Multitemporal Variations Research Articles

EXPERIMENTAL RELATIONSHIP BETWEEN LAND USE/LAND COVER AND UNDERGROUND FLOW IN AL BA COMMUNE IN THE CENTRAL REGION OF VIETNAM

Rapid urbanization and intensive agricultural practices in Vietnam's Central Highlands have substantially transformed land use/land cover (LULC) patterns, with implications for groundwater resources necessitating measurement. The objective of this investigation is to examine the links between multi-temporal variations in LULC and changes in underground water flow in Al Ba Commune, Gia Lai Province. Supervised object-based classification of Landsat and Sentinel imagery from the past 25 years has produced consistent LULC maps as inputs for the model. Geospatial data of LULC, meteorological data, and in-situ data of groundwater flow (Q) were used to calibrate and validate the integrated hydrological MIKE SHE model and simulate past Q conditions for correlation analysis. With these data on LULC and groundwater flow, this study investigates the relationship between LULC changes and Q using Multivariate Linear Regression (MLR) and Ridge Regression models. The MLR model showed high R² (0.91) but positive impacts of all LULC classes on Q, contrary to expectations. Further analysis with Variance Inflation Factor (VIF) revealed multicollinearity among LULC variables, which was addressed using Ridge Regression with a bias factor to correct for this issue. The revised model demonstrated that non-vegetative covers negatively affect Q while vegetative covers have a positive impact. These results highlight the complex dynamics of LULC changes on groundwater resources, which can be detected by statistical approaches. The results of study could be important for sustainable land management.

Multi-temporal variations in evapotranspiration partitioning and its controlling factors of a xerophytic shrub ecosystem

Partitioning evapotranspiration (ET) into its components of canopy interception (Ic), transpiration (T) and soil evaporation (E) enhances understanding of hydrological cycle and plant water use strategy in drylands. However, variations in all three ET components and their fractions across multi-temporal scales (daily, monthly, annual), and their controlling factors remain poorly understood for shrub ecosystems. In this study, we aimed to address these issues by measuring daily rainfall partitioning, sap flow, soil evaporation and soil moisture in a xerophytic shrub (Salix psammophila) ecosystem in northern China during 2019–2021. We found T dominated ET with a mean ratio of T to ET ranging 61.7 %–71.1 %, which was consistently higher than the mean ratio of Ic and E to ET ranging 12.1 %-41.5 % and 24.5 %–32.2 %, respectively, from daily to annual scales (p < 0.05). There was no significant difference in mean ratio of T to ET among different temporal scales (p > 0.05), while mean ratios of Ic and E to ET were significantly higher at daily scale than those at monthly and annual scales (p < 0.05). Compared with monthly and annual scales, ET components and their ratios at daily scale were more responsive to bio-/abiotic factors. ET components were more susceptible to be affected by the influencing factors when compared to their ratios, regardless of the temporal scales. Specifically, daily ET components and their ratios were mainly controlled by precipitation and solar radiation. In addition, soil moisture also explained 10.2 % and 10.9 % of the variations of daily T and ET, respectively. At monthly scale, however, variations in T and ET were mainly controlled by LAI with explained variance of 26.6 % and 32.4 %, respectively. Our results highlighted the significant differences in ET partitioning and their different responses to bio- and abiotic factors at various temporal scales of the shrub ecosystems in drylands.

Utilizing advanced and modified conventional trend methods to evaluate multi-temporal variations in rainfall characteristics over India

Utilizing advanced and modified conventional trend methods to evaluate multi-temporal variations in rainfall characteristics over India

Effects of multi-temporal scale drought on vegetation dynamics in Inner Mongolia from 1982 to 2015, China

Climate change is causing severe changes in the ecosystem, thus understanding how plants respond to drought is essential to protecting ecosystems in Inner Mongolia. Multi-temporal variations of drought in Inner Mongolia were studied using the Standardized Precipitation Evapotranspiration Index (SPEI), and the vegetation growth was analyzed using the Normalized Difference Vegetation Index (NDVI). Moreover, the correlation between droughts of different lengths and NDVI was studied. Subsequently, we developed an optimal binary probability model to calculate the probability of vegetation productivity loss at different drought levels using the copula method. The results showed: (1) a weak aridification in the western parts and significant wetness in the central and eastern parts of Inner Mongolia; (2) a significant decreasing trend of NDVI from 1982 to 2009 and a significant increasing trend from 2010 to 2015; (3) a strong positive correlation between NDVI and SPEI and a difference between their related time scales based on soil textures; and (4) a higher probability of vegetation productivity loss with increasing drought at different drought levels.

