Albania Rural Population data was reported at 971,992.000 Person in 2023. This records a decrease from the previous number of 1,005,551.000 Person for 2022. Albania Rural Population data is updated yearly, averaging 1,573,809.500 Person from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 2,089,320.000 Person in 1990 and a record low of 971,992.000 Person in 2023. Albania Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Population and Urbanization Statistics. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population. Aggregation of urban and rural population may not add up to total population because of different country coverages.;World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.;Sum;

Summary File 4 (SF 4) from the United States 2000 Census contains the sample data, which is the information compiled from the questions asked of a sample of all people and housing units. Population items include basic population totals: urban and rural, households and families, marital status, grandparents as caregivers, language and ability to speak English, ancestry, place of birth, citizenship status, year of entry, migration, place of work, journey to work (commuting), school enrollment and educational attainment, veteran status, disability, employment status, industry, occupation, class of worker, income, and poverty status. Housing items include basic housing totals: urban and rural, number of rooms, number of bedrooms, year moved into unit, household size and occupants per room, units in structure, year structure built, heating fuel, telephone service, plumbing and kitchen facilities, vehicles available, value of home, monthly rent, and shelter costs. In Summary File 4, the sample data are presented in 213 population tables (matrices) and 110 housing tables, identified with "PCT" and "HCT" respectively. Each table is iterated for 336 population groups: the total population, 132 race groups, 78 American Indian and Alaska Native tribe categories (reflecting 39 individual tribes), 39 Hispanic or Latino groups, and 86 ancestry groups. The presentation of SF4 tables for any of the 336 population groups is subject to a population threshold. That is, if there are fewer than 100 people (100-percent count) in a specific population group in a specific geographic area, and there are fewer than 50 unweighted cases, their population and housing characteristics data are not available for that geographic area in SF4. For the ancestry iterations, only the 50 unweighted cases test can be performed. See Appendix H: Characteristic Iterations, for a complete list of characteristic iterations.

The statistic depicts a comparison of the number of wireless broadband providers available in urban and rural areas of Alabama. In 95.2 percent of the urban areas in Alabama, there are at least 2 providers available.

Albania Improved Water Source: Rural: % of Rural Population with Access data was reported at 95.200 % in 2015. This stayed constant from the previous number of 95.200 % for 2014. Albania Improved Water Source: Rural: % of Rural Population with Access data is updated yearly, averaging 93.900 % from Dec 1994 (Median) to 2015, with 22 observations. The data reached an all-time high of 95.200 % in 2015 and a record low of 93.000 % in 1998. Albania Improved Water Source: Rural: % of Rural Population with Access data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Social: Health Statistics. Access to an improved water source, rural, refers to the percentage of the rural population using an improved drinking water source. The improved drinking water source includes piped water on premises (piped household water connection located inside the user’s dwelling, plot or yard), and other improved drinking water sources (public taps or standpipes, tube wells or boreholes, protected dug wells, protected springs, and rainwater collection).; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/).; Weighted average;

Graph and download economic data for U.S. Granted Utility Patents Originating in Non Metro/Micropolitan Statistical Areas in Alabama (PATENTCBSA900901) from 2000 to 2015 about rural, patent granted, patents, intellectual property, origination, AL, and USA.

Summary File 3 contains sample data, which is the information compiled from the questions asked of a sample of all people and housing units in the United States. Population items include basic population totals as well as counts for the following characteristics: urban and rural, households and families, marital status, grandparents as caregivers, language and ability to speak English, ancestry, place of birth, citizenship status, year of entry, migration, place of work, journey to work (commuting), school enrollment and educational attainment, veteran status, disability, employment status, industry, occupation, class of worker, income, and poverty status. Housing items include basic housing totals and counts for urban and rural, number of rooms, number of bedrooms, year moved into unit, household size and occupants per room, units in structure, year structure built, heating fuel, telephone service, plumbing and kitchen facilities, vehicles available, value of home, and monthly rent and shelter costs. The Summary File 3 population tables are identified with a "P" prefix and the housing tables are identified with an "H," followed by a sequential number. The "P" and "H" tables are shown for the block group and higher level geography, while the "PCT" and "HCT" tables are shown for the census tract and higher level geography. There are 16 "P" tables, 15 "PCT" tables, and 20 "HCT" tables that bear an alphabetic suffix on the table number, indicating that they are repeated for nine major race and Hispanic or Latino groups. There are 484 population tables and 329 housing tables for a total of 813 unique tables. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR13342.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The statistic depicts the availability of certain download speeds in rural as compared to urban areas of Alabama. In 100 percent of the urban areas, a download speed of 786 kbps was available in 2011.

