These instruments consist of a pipe or cable anchored at the bottom of a well casing. You can filter the list by the topic categories in the menu at the . Once your request is completed:From the Explore Requests page, click the View icon in order to view and interact with your results. 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. (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. Depending on the dataset chosen, the visualizer provides the included latitude/longitude or an actual site location name and data collection relative time frames. Data-Driven Wildfire Risk Prediction in Northern California - MDPI Yet, little information is available about how such restoration activities have influenced wildlife species and habitats. 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. You need to be signed in to access your workspace. This dataset is a compilation of the data export tables available on WUEdata for the 2020 Urban Water Management Plans (UWMPs). Recognizing the connections between interdependent Earth systems is critical for understanding the world in which we live. A Data Mining Approach to Predict Forest Fires using Meteorological Data. ORNL DAAC also has several MODIS and VIIRS Subset Tools for subsetting data. NASA data provide key information on land surface parameters and the ecological state of our planet. The Wildfire Data Pathfinder addresses (but is not limited to) the following SDGs: The opportunities to connect NASA data to the SDGs are infinite; therefore, the datasets included in specific Data Pathfinders are not intended to be comprehensive. Complete accounting of all incorporated cities, including the boundary and name of each individual city. Coming soon: RT and URT data as part of the CSV, ShapeFile and KML/KMZ Active Fire downloads NASA EOSDIS defines Real-Time as data that is made available within 60 minutes of satellite overpass. Country Yearly Summary [.csv] Note: Dataset is based on Standard Processing (SP) and will display countries that have hotspot detection for a given year and instrument. For data older than seven days, use the Archive Download Details about regional coordinates. ________________________________________________________________________________, Discrepancies between wildfire perimeter data and Redbook Large Damaging Fires. This data displays fire perimeters dating back to 1878 up till the last calendar year, 2019 in California. This fixesgeometric distortionsdue to slant range, layover, shadow, and foreshortening. Data Basin is a science-based mapping and analysis platform that supports learning, research, and sustainable environmental stewardship. A Data Mining Approach to Predict Forest Fires using Meteorological Data. The fire perimeter and prescribed fire feature service provides a reasonable view of the spatial distribution of past fires. Dual polarization, for example, refers to two different signal directions:horizontal/vertical and vertical/horizontal (HV and VH). These remotely sensed Earth observations provide consistent and continuous information on the state of Earth processes and their change over time.