At NASA they use Geographic Information systems to provide:maps and powerful capabilities to visualise, analyse and interact with big dataFind out more about how they do this in this ArcGIS StoryMap created by NASA in 2020. This StoryMap includes a section on where you can find NASA data.

As GIS and computing technologies advanced rapidly, many indoor space studies began to adopt GIS technology, data models, and analysis methods. However, even with a considerable amount of research on indoor GIS and various indoor systems developed for different applications, there has not been much attention devoted to adopting indoor GIS for the evaluation space usage. Applying indoor GIS for space usage assessment can not only provide a map-based interface for data collection, but also brings spatial analysis and reporting capabilities for this purpose. This study aims to explore best practice of using an indoor GIS platform to assess space usage and design a complete indoor GIS solution to facilitate and streamline the data collection, a management and reporting workflow. The design has a user-friendly interface for data collectors and an automated mechanism to aggregate and visualize the space usage statistics. A case study was carried out at the Purdue University Libraries to assess study space usage. The system is efficient and effective in collecting student counts and activities and generating reports to interested parties in a timely manner. The analysis results of the collected data provide insights into the user preferences in terms of space usage. This study demonstrates the advantages of applying an indoor GIS solution to evaluate space usage as well as providing a framework to design and implement such a system. The system can be easily extended and applied to other buildings for space usage assessment purposes with minimal development efforts.

Open spaces of conservation and recreation interest in Boston, Massachusetts, USA, regardless of ownership.

In an urban setting, parks are created and allocated to serve a broad range of public needs. Accessible green space is an essential way to improve quality of life—providing opportunities from active healthy living to environmental resiliency. Parks strengthen our families and our Neighborhoods, and are designed to creatively bring us together as a community. While parks and green space, as a whole, are appreciated for recreation, open space offers other types of opportunities, such as designed sustainable initiatives, improving the local watershed, expanding green technology or transportation alternatives.A green space inventory, in part with the Albany 2030 Comprehensive Plan, was conducted to identify areas where the community has access to outdoor areas within a quarter-mile (or 15-minute) walking radius. Therefore this GIS inventory does not just include official City-managed parks, but combines lists and observances where other accessible open space exists (such as, pocket parks, community gardens, dog parks, sites of beautification, historic landmarks, road medians, etc.) that offer an opportunity for active recreation, passive enjoyment or sustainability initiatives (i.e., multi-use paths, stormwater management, etc.). The properties are managed jointly by the Department of Recreation and the Department of General Services. The City continues to implement its Park Renovation Plan, a City-funded effort to upgrade play spaces with improved accessibility, playground equipment, and picnic areas for people of all ages and abilities, in compliance with the Americans With Disabilities Act. Albany is 25% green space—almost three times the recommended recreational acres-to-person ratio, according to the National Recreation & Park Association. This list of open space continues to grow and change along with recreational opportunities, maintenance support, funding sources, and community needs.
Resources City Departments work in collaboration to help support and facilitate green space needs and improvements throughout the City. Department of RecreationDepartment of General ServicesPlanning DepartmentWater & Water SupplyReport property issues on SeeClickFixFind Park programs and activities at The RecDesk

We are applying Geographic Information Systems (GIS) to new orbital data sets for lunar resource assessment and the identification of past habitable environments on Mars. GIS has not previously been used for planetary resource assessment and its applicability to martian habitability is in its infancy. NASA has recognized the interest in this technology with the recent establishment of a NASA-wide Enterprise Agreement with ESRI, the developers of ArcGIS. Lunar resource assessment is recognized as a key to future exploration and sustainability. The recognition of martian habitable environments is a top priority goal of NASA's Mars Program.

This is a one-year project to apply a GIS analysis tool to new orbital data for lunar resource assessment and martian habitability identification. We used ArcGIS, the state-of-the-art software for mapping, integrating, and analysis of spatial data. We focused on the assessment of several regional lunar pyroclastic deposits and habitability analysis in the Chryse-Acidalia portion of the martian lowlands. This work expands upon a previous 3-year project enabled through IRD funds. As a direct result of this project three scientific papers have been published: Allen, C.C., Greenhagen, B.T., Donaldson Hanna, K.L., and Paige, D.P. (2012) Analysis of lunar pyroclastic deposit FeO abundances by LRO Diviner, Journal of Geophysical Research, 117, E00H28, doi:10.1029/2011JE003982. Oehler, D.Z. and Allen, C.C. (2012) Giant polygons and mounds in the lowlands of Mars: signatures of an ancient ocean ?, Astrobiology, 12, 1-15. Oehler, D.Z. and Allen, C.C. (2012) Focusing the search for biosignatures on Mars: Facies prediction with an example from Acidalia Planitia, in Sedimentary Geology of Mars (J.P. Grotzinger and R.E. Milliken, eds.), SEPM Special Publication No. 102, 183-194.

