypt is known as the Crocodile Temple because it's dedicated to Sobek, the crocodile god. The temple is also dedicated to Haroeris, the falcon god. Crocodile mummies are found in many Egyptian tombs, and were an important part of ancient Egyptian religion and rituals. The mummies were created by crocodile priests who wrapped the crocodiles in the same material and care as human mummies. These ancient crocodile mummies are so well-preserved, they almost look alive. Archaeologists have unearthed the remains of 10 mummified crocodiles from an Egyptian tomb that are so well-preserved, one scientist said it's "like almost a real crocodile just lying there in front of you is making EGYPT BIODIVERSITY AND ECOSYSTEM A CROCODILE GOD'S COUNTRY AND THIS CROCODILE FAMILY WILL OVERCOME HUMANS LIKE THEY HAD OVERCOME DINOSAURS IN FUTURE DEPEND ON THE CONSERVATION & PROTECTION OF CROCODILE NOW DONE BY COUNTRIES ACROSS THE WORLDThe Divine God Animals of Egypt are Sobek, crocodile-headed god of the Nile; Sekhmet, leonine goddess of war; Anubis, jackal god of the underworld; and Hathor, mother goddess with a cow's horns , Bastet was the goddess of protection, pleasure, and the bringer of good health. She had the head of a cat and a slender female body, Seth beast not a animals . Where Sobek was a crocodile-headed god with several important connotations, including his association with the colour green. The worship of Sobek peaked in the Middle Kingdom (c. 2055 -1650 BC), whose name is seen lent to several Twelfth and Thirteenth Dynasty Pharaohs such as Sobeknefru and Sobekhotep I –IV. Nile crocodiles is associated with the sacred and Nile crocodiles and is often represented as a crocodile-headed humanoidSUMMARY- EGYPT IS CROCODILE GOD'S OWN COUNTRY BIODIVERSITY & ECOSYSTEME @ BIODIVERSITY HERITAGE SITE IN AFRICAN CONTINENTTHE E@ CROCODILE IN THE BIODIVERSITY HERITAGE SITE OF AFRICAN CONTINENT WHERE E IS EAST AFRICA THE BEST More International travel to east African safari than the south Africa and west Africa even though Africa is the best for safari Tourist . The National park & animals conservation projects are less in west Africa compared to South Africa and East Africa where the largest number of national parks are in East Africa compared to south Africa and west Africa . In Kenya there is 24 National park , Tanzania there is 22 national parks and in west Africa Zambia there is 21 national park and south Africa there is 20 national parks , in west Africa Ivory coast and Nigeria there is 8 national park each making east Africa the best for safari tourist . In east Africa the infrastructure for tourist is far more better than west and south Africa making east Africa the best as they advertise more than the west . Compared to the land area , the land areas used for conservation is more in east Africa than in west so this make East Africa the best than south and west making East or West East Africa the best where E @Stands for east African tourist safari E @ BIODIVERSITY HERITAGE SITE IN AFRICAN CONTINENT WHERE E IS EAST AFRICAN NILE CROCODILE E @ BIODIVERSITY HERITAGE SITE IN AFRICAN CONTINENT WHERE E IS EAST AFRICAN NILE CROCODILE & SOBEKSPACE ECOSYSTEM & DATABASE TECHNOLOGY ANALYSE AFRICA BIODIVERSITY BY THE E @ NILE CROCODILE HABITAT & THE E @ BIODIVERSITY HERITAGE SITEEGYPT CROCODILE GOD'S OWN COUNTRY BIODIVERSITY & ECOSYSTEMRESEARCHING SPACE ECOSYSTEM FOR E @ BIODIVERSITY HERITAGE SITE (BHS) FOR E @ CROCODILE DIVERSITY , E @ HABITAT DIVERSITY & E @ ECOSYSTEM DIVERSITY IN AFRICA. THE SUSTAINABLE DEVELOPMENT OF SPACE ECOSYSTEM FOR SPACE DATABASE AND TECHNOLOGY WILL DEVELOP THE E @ AFRICAN BIODIVERSITY DATA BASE THAT MONITORS & CONTROL THE E @ BIODIVERSITY HERITAGE SITE (BHS) FOR E @ CROCODILE DIVERSITY , E @ HABITAT DIVERSITY & E @ ECOSYSTEM DIVERSITY IN AFRICASPACE ECOSYSTEM & SPACE DATABASE TECHNOLOGY DEVELOPING THE E @ BIODIVERSITY HERITAGE SITE IS THE CONVERSION OF AFRICA DIVERSE DIGITAL DATA BASE TO AFRICA SPACIAL BIODIVERSITY DATA BASE ECOSYSTEM . The Conversion of Digital to Spacial Maps connecting the Space Ecosystem is a vision of Future like Vision 2050 Developing African countries from Developing to a Developed Country Achieving sustainable development in the field of Climatic change, Energy for all, Food for all, etc .The conversion will shape up the economy of African countries in large scale cultivation, Cultivation of Bare land, Automated Machinery & technology , Saving large quantity of energy and fuel for the future . The