Mobile Map Packages (MMPK’s) can be used in the ESRI Field Maps app (no login required), either by direct download in the Field Maps app or by sideloading from your PC. They can also be used in desktop applications that support MMPK’s such as ArcGIS Pro, and ArcGIS Navigator. MMPK’s will expire quarterly and have a warning for the user at that time but will still function afterwards. They are updated quarterly to ensure you have the most up to date data possible. These mobile map packages include the following national datasets along with others: Surface Management Agency, Public Land Survey System (PLSS), BLM Recreation Sites, National Conservation Lands, ESRI’s Navigation Basemap and Vector Tile Package. Last updated 20250321. Contact jlzimmer@blm.gov with any questions.

TurtleSAT - Turtle Survey and Analysis Tools - is an mobile app and citizen science mapping tool produced by the 1 Million Turtles Community Conservation program, allowing communities to map the location of freshwater turtles in waterways and wetlands across the country.

Australia's freshwater turtles are under serious threat, and they need our help for survival! Mounting evidence now suggests that many turtle species are declining across vast areas of Australia due to widespread drought, fox predation and human activities. To ensure their survival, important evidence needs to be gathered to find out where turtles live and breed, what the major causes of decline are across Australia, how far they disperse, and whether there are important source populations that help populate other areas.

The app invites users assist by recording where they see turtles, their nests, if they are killed on the road, or any other evidence of turtles like skeletal remains.

The TurtleSAT project is being coordinated by Dr Ricky Spencer at the University of Western Sydney in partnership with the University of Sydney, the University of South Australia, the Field Naturalists Society of South Australia and community groups throughout the Murray River region. The Centre for Invasive Species Solutions and NSW Department of Primary Industries support the project through the FeralScan program and its associated web-mapping technology.

This data set contains true color (RGB) ortho-rectified mosaic tiles, created as a product from the NOAA Integrated Ocean and Coastal Mapping (IOCM) initiative. The source imagery was acquired from 20110217 - 20110217. The images were acquired with an Applanix Digital Sensor System (DSS). The original images were acquired at a higher resolution than the final ortho-rectified mosaic. Ortho-rectified mosaic tiles are an ancillary product of NOAA's Coastal Mapping Program (CMP), created through a wider Integrated Ocean and Coastal Mapping initiative to increase support for multiple uses of the data.

Data are in Geotiff format with associated browse graphic (.jpg) and HIStory (.his) files. Federal Geographic Data Committee metadata is included as .txt and .xml files.

The ground sample distance (GSD) for each pixel is 0.50 m.

Description: This data set contains information on the households that met the inclusion criteria for this study. Information was collected from the primary respondent on themselves and their knowledge of the other household members. For the household survey, 1961 of the 2032 (96.5%) eligible families participated and completed the baseline survey. Abstract: More than two decades after the end of Apartheid, the well-being of South African children is still in a precarious state. An emerging body of research examines the role that poverty and HIV/AIDS play in household functioning, parental illness and death, children's adverse experiences and children's health, education and psychosocial development (e.g. Birdthistle, 2004, Foster & Williamson, 2000; Richter, 2004; Williamson, 2000). However, many urgent scientific and policy questions remain. These include: What are the separate and combined effects of household poverty, parental illness and death on household functioning and children's adverse life experiences and well-being? How do communities, households and children cope with the dual crises of poverty and HIV/AIDS? Who is able to access government-funded grants and services and what is the impact of these on household conditions, children's adverse experiences and children's well-being? How does the impact of grants and services on households and children vary as a function of community factors? The overarching goals of "Sibhekelela izingane zethu" or "We look out for our children" are to generate usable knowledge about how South African children are being affected by the co-occurring adversities caused by household poverty and HIV/AIDS, and assess the reach and influence of current government-funded grants and services. Data was collected from 24 communities defined by careful GIS mapping. All households were visited and those with a child between the ages of 7 and 10 years enrolled. Data was collected on all household members, the child's Caregiver and the child. More specifically, the major themes explored in the Household Survey were: Demographics Education Health Social welfare and service access Employment Positive and negative household shocks Living environment and food security Community participation and cohesion Face-to-face interview Psychological measurements 12 571 households within the demarked 24 school community boundaries. Study participants (children and their households) were systematically sampled from 24 communities in the Msunduzi municipality in KwaZulu-Natal (KZN), South Africa. This area is characterized by high rates of both household poverty and HIV/AIDS. This area was chosen for its general demographic representativeness of South Africa, although its population is 95% Zulu. Each community was selected based upon the presence of a school serving 7-11-year-old children, and was demarcated using a combination of information about the school’s catchment area, geographic boundaries identified by aerial maps and ethnographic mapping including transport routes to school and work for adults in the area. The boundary created from these sources of information was then merged with a physical 1 km radius in rural and 500 meter radius in urban school communities to generate the final school boundary. High resolution aerial mapping was used to identify and enumerate all households within each geographically bounded community. Depending on visiting point density, one of three strategies was followed to enumerate households. In communities with more than 600 potential visiting points, twenty households were randomly selected from each community for use as cluster nodes, around each of which a cluster of the nearest 30 households (including the cluster node) was selected. In communities with 450-599 potential visiting points, 20 clusters of 30 visiting points was not possible. To accommodate the reduced number of visiting points, as many cluster nodes as would allow cluster of 30 visiting points per cluster were randomly chosen and then the nearest 30 household (including the cluster node) selected. In communities with 450 or fewer visiting points, no cluster nodes were chosen and all visiting points selected for enumeration. All selected households were screened for eligibility in the study. Eligible households (defined as those which served as primary residences for at least one child aged 7-11 years were recruited to the study. If more than one eligible child was found living in the household, a kish grid was used to select the focal child. This process was repeated until all selected visiting points in the school community had been enumerated. A total of 1,961 households were recruited into the study. Following a consent process, the household head or a person who viewed themselves as a delegate of the household head completed a face-to-face questionnaire interview about the household conducted in isiZulu. Interviews were conducted by trained Zulu-speaking interviewers. A team of 8 interviewers was supervised in the field by a team coordinator who checked all submitted paper work and resolved any queries that arose in the field. At a later appointment, following an additional consent process, the primary caregiver of the 7-11-year-old focal child in each household completed a face-to-face questionnaire interview about himself or herself and about the child. In approximately 85% of households, the caregiver was the same person who completed the household survey. At a subsequent appointment, following an additional consent process, the focal child completed both a face-to-face questionnaire interview and a series of cognitive assessments. These assessments were conducted either at the child's school or at the child's home after school and on school holidays. All survey responses were recorded electronically on mobile phones. The commercially available Mobenzi Researcher mobile survey software and data management portal were used (www.clyral.com). Mobenzi Researcher is a Java 2 Micro Edition (J2Me) application and provides full survey functionality, including the ability to create various question types, mark fields as mandatory and intelligently manage survey branching. Respondents were compensated for their time with a food parcel to the value of R30 ($5) at the initial household interview. The child was provided with a small packet of snacks during their interview and psychometric assessment.

