It is followed by an enumeration of each Redbook fire missing from the spatial data. Menu. If you have specific questions about how to use data, tools, or resources mentioned in this Data Pathfinder, please visit the Earthdata Forum. USGS researchers created a comprehensive wildfiredataset for the United States that spans 142 years, from 1878-2019. DMC - DMC index from the FWI system: 1.1 to 291.3 7. In 2021,58,985 wildfires were reported across the U.S. that consumed 7,125,643 acres, according to the2021 Annual Reportby the National Interagency Coordination Center (NICC), which coordinates the mobilization of resources for wildland fire and other incidents throughout the U.S. It is critical for maintaining species diversity, regulating climate, and providing numerous ecosystem functions. This is not the case when using data from active sensors, which send out a signal and measure the intensity ofthe returned signal. Passive instruments (those that use energyreflected or emitted from Earth for measurements) are not able to penetrate cloud or vegetation cover, which can lead to data gaps or a decrease in data utility, such asthe inability to detect afire or sense the radiative power of small fires. California wildfire spread derived using VIIRS satellite observations and an object-based tracking system Yang Chen, Stijn Hantson, Niels Andela, Shane R. Coffield, Casey A. Graff, Douglas C.. The cryosphere plays a critical role in regulating climate and sea levels. The site suitability criteria included in the techno-economic land use screens are listed below. The fire perimeter and prescribed fire feature service provides a reasonable view of the spatial distribution of past fires. Mailing address: PO Box 944246 NASA provides datasets and tools for assessing and managing wildfires before, during, and after an event. A guide produced by the Climate Hazards Center, University of California Santa Barbara, provides tutorials for using this tool. From 2009 to 2022 CAL FIRE maintained this dataset by processing and Use this app to examine the known status of structures damaged by the flooding. In the State of California, the health and risk factors associated with forest and rangelands are a matter of utmost importance. Below are descriptions of changes in data collection criteria used when compiling these two data sets. Recent Large Fire Perimeters (>=5000 acres), CAL FIRE Notices of Timber Operations TA83, CAL FIRE Nonindustrial Timber Management Plans TA83, CAL FIRE Exemption Notices Right-of-Way TA83, CAL FIRE Exemption Notices Historical TA83, CAL FIRE Timber Harvesting Plans Historical TA83, 2023TulareFloodingIncident 2023 DINS Public View, 2023 Tulare Flooding Incident Flood Structure Status, 2023TulareFloodingIncident Flood Structure Status Map. Official websites use .gov Specify a site by entering the site's geographic coordinates and the area surrounding that site, from one pixel up to 201 x 201 km. Fire20_1 was released April 30th, 2021. In effect, the SVM model predicts better small fires, which are the majority. Depending on the dataset chosen, the visualizer provides the included latitude/longitude or an actual site location name and data collection relative time frames. This dataset contains files and materials in support of the California's Groundwater Live website. Land, Atmosphere Near Real-Time Data (LANCE), Fire Information for Resource Management System (FIRMS), Open Data, Services, and Software Policies, Application Programming Interfaces (APIs), Earth Science Data Systems (ESDS) Program, Commercial Smallsat Data Acquisition (CSDA) Program, Interagency Implementation and Advanced Concepts Team (IMPACT), Earth Science Data and Information System (ESDIS) Project, Earth Observing System Data and Information System (EOSDIS), Distributed Active Archive Centers (DAAC), fire information for resource management system (firms), open data, services, and software policies, earth science data systems (esds) program, commercial smallsat data acquisition (csda) program, interagency implementation and advanced concepts team (impact), earth science data and information system (esdis) project, earth observing system data and information system (eosdis), distributed active archive centers (daacs), number, severity, and overall size of wildfires has increased, 58,985 wildfires were reported across the U.S. that consumed 7,125,643 acres, Resilience Analysis and Planning Tool (RAPT), Soil Moisture Data Sets Become Fertile Ground for Applications, Early Warning eXplorer (EWX) Next Generation Viewer, Normalized Difference Vegetation Index (NDVI), Data Management Guidance for ESD-Funded Researchers, Atmospheric Infrared Sounder (AIRS) Level 3 products, Global Change Observation Mission Water 1 (GCOM-W1), Advanced Microwave Scanning Radiometer-2 (AMSR2), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), ASTER productsare produced from on-demand data acquisition requests and are not categorized by regular temporal ranges, Aerosol Optical Depth, Active Fire and Thermal Anomalies, Vegetation Indices, Land Surface Temperature, Land Surface Reflectance, Moderate Resolution Imaging Spectroradiometer (MODIS), Radar (active; failed 208 days after launch) and a radiometer (passive), TRMM Multi-satellite Precipitation Algorithm (TMPA) and Integrated Multi-satelliteRetrievals for GPM (IMERG), Active Fire and Thermal Anomalies, Vegetation Indices, Land Surface Temperature, Land Surface Reflectance, Visible Infrared Imaging Radiometer Suite (VIIRS), Active Fire and Thermal Anomalies, Land Surface Reflectance, Target 1.5: By 2030, build the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and other economic, social, and environmental shocks and disasters, Target 2.4: By 2030, ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production; that help maintain ecosystems; that strengthen capacity for adaptation to climate change, extreme weather, drought, flooding, and other disasters; and that progressively improve land and soil quality, Target 11.5: By 2030, significantly reduce the number of deaths and the number of people affected and substantially decrease the direct economic losses relative to global gross domestic product caused by disasters, including water-related disasters, with a focus on protecting the poor and people in vulnerable situations, Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries, Target 13.2: Integrate climate change measures into national policies, strategies, and planning, Target 13.3: Improve education, awareness-raising, and human and institutional capacity on climate change mitigation, adaptation, impact reduction, and early warning, Time-averaged maps: Asimple way to observe the variability of data values over a region of interest, Map animations: Ameans to observe spatial patterns and detect unusual events over time, Area-averaged time series: Used to display the value of a data variable that has been averaged from all the data values acquired for a selected region for each time step, Histogram plots:Used to display the distribution of values of a data variable in a selected region and time interval, Point samples, for geographic coordinates, Area samples, for spatial areas via vector polygons. Due to missing perimeters (see Use Limitations) this layer should be used carefully for statistical analysis and reporting. 512-523, 2007. These datasets are generally restricted to specific locations, fire sizes, or time periods. Upload a vector polygon file in shapefile format (you can upload a single file with multiple features or multipart single features). Work fast with our official CLI. A lock () or https:// means youve safely connected to the .gov website. The Sustainable Development Goals (SDGs) are a collection of 17 interlinked global goals designed to be a blueprint for a sustainable future for all of Earths inhabitants. With the Fixed Subsets Tool, you can download pre-processed subsets for more than 3,000field and flux tower sites for validation of models and remote sensing products. ***This data set is superseded by Welty, J.L., and Jeffries, M.I., 2021, Combined wildland fire datasets for the United States and certain territories, 1800s-Present: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZXGFY3. . Click here to see the full XML file that was originally uploaded with this layer. This process is critical for analyzing images quantitatively; it is also important for comparing images from different sensors, modalities, processors, andacquisition dates. More about Data Basin. Image Beginner Intermediate Computer Vision Deep Learning. Download National Datasets. The ESA (European Space Agency) Sentinel-1 Mission consists of two satellites, Sentinel-1A and Sentinel-1B, with synthetic aperture radar (SAR) instruments operating at a C-Band frequency. Official website of the State of California. Forest and Rangeland Ecosystem Science Center, Click on title to download individual files attached to this item, Wildfires_1878_2019_ContiguousUS_Wildfire_Rasters.zip, Wildfires 1878-2019 Contiguous US Wildfire Rasters, Wildfires_1878_2019_Alaska_Wildfire_Rasters.zip, Wildfires 1878-2019 Alaska Wildfire Rasters, Wildfires_1878_2019_Hawaii_Wildfire_Rasters.zip, Wildfires 1878-2019 Hawaii Wildfire Rasters, Build Version: 2.184.0-351-g4d49188-0 The .shp, .shx, .dbf, or .prj files must be zipped into a file folder to upload. Use Git or checkout with SVN using the web URL. Finding a sensor with the spatio-temporal resolution capable of addressing your research, application, or decision-makingneeds is a crucial first step in using remotely senseddata. View a schedule of