scholarly journals Start of the Green Season and Normalized Difference Vegetation Index in Alaska’s Arctic National Parks

2021 ◽  
Vol 13 (13) ◽  
pp. 2554
Author(s):  
David K. Swanson
Keyword(s):  
National Parks ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Free Surfaces ◽  
Modis Ndvi ◽  
Curve Fit ◽  
Winter Snow ◽  
Systematic Sample ◽  
Low Levels ◽  
Northern Alaska

Daily Normalized Difference Vegetation Index (NDVI) values from the MODIS Aqua and Terra satellites were compared with on-the-ground camera observations at five locations in northern Alaska. Over half of the spring rise in NDVI was due to the transition from the snow-covered landscape to the snow-free surface prior to the deciduous leaf-out. In the fall after the green season, NDVI fluctuated between an intermediate level representing senesced vegetation and lower values representing clouds and intermittent snow, and then dropped to constant low levels after establishment of the permanent winter snow cover. The NDVI value of snow-free surfaces after fall leaf senescence was estimated from multi-year data using a 90th percentile smoothing spline curve fit to a plot of daily NDVI values vs. ordinal date. This curve typically showed a flat region of intermediate NDVI values in the fall that represent cloud- and snow-free days with senesced vegetation. This “fall plateau” was readily identified in a large systematic sample of MODIS NDVI values across the study area, in typical tundra, shrub, and boreal forest environments. The NDVI level of the fall plateau can be extrapolated to the spring rising leg of the annual NDVI curve to approximate the true start of green season.

scholarly journals Phenology-Based Residual Trend Analysis of MODIS-NDVI Time Series for Assessing Human-Induced Land Degradation

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3676 ◽  
Author(s):  
Hao Chen ◽  
Xiangnan Liu ◽  
Chao Ding ◽  
Fang Huang
Keyword(s):  
Trend Analysis ◽  
Land Degradation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growing Season ◽  
Practical Method ◽  
Large Area ◽  
Modis Ndvi ◽  
Daily Precipitation Data ◽  
Improved Model

Land degradation is a widespread environmental issue and an important factor in limiting sustainability. In this study, we aimed to improve the accuracy of monitoring human-induced land degradation by using phenological signal detection and residual trend analysis (RESTREND). We proposed an improved model for assessing land degradation named phenology-based RESTREND (P-RESTREND). This method quantifies the influence of precipitation on normalized difference vegetation index (NDVI) variation by using the bivariate linear regression between NDVI and precipitation in pre-growing season and growing season. The performances of RESTREND and P-RESTREND for discriminating land degradation caused by climate and human activities were compared based on vegetation-precipitation relationship. The test area is in Western Songnen Plain, Northeast China. It is a typical region with a large area of degraded drylands. The MODIS 8-day composite reflectance product and daily precipitation data during 2000–2015 were used. Our results showed that P-RESTREND was more effective in distinguishing different drivers of land degradation than the RESTREND. Degraded areas in the Songnen grasslands can be effectively detected by P-RESTREND. Therefore, this modified model can be regarded as a practical method for assessing human-induced land degradation.

scholarly journals Using satellite data to improve the leaf phenology of a global terrestrial biosphere model

2015 ◽  
Vol 12 (23) ◽  
pp. 7185-7208 ◽  
Author(s):  
N. MacBean ◽  
F. Maignan ◽  
P. Peylin ◽  
C. Bacour ◽  
F.-M. Bréon ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Terrestrial Biosphere ◽  
Modis Ndvi ◽  
Growing Season Length ◽  
Median Correlation ◽  
Temperate Deciduous ◽  
Correct Representation ◽  
Biosphere Model ◽  
Deciduous Plant