Legacy product - no abstract available

Stamp Out COVID-19An apple a day keeps the doctor away.Linda Angulo LopezDecember 3, 2020https://theconversation.com/coronavirus-where-do-new-viruses-come-from-136105SNAP Participation Rates, was explored and analysed on ArcGIS Pro, the results of which can help decision makers set up further SNAP-D initiatives.In the USA foods are stored in every State and U.S. territory and may be used by state agencies or local disaster relief organizations to provide food to shelters or people who are in need.US Food Stamp Program has been ExtendedThe Supplemental Nutrition Assistance Program, SNAP, is a State Organized Food Stamp Program in the USA and was put in place to help individuals and families during this exceptional time. State agencies may request to operate a Disaster Supplemental Nutrition Assistance Program (D-SNAP) .D-SNAP Interactive DashboardAlmost all States have set up Food Relief Programs, in response to COVID-19.Scroll Down to Learn more about the SNAP Participation Analysis & ResultsSNAP Participation AnalysisInitial results of yearly participation rates to geography show statistically significant trends, to get acquainted with the results, explore the following 3D Time Cube Map:Visualize A Space Time Cube in 3Dhttps://arcg.is/1q8LLPnetCDF ResultsWORKFLOW: a space-time cube was generated as a netCDF structure with the ArcGIS Pro Space-Time Mining Tool : Create a Space Time Cube from Defined Locations, other tools were then used to incorporate the spatial and temporal aspects of the SNAP County Participation Rate Feature to reveal and render statistically significant trends about Nutrition Assistance in the USA.Hot Spot Analysis Explore the results in 2D or 3D.2D Hot Spotshttps://arcg.is/1Pu5WH02D Hot Spot ResultsWORKFLOW: Hot Spot Analysis, with the Hot Spot Analysis Tool shows that there are various trends across the USA for instance the Southeastern States have a mixture of consecutive, intensifying, and oscillating hot spots.3D Hot Spotshttps://arcg.is/1b41T43D Hot Spot ResultsThese trends over time are expanded in the above 3D Map, by inspecting the stacked columns you can see the trends over time which give result to the overall Hot Spot Results.Not all counties have significant trends, symbolized as Never Significant in the Space Time Cubes.Space-Time Pattern Mining AnalysisThe North-central areas of the USA, have mostly diminishing cold spots.2D Space-Time Mininghttps://arcg.is/1PKPj02D Space Time Mining ResultsWORKFLOW: Analysis, with the Emerging Hot Spot Analysis Tool shows that there are various trends across the USA for instance the South-Eastern States have a mixture of consecutive, intensifying, and oscillating hot spots.Results ShowThe USA has counties with persistent malnourished populations, they depend on Food Aide.3D Space-Time Mininghttps://arcg.is/01fTWf3D Space Time Mining ResultsIn addition to obvious planning for consistent Hot-Hot Spot Areas, areas oscillating Hot-Cold and/or Cold-Hot Spots can be identified for further analysis to mitigate the upward trend in food insecurity in the USA, since 2009 which has become even worse since the outbreak of the COVID-19 pandemic.After Notes:(i) The Johns Hopkins University has an Interactive Dashboard of the Evolution of the COVID-19 Pandemic.Coronavirus COVID-19 (2019-nCoV)(ii) Since March 2020 in a Response to COVID-19, SNAP has had to extend its benefits to help people in need. The Food Relief is coordinated within States and by local and voluntary organizations to provide nutrition assistance to those most affected by a disaster or emergency.Visit SNAPs Interactive DashboardFood Relief has been extended, reach out to your state SNAP office, if you are in need.(iii) Follow these Steps to build an ArcGIS Pro StoryMap:Step 1: [Get Data][Open An ArcGIS Pro Project][Run a Hot Spot Analysis][Review analysis parameters][Interpret the results][Run an Outlier Analysis][Interpret the results]Step 2: [Open the Space-Time Pattern Mining 2 Map][Create a space-time cube][Visualize a space-time cube in 2D][Visualize a space-time cube in 3D][Run a Local Outlier Analysis][Visualize a Local Outlier Analysis in 3DStep 3: [Communicate Analysis][Identify your Audience & Takeaways][Create an Outline][Find Images][Prepare Maps & Scenes][Create a New Story][Add Story Elements][Add Maps & Scenes] [Review the Story][Publish & Share]A submission for the Esri MOOCSpatial Data Science: The New Frontier in AnalyticsLinda Angulo LopezLauren Bennett . Shannon Kalisky . Flora Vale . Alberto Nieto . Atma Mani . Kevin Johnston . Orhun Aydin . Ankita Bakshi . Vinay Viswambharan . Jennifer Bell & Nick Giner

