Performance of LAI‐MODIS and the influence on drought simulation in a Mediterranean forest

Chakroun, Hédia; Mouillot, Florent; Nasr, Z.; Nouri, Milad; Ennajah, Amel; Ourcival, Jean‐Marc

doi:10.1002/eco.1426

Cited by 17 publications

(14 citation statements)

References 82 publications

(112 reference statements)

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“…We compared the three MODIS LAI products to measured plots of LAI over the study region of Kroumirie in 2006 (refer to [44] for a detailed explanation of LAI measurements). The least RMSE was obtained with TERRA (RMSE = 2.36), compared to AQUA (RMSE = 3.24) and to TERRA/AQUA (RMSE = 3.49).…”

Section: Modis Images Processingmentioning

confidence: 99%

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Regional Equivalent Water Thickness Modeling from Remote Sensing across a Tree Cover/LAI Gradient in Mediterranean Forests of Northern Tunisia

2015

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Abstract:The performance of vegetation indexes derived from moderate resolution imaging spectroradiometer (MODIS) sensors is explored for drought monitoring in the forests of Northern Tunisia; representing a transition zone between the Mediterranean Sea and the Sahara Desert. We investigated the suitability of biomass and moisture vegetation indexes for vegetation water content expressed by the equivalent water thickness (EWT) in a Mediterranean forest ecosystem with contrasted water budgets and desiccation rates. We proposed a revised EWT at canopy level (EWTCAN) based on weekly field measurements of fuel moisture in seven species during the 2010 dry period, considering the mixture of plant functional types for water use (trees, shrubs and herbaceous layers) and a varying vegetation cover. MODIS vegetation indexes computed and smoothed over the dry season were highly correlated with the EWTCAN. The performances of moisture indexes Normalized Difference Infrared Index (NDII6 and NDII7) and Global Moisture Vegetation Index (GVMI6 and GVMI7) were comparable, whereas for biomass vegetation indexes, Normalized Difference 1938Vegetation Index (NDVI), Modified Soil Adjusted Vegetation Index (MSAVI) and Adjusted Normalized Difference Vegetation Index (ANDVI) performed better than Enhanced Vegetation Index (EVI) and Soil Adjusted Vegetation Index (SAVI). We also identified the effect of Leaf Area Index (LAI) on EWTCAN monitoring at the regional scale under the tree cover/LAI gradient of the region from relatively dense to open forest. Statistical analysis revealed a significant decreasing linear relationship; indicating that for LAI less than two, the greater the LAI, the less responsive are the vegetation indexes to changes in EWTCAN; whereas for higher LAI, its influence becomes less significant and was not considered in the inversion models based on vegetation indexes. The EWTCAN time-course from LAI-adapted inversion models based on significantly-related vegetation indexes to EWTCAN showed close profiles resulting from the inversion models using NDVI, ANDVI, MSAVI and NDII6 applied during the dry season. The developed EWTCAN model from MODIS vegetation indexes for the study region was finally tested for its ability to capture the topo-climatic effects on the seasonal and the spatial patterns of desiccation/rewetting for keystone periods of Mediterranean vegetation functioning. Implications for further use in scientific developments or management are discussed.

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Section: Modis Images Processingmentioning

confidence: 99%

“…However, the RMSE value remained high even for the TERRA product, especially for highly-covered plots (NDVI > 0.6). Thus, we suggested a calibration method for the TERRA-MODIS LAI product based on both ground measurements and SPOT images that were used as ground truth LAI maps (refer to [44] for the calibration process details).…”

Section: Modis Images Processingmentioning

confidence: 99%

Regional Equivalent Water Thickness Modeling from Remote Sensing across a Tree Cover/LAI Gradient in Mediterranean Forests of Northern Tunisia

2015

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“…The study area is situated in the Bellif national forest, located in the North Western part of Tunisia (North Africa, Southern bound of the Mediterranean basin) in the Nefza forest subdivision (Figure 1), claimed to be the most productive cork oak forest in Tunisia [40,41], due to fertile soils, mild temperatures, and heavy rainfall on its coastal foothills [42]. The climate is Mediterranean sub-humid, characterized by hot and dry summers and mild and wet winters.…”

Section: Study Sitementioning

confidence: 99%

“…We used this model to extrapolate measured soil respiration values to the entire period of our experiment and get the annual carbon flux. SWC was then simulated on a daily time step for the 0-30 cm top soil layer from meteorological variables and soil texture following Mouillot et al [55] (and further used in the region [42]) and validated against soil moisture measurements. T was modelled from registered air temperature at the Nefza meteorological station and following the linear regression T = α × Tair + β.…”

