Check out the Year to Date Dashboard or the Year End Dashboard for this dataset. You can also use the data download tool to choose the topic of interest (i.e. arrests), the geography level (i.e. police district), and time frame to export as a csv or json dataset.View metadata for key information about this dataset.Philadelphia’s District Attorney’s Office (DAO) releases interactive data reports on the their work, including incidents (from the Philadelphia Police Department), arrests, charges, bail, outcomes, case length, future years of incarceration, future years of supervision, summary arrests, summary charges, summary case outcomes, and summary case lengths. Dashboards are organized into final year-end data (updated at the end of each year) and year-to-date data (updated daily). Each dashboard displays one or more interactive graphs showing trends, a table of data, and, optionally, an interactive map displaying the data by police districts. The dashboard does not provide for downloading data.See this data at different boundary levels:SUM_CASE_LENGTH_CITYWIDESUM_CASE_LENGTH_PDSUM_CASE_LENGTH_ZIPCODEFor questions about this dataset, contact nathaniel.lownes@phila.gov. For technical assistance, email maps@phila.gov.

Check out the Year to Date Dashboard or the Year End Dashboard for this dataset. You can also use the data download tool to choose the topic of interest (i.e. arrests), the geography level (i.e. police district), and time frame to export as a csv or json dataset.View metadata for key information about this dataset.Philadelphia’s District Attorney’s Office (DAO) releases interactive data reports on the their work, including incidents (from the Philadelphia Police Department), arrests, charges, bail, outcomes, case length, future years of incarceration, future years of supervision, summary arrests, summary charges, summary case outcomes, and summary case lengths. Dashboards are organized into final year-end data (updated at the end of each year) and year-to-date data (updated daily). Each dashboard displays one or more interactive graphs showing trends, a table of data, and, optionally, an interactive map displaying the data by police districts. The dashboard does not provide for downloading data.See this data at different boundary levels:SUM_CASE_OUTCOMES_CENSUSSUM_CASE_OUTCOMES_PDSUM_CASE_OUTCOMES_ZIPCODEFor questions about this dataset, contact nathaniel.lownes@phila.gov. For technical assistance, email maps@phila.gov.

This EnviroAtlas dataset is a summary of total population near major roads without any tree buffer within 12-digit Hydrologic Units (HUC_12), based on the National Land Cover Database 2011 (NLCD 2011) percent tree canopy cover (TCC 2011) dataset. The metric is a measure of potential exposure to particulate matter from exhaust from traffic. Studies have shown that tree buffers can help improve air quality by filtering particulate matter for those living or working near roads. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This map features the Snow Amount component of the Winter Storm Severity Index (WSSI). This map is meant to be viewed within the context of the WSSI Interactive storymap. More information about the WSSI and the Flash Freeze component can be found here.

This map displays protection-weighted range-size rarity of species in the lower 48 United States that are protected by the Endangered Species Act and/or considered to be in danger of extinction. It is part of the Map of Biodiversity Importance (MoBI) data collection, a series of maps that identify areas of high importance for protecting species from extinction in the contiguous United States. Building on habitat suitability models for 2,216 of the nation’s most imperiled species, and information on range size and degree of protection derived from those models, the MoBI project provides a series of maps that can help inform conservation efforts. This map depicts summed protection-weighted range-size rarity for Critically Imperiled (categorized by NatureServe as “G1”), Imperiled (“G2”), and ESA-listed (i.e., full species listed as Endangered or Threatened under the Endangered Species Act) species in the following groups:Vertebrates (birds, mammals, amphibians, reptiles, freshwater fishes; 309 species) Freshwater invertebrates (mussels and crayfishes; 228 species) Pollinators (bumblebees, butterflies, and skippers; 43 species) Vascular plants (1,636 species)High values identify areas where more unprotected, restricted-range species are likely to occur. These areas are of interest to conservationists due to both the restricted range sizes and need for protection from threats such as habitat loss.Habitat models for most species were generated using the random forest algorithm. Data to train the models came from the NatureServe Network (e.g. state Natural Heritage Programs) supplemented by data from USGS BISON, and other sources of population and locality data. Environmental predictors used for the modeling include representations of terrain, climate, land cover, soils, and hydrology. The modeling resolution for terrestrial species was either 30 m (most species) or 330 m (some wide-ranging species). Models for aquatic species used the medium resolution National Hydrography Dataset (NHD) as the modeling unit. For species not amenable to random forest modeling, habitat maps were derived by buffering locality data and/or building simple deductive models based on habitat information. NatureServe converted habitat maps to a 990-m raster to provide a consistent unit of aggregation and avoid revealing the precise location of sensitive species. Range-size rarity for each species is the inverse of the total area mapped as suitable habitat (using the 990-m raster). Protection-weighted range-size rarity (PWRSR) maps combine information on both range-size rarity and the degree to which habitat for the species is protected. Protected habitat was defined as that occurring within protected areas managed for biodiversity (i.e., Gap Status 1 and 2 lands in the USGS Protected Areas Database; PAD-US 2.0). Each species was assigned a PWRSR score equal to the product of range-size rarity and the percent of habitat that is unprotected. The PWRSR raster sums these scores for all species with habitat that overlaps a cell.These data layers are intended to identify areas of high potential value for on-the-ground biodiversity protection efforts. As a synthesis of predictive models, they cannot guarantee either the presence or absence of imperiled species at a given location. For site-specific decision-making, these data should be used in conjunction with field surveys and/or documented occurrence data, such as is available from the NatureServe Network.For more information, see:Hamilton, H., Smyth, R.L., Young, B.E., Howard, T.G., Tracey, C., Breyer, S., Cameron, D.R., Chazal, A., Conley, A.K., Frye, C. and Schloss, C. (2022), Increasing taxonomic diversity and spatial resolution clarifies opportunities for protecting imperiled species in the U.S.. Ecological Applications. Accepted Author Manuscript e2534. https://doi.org/10.1002/eap.2534April 2021 Release Note: These data were updated with improved data. 38 species were added to the aggregate result that were previously erroneously excluded. In addition, a minor issue with how the original data were snapped was fixed, ensuring that all species within all of the MOBI layers are aligned consistently, regardless of the layers to which a given species contributes. Results may thus differ somewhat from the February 2020 release.

Soils and soil moisture greatly influence the water cycle and have impacts on runoff, flooding and agriculture. Soil type and soil particle composition (sand, clay, silt) affect soil moisture and the ability of the soil to retain water. Soil moisture is also affected by levels of evaporation and plant transpiration, potentially leading to near dryness and eventual drought.Measuring and monitoring soil moisture can ensure the fitness of your crops and help predict or prepare for flash floods and drought. The GLDAS soil moisture data is useful for modeling these scenarios and others, but only at global scales. Dataset SummaryThe GLDAS Soil Moisture layer is a time-enabled image service that shows average monthly soil moisture from 2000 to the present at four different depth levels. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-1). The model is run with 3-hourly time steps and aggregated into monthly averages. Review the complete list of model inputs, explore the output data (in GRIB format), and see the full Hydrology Catalog for all related data and information!What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop. The GLDAS soil moisture data is useful for modeling, but only at global scales. Time: This is a time-enabled layer. It shows the total evaporative loss during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is one year.Depth: This layer has four depth levels. By default they are summed, but you can view each using the multidimensional filter. You must disable time animation on the layer before using its multidimensional filter. It is also possible to toggle between depth layers using raster functions, accessed through the Image Display tab.Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.This layer has query, identify, and export image services available. This layer is part of a larger collection of earth observation maps that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the earth observation layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about earth observations layers and the Living Atlas of the World. Follow the Living Atlas on GeoNet.