Dynamics of vegetation indices in tropical and subtropical savannas defined by ecoregions and Moderate Resolution Imaging Spectroradiometer (MODIS) land cover

2012 ◽  
Vol 27 (2) ◽  
pp. 153-191 ◽  
Author(s):  
Michael J. Hill ◽  
Miguel O. Román ◽  
Crystal B. Schaaf
Keyword(s):  
Land Cover ◽  
Vegetation Indices ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Dynamics Of Vegetation

Improved fuel moisture prediction in non-native tropical Megathyrsus maximus grasslands using Moderate-Resolution Imaging Spectroradiometer (MODIS)-derived vegetation indices

2017 ◽  
Vol 26 (5) ◽  
pp. 384
Author(s):  
L. M. Ellsworth ◽  
A. P. Dale ◽  
C. M. Litton ◽  
T. Miura
Keyword(s):  
Vegetation Index ◽  
Vegetation Indices ◽  
Fuel Moisture ◽  
Fire Behaviour ◽  
Native Grass ◽  
Tropical Ecosystems ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Live Fuel Moisture ◽  
Moderate Resolution Imaging Spectroradiometer

The synergistic impacts of non-native grass invasion and frequent human-derived wildfires threaten endangered species, native ecosystems and developed land throughout the tropics. Fire behaviour models assist in fire prevention and management, but current models do not accurately predict fire in tropical ecosystems. Specifically, current models poorly predict fuel moisture, a key driver of fire behaviour. To address this limitation, we developed empirical models to predict fuel moisture in non-native tropical grasslands dominated by Megathyrsus maximus in Hawaii from Terra Moderate-Resolution Imaging Spectroradiometer (MODIS)-based vegetation indices. Best-performing MODIS-based predictive models for live fuel moisture included the two-band Enhanced Vegetation Index (EVI2) and Normalized Difference Vegetation Index (NDVI). Live fuel moisture models had modest (R2=0.46) predictive relationships, and outperformed the commonly used National Fire Danger Rating System (R2=0.37) and the Keetch–Byram Drought Index (R2=0.06). Dead fuel moisture was also best predicted by a model including EVI2 and NDVI, but predictive capacity was low (R2=0.19). Site-specific models improved model fit for live fuel moisture (R2=0.61), but limited extrapolation. Better predictions of fuel moisture will improve fire management in tropical ecosystems dominated by this widespread and problematic non-native grass.

scholarly journals Limitations and Challenges of MODIS-Derived Phenological Metrics Across Different Landscapes in Pan-Arctic Regions

2018 ◽  
Vol 10 (11) ◽  
pp. 1784 ◽  
Author(s):  
Siyu Wang ◽  
Xinchen Lu ◽  
Xiao Cheng ◽  
Xianglan Li ◽  
Matthias Peichl ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Vegetation Indices ◽  
Optical Remote Sensing ◽  
Arctic Ecosystems ◽  
Arctic Regions ◽  
Land Cover Dynamics ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Phenological Metrics

Recent efforts have been made to monitor the seasonal metrics of plant canopy variations globally from space, using optical remote sensing. However, phenological estimations based on vegetation indices (VIs) in high-latitude regions such as the pan-Arctic remain challenging and are rarely validated. Nevertheless, pan-Arctic ecosystems are vulnerable and also crucial in the context of climate change. We reported the limitations and challenges of using MODerate-resolution Imaging Spectroradiometer (MODIS) measurements, a widely exploited set of satellite measurements, to estimate phenological transition dates in pan-Arctic regions. Four indices including normalized vegetation difference index (NDVI), enhanced vegetation index (EVI), phenology index (PI), plant phenological index (PPI) and a MODIS Land Cover Dynamics Product MCD12Q2, were evaluated and compared against eddy covariance (EC) estimates at 11 flux sites of 102 site-years during the period from 2000 to 2014. All the indices were influenced by snow cover and soil moisture during the transition dates. While relationships existed between VI-based and EC-estimated phenological transition dates, the R2 values were generally low (0.01–0.68). Among the VIs, PPI-estimated metrics showed an inter-annual pattern that was mostly closely related to the EC-based estimations. Thus, further studies are needed to develop region-specific indices to provide more reliable estimates of phenological transition dates.

scholarly journals Phenological Dynamics of Vegetation Using the Enhanced Vegetation Index (EVI) in Regions of Bahia State

