View In:
ArcGIS JavaScript
ArcGIS Online Map Viewer
ArcGIS Earth
ArcMap
View Footprint In:
ArcGIS Online Map Viewer
Service Description: Flooded and non-flooded regions were delineated from recent Hurricanes using a random forest classification model leveraging pre- and post-storm synthetic aperture radar from the European Space Agency's Sentinel-1 sensor, in addition to topography, floodplain, and landcover data. The classification model was trained with USGS and NCDEMS high-water marks, in addition to flooded and non-flooded regions delineated from high-resolution NOAA aerial photography; the model achieved >91% accuracy against an independent withheld sample for each storm. Within regions where flooding was detected, opportunities for buyouts, conservation of forests and wetlands, or lands where restoration or easements could be implemented were identified using the National Land Cover Dataset (2011). For additional details regarding the methods, please see the peer-reviewed publication and data and code archives referenced in the Credits below.
Note: Do not download this raster using the map at the top of the page. Instead, click Download then "Download Floodplain Resilience raster." The link will take you to a page where the raster can be downloaded.
Floodplain_Resilience
Description: Flooded and non-flooded regions were delineated from recent Hurricanes using a random forest classification model leveraging pre- and post-storm synthetic aperture radar from the European Space Agency's Sentinel-1 sensor, in addition to topography, floodplain, and landcover data. The classification model was trained with USGS and NCDEMS high-water marks, in addition to flooded and non-flooded regions delineated from high-resolution NOAA aerial photography; the model achieved >91% accuracy against an independent withheld sample for each storm. Within regions where flooding was detected, opportunities for buyouts, conservation of forests and wetlands, or lands where restoration or easements could be implemented were identified using the National Land Cover Dataset (2011). For additional details regarding the methods, please see the peer-reviewed publication and data and code archives referenced in the Credits below.
Note: Do not download this raster using the map at the top of the page. Instead, click Download then "Download Floodplain Resilience raster." The link will take you to a page where the raster can be downloaded.
false
Extent:
XMin: 1191434.7212242186
YMin: 30682.29697972536
XMax: 3075104.7212242186
YMax: 1042222.2969797254
Spatial Reference: 102719
(2264)
Initial Extent:
XMin: 1191434.7212242186
YMin: 30682.29697972536
XMax: 3075104.7212242186
YMax: 1042222.2969797254
Spatial Reference: 102719
(2264)
Full Extent:
XMin: 1191434.7212242186
YMin: 30682.29697972536
XMax: 3075104.7212242186
YMax: 1042222.2969797254
Spatial Reference: 102719
(2264)
Pixel Size X: 30.0
Pixel Size Y: 30.0
Band Count: 3
Pixel Type: U8
RasterFunction Infos: {"rasterFunctionInfos": [
{
"name": "None",
"description": "Make a Raster or Raster Dataset into a Function Raster Dataset.",
"help": ""
},
{
"name": "Floodplain_Resilience_RFT",
"description": "Floodplain Resilience colormap",
"help": ""
}
]}
Mensuration Capabilities: Basic
Has Histograms: false
Has Colormap: false
Has Multi Dimensions : false
Rendering Rule:
Min Scale: 0
Max Scale: 0
Copyright Text: Schaffer-Smith, D., Myint, S.W., Muenich, R.L., Tong, D., and DeMeester, J.E. 2020. Repeated hurricanes reveal risks and opportunities for social-ecological resilience to flooding and water quality problems. Environmental Science & Technology. Schaffer-Smith, D. 2020. Hurricanes Matthew and Florence: impacts and opportunities to improve floodplain management. Knowledge Network for Biocomplexity. doi:10.5063/F1SB443J. https://knb.ecoinformatics.org/ Schaffer-Smith, D. 2020. Supporting code for: Schaffer-Smith, D., Myint, S.W., Muenich, R.L., Tong, D., & DeMeester, J.E. 2020. Repeated hurricanes reveal risks and opportunities for social-ecological resilience to flooding and water quality problems. Environmental Science & Technology. https://github.com/dschaffersmith/repeatFloodingNC
Service Data Type: esriImageServiceDataTypeRGB
Min Values: N/A
Max Values: N/A
Mean Values: N/A
Standard Deviation Values: N/A
Object ID Field: objectid
Fields:
-
objectid
(
type: esriFieldTypeOID, alias: OBJECTID
)
-
name
(
type: esriFieldTypeString, alias: Name, length: 200
)
-
minps
(
type: esriFieldTypeDouble, alias: MinPS
)
-
maxps
(
type: esriFieldTypeDouble, alias: MaxPS
)
-
lowps
(
type: esriFieldTypeDouble, alias: LowPS
)
-
highps
(
type: esriFieldTypeDouble, alias: HighPS
)
-
category
(
type: esriFieldTypeInteger, alias: Category
,
Coded Values:
[0: Unknown]
,
[1: Primary]
,
[2: Overview]
, ...6 more...
)
-
tag
(
type: esriFieldTypeString, alias: Tag, length: 100
)
-
groupname
(
type: esriFieldTypeString, alias: GroupName, length: 100
)
-
productname
(
type: esriFieldTypeString, alias: ProductName, length: 100
)
-
centerx
(
type: esriFieldTypeDouble, alias: CenterX
)
-
centery
(
type: esriFieldTypeDouble, alias: CenterY
)
-
zorder
(
type: esriFieldTypeInteger, alias: ZOrder
)
-
shape
(
type: esriFieldTypeGeometry, alias: Shape
)
Default Mosaic Method: Northwest
Allowed Mosaic Methods: NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None
SortField:
SortValue: null
Mosaic Operator: First
Default Compression Quality: 75
Default Resampling Method: Bilinear
Max Record Count: 1000
Max Image Height: 4100
Max Image Width: 15000
Max Download Image Count: 20
Max Mosaic Image Count: 20
Allow Raster Function: true
Allow Copy: true
Allow Analysis: true
Allow Compute TiePoints: false
Supports Statistics: true
Supports Advanced Queries: true
Use StandardizedQueries: true
Raster Type Infos:
Name: Raster Dataset
Description: Supports all ArcGIS Raster Datasets
Help:
Has Raster Attribute Table: false
Edit Fields Info: null
Ownership Based AccessControl For Rasters: null
Child Resources:
Info
Statistics
Key Properties
Legend
Raster Function Infos
Supported Operations:
Export Image
Query
Identify
Measure
Compute Histograms
Compute Statistics Histograms
Get Samples
Compute Class Statistics
Query Boundary
Compute Pixel Location
Compute Angles
Validate
Project