Data
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.4225/59/59cb372aed124&rft.title=Landsat-derived monthly NDVI and MNDWI over Coongie Lakes Ramsar convention wetland in Central Australia (January 1988 to September 2011)&rft.identifier=10.4225/59/59cb372aed124&rft.publisher=University of Technology Sydney&rft.description=Monthly Normalized Difference Vegetation Index (NDVI) and Modified Normalized Difference Wetness Index (MNDWI) derived from Landsat satellite (30m spatial resolution) over the Coongie Lakes wetland area from January 1988 to September 2011 Related publication: Zunyi Xie, Alfredo Huete, Xuanlong Ma, Natalia Restrepo-Coupe, Rakhesh Devadas, Kenneth Clarke, Megan Lewis, Landsat and GRACE observations of arid wetland dynamics in a dryland river system under multi-decadal hydroclimatic extremes, Journal of Hydrology, Volume 543, 2016, Pages 818-831, ISSN 0022-1694, http://dx.doi.org/10.1016/j.jhydrol.2016.11.001 Normalized Difference Vegetation Index (NDVI) was used as a proxy of canopy ‘‘greenness” in our analyses. NDVI has been shown to be closely associated with various vegetation biophysical parameters (e.g., canopy cover, leaf area index, fraction of absorbed photosynthetic radiation and biomass) across different ecosystems. We calculated 24 years (January 1988 to September 2011) of monthly NDVI using Landsat surface reflectance band 3 and band 4. The formulation of NDVI is, NDVI = (NIR - Red) / (NIR + Red) where NIR is the near-infrared surface reflectance (band 4760– 900 nm) and Red is the red surface reflectance (band 3, 630– 690 nm). Modified Normalized Difference Wetness Index (MNDWI), a relatively strong performing metric compared to various water detection indices across a range of environments, is calculated as: MNDWI = (Green - MIR) / (Green + MIR) where Green is the green surface reflectance (band 2, 520–600 nm) and MIR is the middle infrared surface reflectance (band 51,550–1750 nm). The following two decision rules were uniformly applied to all Landsat pixels for presence of standing water Floodwater if (MNDWI greater than 0:123) or (MNDWI greater than -0.5 and Band4 less than 2000 and Band7 less than 1000) Example file name: CoongieLakes.LT5.p098r079.1988.01.17.sr.ndvi.tif CoongieLakes = study site LT5 = Landsat 5 p098r079 = path xxx row xxx 1988 = yyyy 01 = mm 17 = dd sr = surface reflectance ndvi = normalised vegetation index&rft.creator=Alfredo Huete&rft.creator=Doctor Anna Clark&rft.creator=Doctor Natalia Restrepo Coupe&rft.creator=Dr Xuanlong Ma&rft.creator=Huete, Alfredo&rft.creator=Professor Alfredo Huete&rft.creator=Professor Alfredo Huete&rft.creator=Rakhesh Devadas&rft.date=2017&rft.relation=https://doi.org/10.1016/j.jhydrol.2016.11.001&rft.coverage=POLYGON((139.08691305667 -28.250762650761,139.08691305667 -26.59302890097,140.71288961917 -26.59302890097,140.71288961917 -28.250762650761,139.08691305667 -28.250762650761))&rft_rights=Copyright, University of Technology Sydney, 2017&rft_rights=CC BY: Attribution 3.0 AU http://creativecommons.org/licenses/by/3.0/au&rft_subject=NDVI&rft_subject=MNDWI&rft_subject=Landsat&rft_subject=Wetland&rft_subject=Ecological Impacts of Climate Change&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=ECOLOGICAL APPLICATIONS&rft_subject=Effects of Climate Change and Variability on Australia (excl. Social Imapcts)&rft_subject=ENVIRONMENT&rft_subject=CLIMATE AND CLIMATE CHANGE&rft_subject=Applied research&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

Open Licence view details
CC-BY

CC BY: Attribution 3.0 AU
http://creativecommons.org/licenses/by/3.0/au

Copyright, University of Technology Sydney, 2017

Access:

Other

Full description

Monthly Normalized Difference Vegetation Index (NDVI) and Modified Normalized Difference Wetness Index (MNDWI) derived from Landsat satellite (30m spatial resolution) over the Coongie Lakes wetland area from January 1988 to September 2011

Related publication: Zunyi Xie, Alfredo Huete, Xuanlong Ma, Natalia Restrepo-Coupe, Rakhesh Devadas, Kenneth Clarke, Megan Lewis, Landsat and GRACE observations of arid wetland dynamics in a dryland river system under multi-decadal hydroclimatic extremes, Journal of Hydrology, Volume 543, 2016, Pages 818-831, ISSN 0022-1694, http://dx.doi.org/10.1016/j.jhydrol.2016.11.001

Normalized Difference Vegetation Index (NDVI) was used as a proxy of canopy ‘‘greenness” in our analyses. NDVI has been shown to be closely associated with various vegetation biophysical parameters (e.g., canopy cover, leaf area index, fraction of absorbed photosynthetic radiation and biomass) across different ecosystems. We calculated 24 years (January 1988 to September 2011) of monthly NDVI using Landsat surface reflectance band 3 and band 4. The formulation of NDVI is,
NDVI = (NIR - Red) / (NIR + Red)
where NIR is the near-infrared surface reflectance (band 4760– 900 nm) and Red is the red surface reflectance (band 3, 630– 690 nm).

Modified Normalized Difference Wetness Index (MNDWI), a relatively strong performing metric compared to various water detection indices across a range of environments, is calculated as:
MNDWI = (Green - MIR) / (Green + MIR)
where Green is the green surface reflectance (band 2, 520–600 nm) and MIR is the middle infrared surface reflectance (band 51,550–1750 nm).
The following two decision rules were uniformly applied to all Landsat pixels for presence of standing water
Floodwater if (MNDWI greater than 0:123) or (MNDWI greater than -0.5 and Band4 less than 2000 and Band7 less than 1000)

Example file name: CoongieLakes.LT5.p098r079.1988.01.17.sr.ndvi.tif
CoongieLakes = study site
LT5 = Landsat 5
p098r079 = path xxx row xxx
1988 = yyyy
01 = mm
17 = dd
sr = surface reflectance
ndvi = normalised vegetation index

Data time period: 1988 to 09 2011

Data time period: 24

This dataset is part of a larger collection

Spatial Coverage And Location

text: POLYGON((139.08691305667 -28.250762650761,139.08691305667 -26.59302890097,140.71288961917 -26.59302890097,140.71288961917 -28.250762650761,139.08691305667 -28.250762650761))

Identifiers