scholarly journals Deriving Vegetation Dynamics of Natural Terrestrial Ecosystems from MODIS NDVI/EVI Data over Turkey

Sensors ◽  
2008 ◽  
Vol 8 (9) ◽  
pp. 5270-5302 ◽  
Author(s):  
Fatih Evrendilek ◽  
Onder Gulbeyaz
Keyword(s):  
Vegetation Dynamics ◽  
Terrestrial Ecosystems ◽  
Modis Ndvi

scholarly journals Interactive impacts of fire and vegetation dynamics on global carbon and water budget using Community Land Model version 4.5

2019 ◽  
Vol 12 (1) ◽  
pp. 457-472 ◽  
Author(s):  
Hocheol Seo ◽  
Yeonjoo Kim
Keyword(s):  
Vegetation Dynamics ◽  
Vegetation Type ◽  
Soil Layer ◽  
Terrestrial Ecosystems ◽  
Water Fluxes ◽  
Moisture Profile ◽  
Community Land Model ◽  
Model Version ◽  
Global Increase ◽  
Induced Changes

Abstract. Fire plays an important role in terrestrial ecosystems. The burning of biomass affects carbon and water fluxes and vegetation distribution. To understand the effect of interactive processes of fire and ecological succession on surface carbon and water fluxes, this study employed the Community Land Model version 4.5 to conduct a series of experiments that included and excluded fire and dynamic vegetation processes. Results of the experiments that excluded the vegetation dynamics showed a global increase in net ecosystem production (NEP) in post-fire regions, whereas the inclusion of vegetation dynamics revealed a fire-induced decrease in NEP in some regions, which was depicted when the dominant vegetation type was changed from trees to grass. Carbon emissions from fires are enhanced by reduction in NEP when vegetation dynamics are considered; however, this effect is somewhat mitigated by the increase in NEP when vegetation dynamics are not considered. Fire-induced changes in vegetation modify the soil moisture profile because grasslands are more dominant in post-fire regions. This results in less moisture within the top soil layer than that in unburned regions, even though transpiration is reduced overall. These findings are different from those of previous fire model evaluations that ignored vegetation dynamics and thus highlight the importance of interactive processes between fires and vegetation dynamics in evaluating recent model developments.

scholarly journals GRASSLAND NPP MONITORING BASED ON MULTI-SOURCE REMOTE SENSING DATA FUSION

2018 ◽  
Vol XLII-3 ◽  
pp. 113-118
Author(s):  
Y. R. Cai ◽  
J. H. Zheng ◽  
M. J. Du ◽  
C. Mu ◽  
J. Peng
Keyword(s):  
Carbon Cycle ◽  
Primary Productivity ◽  
Vegetation Index ◽  
Net Primary Productivity ◽  
Terrestrial Ecosystem ◽  
Remote Sensing Data ◽  
Terrestrial Ecosystems ◽  
The United States ◽  
Estimation Accuracy ◽  
Modis Ndvi

Vegetation is an important part of the terrestrial ecosystem. It plays an important role in the energy and material exchange of the ground-atmosphere system and is a key part of the global carbon cycle process.Climate change has an important influence on the carbon cycle of terrestrial ecosystems. Net Primary Productivity (Net Primary Productivity)is an important parameter for evaluating global terrestrial ecosystems. For the Xinjiang region, the study of grassland NPP has gradually become a hot issue in the ecological environment.Increasing the estimation accuracy of NPP is of great significance to the development of the ecosystem in Xinjiang. Based on the third-generation GIMMS AVHRR NDVI global vegetation dataset and the MODIS NDVI (MOD13A3) collected each month by the United States Atmospheric and Oceanic Administration (NOAA),combining the advantages of different remotely sensed datasets, this paper obtained the maximum synthesis fusion for New normalized vegetation index (NDVI) time series in 2006–2015.Analysis of Net Primary Productivity of Grassland Vegetation in Xinjiang Using Improved CASA Model The method described in this article proves the feasibility of applying data processing, and the accuracy of the NPP calculation using the fusion processed NDVI has been greatly improved. The results show that: (1) The NPP calculated from the new normalized vegetation index (NDVI) obtained from the fusion of GIMMS AVHRR NDVI and MODIS NDVI is significantly higher than the NPP calculated from these two raw data; (2) The grassland NPP in Xinjiang Interannual changes show an overall increase trend; interannual changes in NPP have a certain relationship with precipitation.

scholarly journals Global Evaluation of the Ecosystem Demography Model (ED v3.0)