Albania Rural Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data was reported at 2.784 % in 2015. This records an increase from the previous number of 2.701 % for 2000. Albania Rural Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data is updated yearly, averaging 2.701 % from Dec 1990 (Median) to 2015, with 3 observations. The data reached an all-time high of 2.784 % in 2015 and a record low of 2.648 % in 1990. Albania Rural Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Environmental: Land Use, Protected Areas and National Wealth. Rural population below 5m is the percentage of the total population, living in areas where the elevation is 5 meters or less.;Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.;Weighted average;

This survey was conducted to obtain baseline data as part of an evaluation of the Southern Rural Access Program (SRAP), a Robert Wood Johnson Foundation initiative to improve access to health care services in select rural areas of eight states: Alabama, Arkansas, Georgia, Louisiana, Mississippi, South Carolina, West Virginia, and eastern Texas. Within these states, 150 nonmetropolitan counties were selected for SRAP participation based on perceived local health needs, willingness of local organizations and providers to partner with the program's efforts, and prospects for long-term program viability. The SRAP counties demonstrated greater socioeconomic need than other nonmetropolitan counties in the eight states: approximately 50 percent higher poverty rates, 30 percent higher unemployment, and 40 percent greater minority proportions. Topics covered by the survey include health status, health insurance coverage, health care access challenges, confidence in and satisfaction with health care, and utilization of outpatient services including specific disease prevention services. Personal demographic characteristics collected by the survey include age, sex, race, Hispanic origin, primary language spoken at home, marital status, educational achievement, work status, income, number of children at home, and the state, county, town, and ZIP code of residence. The data file also contains county-level and Primary Care Service Area (PCSA)-level contextual variables from external sources, such as population size, population composition by race, number of hospital beds, and variables indicating the presence of short term hospitals and Federally Qualified Health Centers.

Alabama faces major challenges that affect Black, rural, and low-income communities. This story map explains these problems and their impacts.Alabama's Political LandscapeBlack voters in Alabama are underrepresented because of unfair voting districts. These districts are drawn to weaken their political power. Despite making up a large part of the population, Black communities have limited representation in government.The Effect of Climate ChangeClimate change is causing more flooding in Alabama. In rural areas, old septic tanks fail during heavy rains, polluting the water and creating health problems. Many communities do not have the resources to fix these issues or prepare for future problems.Digital DivideMany people in Alabama cannot access the internet because broadband is too expensive or unavailable. This is especially true in rural areas. Without the internet, families struggle to find jobs, access education, or get basic information. Public libraries are often the only option, but they cannot meet the growing need.Environmental JusticePollution and environmental hazards in Alabama often affect Black and low-income communities the most. Factories and landfills are built near their homes, making the air and water unsafe. Flooding from poor drainage systems damages homes and neighborhoods, with little help for recovery.Communities in Alabama are working hard to solve these problems and create a better future for everyone.