Conversion to Spacial ecosystem 3 D maps will develop remote area of land like forest, water ways, water falls where large number of species inhabitant like crocodile and the conservation and reproduction of the habitat is the main aim of many organization like World Wildlife organization is due to Crocodile are important to the ecosystem The World Wildlife organization had many project and one such is E @ Crocodile in the Biodiversity Heritage site where E @ Stands for Infinite Number of Crocodile Projects as e∞ is equal to infinity in which e is constant considering a crocodile and ∞ is variable considering the project .This is because e is a number greater than 1, and when multiplied by itself an infinite number of times, it results in a number that is extremely large. so E @ Crocodile s infinity e∞ , Absolute infinity Ω ω & Infinity series( Σ ) like Crocodile is the beginning and the end in the book of revelation as Crocodile is the earth for million of years from Dinosaurs period to the ancient world E @ Crocodile Biodiversity & Ecosystem where E is Infinity ProjectsINFINITY OF E @CROCODILE IN THE BHS IS THE BEGINNING & END OF THE THINGS WHERE E IS INFINITY OF CROCODILE PROJECT ALL ALONG AFRICA Secret of Art is Infinity - Aaron’s crocodile eat the Egyptian magicians Pharaoh crocodile" make the God the Great by the Crocodile The theme for World Wildlife Day (WWD) 2024 was "Connecting People and Planet: Exploring Digital Innovation in Wildlife Conservation". The day was celebrated on March 3, 2024 . The theme for World Wildlife Day (WWD) 2025 is "Wildlife Conservation Finance: Investing in People and Planet". The theme emphasizes the importance of investing in wildlife to ensure a resilient future for people and the planet.The March 3 and 4 day highlighted the loss of biodiversity and the need for digital innovation in wildlife conservation and that digital conservation and in future this digital conservation is used for raising funds in the projects in 2025 in the Wildlife Conservation Finance: Investing in People and Planet and E @ Crocodile in the Biodiversity Heritage site in the African continent is given below is the digital conservation of crocodile & Planet for year 2024 and 2025 E @ Crocodile Biodiversity & Ecosystem where E is Electronic governance of Crocodile Site in Egypt & AfricaE @ Crocodile in the Biodiversity heritage site where E @ means electronic governance' of African crocodile site is using information and communication technologies (ICTs) (such as Wide Area Networks, the Internet, and mobile computing) at various levels of the government and the public sector and beyond, for the purpose of enhancing governance.MASSACRED IN CROCODILE ISLANDS RAMREE - INDONESIA WORLD WAR 2 THE ART OF WORLD BIODIVERSITY IS PEACE AND NOT CONFLICT - THE ART OF PEACE IS UNITY & NOT SEPARATION ,THE ART OF WAR IS THE WAR THAT IS LAST RESORT FOR PEACE WHEN DIALOGUE & DIPLOMACY FAIL. WAR IS DESTRUCTION, BIODIVERSITY LOSS IS THE HISTORICAL CROCODILES WAR IN THE MANGROVE SWAMPS OF RAMREE ISLANDS. MY HEART WILL GO ON FOR NILE CROCODILE HABITAT- The Message of My Hear will Go on is the is that - I Know my heart will go on" uses the metaphor of the heart continuing to beat in response to strong emotions, like love or fear convey the idea that Emotions remains strong and persistent, even through challenges and separation when in a crocodile encounter In Wild is fear and when in Swimming with Crocodile In 'Cage of Death' In Australian is fun and joy . "We'll stay forever in many way" & reassures that Human and crocodile bond is unbreakable even in the fear emotion while in a crocodile territory . it is one of hope and resilience in the face of loss and adversity. it is the ability to withstand adversity and bounce back from difficult life

ZA：最大城市人口：占城镇人口百分比在12-01-2017达26.327%，相较于12-01-2016的26.291%有所增长。ZA：最大城市人口：占城镇人口百分比数据按年更新，12-01-1960至12-01-2017期间平均值为23.218%，共58份观测结果。该数据的历史最高值出现于12-01-2017，达26.327%，而历史最低值则出现于12-01-1991，为18.806%。CEIC提供的ZA：最大城市人口：占城镇人口百分比数据处于定期更新的状态，数据来源于World Bank，数据归类于Global Database的南非 – 表 ZA.世界银行：人口和城市化进程统计。

In 2023, according to data provided by StartupBlink, the best city for startups in Africa was Lagos, in Nigeria, with a total score of **** points. The largest city in Africa and an important financial hub for Nigeria and the whole continent, Lagos ranked **** among 1,000 cities worldwide. Cairo, in Egypt, and Cape Town, in South Africa, followed as leading cities for startups on the African continent.