upcoming webinars and events, as well as videos of past webinars. Dual polarization, for example, refers to two different signal directions:horizontal/vertical and vertical/horizontal (HV and VH). (2023-04-27 10:38), Forest and Rangeland Ecosystem Science Center (FRESC), Combined wildfire datasets for the United States and certain territories, 1878-2019, Combined wildland fire datasets for the United States and certain territories, 1800s-Present, https://www.sciencebase.gov/vocab/category/item/identifier, __disk__99/b0/ed/99b0ed6b58aed771004d31525281bd0e2b75dda3, __disk__fe/7d/84/fe7d843b047231e9d182f55e9fb3fd146009e005. The Sun influences a variety of physical and chemical processes in Earths atmosphere. The acreage estimation of the fire is somewhat higher than what is reported elsewhere, possibly due to the low resolution (1km) sampling of the dataset. If NetCDF-4 is selected, outputs will be grouped into .nc files by product and by feature. Processes occurring deep within Earth constantly are shaping landforms. . Thisis one of the most comprehensive wildfiredatasets available and was created from 12 different and online wildfiredatasets. NASA continually monitors solar radiation and its effect on the planet. KMZ files are also provided for data visualization in Google Earth. This is one of the most comprehensive wildfire datasets available and was created from 12 different and online wildfire datasets. Currently, wildfire boundaries can only be found in disparate local or national datasets. The CAL FIRE Forest Health Research Program supports scientific studies that provide critical information and tools to forest landowners, resource agencies, fire management organizations and policy makers across California on a variety of topics related to forest health and management. This,in turn, requires more time between observations of a given area. The Wildland Fire Interagency Geospatial Services (WFIGS) Group provides authoritative geospatial data products under the interagency Wildland Fire Data Program. included in the techno-economic land use screens are listed below. Data collected by sensors aboard orbiting satellites, carried aboard aircraft, or installed on the ground provide a wealth of data that can be used to assess conditions before a burn, track the movement of a wildfire in near real-time, and assess the environmental impact of an historic burn. 512-523, 2007. This integration helps to validate and calibrate the data, and provides spatial and temporal data continuity. (BEU), Dutch Kern #30 (KRN), 1987- Peach (RRU), Ave 32 (TUU), Conover (RRU), Eagle #1 (LNU), State 767 aka Bull (RRU), Denny (TUU), Dog Bar (NEU), Crank (LMU), White Deer (FKU), Briceburg (LMU), Post (RRU), Antelope (RRU), Cougar-I (SKU), Pilitas (SLU) Freaner (SHU), Fouts Complex (LNU), Slides (TGU), French (BTU), Clark (PNF), Fay/Top (SQF), Under, Flume, Bear Wallow, Gulch, Bear-1, Trinity, Jessie, friendly, Cold, Tule, Strause, China/Chance, Bear, Backbone, Doe, (SHF) Travis Complex, Blake, Longwood (SRF), River-II, Jarrell, Stanislaus Complex 14k (STF), Big, Palmer, Indian (TNF) Branham (BLM), Paul, Snag (NPS), Sycamore, Trail, Stallion Spring, Middle (KRN), SLU-864. Whether you are a scientist, an educator, a student, or are just interested in learning more about NASAs Earth science data and how to use them, we have the resources to help. California WildFires (2013-2020) | Kaggle menu Skip to content explore Home emoji_events Competitions table_chart Datasets tenancy Models code Code comment Discussions school Learn expand_more More auto_awesome_motion View Active Events search Sign In Register LANCE data products are available generally within three hours of a satellite observation, which allows for near real-time (NRT) monitoring and decision making. Use the query web API to retrieve data with a set . These full disk hemispheric views allow for almost real-time viewing of changes occurring around most of the world. Data collected by the FIA program captures and quantifies tree growth, removal, and mortality. Two types of sample requests are available: After choosing to request an area extraction, you will be taken to the Extract Area Sample page where you will specify a series of parameters that are used to extract data for your area(s) of interest. This script creates a csv file called fires.csv that has the dates from the original data stripped of its time stamps as well as fires_by_county.csv which has the county information and the . CAL FIRE (including c ontract counties) , USDA Forest Service Region 5, USDI Bureau of Land Managment & National Park Service, and other agencies jointly maintain a comprehensive fire perimeter GIS layer for public and private lands throughout the state. Conducted every seven years, the Forest and Rangeland Assessment links