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Numerical summaries of vegetation indices and land surface temperature derived from remotely sensed imagery in Phoenix Area Social Survey (PASS) neighborhoods of central Arizona

General Information
Data Package:
Local Identifier:knb-lter-cap.668.2
Title:Numerical summaries of vegetation indices and land surface temperature derived from remotely sensed imagery in Phoenix Area Social Survey (PASS) neighborhoods of central Arizona
Alternate Identifier:DOI PLACE HOLDER
Abstract:

This project calculates two vegetation indices: Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI), and land surface temperature (LST) from remotely sensed imagery. NDVI and SAVI are calculated from the 2010, 2013, 2015, and 2017 NAIP imagery (1m resolution). LST is calculated from Landsat 5 and 8 imagery (30m resolution) from summer months in 1985, 1990, 1995, 2000, 2005, 2010, and 2015. Summary values are calculated for each of the aforementioned data resources for 2011 and 2017 Phoenix Area Social Survey (PASS) study area boundaries. Tabular summaries of the mean, median, minimum, maximum, and standard deviation of the NDVI, SAVI, and LST values for the 2011 and 2017 Phoenix Area Social Survey boundaries (45 and 12 neighborhoods, respectively) are provided.

Javascript code used to process NDVI, SAVI, and LST imagery, and R code used to calculate numerical summaries of NDVI, SAVI, and LST in PASS neighborhoods are included with this dataset.

Locations and areas of PASS study neighborhood boundaries are available through the Environmental Data Initiative:

–PASS 2011:

Harlan S., R. Aggarwal, D. Childers, J. Declet-Barreto, S. Earl, K. Larson, M. Nation, D. Ruddell, K. Smith, P. Warren, A. Wutich, A. York. 2018. Phoenix Area Social Survey (PASS): 2011. Environmental Data Initiative. https://doi.org/10.6073/pasta/f39a2c9d8e78e6d7a949e93af12e9bf9

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=631

–PASS 2017:

Larson K., A. York, R. Andrade, S. Wittlinger. 2019. Phoenix Area Social Survey (PASS): 2017. Environmental Data Initiative. https://doi.org/10.6073/pasta/98dd5b92117e9d728b09e582fb4d1b17

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=667

Source data (NDVI, SAVI, and LST) are available through the Environmental Data Initiative:

–NDVI 2010

Stuhlmacher M., L. Watkins. 2019. Normalized Difference Vegetation Index (NDVI) derived from 2010 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/8a465e9b76035bffeb00f3a6134eb913

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=669

–NDVI 2013

Stuhlmacher M., L. Watkins. 2019. Normalized Difference Vegetation Index (NDVI) derived from 2013 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/3382f4ad4ac4287768ded16ccbdb6f59

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=670

–NDVI 2015

Stuhlmacher M. 2019. Normalized Difference Vegetation Index (NDVI) derived from 2015 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/1cec448d93395f635506e3abb8aa841d

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=671

–NDVI 2017

Stuhlmacher M. 2019. Normalized Difference Vegetation Index (NDVI) derived from 2017 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/8b4b471a33c83f274c35dcdc0b5dec75

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=672

–SAVI 2010

Stuhlmacher M. 2019. Soil-Adjusted Vegetation Index (SAVI) derived from 2010 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/f4988cde318c85b76b0edbaa3219d682

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=673

–SAVI 2013

Stuhlmacher M. 2019. Soil-Adjusted Vegetation Index (SAVI) derived from 2013 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/82f2bd5d8f9e4e7ae6b82066b957e37d

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=674

–SAVI 2015

Stuhlmacher M. 2019. Soil-Adjusted Vegetation Index (SAVI) derived from 2015 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/281c4942e95e9f3246ca67203ec081d0

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=675

–SAVI 2017

Stuhlmacher M. 2019. Soil-Adjusted Vegetation Index (SAVI) derived from 2017 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/f715f5f896f5f47118240e3f174e476b

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=676

–LST

Stuhlmacher M., L. Watkins. 2019. Remotely-sensed Land Surface Temperature (LST) for the central Arizona region during summer months over five-year periods: 1985-2015. Environmental Data Initiative. https://doi.org/10.6073/pasta/c526299a0e4e4f7d6e921aac18528e24

