scholarly journals Wetland Dynamics Inferred from Spectral Analyses of Hydro-Meteorological Signals and Landsat Derived Vegetation Indices

2019 ◽  
Vol 12 (1) ◽  
pp. 12
Author(s):  
Subrina Tahsin ◽  
Stephen C. Medeiros ◽  
Arvind Singh
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Frequency Domain ◽  
Water Level ◽  
Vegetation Index ◽  
Time Lag ◽  
Forested Wetlands ◽  
Wetland Dynamics ◽  
Apalachicola Bay ◽  
Emergent Wetlands

The dynamic response of coastal wetlands (CWs) to hydro-meteorological signals is a key indicator for understanding climate driven variations in wetland ecosystems. This study explored the response of CW dynamics to hydro-meteorological signals using time series of Landsat-derived normalized difference vegetation index (NDVI) values at six locations and hydro-meteorological time-series from 1984 to 2015 in Apalachicola Bay, Florida. Spectral analysis revealed more persistence in NDVI values for forested wetlands in the annual frequency domain, compared to scrub and emergent wetlands. This behavior reversed in the decadal frequency domain, where scrub and emergent wetlands had a more persistent NDVI than forested wetlands. The wetland dynamics were found to be driven mostly by the Apalachicola Bay water level and precipitation. Cross-spectral analysis indicated a maximum time-lag of 2.7 months between temperature and NDVI, whereas NDVI lagged water level by a maximum of 2.2 months. The quantification of persistent behavior and subsequent understanding that CW dynamics are mostly driven by water level and precipitation suggests that the severity of droughts, floods, and storm surges will be a driving factor in the future sustainability of CW ecosystems.

scholarly journals Assessing Stream-Aquifer Connectivity in a Coastal California Watershed

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 416
Author(s):  
Bwalya Malama ◽  
Devin Pritchard-Peterson ◽  
John J. Jasbinsek ◽  
Christopher Surfleet
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Water Level ◽  
Time Series Data ◽  
Series Data ◽  
Low Permeability ◽  
Pumping Tests ◽  
Stream Flows ◽  
The Impact

We report the results of field and laboratory investigations of stream-aquifer interactions in a watershed along the California coast to assess the impact of groundwater pumping for irrigation on stream flows. The methods used include subsurface sediment sampling using direct-push drilling, laboratory permeability and particle size analyses of sediment, piezometer installation and instrumentation, stream discharge and stage monitoring, pumping tests for aquifer characterization, resistivity surveys, and long-term passive monitoring of stream stage and groundwater levels. Spectral analysis of long-term water level data was used to assess correlation between stream and groundwater level time series data. The investigations revealed the presence of a thin low permeability silt-clay aquitard unit between the main aquifer and the stream. This suggested a three layer conceptual model of the subsurface comprising unconfined and confined aquifers separated by an aquitard layer. This was broadly confirmed by resistivity surveys and pumping tests, the latter of which indicated the occurrence of leakage across the aquitard. The aquitard was determined to be 2–3 orders of magnitude less permeable than the aquifer, which is indicative of weak stream-aquifer connectivity and was confirmed by spectral analysis of stream-aquifer water level time series. The results illustrate the importance of site-specific investigations and suggest that even in systems where the stream is not in direct hydraulic contact with the producing aquifer, long-term stream depletion can occur due to leakage across low permeability units. This has implications for management of stream flows, groundwater abstraction, and water resources management during prolonged periods of drought.

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

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.

scholarly journals Early Drought Detection by Spectral Analysis of Satellite Time Series of Precipitation and Normalized Difference Vegetation Index (NDVI)

2016 ◽  
Vol 8 (5) ◽  
pp. 422 ◽  
Author(s):  
Mattijn van Hoek ◽  
Li Jia ◽  
Jie Zhou ◽  
Chaolei Zheng ◽  
Massimo Menenti
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index

scholarly journals Potential of Sentinel-2 satellite images to monitor vine fields grown at a territorial scale

OENO One ◽  
2019 ◽  
Vol 53 (1) ◽  
Author(s):  
Nicolas Devaux ◽  
Thomas Crestey ◽  
Corentin Leroux ◽  
Bruno Tisseyre
Keyword(s):  
Time Series ◽  
Temporal Resolution ◽  
Vegetation Index ◽  
Management Practices ◽  
Regional Scale ◽  
Time Lag ◽  
Short Note ◽  
Ndvi Time Series ◽  
The Impact ◽  
Sentinel 2

Aim: The aim of this short note is to provide first insights into the ability of Sentinel-2 images to monitor vine growth across a whole season. It focuses on verifying the practical temporal resolution that can be reached with Sentinel-2 images, the main stages of Mediterranean vineyard development as well as potential relevant agronomic information that can be seen on the temporal vegetation curves arising from Sentinel-2 images.Methods and results: The study was carried out in 2017 in a production vineyard located in southern France, 2 km from the Mediterranean seashore. Sentinel-2 images acquired during the whole vine growing cycle were considered, i.e. between the 3rd of March 2017 and the 10th of October 2017. The images were used to compute the classical normalized difference vegetation index (NDVI). Time series of NDVI values were analyzed on four blocks chosen for exhibiting different features, e.g. age, missing plants, weeding practices. The practical time lag between two usable images was closer to 16 days than to the 10 theoretical days (with only one satellite available at the date of the experiment), i.e. near 60% of the theoretical one. Results show that it might be possible to identify i) the main steps of vine development (e.g. budburst, growth, trimming, growth stop and senescence), ii) weed management and inter-row management practices, and iii) possible reasons for significant inter-block differences in vegetative expression (e.g. young vines that have recently been planted, low-productive blocks affected by many missing vines).Conclusions: Although this experiment was conducted at a time when Sentinel-2b was not fully operational, results showed that a sufficient number of usable images was available to monitor vine development. The availability of two Sentinel satellites (2a and 2b) in upcoming seasons should increase the number of usable images and the temporal resolution of the time series. This study also showed the limitations of the Sentinel-2 images’ resolution to provide within-block information in the case of small blocks or blocks with complex borders or both.Significance and impact of the study: This technical note demonstrated the potential of Sentinel-2 images to characterize vineyard blocks’ vigor and to monitor winegrowers’ practices at a territorial (regional) scale. The impact of management operations such as weeding and trimming, along with their incidence on canopy size, were observed on the NDVI time series. Some relevant parameters (slope, maximum values) may be derived from the NDVI time series, providing new insights into the monitoring of vineyards at a large scale. These results provided areas for further investigation, especially regarding the development of new indicators to characterize block-climate relationships.