Hearing loss is a major public health concern due to its negative association with emotional well-being, cognition, and physical ailments, such as diabetes. Access to audiologists and otolaryngologists in many regions across the US is poor or extremely limited. Rural populations are older, less educated, and have lower household incomes compared to populations in metropolitan areas. Also, with increasing age adults experience greater rates of hearing loss. Fortunately, the 2022 FDA Final Rule for Over-the-Counter Hearing Aids (OTC HAs) could revolutionize assess to hearing aids and hearing healthcare by allowing adults with perceived mild-to-moderate hearing loss to purchase these devices over the counter, without medical clearance or care from an audiologist. Pharmacies located in rural areas now have the option to provide OTC HAs, something previously not possible. Currently, however, there are no established guidelines for effective provision of these devices in pharmacies located in rural communities. Educating pharmacy technicians to provide basic hearing healthcare related to OTC HAs use could address a critical need and create a new care delivery model to ensure sustainable, long-term access to hearing healthcare. The long-term goal of this study is to create a sustainable interprofessional collaborative between audiologists and pharmacists for the development of a hearing healthcare model that improves access and affordability of care in rural regions across the country. The specific aims are to 1) Determine an effective approach for educating pharmacy technicians for the provision of OTC HAs in rural community pharmacies, and 2) Identify satisfaction of care provided by pharmacy technicians and initial performance with OTC HAs in adults with hearing loss living in rural communities. A stepped wedged clinical trial design will be used to study the effectiveness of a comprehensive educational training program for pharmacy technicians. Technicians from rural Alabama and Mississippi, placed within four different clusters, will participate in a multimodal training program for the purpose of developing basic clinical skills to assist adults with perceived mild-to-moderate hearing loss. Additionally, adults with hearing loss who receive clinical services from trained pharmacy technicians will be asked to report on the care they received and benefit from their OTC HAs. The central hypotheses are a) that pharmacy technician training will result in greater understanding of hearing healthcare concepts compared to no training, and b) the training will lead to successful provision of basic hearing healthcare to adults with hearing loss in rural communities. The expected outcome of this project will be the establishment of a multimodal education program, leveraging the increased access of OTC HAs, to support those with hearing loss in rural pharmacies across the county. The ability of pharmacy technicians to provide this support will dramatically increase the availability of hearing services in rural communities, which will positively impact the quality of life for those with hearing loss.

Albania Improved Sanitation Facilities: Rural: % of Rural Population with Access data was reported at 90.200 % in 2015. This stayed constant from the previous number of 90.200 % for 2014. Albania Improved Sanitation Facilities: Rural: % of Rural Population with Access data is updated yearly, averaging 77.950 % from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 90.200 % in 2015 and a record low of 68.700 % in 1994. Albania Improved Sanitation Facilities: Rural: % of Rural Population with Access data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Social: Health Statistics. Access to improved sanitation facilities, rural, refers to the percentage of the rural population using improved sanitation facilities. Improved sanitation facilities are likely to ensure hygienic separation of human excreta from human contact. They include flush/pour flush (to piped sewer system, septic tank, pit latrine), ventilated improved pit (VIP) latrine, pit latrine with slab, and composting toilet.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/).; Weighted average;

Albania Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data was reported at 15.300 % in 2012. This records an increase from the previous number of 14.600 % for 2008. Albania Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data is updated yearly, averaging 19.750 % from Dec 2002 (Median) to 2012, with 4 observations. The data reached an all-time high of 29.600 % in 2002 and a record low of 14.600 % in 2008. Albania Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Social: Poverty and Inequality. Rural poverty headcount ratio is the percentage of the rural population living below the national poverty lines.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

Albania Urban Population data was reported at 1,773,980.000 Person in 2023. This records an increase from the previous number of 1,772,138.000 Person for 2022. Albania Urban Population data is updated yearly, averaging 1,204,201.000 Person from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 1,773,980.000 Person in 2023 and a record low of 493,982.000 Person in 1960. Albania Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Population and Urbanization Statistics. Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages.;World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.;Sum;

Albania Rural Land Area data was reported at 27,331.602 sq km in 2015. This records a decrease from the previous number of 27,369.241 sq km for 2000. Albania Rural Land Area data is updated yearly, averaging 27,369.241 sq km from Dec 1990 (Median) to 2015, with 3 observations. The data reached an all-time high of 27,562.435 sq km in 1990 and a record low of 27,331.602 sq km in 2015. Albania Rural Land Area data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Environmental: Land Use, Protected Areas and National Wealth. Rural land area in square kilometers, derived from urban extent grids which distinguish urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights. Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons.;Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.;Sum;

Variations in any telehealth use by race/ethnicity, RUCA, zip-code level poverty & broadband access among Alabama pediatric Medicaid enrollees.

Albania Rural Land Area Where Elevation is Below 5 Meters: % of Total Land Area data was reported at 3.520 % in 2015. This records a decrease from the previous number of 3.542 % for 2000. Albania Rural Land Area Where Elevation is Below 5 Meters: % of Total Land Area data is updated yearly, averaging 3.542 % from Dec 1990 (Median) to 2015, with 3 observations. The data reached an all-time high of 3.571 % in 1990 and a record low of 3.520 % in 2015. Albania Rural Land Area Where Elevation is Below 5 Meters: % of Total Land Area data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Environmental: Land Use, Protected Areas and National Wealth. Rural land area below 5m is the percentage of total land where the rural land elevation is 5 meters or less.;Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.;Weighted average;