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=677

Publication Date:2019-11-19

Time Period
Begin:
1985-07-23
End:
2017-06-05

People and Organizations
Contact:Information Manager (Central Arizona–Phoenix LTER) [  email ]
Creator:Stuhlmacher, Michelle (Arizona State University)
Creator:Watkins, Lance (Arizona State University)

Data Entities
Data Table Name:
668_pass_vegetation_indices_fcb40ec5614cf91000f62dec9b09a6c6.csv
Description:
numerical summaries of vegetation indices derived from remotely sensed imagery in Phoenix Area Social Survey (PASS) neighborhoods of central Arizona
Other Name:
668_combineTabular_467bd230acca6165458f531137f69eb8.R
Description:
R code to combine GEE CSV output into files based on year/indice/PASS neighborhood
Other Name:
668_LandsatProv_LST_fe3971846199a6247233648972574271.js
Description:
JavaScript code used in Google Earth Engine to calculate land surface temperature from Landsat (1985-2015, one image every 5 years cropped to CAP study area boundary
Other Name:
668_NAIP_NDVI_0b00171d88eaea63be7c0ec6a9d74462.js
Description:
JavaScript code used in Google Earth Engine to calculate NDVI from NAIP for 2010, 2013, 2015, 2017 cropped to CAP study area boundary
Other Name:
668_NAIP_SAVI_c4de7c880b56dd6df7d56f295cd2d3ba.js
Description:
JavaScript code used in Google Earth Engine to calculate SAVI from NAIP for 2010, 2013, 2015, 2017 cropped to CAP study area boundary
Detailed Metadata

Data Entities

Data Table

Data:https://pasta-s.lternet.edu/package/data/eml/knb-lter-cap/668/2/d8ce054d14f9ab4225a6ceb9468ccf11
Name:668_pass_vegetation_indices_fcb40ec5614cf91000f62dec9b09a6c6.csv
Description:numerical summaries of vegetation indices derived from remotely sensed imagery in Phoenix Area Social Survey (PASS) neighborhoods of central Arizona
Number of Records:2280
Number of Columns:9

Table Structure
Object Name:668_pass_vegetation_indices_fcb40ec5614cf91000f62dec9b09a6c6.csv
Size:193287 bytes
Authentication:fcb40ec5614cf91000f62dec9b09a6c6 Calculated By MD5
Text Format:
Number of Header Lines:1
Record Delimiter:\r\n
Orientation:column
Simple Delimited:
Field Delimiter:,
Quote Character:"

Table Column Descriptions
 
Column Name:pass_year  
pass_id  
block_group  
sensor  
image_date  
image_year  
indice  
statistic  
value  
Definition:year of PASS boundary data used for tabular summaryID of PASS neighborhood2000 census block group identifier from the PASS boundary filename of aerial or satellite sensor from which data were derivedNAIP (except 2010) is presented as a date range YYYYMMDD-YYYYMMDD because it takes several days for the planes to fly over an area and capture aerial imageryyear of imagery captureindice or other value calculated from the aerial or satellite imagerysummary statistic generatedvalue from evaluating all pixels in the defined area boundary for the identified source and statistic
Storage Type:string  
string  
string  
string  
string  
date  
string  
string  
float  
Measurement Type:nominalnominalnominalnominalnominaldateTimenominalnominalratio
Measurement Values Domain:
Allowed Values and Definitions
Enumerated Domain 
Code Definition
Code2011
DefinitionPASS survey: 2011
Source
Code Definition
Code2017
DefinitionPASS survey: 2017
Source
DefinitionID of PASS neighborhood
Definition2000 census block group identifier from the PASS boundary file
Allowed Values and Definitions
Enumerated Domain 
Code Definition
CodeNAIP
DefinitionNational Agriculture Imagery Program
Source
Definitiondate or date range when the imagery was collected: YYYYMMDD; NAIP (except 2010) is presented as a date range YYYYMMDD-YYYYMMDD because it takes several days for the planes to fly over an area and capture aerial imagery
FormatYYYY
Precision
Allowed Values and Definitions
Enumerated Domain 
Code Definition
CodeNDVI
DefinitionNormalized Difference Vegetation Index
Source
Code Definition
CodeSAVI
DefinitionSoil Adjusted Vegetation Index
Source
Allowed Values and Definitions
Enumerated Domain 
Code Definition
Codemax
Definitionmaximum
Source
Code Definition
Codemean
Definitionmean
Source
Code Definition
Codemedian
Definitionmedian
Source
Code Definition
Codemin
Definitionminimum
Source
Code Definition
Codesd
Definitionstandard deviation
Source
Unitdimensionless
Typereal
Min-1.487395 
Max1.49345 
Missing Value Code:                  
Accuracy Report:                  
Accuracy Assessment:                  
Coverage:                  
Methods:                  