Anthropometrics Face-to-face interview Psychological measurements 12 571 households within the demarked 24 school community boundaries. Study participants (children and their households) were systematically sampled from 24 communities in the Msunduzi municipality in KwaZulu-Natal (KZN), South Africa. This area is characterized by high rates of both household poverty and HIV/AIDS. This area was chosen for its general demographic representativeness of South Africa, although its population is 95% Zulu. Each community was selected based upon the presence of a school serving 7-11-year-old children, and was demarcated using a combination of information about the school’s catchment area, geographic boundaries identified by aerial maps and ethnographic mapping including transport routes to school and work for adults in the area. The boundary created from these sources of information was then merged with a physical 1 km radius in rural and 500 meter radius in urban school communities to generate the final school boundary. High resolution aerial mapping was used to identify and enumerate all households within each geographically bounded community. Depending on visiting point density, one of three strategies was followed to enumerate households. In communities with more than 600 potential visiting points, twenty households were randomly selected from each community for use as cluster nodes, around each of which a cluster of the nearest 30 households (including the cluster node) was selected. In communities with 450-599 potential visiting points, 20 clusters of 30 visiting points was not possible. To accommodate the reduced number of visiting points, as many cluster nodes as would allow cluster of 30 visiting points per cluster were randomly chosen and then the nearest 30 household (including the cluster node) selected. In communities with 450 or fewer visiting points, no cluster nodes were chosen and all visiting points selected for enumeration. All selected households were screened for eligibility in the study. Eligible households (defined as those which served as primary residences for at least one child aged 7-11 years were recruited to the study. If more than one eligible child was found living in the household, a kish grid was used to select the focal child. This process was repeated until all selected visiting points in the school community had been enumerated. A total of 1,961 households were recruited into the study. Following a consent process, the household head or a person who viewed themselves as a delegate of the household head completed a face-to-face questionnaire interview about the household conducted in isiZulu. Interviews were conducted by trained Zulu-speaking interviewers. A team of 8 interviewers was supervised in the field by a team coordinator who checked all submitted paper work and resolved any queries that arose in the field. At a later appointment, following an additional consent process, the primary caregiver of the 7-11-year-old focal child in each household completed a face-to-face questionnaire interview about himself or herself and about the child. In approximately 85% of households, the caregiver was the same person who completed the household survey. At a subsequent appointment, following an additional consent process, the focal child completed both a face-to-face questionnaire interview and a series of cognitive assessments. These assessments were conducted either at the child's school or at the child's home after school and on school holidays. All survey responses were recorded electronically on mobile phones. The commercially available Mobenzi Researcher mobile survey software and data management portal were used (www.clyral.com). Mobenzi Researcher is a Java 2 Micro Edition (J2Me) application and provides full survey functionality, including the ability to create various question types, mark fields as mandatory and intelligently manage survey branching. Respondents were compensated for their time with a food parcel to the value of R30 ($5) at the initial household interview. The child was provided with a small packet of snacks during their interview and psychometric assessment.