Cavity-nesting birds are a diverse and charismatic community, with a common need for tree cavities that makes them vulnerable to land management by humans. However, little research has formally integrated human social aspects into management recommendations for the conservation of cavity-nesting birds. In agroecosystems, people's management decisions modify and define the habitat availability for native cavity-nesting species. These behaviors during adulthood are related to people's worldviews and are shaped, in part, by childhood experiences. On-going forest loss may reduce opportunities for children to interact with and learn from cavity-nesting birds and their habitats. We used a social-ecological framework to assess rural children's knowledge and representations of native cavity-nesting birds and their habitats in agroecosystems of the threatened Atlantic Forest of Argentina. We employed “freelists” and "draw-and-explain" strategies with 235 children from 19 rural schools, and then compared results with a 4-year dataset of trees (n = 328) and tree-cavity nests (n = 164) in the same study area. Children listed a high diversity (93 taxa) of native cavity-nesting birds, especially parrots (Psittacidae), toucans (Ramphastidae), and woodpeckers (Picidae), which they mostly recognized as cavity-nesters. However, children drew agricultural landscapes with few of the habitat features that these birds require (e.g., tree cavities, native forest). Exotic trees were overrepresented in drawings (40% of mentions) compared to our field dataset of nests (10%) and trees on farms (15%). Although children mentioned and depicted a high diversity of native cavity-nesting birds, our results may reveal a problematic extinction of experience regarding how these birds interact with their habitat. To strengthen children's contextualized knowledge and promote their long-term commitment to the conservation of cavity-nesting species, we recommend fostering meaningful experiences for children to interact with native cavity-nesting birds and recognize their habitat needs. A version of this article translated into Spanish is available in the Supplementary Material 1. Methods Study area and socioecological context We worked in high altitude terrain within the department of San Pedro, Misiones province (26° 36'S, 54° 01'W; 500-700 m a.s.l., 1200-1400 mm annual rainfall). The study area encompassed much of the remaining extent of Araucaria mixed rainforest in Argentina. This forest is composed of >100 tree species, including Nectandra spp. and Ocotea spp. (laureles), Balfourodendron riedalianum (guatambú) and Araucaria angustifolia (Paraná pine), a critically endangered species (Cabrera 1976, Kershaw and Wagstaff 2001, Thomas 2013). The study area covers two Important Bird Areas: San Pedro (AICA AR123) and Cruce Caballero Provincial Park (AICA AR122; Bodrati and Cockle 2005, Bodrati et al. 2005, Birdlife International 2019). Here, researchers have recorded at least 75 bird species in 21 families that are known or strongly suspected to nest in tree cavities (Bonaparte 2024). Twenty-four of these species are endemic to the Atlantic Forest and seven are internationally threatened or near-threatened. In well-preserved Atlantic Forest, many cavity-nesting species select cavities in large, live, native trees for nesting (Cockle et al. 2011). However, in family agroecosystems, dead trees with cavities excavated by woodpeckers become increasingly important to the cavity-nesting community, probably because they replace the resource of large native trees with decay-formed cavities that are scarce in agroecosystems (Bonaparte et al. 2020). The study area encompassed both public and private lands and comprised a mosaic of small and medium-sized family farms (mean ± SD = 36 ± 24 ha). This mosaic is characterized by patches and corridors of forest, as well as open paddocks, annual and perennial plantations, and both native and exotic tree plantations, interspersed with three provincial parks that have varying histories of selective logging and other land uses (Varns 2012). Scattered native and exotic trees are common in plantations, in pastures, and around residential areas; provide diverse ecosystem services to agricultural families; and constitute important habitat elements for many cavity-nesting bird species (Bonaparte et al. 2020). Traditionally, people that live and farm in rural areas of Misiones call themselves "colonos", and the rural areas they inhabit are referred to as "colonia". The “colono” families have varied origins (many are immigrants from Europe, Brazil, or Paraguay). In many cases, they arrived in Misiones during the 20th century with permits to occupy small plots on fiscal lands or as occupants of private lands. In our study area, 67% of the human population resides in rural areas (IPEC 2015) and their main productive activity is family agriculture, with no salaried labor (or little when it exists) and low accumulation potential (Baranger et al. 2008). Their production may be destined for family consumption, informal sales, and industry-oriented sales (Furlán et al. 2015). Study design and participants There are some difficulties in assessing children's ideas because they may lack the vocabulary they need to express themselves, or because they are sometimes shy and it is difficult for an unfamiliar person to access their opinion (Sullivan et al. 2018). However, there are several tools