Abstract. Correct representation of seasonal leaf dynamics is crucial for terrestrial biosphere models (TBMs), but many such models cannot accurately reproduce observations of leaf onset and senescence. Here we optimised the phenology-related parameters of the ORCHIDEE TBM using satellite-derived Normalized Difference Vegetation Index data (MODIS NDVI v5) that are linearly related to the model fAPAR. We found the misfit between the observations and the model decreased after optimisation for all boreal and temperate deciduous plant functional types, primarily due to an earlier onset of leaf senescence. The model bias was only partially reduced for tropical deciduous trees and no improvement was seen for natural C4 grasses. Spatial validation demonstrated the generality of the posterior parameters for use in global simulations, with an increase in global median correlation of 0.56 to 0.67. The simulated global mean annual gross primary productivity (GPP) decreased by ~ 10 PgC yr−1 over the 1990–2010 period due to the substantially shortened growing season length (GSL – by up to 30 days in the Northern Hemisphere), thus reducing the positive bias and improving the seasonal dynamics of ORCHIDEE compared to independent data-based estimates. Finally, the optimisations led to changes in the strength and location of the trends in the simulated vegetation productivity as represented by the GSL and mean annual fraction of absorbed photosynthetically active radiation (fAPAR), suggesting care should be taken when using un-calibrated models in attribution studies. We suggest that the framework presented here can be applied for improving the phenology of all global TBMs.

scholarly journals Does EO NDVI seasonal metrics capture variations in species composition and biomass due to grazing in semi-arid grassland savannas?

2015 ◽  
Vol 12 (14) ◽  
pp. 4407-4419 ◽  
Author(s):  
J. L. Olsen ◽  
S. Miehe ◽  
P. Ceccato ◽  
R. Fensholt
Keyword(s):  
Time Series ◽  
Species Composition ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Regional Scale ◽  
Grazing Intensity ◽  
Test Site ◽  
Grazing Pressure ◽  
Modis Ndvi ◽  
Coarse Resolution

Abstract. Most regional scale studies of vegetation in the Sahel have been based on Earth observation (EO) imagery due to the limited number of sites providing continuous and long term in situ meteorological and vegetation measurements. From a long time series of coarse resolution normalized difference vegetation index (NDVI) data a greening of the Sahel since the 1980s has been identified. However, it is poorly understood how commonly applied remote sensing techniques reflect the influence of extensive grazing (and changes in grazing pressure) on natural rangeland vegetation. This paper analyses the time series of Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI metrics by comparing it with data from the Widou Thiengoly test site in northern Senegal. Field data include grazing intensity, end of season standing biomass (ESSB) and species composition from sizeable areas suitable for comparison with moderate – coarse resolution satellite imagery. It is shown that sampling plots excluded from grazing have a different species composition characterized by a longer growth cycle as compared to plots under controlled grazing or communal grazing. Also substantially higher ESSB is observed for grazing exclosures as compared to grazed areas, substantially exceeding the amount of biomass expected to be ingested by livestock for this area. The seasonal integrated NDVI (NDVI small integral; capturing only the signal inherent to the growing season recurrent vegetation), derived using absolute thresholds to estimate start and end of growing seasons, is identified as the metric most strongly related to ESSB for all grazing regimes. However plot-pixel comparisons demonstrate how the NDVI/ESSB relationship changes due to grazing-induced variation in annual plant species composition and the NDVI values for grazed plots are only slightly lower than the values observed for the ungrazed plots. Hence, average ESSB in ungrazed plots since 2000 was 0.93 t ha−1, compared to 0.51 t ha−1 for plots subjected to controlled grazing and 0.49 t ha−1 for communally grazed plots, but the average integrated NDVI values for the same period were 1.56, 1.49, and 1.45 for ungrazed, controlled and communal, respectively, i.e. a much smaller difference. This indicates that a grazing-induced development towards less ESSB and shorter-cycled annual plants with reduced ability to turn additional water in wet years into biomass is not adequately captured by seasonal NDVI metrics.

scholarly journals Climate Drivers Linked to Changing Seasonality of Alaska Coastal Tundra Vegetation Productivity

2015 ◽  
Vol 19 (19) ◽  
pp. 1-29 ◽  
Author(s):  
Peter A. Bieniek ◽  
Uma S. Bhatt ◽  
Donald A. Walker ◽  
Martha K. Raynolds ◽  
Josefino C. Comiso ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Sea Breeze ◽  
Tundra Vegetation ◽  
Land Surface Temperatures ◽  
Alaskan Tundra ◽  
Northern Alaska