Section: Soil Respiration Modellingmentioning

confidence: 99%

Warm and Fertile Sub-Humid Conditions Enhance Litterfall to Sustain High Soil Respiration Fluxes in a Mediterranean Cork Oak Forest

Zribi

Mouillot

Gharbi

et al. 2015

Forests

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Soil respiration is a major component of the global carbon budget and Mediterranean ecosystems have usually been studied in locations with shallow soils, mild temperatures, and a prolonged dry season. This study investigates seasonal soil respiration rates and underlying mechanisms under wetter, warmer, and more fertile conditions in a Mediterranean cork oak forest of Northern Tunisia (Africa), acknowledged as one of the most productive forests in the Mediterranean basin. We applied a soil respiration model based on soil temperature and relative water content and investigated how ecosystem functioning under these favorable conditions affected soil carbon storage through carbon inputs to the soil litter. Annual soil respiration rates varied between 1774 gC m −2 year −1 and 2227 gC m −2 year −1 , which is on the highest range of observations under Mediterranean climate conditions. We attributed this high soil carbon flux as a response to favorable temperatures and soil water content, but this could be sustained only by a small carbon allocation to roots (root/shoot ratio = 0.31-0.41) leading to a large allocation to leaves OPEN ACCESSForests 2015, 6 2919 with a multiannual leaf production, enhanced annual twig elongation (11.5-28.5 cm) with a reduced leaf life span (<1 year) maintaining a low LAI (1.68-1.88) and generating a high litterfall (386-636 gC m −2 year −1 ). Thus, the favorable climatic and edaphic conditions experienced by these Mediterranean cork oak forests drove high soil respiration fluxes which balanced the high carbon assimilation leading to a relatively small overall contribution (10.96-14.79 kgC m −2 ) to soil carbon storage.

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“…In the southern shore of the Mediterranean basin known as one of the most exposed regions to climate changes [4], there is a need of consistent drought monitoring to ensure a balanced ecohydrological functioning and to help mitigate climate changes effects. In [5] hydric stress and drought impacts on ecohydrologic balance were studied in a forested ecosystem of northern Tunisia.…”

Section: Introductionmentioning

confidence: 99%

Quality Assessment of MODIS Time Series Images and the Effect on Drought Monitoring

Chakroun¹

2017

OJAppS

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Drought Monitoring by remotely sensed moisture vegetation indexes is being an active research subject as the vegetation spectral responses are showed to be highly correlated to water content. The MODIS (MODerate resolution Imaging Spectro-radiometer) sensor of the Terra satellite provides MOD09A1 product of BRDF (Bidirectional Reflectance Distribution Function) used in computing moisture vegetation indexes (MVI). The exploration of an MVI time-series in the Kroumirie forest in Northern Tunisia showed important noise due to both clouds contamination and sensor defaults that had to be removed. Amongst methods for removing these imperfections, TIMESAT tool was designed for correcting time-series of satellite data and also to retrieve seasonal parameters from smoothed vegetation indexes. The methodology of smoothing functions to fit the time series data is based on two stages. First, a least square fit to the upper envelope of the vegetation indices series is applied. The second stage is achieved by local and adaptive fitting functions. The corrections have been made by spikes removal due to abrupt change of MVI variations and by fitting the MVI time-series to the upper envelop to correct the negative biases of remote sensing vegetation indexes. The adaptive SavitskyGolay function filter compared to local filtering process produces variations that conserve local variations for all the tested MVI. Seasonal vegetation parameters were extracted for each year of the time-series analysis and compared to the Standardized Precipitation Index (SPI) calculated at meteorological station level and for different time scales. Positive relations were found between SPI and the seasonal parameters expressed by the length and the amplitude of the season, indicating MODIS derived MVI sensitivity to water deficit or surplus conditions. The 6-month SPI showed the best performance when related to water sensitive indexes suggesting that MODIS derived indexes are more correlated to the precipitation variations over seasons.

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Performance of LAI‐MODIS and the influence on drought simulation in a Mediterranean forest

Cited by 17 publications

References 82 publications

Regional Equivalent Water Thickness Modeling from Remote Sensing across a Tree Cover/LAI Gradient in Mediterranean Forests of Northern Tunisia

Regional Equivalent Water Thickness Modeling from Remote Sensing across a Tree Cover/LAI Gradient in Mediterranean Forests of Northern Tunisia

Warm and Fertile Sub-Humid Conditions Enhance Litterfall to Sustain High Soil Respiration Fluxes in a Mediterranean Cork Oak Forest

Quality Assessment of MODIS Time Series Images and the Effect on Drought Monitoring

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