adapted for children of different ages that help researchers understand how they see and what they know about the landscape around them. A widely used tool in ethnobiology is the "freelisting" method, hereafter referred to as freelists. This method highlights elements within a given domain that are locally important or significant to respondents (Puri 2010). From freelist data (see below), researchers can calculate relative salience (a statistic that includes rank and frequency) of items within a given domain across all respondents (Quinlan 2005). Another tool used to assess children's representations and interpretations of their environment is the "draw-and-explain" method (Moseley et al. 2010), which seeks to access, in an easy and familiar way, children's ideas and visual representations of a given place (Barraza and Robottom 2008, Franquesa-Soler and Serio-Silva 2017). The combined assessment of these two activities constitutes a mixed approach that allowed us to obtain quantitative and qualitative information about children's knowledge, observations of their environment, and the most salient, important, and familiar elements of their surroundings. In this study we used a mixed methods approach composed of two steps. The first step consisted of two independent activities, specially adapted for rural students in the last three grades of formal primary education in Argentina (10 to 13 years of age). The activities developed with the participant students consisted of a freelisting method (Puri 2010) and a drawing activity (“draw-and-explain” method; Moseley et al. 2010), carried out at school. The second step consisted of comparing the results obtained from the activities with the participants with field data on the cavity-nesting bird community in the area and the characteristics and species of trees they use for nesting (e.g., tree species used as nest trees). Prior to starting the data collection at each school, we held a private, in-person meeting with the principal or teacher in charge. During these 15- to 30-minute meetings, we provided a formal letter describing our objectives, methodology, scope of the study, and expected forms of disseminating results. We then verbally described the details written in the letter, explained the planned activities, and answered questions about the research and logistics. Finally, we verbally requested their free, prior, and informed consent to carry out the activities (Newing 2010), and agreed on a date to visit the school and perform the activities. During April and May 2019, we visited 19 rural schools. Previously, we visited one additional school as a pilot to test and adjust the activities with 18 students; the results of the activities in the pilot school are not presented here. All schools visited were rural public schools with 12 to 120 students each. Participants were 236 students aged 10 to 13 years (mean ± SD = 11.6 ± 0.8; 9% 10 years old, 37% 11 years old, 43% 12 years old, and 11% 13 years old), in the last three years of formal primary education in Argentina. We decided not to gather data on the gender of study participants because our research was not focused on gender-related questions (Radi 2021). Collecting these data a posteriori based on participants' first names leads to misgendering and reinforces harmful cisnormative constructs. We consider the participant group in this study, students of public rural primary schools, to be representative because there are no private schools in the area and we did not observe gender bias in the groups of students attending classes. Description of methodologies at each school Upon arrival in the classroom, we conducted a playful icebreaker and gave a brief introductory talk (Barreau et al. 2016). During the introductory talk, we described in a general but clear way our objectives and the activities we would conduct with the participants, trying not to bias their upcoming answers. We asked the participants to complete the activities individually. Additionally, we informed them that our proposal was neither a school assignment nor mandatory, so they could opt out of the activities if they wished. The first activity we developed at each school was the freelist to assess the salience and knowledge of native birds. For this, we provided each participant with a pencil and a sheet of paper with spaces to write their name, age, and grade, followed by ten numbered rows to write the names of bird species. We instructed the children to complete

Variations in any telehealth use by race/ethnicity, RUCA, zip-code level poverty & broadband access among pediatric Medicaid enrollees, stratification by gender.

Albania Rural Land Area Where Elevation is Below 5 Meters data was reported at 991.338 sq km in 2015. This records a decrease from the previous number of 997.505 sq km for 2000. Albania Rural Land Area Where Elevation is Below 5 Meters data is updated yearly, averaging 997.505 sq km from Dec 1990 (Median) to 2015, with 3 observations. The data reached an all-time high of 1,005.562 sq km in 1990 and a record low of 991.338 sq km in 2015. Albania Rural Land Area Where Elevation is Below 5 Meters data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Environmental: Land Use, Protected Areas and National Wealth. Rural land area below 5m is the total rural land area in square kilometers where the elevation is 5 meters or less.;Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.;Sum;