Non-Categorized Data Resource

Name:668_combineTabular_467bd230acca6165458f531137f69eb8.R
Entity Type:R
Description:R code to combine GEE CSV output into files based on year/indice/PASS neighborhood
Physical Structure Description:
Object Name:668_combineTabular_467bd230acca6165458f531137f69eb8.R
Size:19090 byte
Authentication:467bd230acca6165458f531137f69eb8 Calculated By MD5
Externally Defined Format:
Format Name:R
Data:https://pasta-s.lternet.edu/package/data/eml/knb-lter-cap/668/2/b7ad2624187bd21ac77f763f3d9cbcca

Non-Categorized Data Resource

Name:668_LandsatProv_LST_fe3971846199a6247233648972574271.js
Entity Type:js
Description:JavaScript code used in Google Earth Engine to calculate land surface temperature from Landsat (1985-2015, one image every 5 years cropped to CAP study area boundary
Physical Structure Description:
Object Name:668_LandsatProv_LST_fe3971846199a6247233648972574271.js
Size:24516 byte
Authentication:fe3971846199a6247233648972574271 Calculated By MD5
Externally Defined Format:
Format Name:js
Data:https://pasta-s.lternet.edu/package/data/eml/knb-lter-cap/668/2/1ec0d69f9134b4e059cbb1deed8f6a85

Non-Categorized Data Resource

Name:668_NAIP_NDVI_0b00171d88eaea63be7c0ec6a9d74462.js
Entity Type:js
Description:JavaScript code used in Google Earth Engine to calculate NDVI from NAIP for 2010, 2013, 2015, 2017 cropped to CAP study area boundary
Physical Structure Description:
Object Name:668_NAIP_NDVI_0b00171d88eaea63be7c0ec6a9d74462.js
Size:12191 byte
Authentication:0b00171d88eaea63be7c0ec6a9d74462 Calculated By MD5
Externally Defined Format:
Format Name:js
Data:https://pasta-s.lternet.edu/package/data/eml/knb-lter-cap/668/2/3dda5b3e1462bf5a0220b7d5981f0081

Non-Categorized Data Resource

Name:668_NAIP_SAVI_c4de7c880b56dd6df7d56f295cd2d3ba.js
Entity Type:js
Description:JavaScript code used in Google Earth Engine to calculate SAVI from NAIP for 2010, 2013, 2015, 2017 cropped to CAP study area boundary
Physical Structure Description:
Object Name:668_NAIP_SAVI_c4de7c880b56dd6df7d56f295cd2d3ba.js
Size:12598 byte
Authentication:c4de7c880b56dd6df7d56f295cd2d3ba Calculated By MD5
Externally Defined Format:
Format Name:js
Data:https://pasta-s.lternet.edu/package/data/eml/knb-lter-cap/668/2/f97eb06e3a8807eea8cf6173a5cda674

Data Package Usage Rights

Copyright Board of Regents, Arizona State University. This information is released to the public and may be used for academic, educational, or commercial purposes subject to the following restrictions. While the CAP LTER will make every effort possible to control and document the quality of the data it publishes, the data are made available 'as is'. The CAP LTER cannot assume responsibility for damages resulting from mis-use or mis-interpretation of datasets, or from errors or omissions that may exist in the data. It is considered a matter of professional ethics to acknowledge the work of other scientists that has resulted in data used in subsequent research. The CAP LTER expects that any use of data from this server will be accompanied with the appropriate citations and acknowledgments. The CAP LTER encourages users to contact the original investigator responsible for the data that they are accessing. Where appropriate, researchers whose projects are integrally dependent on CAP LTER data are encouraged to consider collaboration and/or co-authorship with original investigators. The CAP LTER requests that users submit to the Julie Ann Wrigley Global Institute of Sustainability at Arizona State University reference to any publication(s) resulting from the use of data obtained from this site.

