THE RECONSTRUCTION OF NDVI TIME SERIES USING SPATIO-TEMPORAL INFORMATION

Abstract. Due to the influence of cloud cover, atmospheric disturbance and many other factors, normalized difference vegetation index (NDVI) corrupted by noises has a negative effect on the downstream applications. To this end, researchers have developed a large number of methods to reconstruct NDVI time series. The harmonic analysis of time series (HANTS) is one of the most widely used approaches of NDVI reconstruction. In this paper, HANTS algorithm was improved by the utilization of spatio-temporal information of NDVI time series with spatial filling and filtering, which makes up the deficiency of HANTS that only uses temporal information of NDVI time series. The simulation experiments on moderate resolution imaging spectroradiometer (MODIS) NDVI time series have proved that our method has effectively improved the quantitative and qualitative reconstruction performance of HANTS algorithm.

Download Full-text

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

Frontiers in Sustainable Food Systems ◽

10.3389/fsufs.2020.541170 ◽

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.

Download Full-text

Cropland area estimates using Modis NDVI time series in the state of Mato Grosso, Brazil

Pesquisa Agropecuária Brasileira ◽

10.1590/s0100-204x2012000900012 ◽

2012 ◽

Vol 47 (9) ◽

pp. 1270-1278 ◽

Cited By ~ 19

Author(s):

Daniel de Castro Victoria ◽

Adriano Rolim da Paz ◽

Alexandre Camargo Coutinho ◽

Jude Kastens ◽

J. Christopher Brown

Keyword(s):

Time Series ◽

Crop Production ◽

Vegetation Index ◽

The State ◽

Mato Grosso ◽

Cropland Area ◽

Modis Ndvi ◽

Ndvi Time Series ◽

Moderate Resolution Imaging Spectroradiometer ◽

Production Areas

The objective of this work was to evaluate a simple, semi‑automated methodology for mapping cropland areas in the state of Mato Grosso, Brazil. A Fourier transform was applied over a time series of vegetation index products from the moderate resolution imaging spectroradiometer (Modis) sensor. This procedure allows for the evaluation of the amplitude of the periodic changes in vegetation response through time and the identification of areas with strong seasonal variation related to crop production. Annual cropland masks from 2006 to 2009 were generated and municipal cropland areas were estimated through remote sensing. We observed good agreement with official statistics on planted area, especially for municipalities with more than 10% of cropland cover (R² = 0.89), but poor agreement in municipalities with less than 5% crop cover (R² = 0.41). The assessed methodology can be used for annual cropland mapping over large production areas in Brazil.

Download Full-text

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

Biogeosciences ◽

10.5194/bg-12-4407-2015 ◽

2015 ◽

Vol 12 (14) ◽

pp. 4407-4419 ◽

Cited By ~ 13

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.

Download Full-text

Variação Espacial e Temporal de NDVI na Lagoa do Peixe, RS (Spatial and Temporal Variation of NDVI in the Peixe Lagoon, RS)

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v4i5.232706 ◽

2012 ◽

Vol 4 (5) ◽

pp. 897 ◽

Cited By ~ 1

Author(s):

Luana Portz ◽

Laurindo Antonio Guasselli ◽

Iran Carlos Stalliviere Corrêa

Keyword(s):

Time Series ◽

Temporal Variation ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Analysis Data ◽

Landsat Tm ◽

Spatial And Temporal Variation ◽

Rainfall Analysis ◽

Ndvi Time Series ◽

High Precipitation

Neste estudo foram analisadas as variações espaciais e temporais do Índice de Vegetação por Diferença Normalizada (NDVI) na lagoa do Peixe, no litoral do Rio Grande do Sul. Para alcançar o objetivo proposto foram utilizadas imagens de satélite Landsat TM5, entre os anos de 1986 e 2009, seguindo os procedimentos de elaboração de mosaico das cenas, verificação de campo, geração das imagens de NDVI, análise de dados de precipitação acumulada, geração dos mapas finais e análise qualitativa dos resultados obtidos. Os resultados obtidos com a geração de imagens de NDVI mostraram que a análise espaço-temporal associada aos dados de precipitação fornecem informações de valiosa importância sobre a dinâmica da lagoa do Peixe. A importância do NDVI neste estudo se destaca pelo contraste existente entre água e vegetação, realçando os diferentes níveis de água sobre os bancos vegetados presentes na borda oeste da lagoa. Estes bancos são um importante controlador da dinâmica de circulação lagunar, onde em períodos de seca ocorre a compartimentação da lagoa, enquanto que em épocas de grande precipitação e acumulação de água estes bancos ficam submersos. Palavras-chave: Landsat TM, série temporal, Parque Nacional. Spatial and Temporal Variation of NDVI in the Peixe Lagoon, RS ABSTRACTThis paper analyzed the spatial and temporal variation of Normalized Difference Vegetation Index (NDVI) in the Peixe lagoon. To reach the purpose, the NDVI time-series were collected from the study area between year 1986 and 2009 derived from Landsat TM5 satellite. The adopted methodology may be subdivided into the following steps: mosaic of scenes, fild verification, generation of NDVI time-series and qualitative analysis, in addition, it was complemented with rainfall analysis. The results obtained with the NDVI time-series associated with the rainfall analysis data provide valuable information about the environmental dynamics. The importance of NDVI in this work is given by the contrast between water and vegetation, highlighting the different levels of water over vegetated banks present on the western edge of the lagoon. These banks are an important driver circulation in the lagoon, where in periods of drought occurs the partitioning of the lagoo, while in periods of high precipitation and accumulation of water they are submerged. Keywords: Landsat TM, time-series, National Park.