together state requirements for natural resource inventories and strategies, and the federal government's desire to rely more heavily on these state programs in determining priorities for funding. Naturally occurring wildfires can be nearly as impossible to prevent, and as difficult to control, as hurricanes, tornadoes, and floods. Click on title to download individual files attached to this item. You signed in with another tab or window. This dataset was designed to create a comprehensive burned area feature class and summary rasters with a known time component for use as a visualization tool and in multiple analyses. Provided by CEC Land-Use Planning office. Paulo Cortez, pcortez '@' dsi.uminho.pt, Department of Information Systems, University of Minho, Portugal. Upload a vector polygon file in GeoJSON format (can upload a single file with multiple features or multipart single features). Updated on April 7, 2023 HTML ArcGIS GeoServices REST API CSV GeoJSON ZIP KML Albert's Towhee Range - CWHR B485 [ds1646] This dataset contains all the train, test, valid splits for training a yolo model for detecting wildfire smoke. (MVU), Vail (CNF), 1990 Shipman (HUU), Lightning 379 (LMU), Mud, Dye (TGU), State 914 (RRU), Shultz (Yorba) (BDU), Bingo Rincon #3 (MVU), Dehesa #2 (MVU), SLU 1626 (SLU), 1992 Lincoln, Fawn (NEU), Clover, fountain (SHU), state, state 891, state, state (RRU), Aberdeen (BDU), Wildcat, Rincon (MVU), Cleveland (AEU), Dry Creek (MMU), Arroyo Seco, Slick Rock (BEU), STF #135 (TCU), 1993 Hoisington (HUU), PG&E #27 (with an undetermined cause, lol), Hall (TGU), state, assist, local (RRU), Stoddard, Opal Mt., Mill Creek (BDU), Otay #18, Assist/ Old coach (MVU), Eagle (CNF), Chevron USA, Sycamore (FKU), Guerrero, Duck, 1994 Schindel Escape (SHU), blank (PNF), lightning #58 (LMU), Bridge (NEU), Barkley (BTU), Lightning #66 (LMU), Local (RRU), Assist #22 & #79 (SLU), Branch (SLO), Piute (BDU), Assist/ Opal#2 (BDU), Local, State, State (RRU), Gilman fire 7/24 (RRU), Highway #74 (RRU), San Felipe, Assist #42, Scissors #2 (MVU), Assist/ Opal#2 (BDU), Complex (BDF), Spanish (SBC), 1995- State 1983 acres, Lost Lake, State # 1030, State (1335 acres), State (5000 acres), Jenny, City (BDU), Marron #4, Asist #51 (SLO/VNC), 1996 - Modoc NF 707 (Ambrose), Borrego (MVU), Assist #16 (SLU), Deep Creek (BDU), Weber (BDU), State (Wesley) 500 acres (RRU), Weaver (MMU), Wasioja (SBC/LPF), Gale (FKU), FKU 15832 (FKU), State (Wesley) 500 acres, Cabazon (RRU), State Assist (aka Bee) (RRU), Borrego, Otay #269 (MVU), Slaughter house (MVU), Oak Flat (TUU), 1997 - Lightning #70 (LMU), Jackrabbit (RRU), Fernandez (TUU), Assist 84 (Military AFV) (SLU), Metz #4 (BEU), Copperhead (BEU), Millstream, Correia (MMU), Fernandez (TUU), 1998 - Worden, Swift, PG&E 39 (MMU), Chariot, Featherstone, Wildcat, Emery, Deluz (MVU), Cajalco Santiago (RRU), 1999 - Musty #2,3 (BTU), Border # 95 (MVU), Andrews, Roadside 9323 (MMU), Lacy (BDU), Range (SCU), 2000 - Latrobe (AEU), Shell (SLU), Happy Camp (Inyo), Golden Fire (BDU), 2001 - Pacheco (MMU), Orosco (CNF/MVU), Observation (LNF), Modoc Complex (LMU), Happy Camp Complex (SKU), 2002 - Nicholas (MMU), Aliso Assist #73 (MVU), Assist, Leona, Williams (BDU), BLM D596, horse complex (LMU), KNF Assist #15 (SKU), Cajalco Evening State 925 (RRU), Airport, Bouquet, Copper, Inyo Complex (BDU), 2003 - F.K.U. Forest Fires Data Set Download: Data Folder, Data Set Description Abstract: This is a difficult regression task, where the aim is to predict the burned area of forest fires, in the northeast region of Portugal, by using meteorological and other data (see details at: [Web Link] ). Note that an Earthdata Login is required to download data from Earthdata Search. This difference in penetration is due to the dielectric properties of a given medium, which dictate how much of the incoming radiation scatters at the surface, how much signal penetrates into the medium, and how much energy gets lost to the medium through absorption. Abstract: This is a difficult regression task, where the aim is to predict the burned area of forest fires, in the northeast region of Portugal, by using meteorological and other data (see details at: [Web Link]). A spreadsheet file can contain multiple worksheets, so you usually will want to specify which sheet name (s) to read. Specify the range of dates for which you wish to extract data by entering a start and end date (MM-DD-YYYY) or by clicking on the Calendar icon and selecting dates a start and end date in the calendar. These layers include Red Visible, which can be used for analyzing daytime clouds, fog, insolation, and winds; Clean Infrared, which provides cloud top temperature and information about precipitation; and Air Mass RGB, which enables the visualization of the differentiation between air mass types (e.g., dry