scholarly journals Productivity of fodder areas according to Terra Modis data

2019 ◽  
Vol 49 (4) ◽  
pp. 32-41
Author(s):  
E. Yu. Zhukova ◽  
I. N. Barsukova ◽  
A. A. Zhukov
Keyword(s):  
Primary Production ◽  
Vegetation Index ◽  
Gross Primary Production ◽  
Weather Conditions ◽  
Growing Season ◽  
Vegetation Monitoring ◽  
Plant Associations ◽  
Current State ◽  
Maximum Period ◽  
Terra Modis

A quantitative assessment of the current state of natural fodder areas located in the Turano-Uyuk basin (Tuva) was made. Vegetation monitoring was carried out on the basis of Terra Modis satellite data by the following indicators: normalized vegetation index, gross primary production (GPP) and evapotranspiration. The productivity of plant associations was compared, their growth rate and the degree of GPP dependence on the sum of temperatures and evapotranspiration were determined. The results of ground-based studies performed by generally accepted methods were used for verifi cation. Remote indicators of gross production for the growing season ranged from 33.3 t/ha for halophytic meadows, and up to 48.8 t/ ha for wetland habitats. Depending on the species composition, gross productivity of glycophytic meadows during the growing season was 39.9– 48.7 t/ ha. A comparison of the data showed signifi cant differences in the remote and actual productivity of fodder areas, which can be leveled by means of correlation with the ground-based indicators. The best results of the relationship between gross primary production and the vegetation index with the sum of positive temperatures were identifi ed by polynomial equations of the third degree. The maximum period of phytomass development of natural fodder areas (meadow communities) was recorded before the beginning of June. Biological and environmental differences in the growth of vegetation during the season were noted in the period from 10-11 June to 19-20 July. The decrease in the accumulation of gross primary production by mid-July and the end of September was caused by weather conditions. The optimal grazing periods in the meadows in the Turano-Uyuk basin were determined.

scholarly journals Can vegetation index track the interannual variation in gross primary production of temperate deciduous forests?

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Fan Liu ◽  
Chuankuan Wang ◽  
Xingchang Wang
Keyword(s):  
Primary Production ◽  
Vegetation Index ◽  
Near Infrared ◽  
Deciduous Forest ◽  
Gross Primary Production ◽  
Growing Season ◽  
Temperate Deciduous Forest ◽  
Near Infrared Reflectance ◽  
Modis Ndvi ◽  
Temperate Deciduous

Abstract Background Vegetation indices (VIs) by remote sensing are widely used as simple proxies of the gross primary production (GPP) of vegetation, but their performances in capturing the inter-annual variation (IAV) in GPP remain uncertain. Methods We evaluated the performances of various VIs in tracking the IAV in GPP estimated by eddy covariance in a temperate deciduous forest of Northeast China. The VIs assessed included the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), and the near-infrared reflectance of vegetation (NIRv) obtained from tower-radiometers (broadband) and the Moderate Resolution Imaging Spectroradiometer (MODIS), respectively. Results We found that 25%–35% amplitude of the broadband EVI tracked the start of growing season derived by GPP (R2: 0.56–0.60, bias < 4 d), while 45% (or 50%) amplitudes of broadband (or MODIS) NDVI represented the end of growing season estimated by GPP (R2: 0.58–0.67, bias < 3 d). However, all the VIs failed to characterize the summer peaks of GPP. The growing-season integrals but not averaged values of the broadband NDVI, MODIS NIRv and EVI were robust surrogates of the IAV in GPP (R2: 0.40–0.67). Conclusion These findings illustrate that specific VIs are effective only to capture the GPP phenology but not the GPP peak, while the integral VIs have the potential to mirror the IAV in GPP.

scholarly journals Modelling spatial and temporal dynamics of gross primary production in the Sahel from earth-observation-based photosynthetic capacity and quantum efficiency

2017 ◽  
Vol 14 (5) ◽  
pp. 1333-1348 ◽  
Author(s):  
Torbern Tagesson ◽  
Jonas Ardö ◽  
Bernard Cappelaere ◽  
Laurent Kergoat ◽  
Abdulhakim Abdi ◽  
...  
Keyword(s):  
Primary Production ◽  
Quantum Efficiency ◽  
Vegetation Index ◽  
Photosynthetic Capacity ◽  
Gross Primary Production ◽  
Earth Observation ◽  
Arid Ecosystems ◽  
Spatially Explicit ◽  
Equivalent Water Thickness ◽  
Semi Arid