See full Data Guide here. Federal Open Space is a polygon feature-based layer that includes land owned in either easement or fee simple interest by the federal government. This layer is based on information that was collected and mapped at various scales and at different levels of accuracy. Types of property in this layer include open space and recreational land open to the public. Examples include National Park Service land, Army Corps of Engineers land, etc.This layer has not been updated since 2004 and may not be accurate.

ESRI polygon feature class representing the City of Somerville, Massachusetts open space areas including parks, playgrounds, recreation fields, community gardens, cemeteries, natural areas, and other open space types.

The data uploaded includes GPS, GLONASS and GALILEO vTEC, latitude, longitude and elevation angle on 15 January 2022. The TEC is 30-seconds sampled (2880 epochs). The data is in 3-dimensions, with one dimension for number of epochs, other one for number of satellites, and third dimension for the number of stations. There are three separaet mat files for each GNSS mission.The files with names GPSTEC_20220115.mat, GALTEC_20220115.mat, and GLOTEC_20220115.mat are the TEC data over the Japan/Taiwan - Australia/NewZealand region. The TEC data used for the India, Africa and America sectors in Figure S1 are upload with the corresponding names of the sectors/regions included in the filenames.

The GIS electron densiy is uploaded as a compress tar file GISdata.tar.gz.. This includes GIS data for 11, 12, 13, and 15 January 2022, in separate folders. Each folder contains 24 netCDF files correspodning to each UT hour. The data have 31 alttiude points (100-7000 km @20km), 73 latitude points (-90 to 90 @2.5 degree) and 72 longitude points (-180 to 175 @5 degrees).

The FORMOSAT-7/COSMIC-2 IVM data used in the figures and supporting information is uploaded as ivm_Tonga_20220115.nc in netCDF format. The file includes the variables, IVMden, IVMlat, IVMlon, and IVMUT. Here IVMden is the ion density per cm3, IVMlat, IVMlon, and IVMUT are the corresponding latitude, longitude and UT hour.

Summary: Mini Lesson MapStorymap metadata page: URL forthcoming Possible K-12 Next Generation Science standards addressed:Grade level(s) 1: Standard 1-PS4-2 - Waves and their Applications in Technologies for Information Transfer - Make observations to construct an evidence-based account that objects can be seen only when illuminatedGrade level(s) 6-8: Standard MS-PS2-1 - Motion and Stability: Forces and Interactions - Apply Newton’s Third Law to design a solution to a problem involving the motion of two colliding objectsGrade level(s) 6-8: Standard MS-LS1-5 - From Molecules to Organisms: Structures and Processes - Construct a scientific explanation based on evidence for how environmental and genetic factors influence the growth of organismsGrade level(s) 6-8: Standard MS-ESS1-3 - Earth’s Place in the Universe - Analyze and interpret data to determine scale properties of objects in the solar systemGrade level(s) 9-12: Standard HS-PS4-4 - Waves and Their Applications in Technologies for Information Transfer - Evaluate the validity and reliability of claims in published materials of the effects that different frequencies of electromagnetic radiation have when absorbed by matter.Most frequently used words:spacevideomissionexplorationtripApproximate Flesch-Kincaid reading grade level: 9.8. The FK reading grade level should be considered carefully against the grade level(s) in the NGSS content standards above.

Learn more about the project and how to use the canopy assessment data by visiting the StoryMap!

Data Dictionary

The Fundamental GIS: Digital Chart of China, 1:1M, Version 1 consists of vector maps of China and surrounding areas. The maps include roads, railroads, drainage systems, contours, populated places, and urbanized areas for China proper, as well as for China and neighboring countries. The maps are at a scale of one to one million (1:1M). This data set is produced in collaboration with the University of Washington as part of the China in Time and Space (CITAS) project and the Columbia University Center for International Earth Science Information Network (CIESIN).