Multi-Temporal Variations in Surface Albedo on Urumqi Glacier No.1 in Tien Shan, under Arid and Semi-Arid Environment

Surface albedo exerts substantial control over the energy available for glacier melting. For Urumqi Glacier No.1 in the Tien Shan Mountains, China, represented as a “summer accumulation” glacier, the variations in albedo driven by surface processes are complex and still poorly understood. In this study, we examined the interannual trends in ablation-period albedo from 2000 to 2021 using MOD10A1 products, evaluated the variation in bare-ice albedo retrieved from 13 end-of-summer Landsat images obtained between 2002 and 2019, and investigated the seasonal variation and diurnal cycle of surface albedo collected near the equilibrium line of the glacier by an AWS from September 2018 to August 2021. During the period of 2000–2021, the average ablation-period albedo presented a slight but not statistically significant downward trend, with a total decrease of 1.87%. Specifically, the decrease in glacier albedo was quicker in July than that in August, and there was a slight increase in May and June. The blackening phenomenon was shown on the east branch glacier, but not on the west branch glacier. For seasonal variability, a bimodal pattern was demonstrated, different from the unimodal seasonal variation in other midlatitude glaciers. The albedo peaks occurred in December and April or May. Under clear sky conditions, the diurnal cycle presented three patterns: a symmetric pattern, an asymmetric pattern, and a progressive decreasing pattern. Air temperature and solid precipitation are the main drivers of variations in glacier albedo, but in different periods of the ablation season, two climate variables affect albedo to varying degrees. The effect of surface albedo reduction enhanced glacier melting by about 20% over the past 20 years. The short-term increase in albedo caused by summer snowfall can considerably reduce glacier melting by as much as 80% in June.

GPS-Based Multi-Temporal Variation in Precipitable Water over the Territory of Poland

An increase in temperature causes higher evaporation of water from water bodies; consequently, the water content in the atmosphere also increases. The precipitable water (PW), as the water content in the atmospheric air column, is therefore an important parameter to consider when studying climate change. The aim of this study was to analyse multi-annual precipitable water data derived from a dense Global Navigational Satellite Systems (GNSS) network. Twelve years of observations from over a hundred ASG-EUPOS stations were used to estimate changes in precipitation water values over Poland. The data were validated by comparison with the available radio-sounding data. The analysis of the GPS-based PW values showed an upward trend in the PW value of 0.078 mm/year. The spatio-temporal distribution of the mean PW values and their fluctuations over the years were studied and visualised in the form of maps. The results are congruent with the fact that Poland lies on the border of influence of both continental and oceanic climates. Our results are also consistent with other climate research concerning this region.

Homo Sapiens Sapiens Progressive Defaunation During The Great Acceleration: The Cli-Fi Apocalypse Hypothesis

Homo Sapiens Sapiens Progressive Defaunation During The Great Acceleration: The Cli-Fi Apocalypse Hypothesis

Ridership exceedance exposure risk: Novel indicators to assess PM2.5 health exposure of bike sharing riders