Abstract. It has been shown that vegetation growth in semi-arid regions is important to the global terrestrial CO2 sink, which indicates the strong need for improved understanding and spatially explicit estimates of CO2 uptake (gross primary production; GPP) in semi-arid ecosystems. This study has three aims: (1) to evaluate the MOD17A2H GPP (collection 6) product against GPP based on eddy covariance (EC) for six sites across the Sahel; (2) to characterize relationships between spatial and temporal variability in EC-based photosynthetic capacity (Fopt) and quantum efficiency (α) and vegetation indices based on earth observation (EO) (normalized difference vegetation index (NDVI), renormalized difference vegetation index (RDVI), enhanced vegetation index (EVI) and shortwave infrared water stress index (SIWSI)); and (3) to study the applicability of EO upscaled Fopt and α for GPP modelling purposes. MOD17A2H GPP (collection 6) drastically underestimated GPP, most likely because maximum light use efficiency is set too low for semi-arid ecosystems in the MODIS algorithm. Intra-annual dynamics in Fopt were closely related to SIWSI being sensitive to equivalent water thickness, whereas α was closely related to RDVI being affected by chlorophyll abundance. Spatial and inter-annual dynamics in Fopt and α were closely coupled to NDVI and RDVI, respectively. Modelled GPP based on Fopt and α upscaled using EO-based indices reproduced in situ GPP well for all except a cropped site that was strongly impacted by anthropogenic land use. Upscaled GPP for the Sahel 2001–2014 was 736 ± 39 g C m−2 yr−1. This study indicates the strong applicability of EO as a tool for spatially explicit estimates of GPP, Fopt and α; incorporating EO-based Fopt and α in dynamic global vegetation models could improve estimates of vegetation production and simulations of ecosystem processes and hydro-biochemical cycles.

scholarly journals Satellites reveal an increase in gross primary production in a greenlandic high arctic fen 1992–2008

2010 ◽  
Vol 7 (1) ◽  
pp. 1101-1129 ◽  
Author(s):  
T. Tagesson ◽  
M. Mastepanov ◽  
M. P. Tamstorf ◽  
L. Eklundh ◽  
P. Schubert ◽  
...  
Keyword(s):  
Primary Production ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Gross Primary Production ◽  
Field Measurements ◽  
High Arctic ◽  
Research Area ◽  
Strong Increase ◽  
Co2 Uptake ◽  
Flux Measurements

Abstract. Arctic wetlands play a key role in the terrestrial carbon cycle. Recent studies have shown a greening trend and indicated an increase in CO2 uptake in boreal and sub- to low-arctic areas. Our aim was to combine satellite-based normalized difference vegetation index (NDVI) with ground-based flux measurements of CO2 to investigate a possible greening trend and potential changes in gross primary production (GPP) between 1992 and 2008 in a high arctic fen area. The study took place in Rylekaerene in the Zackenberg Research Area (74°28' N 20°34' W), located in the National park of North Eastern Greenland. We estimated the light use efficiency (ε) for the dominant vegetation types from field measured fractions of photosynthetic active radiation (FAPAR) and ground-based flux measurements of GPP. Measured FAPAR were correlated to satellite-based NDVI. The FAPAR-NDVI relationship in combination with ε was applied to satellite data to model GPP 1992–2008. The model was evaluated against field measured GPP. The model was a useful tool for up-scaling GPP and all basic requirements for the model were well met, e.g., FAPAR was well correlated to NDVI and modeled GPP was well correlated to field measurements. The studied high arctic fen area has experienced a strong increase in GPP between 1992 and 2008. The area has during this period also experienced a substantial increase in local air temperature. Consequently, the observed greening trend is most likely due to ongoing climatic change possibly in combination with CO2 fertilization, due to increasing atmospheric concentrations of CO2.

scholarly journals Estimation of Carbon Fluxes from Eddy Covariance Data and Satellite-Derived Vegetation Indices in a Karst Grassland (Podgorski Kras, Slovenia)

