1.0
DCPLUS
20211122
19414300
20211123
19414300
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c1ffe23071e24420a83715ff1a7c2208
Feature Service
https://services.arcgis.com/XG15cJAlne2vxtgt/arcgis/rest/services/Region10MitigationProjectCountySummary_View/FeatureServer
Region10MitigationProjectCountySummary_View
2021-11-22T19:41:43
2021-11-23T15:34:53
Mitigation
HMA
HMGP
PDM
LPDM
FMA
SRL
RFC
Hazard
Hazard Mitigation Assistance Projects from OpenFEMA summarized by county or state.
<font color='#000000' style='font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-ligatures:normal; font-variant-caps:normal; font-weight:400; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; word-spacing:0px; background-color:rgb(255, 255, 255); text-decoration-style:initial; text-decoration-color:initial;'>This Hazard Mitigation Assistant Project data is aggregated from the publicly available <a href='https://www.fema.gov/openfema-data-page/hazard-mitigation-assistance-projects-v2' target='_blank' rel='nofollow ugc noopener noreferrer'>OpenFEMA Dataset: Hazard Mitigation Assistance Projects - v2</a> data.
The data is filtered to Alaska, Idaho, Oregon and Washington then
summarized by county FIPS. Projects not associated with a specific
county are included in the summary at the state level. The projects summarized to the state level have
countyCode == NULL or countyCode == 0.</font><div style='color:rgb(76, 76, 76); font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-ligatures:normal; font-variant-caps:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; word-spacing:0px; background-color:rgb(255, 255, 255); text-decoration-style:initial; text-decoration-color:initial;'><span style='font-weight:bold;'><br /></span></div><div style='color:rgb(76, 76, 76); font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-ligatures:normal; font-variant-caps:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; word-spacing:0px; background-color:rgb(255, 255, 255); text-decoration-style:initial; text-decoration-color:initial;'><span style='font-weight:bold;'>Note: </span>In addition to the county features, there is also an overall state feature in this data for the summary of all projects not associated with a specific County FIPS.</div><div style='color:rgb(76, 76, 76); font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-ligatures:normal; font-variant-caps:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; word-spacing:0px; background-color:rgb(255, 255, 255); text-decoration-style:initial; text-decoration-color:initial;'><br /><span style='font-weight:bold;'></span></div><div style='color:rgb(76, 76, 76); font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-ligatures:normal; font-variant-caps:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; word-spacing:0px; background-color:rgb(255, 255, 255); text-decoration-style:initial; text-decoration-color:initial;'><span style='font-weight:bold;'>Python code used to summarize data:</span></div><div style='color:rgb(76, 76, 76); font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-ligatures:normal; font-variant-caps:normal; font-weight:400; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; word-spacing:0px; background-color:rgb(255, 255, 255); text-decoration-style:initial; text-decoration-color:initial;'># Load the dict to a DataFrame<br />df = pd.DataFrame.from_dict(js['HazardMitigationAssistanceProjects'])<br /><br /># Ensure that the state and county codes are 3 digit strings<br />df['countyCode'] = df['countyCode'].apply(lambda x: x.zfill(3))<br />df['stateNumberCode'] = df['stateNumberCode'].apply(lambda x: x.zfill(2))<br /><br /># Append a fips column with the combined state and county codes<br />df['fips'] = df['stateNumberCode']+df['countyCode']</div><div style='color:rgb(76, 76, 76); font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-ligatures:normal; font-variant-caps:normal; font-weight:400; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; word-spacing:0px; background-color:rgb(255, 255, 255); text-decoration-style:initial; text-decoration-color:initial;'><br /></div><div style='color:rgb(76, 76, 76); font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-ligatures:normal; font-variant-caps:normal; font-weight:400; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; word-spacing:0px; background-color:rgb(255, 255, 255); text-decoration-style:initial; text-decoration-color:initial;'>summary
=
df[['fips','federalShareObligated','numberOfProperties','numberOfFinalProperties','projectAmount','netValueBenefits']].groupby(['fips']).sum()<br /></div><div style='color:rgb(76, 76, 76); font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-ligatures:normal; font-variant-caps:normal; font-weight:400; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; word-spacing:0px; background-color:rgb(255, 255, 255); text-decoration-style:initial; text-decoration-color:initial;'><br /></div><div style='color:rgb(76, 76, 76); font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-ligatures:normal; font-variant-caps:normal; font-weight:400; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; word-spacing:0px; background-color:rgb(255, 255, 255); text-decoration-style:initial; text-decoration-color:initial;'>Description from OpenFEMA:</div><div style='color:rgb(76, 76, 76); font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-ligatures:normal; font-variant-caps:normal; font-weight:400; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; word-spacing:0px; background-color:rgb(255, 255, 255); text-decoration-style:initial; text-decoration-color:initial;'><font color='#1b1b1b' face='Source Sans Pro, sans-serif'><i>The
dataset contains funded projects (financial obligation to grantee)
under the Hazard Mitigation Assistance (HMA) grant programs. FEMA
administers three programs that provide funding for eligible mitigation
planning and projects that reduces disaster losses and protect life and
property from future disaster damages. The three programs are the Hazard
Mitigation Grant Program (HMGP), Flood Mitigation Assistance (FMA)
grant program, and Pre-Disaster Mitigation (PDM) grant program. This
dataset also contains data from the HMA grant programs that were
eliminated by the Biggert Water Flood Insurance Reform Act of 2012:
Repetitive Flood Claims (RFC) grant program and Severe Repetitive Loss
(SRL) grant program. For more information on the Hazard Mitigation
Assistance grant programs, please visit:
https://www.fema.gov/grants/mitigation.</i></font></div>
OpenFEMA: https://www.fema.gov/openfema-data-page/hazard-mitigation-assistance-projects-v2
<span style='font-family:Calibri; font-size:14.6667px;'>User assumes all
risk related to the use of this data. FEMA provides this data "as is"
and disclaims any and all warranties, whether express or implied,
including (without limitation) any implied warranties of merchantability
or fitness for a particular purpose, and there are no express or
implied guarantees of accuracy of the data. In no event will FEMA or
any other Federal Agency be liable to you or to any third party for any
direct, indirect, incidental, consequential, special, or exemplary
damages or lost profit resulting from any use or misuse of this data.</span>
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
c1ffe23071e24420a83715ff1a7c2208
https://services.arcgis.com/XG15cJAlne2vxtgt/arcgis/rest/services/Region10MitigationProjectCountySummary_View/FeatureServer
Feature Service