2021 ◽  
Author(s):  
Lei Ma ◽  
George Hurtt ◽  
Lesley Ott ◽  
Ritvik Sahajpal ◽  
Justin Fisk ◽  
...  
Keyword(s):  
Vegetation Dynamics ◽  
Gross Primary Production ◽  
Critical Role ◽  
Terrestrial Ecosystems ◽  
Global Evaluation ◽  
Ecological Processes ◽  
Modelling Framework ◽  
Global Calibration ◽  
Global Patterns ◽  
Uncertain Future

Abstract. Terrestrial ecosystems play a critical role in the global carbon cycle but have highly uncertain future dynamics. Ecosystem modelling that includes the scaling-up of underlying mechanistic ecological processes has the potential  to improve the accuracy of future projections, while retaining key process-level detail. Over the past two decades,  multiple modelling advances have been made to meet this challenge, including the Ecosystem Demography (ED)  model and its derivatives including ED2 and FATES. Here, we present the global evaluation of the Ecosystem  Demography model (ED v3.0), which likes its predecessors features the formal scaling of physiological processes of  individual-based vegetation dynamics to ecosystem scales, together with integrated submodules of soil  biogeochemistry and soil hydrology, while retaining explicit tracking of vegetation 3-D structure. This new version  builds on previous versions and provides the first global calibration and evaluation, global tracking of the effects of  climate and land-use change on vegetation 3-D structure, new spin-up process and input datasets, as well as  numerous other advances. Model evaluation was performed with respect to a set of important benchmarking  datasets, and model estimates were within observational constraints for multiple key variables including: (i) global  patterns of dominant plant functional types (broadleaf vs evergreen); (ii) spatial distribution, seasonal cycle, and  interannual trends of global Gross Primary Production (GPP); (iii) global interannual variability of Net Biome  Production (NBP); and (iv) global patterns of vertical structure including leaf area and canopy height. With this  global model version, it is now possible to simulate vegetation dynamics from local to global scales and from seconds to centuries, with a consistent mechanistic modelling framework amendable to data from multiple  traditional and new remote sensing sources, including lidar.

Augmenting the multiscale hydrologic modeling system with adequate vegetation dynamics for improved representation of coupled water and carbon cycles

2020 ◽  
Author(s):  
Bahar Bahrami ◽  
Rohini Kumar ◽  
Stephan Thober ◽  
Corinna Rebmann ◽  
Rico Fischer ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Vegetation Dynamics ◽  
Net Primary Productivity ◽  
Water Cycle ◽  
Terrestrial Ecosystems ◽  
Carbon Fluxes ◽  
Low Complexity ◽  
Hydrologic Model ◽  
Model Concept ◽  
Projected Changes

<p>As climate is changing, future functionality and resilience of terrestrial ecosystems are expected to change in numerous ways. However, these projected changes remain uncertain. One of the major sources of uncertainty is the representation of vegetation dynamics which directly respond to increased temperature and ambient CO2 concentrations and thereby alter transpiration. Many of the existing hydrologic models representing components of the water cycle have a very simplified representation of vegetation dynamics that are not able to represent this link.  In this study we aim to augment the existing mesoscale Hydrologic Model (mHM) with a low complexity dynamic vegetation model (DVM). This will provide the model with improved capabilities to represent the coupled water and carbon fluxes. Our analyses focus on representing the vegetation (i.e. biomass growth) including fluxes such as gross and net primary productivity and their inter-linkages to water storage and fluxes (e.g., soil moisture and evapotranspiration) across biomes (e.g., grasslands). These inter-linkages, which are spatially and temporally variable and scale-related, are crucial for adequately representing the coupled water and carbon cycle. For example, the adequate representation of soil moisture is essential to capture the mechanistic response of plant productivity to changes in soil moisture; and vice versa especially under extreme environmental conditions. In this presentation, we will discuss the simplified structure of the DVM based on a Light Use Efficiency (LUE) model concept and couple the model components to the mHM. Furthermore, the coupled simulation results of different water and carbon fluxes will be presented for a test region in Central Germany.   </p>

scholarly journals Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data

2011 ◽  
Vol 8 (11) ◽  
pp. 3359-3373 ◽  
Author(s):  
C. Höpfner ◽  
D. Scherer
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Vegetation Dynamics ◽  
Time Series Data ◽  
Series Data ◽  
Land Cover Types ◽  
Modis Ndvi ◽  
Ndvi Time Series ◽  
Western Morocco ◽  
North Western