Abstract The mechanisms driving trends and variability of the normalized difference vegetation index (NDVI) for tundra in Alaska along the Beaufort, east Chukchi, and east Bering Seas for 1982–2013 are evaluated in the context of remote sensing, reanalysis, and meteorological station data as well as regional modeling. Over the entire season the tundra vegetation continues to green; however, biweekly NDVI has declined during the early part of the growing season in all of the Alaskan tundra domains. These springtime declines coincide with increased snow depth in spring documented in northern Alaska. The tundra region generally has warmed over the summer but intraseasonal analysis shows a decline in midsummer land surface temperatures. The midsummer cooling is consistent with recent large-scale circulation changes characterized by lower sea level pressures, which favor increased cloud cover. In northern Alaska, the sea-breeze circulation is strengthened with an increase in atmospheric moisture/cloudiness inland when the land surface is warmed in a regional model, suggesting the potential for increased vegetation to feedback onto the atmospheric circulation that could reduce midsummer temperatures. This study shows that both large- and local-scale climate drivers likely play a role in the observed seasonality of NDVI trends.

scholarly journals Fire Recurrence and Normalized Difference Vegetation Index (NDVI) Dynamics in Brazilian Savanna

Fire ◽  
2018 ◽  
Vol 2 (1) ◽  
pp. 1 ◽  
Author(s):  
Níckolas Santana
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Trend Analysis ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Policy ◽  
Brazilian Savanna ◽  
Vegetation Phenology ◽  
Modis Ndvi ◽  
Fire Recurrence

Fire is one of the main modeling agents of savanna ecosystems, affecting their distribution, physiognomy and species diversity. Changes in the natural fire regime on savannas cause disturbances in the structural characteristics of vegetation. Theses disturbances can be effectively monitored by time series of remote sensing data in different terrestrial ecosystems such as savannas. This study used trend analysis in NDVI (Normalized Difference Vegetation Index)–MODIS (Moderate Resolution Imaging Spectroradiometer) time series to evaluate the influence of different fire recurrences on vegetation phenology of the Brazilian savanna in the period from 2001 to 2016. The trend analysis indicated several factors responsible for changes in vegetation: (a) The absence of fire in savanna phytophysiognomies causes a constant increase in MODIS–NDVI, ranging from 0.001 to 0.002 per year, the moderate presence of fire in these areas does not cause significant changes, while the high recurrence results in decreases of MODIS–NDVI, ranging from −0.002 to −0.008 per year; (b) Forest areas showed a high decrease in NDVI, reaching up to −0.009 MODIS–NDVI per year, but not related to fire recurrence, indicating the high degradation of these phytophysiognomies; (c) Changes in vegetation are highly connected to the protection status of the area, such as areas of integral protection or sustainable use, and consequently their conservation status. Areas with greater vegetation conservation had more than 70% of positive changes in pixels with significant tendencies. Absence or presence of fire are the main agents of vegetation change in areas with lower anthropic influence. These results reinforce the need for a suitable fire management policy for the different types of Cerrado phytophysiognomies, in addition to highlighting the efficiency of remote sensing time series for evaluation of vegetation phenology.

scholarly journals Savannah Phenological Dynamics Reveal Spatio-Temporal Landscape Heterogeneity in Karamoja Sub-region, Uganda

2020 ◽  
Vol 4 ◽  
Author(s):  
Anthony Egeru ◽  
John Paul Magaya ◽  
Derick Ansyijar Kuule ◽  
Aggrey Siya ◽  
Anthony Gidudu ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landscape Heterogeneity ◽  
Global Environmental Change ◽  
Arid Environment ◽  
Modis Ndvi ◽  
Moderate Resolution ◽  
Spatio Temporal ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Phenological Metrics