Identifying the fine particulate matter (PM2.5) exposure risk for bicycle riders is crucial for promoting the development of theory and technology in transportation-related air pollution assessment as well as urban health planning. Previous studies have employed daily mean PM2.5 concentrations and designed routes to evaluate air pollution exposure risk. However, because the daily mean PM2.5 concentrations cannot fully illustrate the intra-day variations in PM2.5, which are typically higher than daily mean values, the adverse effects of PM2.5 concentrations remain underestimated. Moreover, the quantity and representativeness of monitoring samples make large spatial-scale and multi-temporal-scale analysis challenging. By defining hourly exceedance PM2.5 concentration and sharing bicycle rider data, two novel indicators were proposed in our study: exceedance exposure risk of PM2.5 for sharing bicycle riders (EPSR) and accumulative exceedance exposure risk of PM2.5 for sharing bicycle riders (AEPSR). Standard deviation ellipse analysis was conducted to investigate the multi-temporal variation of ESPR and AEPSR. A geographically weighted regression model was applied to quantify the relationship between city function zones and exceedance PM2.5 exposure risk for sharing bicycle riders. Results revealed that the mean values of EPSR and AEPSR during morning peak periods ranged between 0.109 min μg/m3 and 1.27 min μg/m3 and 6.83 min μg/m3 and 43.41 min μg/m3, respectively, whereas the mean values of EPSR and AEPSR during evening peak periods ranged between 0.19 min μg/m3 and 4.28 min μg/m3 and 14.67 min μg/m3 and 357.66 min μg/m3, respectively. This implied that sharing bicycle riders were exposed to higher PM2.5-related risks during the evening than in the morning. When considering the accumulative effects, the average centers of the AEPSR moved to the north side as compared to the average centers of the EPSR. Expanding areas of EPSR shrunk by 20.25 km2. This indicated that accumulative effects aggregated spatial clusters of exceedance PM2.5 exposure risk for sharing bicycle riders more tightly to the north of the study areas. Spatiotemporal variation of EPSR and AEPSR led us to investigate the mechanism behind this phenomenon. Spatial associations between city function zones and EPSR and AEPSR showed that sharing bicycle riders experienced more severe exceedance PM2.5 exposure risk around financial/corporations and leisure service areas, with R2 values of 0.33 and 0.35, respectively. This spatial association tended to be more significant during the evening peak periods. By developing two novel indicators, the increasing health threats for bicycle riders caused by exceedance PM2.5 were investigated in this study. The mechanism results should be included for developing mitigation strategies to alleviate the adverse effects of air pollution for public rider participators and achieving the goal of eco-health cities.

A Machine Learning Approach to Detecting Pine Wilt Disease Using Airborne Spectral Imagery

Pine Wilt Disease is one of the most destructive pests affecting coniferous forests. After being infected by the harmful Bursaphelenchus xylophilus nematode, most trees die within one year. The complex spreading pattern of the disease and the tedious hard labor process of diagnosis involving field wood sampling followed by laboratory analysis call for alternative methods to detect and manage the infected areas. Remote sensing comes naturally into play owing to the possibility of covering relatively large areas and the ability to discriminate healthy from sick trees based on spectral characteristics. This paper presents the development of machine learning classification algorithms for the detection of Pine Wilt Disease in Pinus pinaster, performed in the framework of the European Commission’s Horizon 2020 project “Operational Forest Monitoring using Copernicus and UAV Hyperspectral Data” (FOCUS) in two provinces of central Portugal. Five flight campaigns have been carried out in two consecutive years in order to capture a multitemporal variation of disease distribution. Classification algorithms based on a Random Forest approach were separately designed for the acquired very-high-resolution multispectral and hyperspectral data, respectively. Both algorithms achieved overall accuracies higher than 0.91 in test data. Furthermore, our study shows that the early detection of decaying trees is feasible, even before symptoms are visible in the field.

Temporal variations in river water surface elevation and slope captured by AirSWOT