Displays Curb Space Categories maintained by the Seattle Department of Transportation.Refresh Cycle: DailyFeature Class: SDOT.CURB_SPACESUpdate: 4/14/2025 BB - New category "MVZ" (Music Venue Zone) added

MCGD_Data_V2.1 contains all the data that we have collected on locations in modern China. Altogether there are 464,887 entries. The data include the name of locations and their variants in Chinese, pinyin, and any recorded transliteration; the name of the province in Chinese and in pinyin; Province ID; the latitude and longitude; the Name ID and Location ID, and NameID_Legacy. The Name IDs all start with H followed by seven digits. This is the internal ID system of MCGD (the NameID_Legacy column records the Name IDs in their original format depending on the source). Locations IDs that start with "DH" are data points extracted from China Historical GIS (Harvard University); those that start with "D" are locations extracted from the data points in Geonames; those that have only digits (8 digits) are data points we have added from various map sources.

One of the main features of the MCGD Main Dataset is the systematic collection and compilation of place names from non-Chinese language historical sources. Locations were designated in transliteration systems that are hardly comprehensible today, which makes it very difficult to find the actual locations they correspond to. This dataset allows for the conversion from these obsolete transliterations to the current names and geocoordinates.

The Satellite-Based Earth Observation (SBEo) market is experiencing robust growth, projected to reach a market size of $12.66 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This expansion is driven by increasing demand across diverse sectors. The defense and intelligence communities rely heavily on SBEo for surveillance, reconnaissance, and strategic decision-making. Simultaneously, the growing need for precise weather forecasting and climate change monitoring fuels significant market growth. Furthermore, the burgeoning Location-Based Services (LBS) market, energy exploration and management initiatives, and the overall rise in data-driven decision-making are key contributing factors. The market is segmented by application (defense, weather, LBS, energy, and others) and type (Value-Added Services (VAS) and raw data), offering diverse opportunities for specialized companies. The competitive landscape includes both established aerospace giants like Airbus SE, Lockheed Martin Corp., and Maxar Technologies Inc., and emerging innovative players like Planet Labs PBC and EarthDaily Analytics, vying for market share with varying competitive strategies focused on technology innovation, data analytics capabilities, and geographic expansion. The market's growth trajectory is influenced by several factors. Technological advancements leading to higher resolution imagery, improved sensor technology, and advanced analytics capabilities are enhancing data quality and usability. Government initiatives promoting space exploration and data accessibility also play a significant role. However, challenges remain, including the high cost of satellite development and launch, regulatory hurdles related to data access and security, and the need to address data privacy concerns. The regional distribution of the market reflects the significant investments in space technology in North America and the rapid development of the space sector in the Asia-Pacific region, particularly in China and Japan. The forecast period, 2025-2033, anticipates sustained growth driven by these dynamic forces and ongoing technological innovation within the industry.

The schema of this dataset pretty much follows that of MassGIS/EOEEA. Not all data represented here is protected in perpetuity. It is important to view the attribute table and review the MassGIS website documentation to fully understand this dataset. A departure from the MassGIS schema is a related table (tbl_info4_ICP). This table has 1-to-1 relationship with the primary feature class. The tbl_info4_ICP contains a lot of funny codes & IDs for the purposes of utilizing these data on the TrailsMV App and the Martha's Vineyard Land Bank website map. Look for other 'views' of this feature layer to see the data symbolized according to various attribute categories.

Park: Publicly accessible park land. Compiled from various sources, including Cleveland Metroparks, Cuyahoga Valley National Park, and other local parks departments.

-Golf Course -Cemetery -Other Public/Institutional

CDFW BIOS GIS Dataset, Contact: Matt Sagues, Description: This is a vegetation map of the Marin County Open Space District Lands. It was produced in 2008 by Aerial Information Systems using hi-resolution (1') natural color imagery provided by the County of Marin, acquired by Vargis (date unknown).

Abstract Tourist activity occurs in a selective and fragmented manner in space. On the coast of Piauí, this fragmentation process has produced two types of territorialization: used territories versus territories neglected by tourism. This research aimed to identify and characterize these territories, considering the densification and / or dispersion of the tourist infrastructure. The methodology employed is a dialogical approach to interpret the spatial organization and its relationship with the tourist segments observed on the coast of Piauí, using Excel and ArcGis 10.1 software to systematize data. The analyses carried out identified how demand influences the organization of tourism infrastructure in some areas of the municipalities. Likewise, the existing organization of infrastructure and tourist services has also shaped visitor profiles in these areas, forming territories used and / or neglected by tourism. It is hoped that this study can inform decision-making by local public authorities concerning the social and environmental impacts of tourism activities.