2019 ◽  
Vol 11 (6) ◽  
pp. 649 ◽  
Author(s):  
Koffi Noumonvi ◽  
Mitja Ferlan ◽  
Klemen Eler ◽  
Giorgio Alberti ◽  
Alessandro Peressotti ◽  
...  
Keyword(s):  
Linear Relationship ◽  
Eddy Covariance ◽  
Vegetation Index ◽  
Gross Primary Production ◽  
Vegetation Indices ◽  
Information Criterion ◽  
Growing Season ◽  
Coefficient Of Determination ◽  
Regression Equations ◽  
Eddy Covariance Method

The Eddy Covariance method (EC) is widely used for measuring carbon (C) and energy fluxes at high frequency between the atmosphere and the ecosystem, but has some methodological limitations and a spatial restriction to an area, called a footprint. Remotely sensed information is usually used in combination with eddy covariance data in order to estimate C fluxes over larger areas. In fact, spectral vegetation indices derived from available satellite data can be combined with EC measurements to estimate C fluxes outside of the tower footprint. Following this approach, the present study aimed to model C fluxes for a karst grassland in Slovenia. Three types of model were considered: (1) a linear relationship between Net Ecosystem Exchange (NEE) or Gross Primary Production (GPP) and each vegetation index; (2) a linear relationship between GPP and the product of a vegetation index with PAR (Photosynthetically Active Radiation); and (3) a simplified LUE (Light Use-Efficiency) model assuming a constant LUE. We compared the performance of several vegetation indices derived from two remote platforms (Landsat and Proba-V) as predictors of NEE and GPP, based on three accuracy metrics, the coefficient of determination (R2), the Root Mean Square Error (RMSE) and the Akaike Information Criterion (AIC). Two types of aggregation of flux data were explored: midday average and daily average fluxes. The vapor pressure deficit (VPD) was used to separate the growing season into two phases, a wet and a dry phase, which were considered separately in the modelling process, in addition to the growing season as a whole. The results showed that NDVI is the best predictor of GPP and NEE during the wet phase, whereas water-related vegetation indices, namely LSWI and MNDWI, were the best predictors during the dry phase, both for midday and daily aggregates. Model 1 (linear relationship) was found to be the best in many cases. The best regression equations obtained were used to map GPP and NEE for the whole study area. Digital maps obtained can practically contribute, in a cost-effective way to the management of karst grasslands.

scholarly journals Eddy covariance carbon flux in a scrub in the Mexican highland

2020 ◽  
Author(s):  
Aurelio Guevara-Escobar ◽  
Enrique González-Sosa ◽  
Mónica Cervantes-Jiménez ◽  
Humberto Suzán-Azpiri ◽  
Mónica Elisa Queijeiro-Bolaños ◽  
...  
Keyword(s):  
Primary Production ◽  
Eddy Covariance ◽  
Vegetation Index ◽  
Carbon Sink ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Net Ecosystem Exchange ◽  
R Package ◽  
Dark Cycle ◽  
Remote Sensors

Abstract. Vegetation fixes C in its biomass through photosynthesis or might release it into the atmosphere through respiration. Measurements of these fluxes would help us understand ecosystem functioning. The eddy covariance technique (EC) is widely used to measure the net ecosystem exchange of C (NEE) which is the balance between gross primary production (GPP) and ecosystem respiration (Reco). Orbital satellites such as MODIS can also provide estimates of GPP. In this study, we measured NEE with the EC in a scrub at Bernal in Mexico, and then partitioned into gross primary production (GPP-EC) and Reco using the recent R package Reddyproc. Measurements of GPP-EC were related to the estimates from the MODIS satellite provided in product MOD17A2H, which contains data of the gross primary productivity (GPP-MODIS). The Bernal site was a carbon sink despite it was an overgrazed site, the average NEE during fifteen months of 2017 and 2018 was −0.78 g C m−2 d−1 and the flux was negative in all measured months. The GPP-MODIS underestimated the ground data when representing the relation with a Theil-Sen regression: GPP-EC = 1.866 + 1.861 GPP-MODIS; an ordinary less squares regression had similar coefficients and the R2 was 0.6. Although cacti (CAM), legume shrubs (C3) and herbs (C3) had a similar vegetation index, the nighttime flux was characterized by positive NEE suggesting that the photosynthetic dark-cycle flux of cacti was lower than Reco. The discrepancy among the GPP flux estimates stresses the need to understand the limitations of EC and remote sensors, while incorporating complementary monitoring and modelling schemes of nighttime Reco, particularly in the presence of species with different photosynthetic cycles.