The Surface Water and Ocean Topography (SWOT) satellite mission aims to improve the frequency and accuracy of global observations of river water surface elevations (WSEs) and slopes. As part of the SWOT mission, an airborne analog, AirSWOT, provides spatially-distributed measurements of WSEs for river reaches tens to hundreds of kilometers in length. For the first time, we demonstrate the ability of AirSWOT to consistently measure temporal dynamics in river WSE and slope. We evaluate data from six AirSWOT flights conducted between June 7–22, 2015 along a ~90 km reach of the Tanana River, AK. To validate AirSWOT measurements, we compare AirSWOT WSEs and slopes against an in situ network of 12 pressure transducers (PTs). Assuming error-free in situ data, AirSWOT measurements of river WSEs have an overall root mean square difference (RMSD) of 11.8 cm when averaged over 1 km2 areas while measurements of river surface slope have an RMSD of 1.6 cm/km for reach lengths >5 km. AirSWOT is also capable of recording accurate river WSE changes between flight dates, with an RMSD of 9.8 cm. Regrettably, observed in situ slope changes that transpired between the six flights are well below AirSWOT's accuracy, limiting the evaluation of AirSWOT's ability to capture temporal changes in slope. In addition to validating the direct AirSWOT measurements, we compare discharge values calculated via Manning's equation using AirSWOT WSEs and slopes to discharge values calculated using PT WSEs and slopes. We define or calibrate the remaining discharge parameters using a combination of in situ and remotely sensed observations, and we hold these remaining parameters constant between the two types of calculations to evaluate the impact of using AirSWOT versus the PT observations of WSE and slope. Results indicate that AirSWOT-derived discharge estimates are similar to the PT-derived discharge estimates, with an RMSD of 13.8%. Additionally, 42% of the AirSWOT-based discharge estimates fall within the PT discharge estimates' uncertainty bounds. We conclude that AirSWOT can measure multitemporal variations in river WSE and spatial variations in slope with both high accuracy and spatial sampling, providing a compelling alternative to in situ measurements of regional-scale, spatiotemporal fluvial dynamics.

Fluoroquinolones in agricultural soils: Multi-temporal variation and risks in Rio de Janeiro upland region

Our main goal was to investigate the potential accumulation of fluoroquinolones (FQs) in agricultural soils over extended periods of land use, predicting leaching and estimating risk quotients for soil microorganisms. Short to long-term of poultry litter fertilization (<1–30 years) were evaluated for enrofloxacin (ENR) and ciprofloxacin (CIP) input, in addition to the emergence of plasmid-mediated quinolone resistance (PMQR) genes. High FQs concentration (range 0.56–100 mg kg−1) were measured in poultry litter samples. In soils, FQs occurrence and risks have changed over the years. An accumulation trend was observed between short and medium-term fertilized soils (ST and MT soils), reaching a range of 330–6138 μg kg−1 ENR and 170–960 μg kg−1 CIP in MT soil, followed by decreased concentrations in long-term fertilized soils (LT soils). The environmental risk assessment showed a high ENR risk quotient (RQ ≥ 1) in ST and MT soils ranging (7–226) and high CIP risk (9–53) in LT soils. The detection of qnrS genes in the area with the lowest FQs concentration emphasizes the importance of a broader approach to environmental assessment, in which not only target compounds are considered. FQs soil-water migration model pointed out a high leaching risk in ST soil. To reduce risks, management measures to decrease antibiotic environmental load should be taken before poultry litter application. In addition, the high weathering of tropical soils contributing to possible fate of antibiotics to water resources through drainage basins should be considered.

Multi-temporal variation of the Ross Sea Polynya in response to climate forcings

The multi-temporal scales of two physical characteristics (areas and occurrence time) of the Ross Sea Polynya (RSP) in Antarctica were analysed using a sea-ice concentration data set (1979–2014) de...

Benthic Habitat Mapping Using Multispectral High-Resolution Imagery: Evaluation of Shallow Water Atmospheric Correction Techniques.

Remote multispectral data can provide valuable information for monitoring coastal water ecosystems. Specifically, high-resolution satellite-based imaging systems, as WorldView-2 (WV-2), can generate information at spatial scales needed to implement conservation actions for protected littoral zones. However, coastal water-leaving radiance arriving at the space-based sensor is often small as compared to reflected radiance. In this work, complex approaches, which usually use an accurate radiative transfer code to correct the atmospheric effects, such as FLAASH, ATCOR and 6S, have been implemented for high-resolution imagery. They have been assessed in real scenarios using field spectroradiometer data. In this context, the three approaches have achieved excellent results and a slightly superior performance of 6S model-based algorithm has been observed. Finally, for the mapping of benthic habitats in shallow-waters marine protected environments, a relevant application of the proposed atmospheric correction combined with an automatic deglinting procedure is presented. This approach is based on the integration of a linear mixing model of benthic classes within the radiative transfer model of the water. The complete methodology has been applied to selected ecosystems in the Canary Islands (Spain) but the obtained results allow the robust mapping of the spatial distribution and density of seagrass in coastal waters and the analysis of multitemporal variations related to the human activity and climate change in littoral zones.