Keywords

By Thesaurus:
LTER controlled vocabularyurban, climate, temperature, vegetation, remote sensing, satellite imagery, geographic information systems, landsat, ndvi, land surface properties, land use, land cover
LTER core areasland use and land cover change, residential landscapes and neighborhoods, climate and heat
Creator Defined Keyword Seturban heat island, land surface properties, national agriculture imagery program, naip, savi, lst, land surface temperature, land architecture, sonoran desert, phoenixareasocialsurvey, phoenix area social survey, pass
CAPLTER Keyword Set Listcap lter, cap, caplter, central arizona phoenix long term ecological research, arizona, az, arid land

Methods and Protocols

These methods, instrumentation and/or protocols apply to all data in this dataset:

Methods and protocols used in the collection of this data package
Description:

Google Earth Engine was used to create single date or seasonal composites of Landsat and NAIP imagery (see below) and compute statistics for the imagery within PASS boundaries.

Three types of products employing annual remotely sensed images from Landsat and NAIP: (1) NDVI was computed from the NAIP sensor with a 1-m spatial resolution, and temporal resolution of 2010-2017, (2) SAVI was computed from the NAIP sensor with a 1-m spatial resolution, and temporal resolution of 2010-2017, (3) LST was computed from the Landsat 5 and 8 sensors with a 30-m spatial resolution, and temporal resolution of 1985-2015.

Landsat and National Agriculture Imagery Program (NAIP) imagery are used because they are complementary in terms of their spatial and temporal resolution. Landsat has greater temporal coverage (1985-2015) but poorer spatial resolution (30m by 30m pixels). NAIP has a more limited temporal coverage (2010-2017) but high spatial resolution (1m x 1m pixels).

Landsat Level-2 Provisional Surface Temperature products, which are part of the U.S. Landsat Analysis Ready Data (ARD) product bundle (Dwyer et al. 2018), were used for calculating LST. The Provisional Surface temperature values are computed from Landsat Collection 1 Level-1 thermal infrared bands and Top of Atmosphere (TOA) Reflectance. The calculations are corrected for atmospheric variations between dates, sensors and locations (i.e., water vapor, ozone, aerosol optical thickness, clouds and digital elevation) using ancillary datasets such as Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Database (GED) data, ASTER Normalized Difference Vegetation Index (NDVI) data, as well as atmospheric profiles, specific humidity, and air temperature from reanalysis data.

The intent is that the surface temperature can be used in time-series analysis, however, current products are only provisional and all users of the surface temperature product should include this disclaimer: USGS Landsat Surface Temperature Science Product may report unvalidated results for certain observational conditions. Additionally, the raw values in these files should not be compared over time because they are from different days/months. Please see the Landsat Surface Temperature Product Guide (USGS 2018) and product overview (https://www.usgs.gov/centers/eros/science/usgs-eros-archive-landsat-archives-landsat-level-2-provisional-surface?qt-science_center_objects=0#qt-science_center_objects) for more information.

The NAIP imagery is taken from an airplane, so while it has a much higher spatial resolution, it may not be reliable for time-series analysis. NAIP products are best for use in an analysis that focuses on a single year or for maps/visualizations.

The Provisional Surface Temperature was accessed using Earth Explorer (https://earthexplorer.usgs.gov/) on October 2019. The values in Kelvin were convereted to Celcius. Cloudless, summertime (July and August) images were used for the calculation.