Download Full-text

Assessing Spatial Limits of Sentinel-2 Data on Arable Crops in the Context of Checks by Monitoring

Remote Sensing ◽

10.3390/rs12142195 ◽

2020 ◽

Vol 12 (14) ◽

pp. 2195 ◽

Cited By ~ 4

Author(s):

Blanka Vajsová ◽

Dominique Fasbender ◽

Csaba Wirnhardt ◽

Slavko Lemajic ◽

Wim Devos

Keyword(s):

Time Series ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Policy Framework ◽

Pixel Size ◽

Control Approach ◽

Continuous State ◽

Ndvi Time Series ◽

High Level ◽

Sentinel 2

The availability of large amounts of Sentinel-2 data has been a trigger for its increasing exploitation in various types of applications. It is, therefore, of importance to understand the limits above which these data still guarantee a meaningful outcome. This paper proposes a new method to quantify and specify restrictions of the Sentinel-2 imagery in the context of checks by monitoring, a newly introduced control approach within the European Common Agriculture Policy framework. The method consists of a comparison of normalized difference vegetation index (NDVI) time series constructed from data of different spatial resolution to estimate the performance and limits of the coarser one. Using similarity assessment of Sentinel-2 (10 m pixel size) and PlanetScope (3 m pixel size) NDVI time series, it was estimated that for 10% out of 867 fields less than 0.5 ha in size, Sentinel-2 data did not provide reliable evidence of the activity or state of the agriculture field over a given timeframe. Statistical analysis revealed that the number of clean or full pixels and the proportion of pixels lost after an application of a 5-m (1/2 pixel) negative buffer are the geospatial parameters of the field that have the highest influence on the ability of the Sentinel-2 data to qualify the field’s state in time. We specified the following limiting criteria: at least 8 full pixels inside a border and less than 60% of pixels lost. It was concluded that compliance with the criteria still assures a high level of extracted information reliability. Our research proved the promising potential, which was higher than anticipated, of Sentinel-2 data for the continuous state assessment of small fields. The method could be applied to other sensors and indicators.

Download Full-text

Changes in Vegetation Phenology and Productivity in Alaska Over the Past Two Decades

Remote Sensing ◽

10.3390/rs12101546 ◽

2020 ◽

Vol 12 (10) ◽

pp. 1546 ◽

Cited By ~ 1

Author(s):

Christopher Potter ◽

Olivia Alexander

Keyword(s):

Time Series ◽

Coastal Plain ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Regional Scale ◽

Data Sets ◽

Vegetation Phenology ◽

Vegetation Growth ◽

The Past ◽

Moderate Resolution Imaging Spectroradiometer

Understanding trends in vegetation phenology and growing season productivity at a regional scale is important for global change studies, particularly as linkages can be made between climate shifts and the vegetation’s potential to sequester or release carbon into the atmosphere. Trends and geographic patterns of change in vegetation growth and phenology from the MODerate resolution Imaging Spectroradiometer (MODIS) satellite data sets were analyzed for the state of Alaska over the period 2000 to 2018. Phenology metrics derived from the MODIS Normalized Difference Vegetation Index (NDVI) time-series at 250 m resolution tracked changes in the total integrated greenness cover (TIN), maximum annual NDVI (MAXN), and start of the season timing (SOST) date over the past two decades. SOST trends showed significantly earlier seasonal vegetation greening (at more than one day per year) across the northeastern Brooks Range Mountains, on the Yukon-Kuskokwim coastal plain, and in the southern coastal areas of Alaska. TIN and MAXN have increased significantly across the western Arctic Coastal Plain and within the perimeters of most large wildfires of the Interior boreal region that burned since the year 2000, whereas TIN and MAXN have decreased notably in watersheds of Bristol Bay and in the Cook Inlet lowlands of southwestern Alaska, in the same regions where earlier-trending SOST was also detected. Mapping results from this MODIS time-series analysis have identified a new database of localized study locations across Alaska where vegetation phenology has recently shifted notably, and where land cover types and ecosystem processes could be changing rapidly.