air, moist air, etc.). The Conservation Biology Institute (CBI) provides scientific expertise to support the conservation and recovery of biological diversity in its natural state through applied research, education, planning, and community service. It also explores the vulnerability of human communities to natural disasters and hazards. It also provides useful information to detect changes inland positionafter an earthquake, volcanic eruption, or landslide. Once you have downloaded the needed SAR data, the datamust be calibrated to account for distortion. Users (including those without specific knowledge of the data) can search for and read about data collections, search for data files by date and spatial area, preview browse images, and download or submit requests for data files, with customization for select data collections. Wildfires emitted 1.76 billion metric tonnes (equivalent to more than 1.9 billion tons) of carbon globally in 2021, according to data from the European Union's Copernicus Atmosphere Monitoring Service. The Department of Forestry and Fire Protection (CAL FIRE) makes no. Terrain correction can be performed by selecting Radar/Geometric/Terrain Correction/ Range-Doppler Terrain Correction. The county dataset and the fire perimeter dataset is joined via a spatial join on QGIS (called join.qgz) and this script opens up the geopackage and saves it as a csv for use in the upcoming scripts. NASA data provide key information on land surface parameters and the ecological state of our planet. Along with these beneficial aspects, they also emit vast quantities of carbon into the atmosphere along with aerosols and other particles that can impact health, restrict visibility, and contribute to global climate change. The land surface discipline includes research into areas such as shrinking forests, warming land, and eroding soils. The biosphere encompasses all life on Earth and extends from root systems to mountaintops and all depths of the ocean. 1. BAJA CALIFORNIA-MEXI: 06-20-2006: 06-25-2006: MEXICO: 4000: UI: TUU-6967: TULARE: W: 06 . ; for more information aboutSAR specifically, see What is SAR?. Important note: DO NOT unzip the downloaded SAR file. State of California Open Data. Five hundred wildfires from the 2020 fire season were added to the database (12 from NPS, 277 from CAL FIRE, 76 from USFS, 37 from BLM, 3 other). Several datasets including land cover, biophysical properties, elevation, and selected ORNL DAAC archived data are available through SDAT. With the Web Service, you can retrieve subset data (in real-time) for any location(s), time period, and area programmatically using a REST web service. Upon selection, the map service will open displaying the various measurementswith the associated granuleand a visualization of the selected granule. Updated on April 29, 2023. SAR is an active sensor that can penetrate cloud cover and vegetation canopy, and also observe at night. The number, severity, and overall size of wildfires has increased, according to theU.S. Department of Agriculture, through contributing factors including extended drought, the build-up of fuels, past fire management strategies, invasive species targeting specific tree species, and the spread of residential communities into formerly natural areas. The datasets provided are wildfires, historical weather, historical weather forecast, vegetation index, and land classes. *** This dataset is comprised of four different zip files. Note that an Earthdata Login is required to use Giovanni. NOTE: In 2013, the California Department of Fish and Game (CDFG, DFG) was renamed to California Department of Fish and Widlife (CDFW). Sacramento, CA 94244, Physical address:715 P Street Sacramento, CA 95814 These data also are integral components of socioeconomic metrics that provide a measure of how humans co-exist with the environment and the stresses they encounter through natural and human-caused changes to the environment. To view statistics from different features or layers, select a different AID from the Feature dropdown or a different layer of interest from the Layer dropdown. TheSoil Moisture Visualizer tool at NASA's Oak Ridge National Laboratory DAAC (ORNL DAAC)integrates in-situ, airborne, and remote sensingdata from a variety of soil moisture datasets covering North Americainto an easy-to-use platform(read more about this toolat Soil Moisture Data Sets Become Fertile Ground for Applications). Find and use NASA Earth science data fully, openly, and without restrictions. Worldview now includes nine geostationary imagery layers from the GOES-East, GOES-West,and Himawari-8 geostationary satellites that areavailable at 10-minute increments for the last 30 days. While Giovanni provides many options for analysis, the following are the more popular ones: The