NDVI is computed using the near-infrared (NIR) and red (RED) bands because red visible light (0.63-0.69 μm) is absorbed by a plant’s chlorophyll while near-infrared light (0.77-0.90 μm) is scattered by the leaf’s mesophyll structure: NDVI = (NIR - RED)/(NIR + RED)

SAVI is computed using the same bands as NDVI along with a constant that corrects for soil brightness (Huete 1988). It is calculated: SAVI = ((1 + L)(NIR – RED))/(NIR + RED + L) where L = 0.5. SAVI is a complementary vegetation indice to NDVI in desert regions, such as the Phoenix metropolitan area, because SAVI minimizes the influence of soil brightness.

The mean, median, minimum, maximum, and standard deviation of pixel values were calculated for the each of the neighborhoods in the PASS (Phoenix Area Social Survey). Neighborhood boundaries vary slightly over the several years the survey has been conducted—to capture all variations in boundaries, the statistics were calculated for both the 2011 and 2017 PASS boundaries.

References

Dwyer, J.L., Roy, D.P., Sauer, B., Jenkerson, C.B., Zhang, H., and Lymburner, L., 2018, Analysis ready data—Enabling analysis of the Landsat archive: Remote Sensing, v. 10, no. 9, art. no. 1363. doi.org/10.3390/rs10091363

Huete, A.R., (1988) A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25 (3): 259-309. https://doi.org/10.1016/0034-4257(88)90106-X

U.S. Geological Survey, Department of the Interior. (2018). Landsat Provisional Surface Temperature Product Guide LSDS-1330, Version 2.0. EROS: Sioux Falls, South Dakota. https://www.usgs.gov/media/files/landsat-provisional-surface-temperature-product-guide

Locations and areas of PASS study neighborhood boundaries are available through the Environmental Data Initiative:

–PASS 2011:

Harlan S., R. Aggarwal, D. Childers, J. Declet-Barreto, S. Earl, K. Larson, M. Nation, D. Ruddell, K. Smith, P. Warren, A. Wutich, A. York. 2018. Phoenix Area Social Survey (PASS): 2011. Environmental Data Initiative. https://doi.org/10.6073/pasta/f39a2c9d8e78e6d7a949e93af12e9bf9

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=631

–PASS 2017:

Larson K., A. York, R. Andrade, S. Wittlinger. 2019. Phoenix Area Social Survey (PASS): 2017. Environmental Data Initiative. https://doi.org/10.6073/pasta/98dd5b92117e9d728b09e582fb4d1b17

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=667

Source data (NDVI, SAVI, and LST) are available through the Environmental Data Initiative:

–NDVI 2010

Stuhlmacher M., L. Watkins. 2019. Normalized Difference Vegetation Index (NDVI) derived from 2010 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/8a465e9b76035bffeb00f3a6134eb913

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=669

–NDVI 2013

Stuhlmacher M., L. Watkins. 2019. Normalized Difference Vegetation Index (NDVI) derived from 2013 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/3382f4ad4ac4287768ded16ccbdb6f59

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=670

–NDVI 2015

Stuhlmacher M. 2019. Normalized Difference Vegetation Index (NDVI) derived from 2015 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/1cec448d93395f635506e3abb8aa841d

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=671

–NDVI 2017

Stuhlmacher M. 2019. Normalized Difference Vegetation Index (NDVI) derived from 2017 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/8b4b471a33c83f274c35dcdc0b5dec75

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=672

–SAVI 2010

Stuhlmacher M. 2019. Soil-Adjusted Vegetation Index (SAVI) derived from 2010 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/f4988cde318c85b76b0edbaa3219d682

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=673

–SAVI 2013

Stuhlmacher M. 2019. Soil-Adjusted Vegetation Index (SAVI) derived from 2013 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/82f2bd5d8f9e4e7ae6b82066b957e37d

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=674

–SAVI 2015

Stuhlmacher M. 2019. Soil-Adjusted Vegetation Index (SAVI) derived from 2015 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/281c4942e95e9f3246ca67203ec081d0

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=675

–SAVI 2017

Stuhlmacher M. 2019. Soil-Adjusted Vegetation Index (SAVI) derived from 2017 National Agriculture Imagery Program (NAIP) data for the central Arizona region. Environmental Data Initiative. https://doi.org/10.6073/pasta/f715f5f896f5f47118240e3f174e476b