scholarly journals Identification of Preferential Runoff Belts in Jinan Spring Basin Based on Hydrological Time-Series Correlation

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3255
Author(s):  
Shuyao Niu ◽  
Longcang Shu ◽  
Hu Li ◽  
Hua Xiang ◽  
Xin Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Water Level ◽  
Groundwater Resources ◽  
Pearson Correlation ◽  
Time Lag ◽  
Spring Water ◽  
Reference Points ◽  
Protection Measures ◽  
Groundwater Movement ◽  
Spring Flow

The Jinan karst system is one of the typical karst systems in North China. The karst springs in Jinan are important historical heritage in China. However, in recent years, due to urbanization and the excessive exploitation of groundwater resources in Jinan City, the rate of spring flow has decreased tremendously. Preferential runoff belts are channels of karst aquifers where fractures and conduits are well-developed and serve as the main pathways for groundwater movement and solute transport. In view of this, a study was conducted in the Jinan Spring Basin to identify preferential runoff belts based on hydrological time-series correlation. Firstly, through cross wavelet transform and Pearson correlation coefficient, the time-lag and correlation of spring water level and precipitation were analyzed, the result show that the precipitation in the areas of Xinglong, Donghongmiao, Qiujiazhuang, Xiying, Yanzishan and Liubu stations has a greater impact on spring water level. In addition, combined with the hydrogeological conditions of the Jinan Spring Basin, the above stations meet the characteristics of the preferential runoff belt. In conclusion, the above stations are most likely to be located on the preferential runoff belt. The results of this study can serve as great reference points for building a correct hydrogeological conceptual model, and for the future planning of spring protection measures.

Spectral Analysis and Distributed Lags in Geographical Studies of Local Unemployment: 2. Distributed Lags

1983 ◽  
Vol 15 (8) ◽  
pp. 1043-1055 ◽  
Author(s):  
R Dunn
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Frequency Domain ◽  
Time Domain ◽  
Spectral Methods ◽  
Distributed Lag ◽  
Distributed Lags ◽  
Distributed Lag Models ◽  
Spectral Estimators ◽  
Empirical Material

This is the second part of a two-part paper in which the related topics of spectral analysis and the identification and estimation of distributed-lag models between time series are discussed. This paper is mainly concerned with distributed-lag models, in particular the use of spectral estimators developed by Hannan. A number of previous studies have used the phase statistics from the cross-spectrum as an indication of lead/lag relations between unemployment series, but it is shown here that this is likely to lead to incorrect conclusions. As an empirical example, lead/lag relations between local unemployment in Severnside and the national series are investigated. The correspondence between time-domain (regression) and frequency-domain (spectral) methods of estimating relations between time series is also discussed, using empirical material from both parts of the paper.

scholarly journals Vegetation Change and Its Response to Climate Extremes in the Arid Region of Northwest China

2021 ◽  
Vol 13 (7) ◽  
pp. 1230
Author(s):  
Simeng Wang ◽  
Qihang Liu ◽  
Chang Huang
Keyword(s):  
Arid Region ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Pearson Correlation ◽  
Time Lag ◽  
Climate Extremes ◽  
Northwest China ◽  
Precipitation Extremes ◽  
Temperature Extremes ◽  
Increasing Trend

Changes in climate extremes have a profound impact on vegetation growth. In this study, we employed the Moderate Resolution Imaging Spectroradiometer (MODIS) and a recently published climate extremes dataset (HadEX3) to study the temporal and spatial evolution of vegetation cover, and its responses to climate extremes in the arid region of northwest China (ARNC). Mann-Kendall test, Anomaly analysis, Pearson correlation analysis, Time lag cross-correlation method, and Least absolute shrinkage and selection operator logistic regression (Lasso) were conducted to quantitatively analyze the response characteristics between Normalized Difference Vegetation Index (NDVI) and climate extremes from 2000 to 2018. The results showed that: (1) The vegetation in the ARNC had a fluctuating upward trend, with vegetation significantly increasing in Xinjiang Tianshan, Altai Mountain, and Tarim Basin, and decreasing in the central inland desert. (2) Temperature extremes showed an increasing trend, with extremely high-temperature events increasing and extremely low-temperature events decreasing. Precipitation extremes events also exhibited a slightly increasing trend. (3) NDVI was overall positively correlated with the climate extremes indices (CEIs), although both positive and negative correlations spatially coexisted. (4) The responses of NDVI and climate extremes showed time lag effects and spatial differences in the growing period. (5) Precipitation extremes were closely related to NDVI than temperature extremes according to Lasso modeling results. This study provides a reference for understanding vegetation variations and their response to climate extremes in arid regions.

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