scholarly journals Relationships between primary production and crop yields in semi-arid and arid irrigated agro-ecosystems

2015 ◽  
Vol XL-7/W3 ◽  
pp. 27-30 ◽  
Author(s):  
H. H. Jaafar ◽  
F. A. Ahmad
Keyword(s):  
Primary Production ◽  
Crop Yield ◽  
Vegetation Index ◽  
Crop Yields ◽  
Gross Primary Production ◽  
Remotely Sensed ◽  
Early Assessment ◽  
Food Shortages ◽  
Semi Arid ◽  
Summer Crop

In semi-arid areas within the MENA region, food security problems are the main problematic imposed. Remote sensing can be a promising too early diagnose food shortages and further prevent the population from famine risks. This study is aimed at examining the possibility of forecasting yield before harvest from remotely sensed MODIS-derived Enhanced Vegetation Index (EVI), Net photosynthesis (net PSN), and Gross Primary Production (GPP) in semi-arid and arid irrigated agro-ecosystems within the conflict affected country of Syria. Relationships between summer yield and remotely sensed indices were derived and analyzed. Simple regression spatially-based models were developed to predict summer crop production. The validation of these models was tested during conflict years. A significant correlation (p<0.05) was found between summer crop yield and EVI, GPP and net PSN. Results indicate the efficiency of remotely sensed-based models in predicting summer yield, mostly for cotton yields and vegetables. Cumulative summer EVI-based model can predict summer crop yield during crisis period, with deviation less than 20% where vegetables are the major yield. This approach prompts to an early assessment of food shortages and lead to a real time management and decision making, especially in periods of crisis such as wars and drought.

scholarly journals Long-term drainage reduces CO<sub>2</sub> uptake and increases CO<sub>2</sub> emission on a Siberian floodplain due to shifts in vegetation community and soil thermal characteristics

2016 ◽  
Vol 13 (14) ◽  
pp. 4219-4235 ◽  
Author(s):  
Min Jung Kwon ◽  
Martin Heimann ◽  
Olaf Kolle ◽  
Kristina A. Luus ◽  
Edward A. G. Schuur ◽  
...  
Keyword(s):  
Primary Production ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Thermal Characteristics ◽  
Growing Season ◽  
Co2 Uptake ◽  
Vegetation Community ◽  
Uptake Rates ◽  
Soil Temperatures

Abstract. With increasing air temperatures and changing precipitation patterns forecast for the Arctic over the coming decades, the thawing of ice-rich permafrost is expected to increasingly alter hydrological conditions by creating mosaics of wetter and drier areas. The objective of this study is to investigate how 10 years of lowered water table depths of wet floodplain ecosystems would affect CO2 fluxes measured using a closed chamber system, focusing on the role of long-term changes in soil thermal characteristics and vegetation community structure. Drainage diminishes the heat capacity and thermal conductivity of organic soil, leading to warmer soil temperatures in shallow layers during the daytime and colder soil temperatures in deeper layers, resulting in a reduction in thaw depths. These soil temperature changes can intensify growing-season heterotrophic respiration by up to 95 %. With decreased autotrophic respiration due to reduced gross primary production under these dry conditions, the differences in ecosystem respiration rates in the present study were 25 %. We also found that a decade-long drainage installation significantly increased shrub abundance, while decreasing Eriophorum angustifolium abundance resulted in Carex sp. dominance. These two changes had opposing influences on gross primary production during the growing season: while the increased abundance of shrubs slightly increased gross primary production, the replacement of E. angustifolium by Carex sp.  significantly decreased it. With the effects of ecosystem respiration and gross primary production combined, net CO2 uptake rates varied between the two years, which can be attributed to Carex-dominated plots' sensitivity to climate. However, underlying processes showed consistent patterns: 10 years of drainage increased soil temperatures in shallow layers and replaced E. angustifolium by Carex sp., which increased CO2 emission and reduced CO2 uptake rates. During the non-growing season, drainage resulted in 4 times more CO2 emissions, with high sporadic fluxes; these fluxes were induced by soil temperatures, E. angustifolium abundance, and air pressure.

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