A Simple Method to Identify Potential Groundwater-Dependent Vegetation Using NDVI MODIS

The potential groundwater-dependent vegetation (pGDV) in the Iberian Peninsula (IP) was mapped, with a simple method, hereafter referred to as SRS-pGDV, that uses only Normalized Difference Vegetation Index (NDVI) time series retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS) T...

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Main Authors: Patrícia Páscoa, Célia M. Gouveia, Cathy Kurz-Besson
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Forests
Subjects:
Online Access:https://www.mdpi.com/1999-4907/11/2/147
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spelling doaj-43a2bbc80c2a4e9cb3516f7b54b4ebb82020-11-25T02:38:54ZengMDPI AGForests1999-49072020-01-0111214710.3390/f11020147f11020147A Simple Method to Identify Potential Groundwater-Dependent Vegetation Using NDVI MODISPatrícia Páscoa0Célia M. Gouveia1Cathy Kurz-Besson2Instituto Português do Mar e da Atmosfera, 1749-077 Lisbon, PortugalInstituto Português do Mar e da Atmosfera, 1749-077 Lisbon, PortugalInstituto Dom Luiz, Faculdade de Ciências da Universidade de Lisboa, 1749-016 Lisbon, PortugalThe potential groundwater-dependent vegetation (pGDV) in the Iberian Peninsula (IP) was mapped, with a simple method, hereafter referred to as SRS-pGDV, that uses only Normalized Difference Vegetation Index (NDVI) time series retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra V6 product, covering the period February 2000 to April 2018. NDVI was standardized, to minimize the effect of the different land cover types. The extreme drought event of 2004/2005 was used to perform the classification. Considering the water scarcity that affected vegetation in the IP during this event, it was postulated that vegetation showing a high standardized NDVI should be classified as pGDV. Irrigated vegetation and areas with sparse vegetation were eliminated. A cluster analysis was performed, in order to classify the pixels as more/less likely to be pGDV. The results obtained were compared with modeled water table depth, and a propensity of pixels identified as pGDV in areas with low water table depth was clearly observed. However, based on CORINE Land Cover types, some areas identified as pGDV are likely irrigated, such as fruit-tree plantations; this inference is in line with the postulated criterion of vegetation access to sources of water other than precipitation. SRS-pGDV could also be applied to regional studies, using NDVI with a higher spatial resolution.https://www.mdpi.com/1999-4907/11/2/147phreatophytesremote sensingdroughtariditygroundwaterwater table depthland cover
collection DOAJ
language English
format Article
sources DOAJ
author Patrícia Páscoa
Célia M. Gouveia
Cathy Kurz-Besson
spellingShingle Patrícia Páscoa
Célia M. Gouveia
Cathy Kurz-Besson
A Simple Method to Identify Potential Groundwater-Dependent Vegetation Using NDVI MODIS
Forests
phreatophytes
remote sensing
drought
aridity
groundwater
water table depth
land cover
author_facet Patrícia Páscoa
Célia M. Gouveia
Cathy Kurz-Besson
author_sort Patrícia Páscoa
title A Simple Method to Identify Potential Groundwater-Dependent Vegetation Using NDVI MODIS
title_short A Simple Method to Identify Potential Groundwater-Dependent Vegetation Using NDVI MODIS
title_full A Simple Method to Identify Potential Groundwater-Dependent Vegetation Using NDVI MODIS
title_fullStr A Simple Method to Identify Potential Groundwater-Dependent Vegetation Using NDVI MODIS
title_full_unstemmed A Simple Method to Identify Potential Groundwater-Dependent Vegetation Using NDVI MODIS
title_sort simple method to identify potential groundwater-dependent vegetation using ndvi modis
publisher MDPI AG
series Forests
issn 1999-4907
publishDate 2020-01-01
description The potential groundwater-dependent vegetation (pGDV) in the Iberian Peninsula (IP) was mapped, with a simple method, hereafter referred to as SRS-pGDV, that uses only Normalized Difference Vegetation Index (NDVI) time series retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra V6 product, covering the period February 2000 to April 2018. NDVI was standardized, to minimize the effect of the different land cover types. The extreme drought event of 2004/2005 was used to perform the classification. Considering the water scarcity that affected vegetation in the IP during this event, it was postulated that vegetation showing a high standardized NDVI should be classified as pGDV. Irrigated vegetation and areas with sparse vegetation were eliminated. A cluster analysis was performed, in order to classify the pixels as more/less likely to be pGDV. The results obtained were compared with modeled water table depth, and a propensity of pixels identified as pGDV in areas with low water table depth was clearly observed. However, based on CORINE Land Cover types, some areas identified as pGDV are likely irrigated, such as fruit-tree plantations; this inference is in line with the postulated criterion of vegetation access to sources of water other than precipitation. SRS-pGDV could also be applied to regional studies, using NDVI with a higher spatial resolution.
topic phreatophytes
remote sensing
drought
aridity
groundwater
water table depth
land cover
url https://www.mdpi.com/1999-4907/11/2/147
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