Phenological properties are critical in understanding global environmental change patterns. This study analyzed phenological dynamics in a savannah dominated semi-arid environment of Uganda. We used moderate-resolution imaging spectroradiometer normalized difference vegetation index (MODIS NDVI) imagery. TIMESAT program was used to analyse the imagery to determine key phenological metrics; onset of greenness (OGT), onset of greenness value, end of greenness time (EGT), end of greenness value, maximum NDVI, time of maximum NDVI, duration of greenup (DOG) and range of normalized difference vegetation index (RNDVI). Results showed that thicket and shrubs had the earliest OGT on day 85 ± 14, EGT on day 244 ± 32 and a DOG of 158 ± 25 days. Woodland had the highest NDVI value for maximum NDVI, OGT, EGT, and RNDVI. In the bushland, OGT occurs on average around day 90 ± 11, EGT on day 255 ± 33 with a DOG of 163 ± 36 days. The grassland showed that OGT occurs on day 96 ± 13, EGT on day 252 ± 36 with a total DOG of 156 ± 33 days. Early photosynthesis activity was observed in central to eastern Karamoja in the districts of Moroto and Kotido. There was a positive relationship between rainfall and NDVI across all vegetation cover types as well as between phenological parameters and season dynamics. Vegetation senescence in the sub-region occurs around August to mid-September (day 244–253). The varied phenophases observed in the sub-region reveal an inherent landscape heterogeneity that is beneficial to extensive pastoral livestock production. Continuous monitoring of savannah phenological patterns in the sub-region is required to decipher landscape ecosystem processes and functioning.

scholarly journals Seasonal Variation of Surface Temperature–Modulating Factors in the Sonoran Desert in Northwestern Mexico

2012 ◽  
Vol 51 (8) ◽  
pp. 1519-1530 ◽  
Author(s):  
Iryna Tereshchenko ◽  
Alexander N. Zolotokrylin ◽  
Tatiana B. Titkova ◽  
Luis Brito-Castillo ◽  
Cesar Octavio Monzon
Keyword(s):  
Surface Temperature ◽  
Sonoran Desert ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Threshold Value ◽  
Radiation Mechanism ◽  
Modis Ndvi ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Northwestern Mexico ◽  
Definition Of

AbstractThe authors explore a new approach to monitoring of desertification that is based on use of results on the relation between albedo and surface temperature for the Sonoran Desert in northwestern Mexico. The criteria of predominance of radiation by using the threshold value of Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) were determined. The radiation mechanism for regulating the temperature of the surface and the definition of threshold values for AVHRR and MODIS NDVI have an objective justification for the energy budget, which is based on the dominance of radiation surface temperature regulation in relation to evapotranspiration. Changes in the extent of arid regions with AVHRR NDVI of <0.08 and MODIS NDVI of <0.10 can be considered to be a characteristic in the evolution of desertification in the Sonoran Desert region. This is true because, in a certain year, the time span of the period when radiation factor predominates is important for the desertification process.

scholarly journals Sistema para el Seguimiento del funcionamiento de ecosistemas en la Red de Parques Nacionales de España mediante Teledetección

2016 ◽  
pp. 119 ◽  
Author(s):  
J. Cabello ◽  
D. Alcaraz-Segura ◽  
A. Reyes ◽  
P. Lourenço ◽  
J. M. Requena ◽  
...  
Keyword(s):  
National Parks ◽  
Land Surface ◽  
Ecosystem Functioning ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Net Primary Production ◽  
Conservation Status ◽  
Vegetation Indices ◽  
Reference Conditions ◽  
Management Actions

<p>Management of protected areas in the current context of global change requires approaches to characterize and to monitor ecosystem functioning. Remote sensing provides adequate tools for that because it provides índices that inform repeatedly and for large areas of land, about matter and energy exchanges between the biota and land surface. Considering this principle, and the continuous improvements in the availability of satellite data of higher quality and friendly use, we have developed with the Autonomous Organization of National Parks of Spain (OAPN), a monitoring system that complements other monitoring initiatives from this agency to inform about the conservation status of national parks. The system, called REMOTE, is based on the most used spectral vegetation indices on scientific literature, EVI (Enhanced Vegetation Index) and NDVI (Normalized Difference Vegetation Index), derived from the time series of satellite images of the MODIS-Terra sensor. The systems allows to progress in identification of reference conditions to understand and predict ecosystems response against environmental perturbations or management actions, and their directional changes (trends) they are experiencing. Likewise, establishment of reference conditions helps to identify anomalies that warn of sudden changes in ecosystem functioning. The system uses as ecosystem functioning indicators three attributes related to the annual carbon gains (net primary production) by the canopy, their seasonality and phenology. In addittion, Remote has been designed and programmed on open and free software allowing future modifications and improvements in an easy way. The implementation of this system aims to inform decision-makers and managers of the Network of National Parks of Spain about the health and conservation status of ecosystems.</p>

scholarly journals Fusion of MODIS and Landsat-Like Images for Daily High Spatial Resolution NDVI