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=676

–LST

Stuhlmacher M., L. Watkins. 2019. Remotely-sensed Land Surface Temperature (LST) for the central Arizona region during summer months over five-year periods: 1985-2015. Environmental Data Initiative. https://doi.org/10.6073/pasta/c526299a0e4e4f7d6e921aac18528e24

newest revision: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=677

People and Organizations

Publishers:
Organization:Central Arizona–Phoenix LTER
Address:
Arizona State University,
Global Institute of Sustainability,
Tempe, AZ 85287-5402 USA
Creators:
Individual: Michelle Stuhlmacher
Organization:Arizona State University
Email Address:
Michelle.Stuhlmacher@asu.edu
Id:https://orcid.org/0000-0002-2730-7091
Individual: Lance Watkins
Organization:Arizona State University
Email Address:
lewatkin@asu.edu
Id:https://orcid.org/0000-0002-8462-5715
Contacts:
Organization:Central Arizona–Phoenix LTER
Position:Information Manager
Address:
Arizona State University,
Global Institute of Sustainability,
Tempe, AZ 85287-5402 USA
Email Address:
caplter.data@asu.edu
Web Address:
https://sustainability.asu.edu/caplter/
Metadata Providers:
Individual: Michelle Stuhlmacher
Organization:Arizona State University
Email Address:
Michelle.Stuhlmacher@asu.edu
Id:https://orcid.org/0000-0002-2730-7091

Temporal, Geographic and Taxonomic Coverage

Temporal, Geographic and/or Taxonomic information that applies to all data in this dataset:

Time Period
Begin:
1985-07-23
End:
2017-06-05
Geographic Region:
Description:CAP LTER study area
Bounding Coordinates:
Northern:  34.01Southern:  32.91
Western:  -113.34Eastern:  -111.59

Project

Parent Project Information:

Title:Central Arizona–Phoenix Long-Term Ecological Research Project
Personnel:
Individual: Daniel Childers
Organization:Arizona State University
Email Address:
dan.childers@asu.edu
Id:https://orcid.org/0000-0003-3904-0803
Role:Principal Investigator
Individual: Nancy Grimm
Organization:Arizona State University
Email Address:
nbgrimm@asu.edu
Id:https://orcid.org/0000-0001-9374-660X
Role:Co-principal Investigator
Individual: Sharon Hall
Organization:Arizona State University
Email Address:
sharonjhall@asu.edu
Id:https://orcid.org/0000-0002-8859-6691
Role:Co-principal Investigator
Individual: Billie Turner II
Organization:Arizona State University
Email Address:
Billie.L.Turner@asu.edu
Id:https://orcid.org/0000-0002-6507-521X
Role:Co-principal Investigator
Individual: Abigail York
Organization:Arizona State University
Email Address:
Abigail.York@asu.edu
Id:https://orcid.org/0000-0002-2313-9262
Role:Co-principal Investigator
Abstract:Phase IV of the Central Arizona-Phoenix LTER (CAP) continues to focus on the question: How do the ecosystem services provided by urban ecological infrastructure (UEI) affect human outcomes and behavior, and how do human actions affect patterns of urban ecosystem structure and function and, ultimately, urban sustainability and resilience? The overarching goal is to foster social-ecological urban research aimed at understanding these complex systems using a holistic, ecology of cities perspective while contributing to an ecology for cities that enhances urban sustainability and resilience. This goal is being met through four broad programmatic objectives: (1) use long-term observations and datasets to articulate and answer new questions requiring a long-term perspective; (2) develop and use predictive models and future-looking scenarios to help answer research questions; (3) employ existing urban ecological theory while articulating new theory; and (4) build transdisciplinary partnerships to foster resilience and enhance sustainability in urban ecosystems while educating urban dwellers of all ages and experiences. CAP IV research is organized around eight interdisciplinary questions and ten long-term datasets and experiments, and researchers are organized into eight Interdisciplinary Research Themes to pursue these long-term research questions.
Funding: NSF Awards: CAP I: DEB-9714833, CAP II: DEB-0423704, CAP III: DEB-1026865, CAP IV: DEB-1832016
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