Remote sensing of vegetation cover changes in the humid tropical rainforests of Southeastern Nigeria (1984–2014)

This study demonstrates a 30-year multi-temporal variations in vegetation cover changes as a means of filling the vegetation knowledge gap in the humid tropical forests of southeastern Nigeria. Lan...

Multi-temporal variation in water consumption of summer maize as determined by the Water Transformation Dynamical Processes Experimental Device

A better understanding of the multi-temporal variation in evapotranspiration (ET) at different crop growth stages is the key for determining a reasonable irrigation schedule. In this study, a new device known as ‘Water Transformation Dynamical Processes Experimental Device’ (WTDPED) was used to monitor ET for maize under controlled environmental and groundwater conditions, and the multi-temporal variations of ET considering the combined impact of environmental factors (air temperature (AT), relative humidity (RH)) and groundwater in homogeneous and layered soils were focused on. During the whole growing period, the ET peaked at 14:00–15:00 on a daily basis. The variation in daily ET followed a bell curve during the entire growing period. The 5-day ET reached its maximum during the 12th leaf and maturity stage. The correlation coefficient between ET and AT reached its maximum value of 0.70 during planting and the third leaf stage. The negative correlation coefficient between RH and ET reached its maximum during the 12th leaf and tasseling-silking stage. Groundwater recharge was positively correlated to ET and the daily contribution was up to 10.07%. The silt sandy loam–loam layered soil was favorable for water and nutrient uptake during the entire growing period of maize.

Assessment of Atmospheric Algorithms to Retrieve Vegetation in Natural Protected Areas Using Multispectral High Resolution Imagery.

The precise mapping of vegetation covers in semi-arid areas is a complex task as this type of environment consists of sparse vegetation mainly composed of small shrubs. The launch of high resolution satellites, with additional spectral bands and the ability to alter the viewing angle, offers a useful technology to focus on this objective. In this context, atmospheric correction is a fundamental step in the pre-processing of such remote sensing imagery and, consequently, different algorithms have been developed for this purpose over the years. They are commonly categorized as imaged-based methods as well as in more advanced physical models based on the radiative transfer theory. Despite the relevance of this topic, a few comparative studies covering several methods have been carried out using high resolution data or which are specifically applied to vegetation covers. In this work, the performance of five representative atmospheric correction algorithms (DOS, QUAC, FLAASH, ATCOR and 6S) has been assessed, using high resolution Worldview-2 imagery and field spectroradiometer data collected simultaneously, with the goal of identifying the most appropriate techniques. The study also included a detailed analysis of the parameterization influence on the final results of the correction, the aerosol model and its optical thickness being important parameters to be properly adjusted. The effects of corrections were studied in vegetation and soil sites belonging to different protected semi-arid ecosystems (high mountain and coastal areas). In summary, the superior performance of model-based algorithms, 6S in particular, has been demonstrated, achieving reflectance estimations very close to the in-situ measurements (RMSE of between 2% and 3%). Finally, an example of the importance of the atmospheric correction in the vegetation estimation in these natural areas is presented, allowing the robust mapping of species and the analysis of multitemporal variations related to the human activity and climate change.

Estimating the regional evapotranspiration in Zhalong wetland with the Two-Source Energy Balance (TSEB) model and Landsat7/ETM+ images