2020 ◽  
Vol 12 (8) ◽  
pp. 1297
Author(s):  
Roberto Filgueiras ◽  
Everardo Chartuni Mantovani ◽  
Elpídio Inácio Fernandes-Filho ◽  
Fernando França da Cunha ◽  
Daniel Althoff ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Regression Models ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
High Spatial Resolution ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Landsat 8 ◽  
Modis Ndvi

One of the obstacles in monitoring agricultural crops is the difficulty in understanding and mapping rapid changes of these crops. With the purpose of addressing this issue, this study aimed to model and fuse the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) using Landsat-like images to achieve daily high spatial resolution NDVI. The study was performed for the period of 2017 on a commercial farm of irrigated maize-soybean rotation in the western region of the state of Bahia, Brazil. To achieve the objective, the following procedures were performed: (i) Landsat-like images were upscaled to match the Landsat-8 spatial resolution (30 m); (ii) the reflectance of Landsat-like images was intercalibrated using the Landsat-8 as a reference; (iii) Landsat-like reflectance images were upscaled to match the MODIS sensor spatial resolution (250 m); (iv) regression models were trained daily to model MODIS NDVI using the upscaled Landsat-like reflectance images (250 m) of the closest day as the input; and (v) the intercalibrated version of the Landsat-like images (30 m) used in the previous step was used as the input for the trained model, resulting in a downscaled MODIS NDVI (30 m). To determine the best fitting model, we used the following statistical metrics: coefficient of determination (r2), root mean square error (RMSE), Nash–Sutcliffe efficiency index (NSE), mean bias error (MBE), and mean absolute error (MAE). Among the assessed regression models, the Cubist algorithm was sensitive to changes in agriculture and performed best in modeling of the Landsat-like MODIS NDVI. The results obtained in the present research are promising and can enable the monitoring of dynamic phenomena with images available free of charge, changing the way in which decisions are made using satellite images.

scholarly journals Detecting Winter Wheat Irrigation Signals Using SMAP Gridded Soil Moisture Data

2019 ◽  
Vol 11 (20) ◽  
pp. 2390 ◽  
Author(s):  
Hao ◽  
Zhao ◽  
Zhang ◽  
Wang ◽  
Jiang
Keyword(s):  
Soil Moisture ◽  
Winter Wheat ◽  
Signal Detection ◽  
Spatial Resolution ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Irrigation Management ◽  
Hebei Province ◽  
Signal Frequency ◽  
Modis Ndvi

The southern part of the Hebei Province is one of China’s major crop-producing regions. Due to the continuous decline in groundwater level, agricultural water use is facing significant challenges. Precision agricultural irrigation management is undoubtedly an effective way to solve this problem. Based on multisource data (time series soil moisture active passive (SMAP) data, Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and evapotranspiration (ET), and meteorological station precipitation), the irrigation signal (frequency, timing and area) is detected in the southern part of the Hebei Province. The SMAP data was processed by the 5-point moving average method to reduce the error caused by the uncertainty of the microwave data derived SM. Irrigation signals can be detected by removing the precipitation effect and setting the SM change threshold. Based on the validation results, the overall accuracy of the irrigation signal detection is 77.08%. Simultaneously, considering the spatial resolution limitation of SMAP pixels, the SMAP irrigation area was downscaled using the winter wheat area extracted from MODIS NDVI. The analytical results of 55 winter wheat samples (5 samples in a group) showed that winter wheat covered by one SMAP pixel had an 82.72% growth consistency in surface water irrigation period, which can indicate a downscaling effectiveness. According to the above statistical analysis, this paper considers that although the spatial resolution of SMAP data is insufficient, it can reflect the change of SM more sensitively. In areas where the crop pattern is relatively uniform, the introduction of high-resolution crop pattern distribution can be used not only to detect irrigation signals but also to validate the effectiveness of irrigation signal detection by analyzing crop growth consistency. Therefore, the downscaling results can indicate the true winter wheat irrigation timing, area and frequency in the study area.

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