2018 ◽  
Vol 7 (7) ◽  
pp. 399
Author(s):  
Wanessa Luana De Brito Costa ◽  
Célia Campos Braga ◽  
Clênia Rodrigues Alcântara ◽  
Adriana De Souza Costa
Keyword(s):  
Wavelet Transformation ◽  
Vegetation Index ◽  
Enhanced Vegetation Index ◽  
Global Power ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Almost All ◽  
Annual Scale ◽  
Dynamics Of Vegetation

The purpose of this study is to analyze the dynamics of EVI (Enhanced Vegetation Index) variability in different time scales of the different biomes in the state of Bahia. Images of the MODIS / Terra (Moderate Resolution Imaging Spectroradiometer) sensor with spatial resolution of 1km were used for the period between 2001 and 2015. For that, the methodology of the Wavelet Transformation (WT) was applied in each homogeneous region HR. The WT allows to identify in different scales important oscillations in the signal, through scales of energy and global power. Thus, it can be observed that the phenological pattern of vegetation predominates on an annual scale in almost all regions, except in HR1, HR4 and HR6 where interactions with smaller scales are detected: intrasazonal and seasonal to some years in the studied period. In this context, it was possible to identify that in the years where there were higher rates of EVI, there is an association with higher rainfall indices in different regions. Therefore, it can be said that EVI is also a good indicator of rainfall.

scholarly journals Effect of Using Multi-Year LULC and Monthly LAI Inputs on the Calibration of a Distributed Hydrologic Model

2021 ◽  
Author(s):  
Ibrahim Olayode Busari ◽  
Mehmet Cüneyd Demirel ◽  
Alice Newton
Keyword(s):  
Land Cover ◽  
Potential Evapotranspiration ◽  
Hydrologic Model ◽  
Parameter Uncertainties ◽  
Area Index ◽  
Distributed Hydrologic Model ◽  
Land Cover Data ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

This study explores the use of satellite-based LULC (Land Use / Land Cover) data while simultaneously correcting potential evapotranspiration (PET) input with Leaf Area Index (LAI) to increase the performance of a physically distributed hydrologic model. The mesoscale hydrologic model (mHM) was selected for this purpose due to its unique features. Since LAI input informs the model about vegetation dynamics, we incorporated the LAI based PET correction option together with multi-year LULC data. The Globcover land cover data was selected for the single land cover cases, and hybrid of CORINE (coordination of information on the environment) and MODIS (Moderate Resolution Imaging Spectroradiometer) land cover datasets were chosen for the cases with multiple land cover datasets. These two datasets complement each other since MODIS has no separate forest class but more frequent (yearly) observations than CORINE. Calibration period spans from 1990 to 2006 and corresponding NSE (Nash-Sutcliffe Efficiency) values varies between 0.23 and 0.42, while the validation period spans from 2007 to 2010 and corresponding NSE values are between 0.13 and 0.39. The results revealed that the best performance is obtained when multiple land cover datasets are provided to the model and LAI data is used to correct PET, instead of default aspect-based PET correction in mHM. This study suggests that to minimize errors due to parameter uncertainties in physically distributed hydrologic models, adequate information can be supplied to the model with care taken to avoid over-parameterizing the model.

scholarly journals BRDF-CORRECTED VEGETATION INDICES CONFIRM SEASONAL PATTERN IN GREENING OF FRENCH GUIANA’S FORESTS

2020 ◽  
Vol 1 (211-212) ◽  
pp. 3-9
Author(s):  
Emil A. Cherrington
Keyword(s):  
Nous Avons ◽  
Seasonal Pattern ◽  
Vegetation Indices ◽  
Dynamique Forestière ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Parmi les outils de caractérisation de la dynamique forestière, la télédétection est particulièrement adaptée pourl’observation des vastes surfaces forestières de Guyane  d’accès difficile. Dans le but de réévaluer les hypothèses énoncées dans des études antérieures sur la capacité des capteurs optiques embarqués sur les satellites à détecter la dynamique de la phénologie, nous avons compilé sur une période de 12 années divers indices de végétation corrigés des effets bi-directionnels de variation des angles d’acquisition (BRDF). Ces indices sont issus de 2 capteurs optiques: SPOT VEGETATION, et MODIS (MODerate resolution Imaging Spectroradiometer). Les données ont été analysées pour évaluer les tendances saisonnières à l'échelle de l’ensemble de la Guyane et également sur quatre sites répartis sur ce territoire. Les données révèlent que les forêts de Guyane présentent un patron de saisonnalité. Le pic annuel des divers indices au cours de la période de septembre à octobre est interprété comme le reflet d’un pic de production de feuilles pendant la saison sèche.

Sign in / Sign up

Export Citation Format

Share Document