Abstract. Vegetation phenology as well as the current variability and dynamics of vegetation and land cover, including its climatic and human drivers, are examined in a region in north-western Morocco that is nearly 22 700 km2 big. A gapless time series of Normalized Differenced Vegetation Index (NDVI) composite raster data from 29 September 2000 to 29 September 2009 is utilised. The data have a spatial resolution of 250 m and were acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The presented approach allows to compose and to analyse yearly land cover maps in a widely unknown region with scarce validated ground truth data by deriving phenological parameters. Results show that the high temporal resolution of 16 d is sufficient for (a) determining local land cover better than global land cover classifications of Plant Functional Types (PFT) and Global Land Cover 2000 (GLC2000) and (b) for drawing conclusions on vegetation dynamics and its drivers. Areas of stably classified land cover types (i.e. areas that did not change their land cover type) show climatically driven inter- and intra-annual variability with indicated influence of droughts. The presented approach to determine human-driven influence on vegetation dynamics caused by agriculture results in a more than ten times larger area compared with stably classified areas. Change detection based on yearly land cover maps shows a gain of high-productive vegetation (cropland) of about 259.3 km2. Statistically significant inter-annual trends in vegetation dynamics during the last decade could however not be discovered. A sequence of correlations was respectively carried out to extract the most important periods of rainfall responsible for the production of green biomass and for the extent of land cover types. Results show that mean daily precipitation from 1 October to 15 December has high correlation results (max. r2=0.85) on an intra-annual time scale to NDVI percentiles (50 %) of land cover types. Correlation results of mean daily precipitation from 16 September to 15 January and percentage of yearly classified area of each land cover type are medium up to high (max. r2=0.64). In all, an offset of nearly 1.5 months is detected between precipitation rates and NDVI values. High-productive vegetation (cropland) is proved to be mainly rain-fed. We conclude that identification, understanding and knowledge about vegetation phenology, and current variability of vegetation and land cover, as well as prediction methods of land cover change, can be improved using multi-year MODIS NDVI time series data. This study enhances the comprehension of current land surface dynamics and variability of vegetation and land cover in north-western Morocco. It especially offers a quick access when estimating the extent of agricultural lands.

scholarly journals Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data

2011 ◽  
Vol 8 (2) ◽  
pp. 3953-3998 ◽  
Author(s):  
C. Höpfner ◽  
D. Scherer
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Vegetation Dynamics ◽  
Time Series Data ◽  
Series Data ◽  
Land Cover Types ◽  
Modis Ndvi ◽  
Ndvi Time Series ◽  
Western Morocco ◽  
North Western

Abstract. Vegetation phenology as well as current variability and dynamics of vegetation and land cover including its climatic and human drivers are examined in a region in north-western Morocco of nearly 22 700 km2. A gapless time series of Normalized Differenced Vegetation Index (NDVI) composite raster data from 29 September 2000 to 29 September 2009 with a spatial resolution of 250 m and acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor is utilised. The presented approach allows to compose and analyse yearly land cover maps in a widely unknown region with scarce validated ground truth data by deriving phenological parameters. Results show that high temporal resolution of 16 d is sufficient (a) for determining land cover better than global land cover classifications of Plant Functional Types (PFT) and Global Land Cover 2000 (GLC2000), and (b) for drawing conclusions on vegetation dynamics and its drivers. Areas of stably classified land cover types show climatically driven inter- and intra-annual variability with indicated influence of droughts. The presented approach to determine human-driven influence on vegetation dynamics caused by agriculture results in a more than ten times larger area compared to the stably classified areas. Change detection based on yearly land cover maps shows a gain of high-productive vegetation (cropland) of about 259.3 km2. However, statistically significant inter-annual trends in vegetation dynamics during the last decade could not be discovered. A sequence of correlations was done to extract the most important period of rainfall for production of green biomass and for the extent of land cover types, respectively. Results show that mean daily precipitation from 1 October to 15 December has high correlation results (max. r2=0.85) at intra-annual time scale to NDVI percentiles (50%) of land cover types. Correlation results of mean daily precipitation from 16 September to 15 January and percentage of yearly classified area of each land cover type are medium up to high (max. r2=0.64). In all, an offset of nearly 1.5 months is detected between precipitation rates and NDVI in 16 d steps. High-productive vegetation (cropland) is proved to be mainly rain-fed. We conclude that identification, understanding and knowledge about vegetation phenology, and current variability of vegetation and land cover as well as prediction methods of land cover change can be improved using multi-year MODIS NDVI time series data. This study enhances the comprehension of current land surface dynamics and variability of vegetation and land cover in north-western Morocco offering a fast access especially for estimating the extent of agricultural lands.

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