NASAWorldviewdata visualization application provides the capability to interactively browse more than 1,000 global, full-resolution satellite imagery layers and then download the underlying data. This dataset contains key characteristics about the data described in the Data Descriptor A global wildfire dataset for the analysis of fire regimes and fire behaviour. Within SDAT, select a dataset of interest. Two regression metrics were measured: MAD and RMSE. FIRMS makes URT data available in less than 60 seconds of satellite fly over for much of the US and Canada _by_county_with_wildfire.csv (for 2008, 2011, 2014, 2017) coal existing_gen_units_2006.xls (2006 - 2014) existing_gen_units_2015 . Open the amplitude file. Large wildfire data scraped from CAL FIRE. It also facilitates exploratory analysis and data discovery for different groups of users. In contrast, the definition of fires whose perimeter should be collected has changed once in the approximately 30 years the data has been in existence. Click here to see the full XML file that was originally uploaded with this layer. Provides a reasonable view of the spatial distribution of past large fires. This map feeds into a web app "-//W3C//DTD HTML 4.01 Transitional//EN\">, Forest Fires Data Set Dismiss page alert. Source: Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. The dataset contains the list of Wildfires that has occurred in California between 2013 and 2020. NASA's Earth Science Data Systems (ESDS) Program maintains many more resources for data analysis that may be helpful. You have JavaScript disabled. Historical California Wildfire Data The California Department of Forestry and Fire Protection (CAL FIRE) maintains historical data about wildfires in California, available for download. RH - relative humidity in %: 15.0 to 100 11. wind - wind speed in km/h: 0.40 to 9.40 12. rain - outside rain in mm/m2 : 0.0 to 6.4 13. area - the burned area of the forest (in ha): 0.00 to 1090.84 (this output variable is very skewed towards 0.0, thus it may make sense to model with the logarithm transform). Once a fire burns through an area, there are many potential impacts, such as loss of vegetation, landslide potential, runoff, and more. Earthquake Zones of Required Investigation . Therefore, it is ideal for flood inundation mapping. Speckle is the grey level variation that occurs between adjacent resolution cells, and createsa grainy texture. Two previous fires were modified, the 1994 Steckel fire was deleted and the two 1979 Hernadez were merged into one fire. This fixesgeometric distortionsdue to slant range, layover, shadow, and foreshortening. View Well Finder. 2009 - Oliver (RRU), Ash (MMU), One-Eleven (SHU L complex). Land managers have invested considerable funding to decrease fuel loads and restore resilient ecosystems in forests and rangelands, using techniques such as grazing, mowing, herbicides, and thinning. Earthdata Search is a tool for searching for and discoveringdata collections from NASA's Earth Observing System Data and Information System (EOSDIS) collectionas well as from U.S. and international agencies acrossEarth science disciplines. California Important Farmland - Time Series View California Important Farmland - Time Series. While there is a file on prescribed burns, we will only be looking at the wildfire history file. The ocean covers almost a third of Earths surface and contains 97% of the planets water. . Recognizing the connections between interdependent Earth systems is critical for understanding the world in which we live. Users can subscribe to email alerts bases on their area of interest. (LNU), Iron Peak (MEU), Murrer (LMU), Rock Creek (BTU), USFS #29, 33, Bluenose, Amador, 8 mile (AEU), Backbone, Panoche, Los Gatos series, Panoche (FKU), Stan #7, Falls #2 (MMU), USFS #5 (TUU), Grizzley, Gann (TCU), Bumb, Piney Creek, HUNTER LIGGETT ASST#2, Pine, Lowes, Seco, Gorda-rat, Cherry (BEU), Las pilitas, Hwy 58 #2 (SLO), Lexington, Finley (SCU), Onions, Owens (BDU), Cabazon, Gavalin, Orco, Skinner, Shell, Pala (RRU), South Mt., Wheeler, Black Mt., Ferndale, (VNC), Archibald, Parsons, Pioneer (BDU), Decker, Gleason (LAC), Gopher, Roblar, Assist #38 (MVU), 1986 Knopki (SRF), USFS #10 (NEU), Galvin (RRU), Powerline (RRU), Scout, Inscription (BDU), Intake (BDF), Assist #42 (MVU), Lightning series (FKU), Yosemite #1 (YNP), USFS Asst. Select the layer(s) of interest to add to the Selected layers list. The data is updated yearly with fire perimeters from the previous fire season. A Data Mining Approach to Predict Forest Fires using Meteorological Data. URT is much quicker than that. Making NASA's free and open Earth science data interactive, interoperable, and accessible for research and societal benefit both today and tomorrow.

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