Download Full-text

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

Fire ◽

10.3390/fire2010001 ◽

2018 ◽

Vol 2 (1) ◽

pp. 1 ◽

Cited By ~ 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.

Download Full-text

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

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-11-0160.1 ◽

2012 ◽

Vol 51 (8) ◽

pp. 1519-1530 ◽

Cited By ~ 6

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.

Download Full-text

Estimation of different data compositions for early-season crop type classification

PeerJ ◽

10.7717/peerj.4834 ◽

2018 ◽

Vol 6 ◽

pp. e4834 ◽

Cited By ~ 10

Author(s):

Pengyu Hao ◽

Mingquan Wu ◽

Zheng Niu ◽

Li Wang ◽

Yulin Zhan

Keyword(s):

Time Series ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Remote Sensing Data ◽

Classification Performance ◽

Distribution Maps ◽

Production Forecasting ◽

Crop Type ◽

Ndvi Time Series ◽

Multi Temporal

Timely and accurate crop type distribution maps are an important inputs for crop yield estimation and production forecasting as multi-temporal images can observe phenological differences among crops. Therefore, time series remote sensing data are essential for crop type mapping, and image composition has commonly been used to improve the quality of the image time series. However, the optimal composition period is unclear as long composition periods (such as compositions lasting half a year) are less informative and short composition periods lead to information redundancy and missing pixels. In this study, we initially acquired daily 30 m Normalized Difference Vegetation Index (NDVI) time series by fusing MODIS, Landsat, Gaofen and Huanjing (HJ) NDVI, and then composited the NDVI time series using four strategies (daily, 8-day, 16-day, and 32-day). We used Random Forest to identify crop types and evaluated the classification performances of the NDVI time series generated from four composition strategies in two studies regions from Xinjiang, China. Results indicated that crop classification performance improved as crop separabilities and classification accuracies increased, and classification uncertainties dropped in the green-up stage of the crops. When using daily NDVI time series, overall accuracies saturated at 113-day and 116-day in Bole and Luntai, and the saturated overall accuracies (OAs) were 86.13% and 91.89%, respectively. Cotton could be identified 40∼60 days and 35∼45 days earlier than the harvest in Bole and Luntai when using daily, 8-day and 16-day composition NDVI time series since both producer’s accuracies (PAs) and user’s accuracies (UAs) were higher than 85%. Among the four compositions, the daily NDVI time series generated the highest classification accuracies. Although the 8-day, 16-day and 32-day compositions had similar saturated overall accuracies (around 85% in Bole and 83% in Luntai), the 8-day and 16-day compositions achieved these accuracies around 155-day in Bole and 133-day in Luntai, which were earlier than the 32-day composition (170-day in both Bole and Luntai). Therefore, when the daily NDVI time series cannot be acquired, the 16-day composition is recommended in this study.

Download Full-text

Mapping Periodic Patterns of Global Vegetation Based on Spectral Analysis of NDVI Time Series

Remote Sensing ◽

10.3390/rs11212497 ◽

2019 ◽

Vol 11 (21) ◽

pp. 2497

Author(s):

Laura Recuero ◽

Javier Litago ◽

Jorge E. Pinzón ◽

Margarita Huesca ◽

Maria C. Moyano ◽

...

Keyword(s):

Time Series ◽

Spectral Analysis ◽

Land Surface ◽

Arid Regions ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Periodic Patterns ◽

Annual Cycles ◽

Ndvi Time Series ◽

Global Vegetation

Vegetation seasonality assessment through remote sensing data is crucial to understand ecosystem responses to climatic variations and human activities at large-scales. Whereas the study of the timing of phenological events showed significant advances, their recurrence patterns at different periodicities has not been widely study, especially at global scale. In this work, we describe vegetation oscillations by a novel quantitative approach based on the spectral analysis of Normalized Difference Vegetation Index (NDVI) time series. A new set of global periodicity indicators permitted to identify different seasonal patterns regarding the intra-annual cycles (the number, amplitude, and stability) and to evaluate the existence of pluri-annual cycles, even in those regions with noisy or low NDVI. Most of vegetated land surface (93.18%) showed one intra-annual cycle whereas double and triple cycles were found in 5.58% of the land surface, mainly in tropical and arid regions along with agricultural areas. In only 1.24% of the pixels, the seasonality was not statistically significant. The highest values of amplitude and stability were found at high latitudes in the northern hemisphere whereas lowest values corresponded to tropical and arid regions, with the latter showing more pluri-annual cycles. The indicator maps compiled in this work provide highly relevant and practical information to advance in assessing global vegetation dynamics in the context of global change.

Download Full-text