This paper aims to integrate a numerical model, vegetation index, and regional evapotranspiration estimation to assess the water cycle in Zhalong wetland, China with the aid of remote sensing technologies. An interdisciplinary analysis was performed to study the eco-hydrological characteristics of the wetland ecosystem. In particular, a new solution for solving the Two-Source Energy Balance (TSEB) was developed and applied. This new solution method is based on a definition of the aerodynamic temperature in a two-layer ground surface structure. Following this new solution for TSEB, the outputs of the Surface Energy Balance Algorithm (SEBAL) may be used as the inputs for TSEB to avoid the complex calculations of the bulk boundary layer and soil surface resistance. The new solution method makes the implementation of TSEB much easier when bi-directional thermal infrared remote sensing images are not available. Daily evapotranspiration and vegetation index of the wetland were calculated from six scenes of Landsat7/ETM+ remote sensing images acquired during 2001 and 2002 in our case study. Spatial distribution of daily evapotranspiration was also provided to help realize the wetland condition. The seasonal changes of vegetation index and evapotranspiration for some typical wetland ground surfaces were analyzed and presented as well to explore the multitemporal variations of plant species holistically. Ultimately, such integrative analysis aids in understanding the general biological patterns associated with these wetland vegetation cover, while specific situations of the wetland ecosystem can be recognized.

Relationships between climatic parameters and forest vegetation: application to burned area in Alicante (Spain)

The main aims of this study is to examine the variability of normalized difference vegetation index (NDVI) on forest vegetation in Alicante (Spain) between 1984 and 1994 and to analyse the influence of climatic parameters in the regeneration of forest areas burned by fires. The zone of study is located between XUTM (m) 730400-760400 and YUTM (m) 4274000-4304000 and is characterised by a great topographic complexity that leads to diverse microclimatic conditions. In this area, the maximum annual rainfall of the Valencian Community is recorded, reaching 850 mm of average annual rainfall ( Belda, 1997). We examined the spatial and temporal analyse of rainfall and soil moisture over this area. To do this, we analysed the water balances of 25 meteorological stations from the Spanish Meteorological Institute, and we used the Kriging method for their interpolation. On the other hand, to perform multitemporal variation of the amount of vegetation, we have several Landsat TM images from 1984 to 1994 (bands 3 and 4) to calculate the NDVI. The image processing consisted of geometric and radiometric correction (atmospheric and topographic) to superimpose all the images and to make their multitemporal comparison possible. Geographical Information System (GIS) was used to monitor forest vegetation and its relationship with climatic parameters (rainfall and soil moisture), particularly IDRISI, where we integrated information from remote sensing and ground data collection. Finally, it appears that NDVI is useful in estimating the variation of amount of vegetation for a long period. In spatial and temporal analyse, the oscillation of the NDVI was low. In general, the wet area had higher values than the dry area. In the burned area, the regeneration followed an exponential curve which was stronger in wet zones and had high correlation coefficients.

Multitemporal C- and L-band polarimetric signatures of crops

Polarimetric synthetic aperture radar (SAR) data of agricultural fields have been acquired by the Danish L- and C-band polarimetric SAR (EMISAR) in March, May, June, and July of 1995, covering the agricultural test site at the Research Centre Foulum located in Central Jutland, Denmark. Polarimetric signatures for a number of agricultural crops, including both spring and winter crops, have been analyzed, both with respect to incidence angle variations, between-field differences, and multitemporal variations for the individual crops. The variation with incidence angle was most pronounced for the early acquisitions (March and May) where the backscatter was dominated by surface scattering. In later acquisitions (June and July), the variation was relatively small except for a few cases. Also, the largest between-field variation was observed for the early acquisitions, probably due to the sensitivity of the polarimetric parameters to differences in plowing and planting direction, soil texture, tillage practice, time of planting, etc. The analysis of the multitemporal signatures revealed significant information about the scattering mechanisms. Especially, the correlation coefficient between HH and VV showed a large difference between spring and winter crops in the beginning of the growing season, because of the dominance of surface scattering for spring crops and volume scattering for winter crops.

Preliminary analysis of ERS-1 wind scatterometer data over land surfaces

Abstract This Letter presents preliminary observations made with the ERS-1 wind scatterometer over land surfaces. A global backscattering coefficient image, synthesized from the original raw data indicates a strong correlation between the radar signal and the distribution of the main vegetation types throughout the world. In particular, tropical vegetation formations are well identified. The effects of angular and multitemporal variations on the backscattering coefficient σ0 are shown for different terrestrial surfaces. Illustrations are given for the African continent which presents numerous vegetation types along a north-south latitudinal gradient. Results indicate the strong capability of the ERS-1 scatterometer to discriminate and monitor vegetation change at a global scale.