scholarly journals Long-Term Variability of Dust Events in Southwestern Iran and Its Relationship with the Drought

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1350
Author(s):  
Nasim Hossein Hamzeh ◽  
Dimitris G. Kaskaoutis ◽  
Alireza Rashki ◽  
Kaveh Mohammadpour
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Distribution ◽  
Dust Storms ◽  
Modis Aod ◽  
Spatio Temporal ◽  
Dust Events ◽  
Southwestern Iran ◽  
Local Dust ◽  
Southwest Iran

Dust storms represent a major environmental challenge in the Middle East. The southwest part of Iran is highly affected by dust events transported from neighboring desert regions, mostly from the Iraqi plains and Saudi Arabia, as well as from local dust storms. This study analyzes the spatio-temporal distribution of dust days at five meteorological stations located in southwestern Iran covering a period of 22 years (from 1997 to 2018). Dust codes (06, 07, 30 to 35) from meteorological observations are analyzed at each station, indicating that 84% of the dust events are not of local origin. The average number of dust days maximizes in June and July (188 and 193, respectively), while the dust activity weakens after August. The dust events exhibit large inter-annual variability, with statistically significant increasing trends in all of five stations. Spatial distributions of the aerosol optical depth (AOD), dust loading, and surface dust concentrations from a moderate resolution imaging spectroradiometer (MODIS) and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) retrievals reveal high dust accumulation over southwest Iran and surrounding regions. Furthermore, the spatial distribution of the (MODIS)-AOD trend (%) over southwest Iran indicates a large spatial heterogeneity during 2000–2018 with trends ranging mostly between −9% and 9% (not statistically significant). 2009 was the most active dust year, followed by 2011 and 2008, due to prolonged drought conditions in the fertile crescent and the enhanced dust emissions in the Iraqi plains during this period. In these years, the AOD was much higher than the 19-year average (2000 to 2018), while July 2009 was the dustiest month with about 25–30 dust days in each station. The years with highest dust activity were associated with less precipitation, negative anomalies of the vegetation health index (VHI) and normalized difference vegetation index (NDVI) over the Iraqi plains and southwest Iran, and favorable meteorological dynamics triggering stronger winds.

scholarly journals A comparison of satellite-based indices for hazard assessment of MSW open dumps using spatial analysis

2018 ◽  
Vol 37 (3) ◽  
pp. 219-236 ◽  
Author(s):  
Khalid Mahmood ◽  
Zia Ul-Haq ◽  
Fiza Faizi ◽  
Syeda A. Batol
Keyword(s):  
Hazard Assessment ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Moving Average ◽  
Vegetation Indices ◽  
Temporal Analysis ◽  
Zone Size ◽  
Vegetation Health ◽  
Spatio Temporal ◽  
Hazardous Zone

This study compares the suitability of different satellite-based vegetation indices (VIs) for environmental hazard assessment of municipal solid waste (MSW) open dumps. The compared VIs, as bio-indicators of vegetation health, are normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), and modified soil adjusted vegetation index (MSAVI) that have been subject to spatio-temporal analysis. The comparison has been made based on three criteria: one is the exponential moving average (EMA) bias, second is the ease in visually finding the distance of VI curve flattening, and third is the radius of biohazardous zone in relation to the waste heap dumped at them. NDVI has been found to work well when MSW dumps are surrounded by continuous and dense vegetation, otherwise, MSAVI is a better option due to its ability for adjusting soil signals. The hierarchy of the goodness for least EMA bias is MSAVI> SAVI> NDVI with average bias values of 101 m, 203 m, and 270 m, respectively. Estimations using NDVI have been found unable to satisfy the direct relationship between waste heap and hazardous zone size and have given a false exaggeration of 374 m for relatively smaller dump as compared to the bigger one. The same false exaggeration for SAVI and MSAVI is measured to be 86 m and -14 m, respectively. So MSAVI is the only VI that has shown the true relation of waste heap and hazardous zone size. The best visualization of distance-dependent vegetation health away from the dumps is also provided by MSAVI.

scholarly journals Spatio-temporal variability of biophysical parameters of irrigated maize using orbital remote sensing

2021 ◽  
Vol 42 (4) ◽  
pp. 2181-2202
Author(s):  
Taiara Souza Costa ◽  
◽  
Robson Argolo dos Santos ◽  
Rosângela Leal Santos ◽  
Roberto Filgueiras ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Crop Coefficient ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Crop Evapotranspiration ◽  
Biophysical Parameters ◽  
Planting Dates ◽  
Maize Crop ◽  
Spatio Temporal

This study proposes to estimate the actual crop evapotranspiration, using the SAFER model, as well as calculate the crop coefficient (Kc) as a function of the normalized difference vegetation index (NDVI) and determine the biomass of an irrigated maize crop using images from the Operational Land Imager (OLI) and Thermal Infrared (TIRS) sensors of the Landsat-8 satellite. Pivots 21 to 26 of a commercial farm located in the municipalities of Bom Jesus da Lapa and Serra do Ramalho, west of Bahia State, Brazil, were selected. Sowing dates for each pivot were arranged as North and South or East and West, with cultivation starting firstly in one of the orientations and subsequently in the other. The relationship between NDVI and the Kc values obtained in the FAO-56 report (KcFAO) revealed a high coefficient of determination (R2 = 0.7921), showing that the variance of KcFAO can be explained by NDVI in the maize crop. Considering the center pivots with different planting dates, the crop evapotranspiration (ETc) pixel values ranged from 0.0 to 6.0 mm d-1 during the phenological cycle. The highest values were found at 199 days of the year (DOY), corresponding to around 100 days after sowing (DAS). The lowest BIO values occur at 135 DOY, at around 20 DAS. There is a relationship between ETc and BIO, where the DOY with the highest BIO are equivalent to the days with the highest ETc values. In addition to this relationship, BIO is strongly influenced by soil water availability.

scholarly journals Development of a dynamic dust source map for NMME-DREAM v1.0 model based on MODIS Normalized Difference Vegetation Index (NDVI) over the Arabian Peninsula

2019 ◽  
Vol 12 (3) ◽  
pp. 979-988 ◽  
Author(s):  
Stavros Solomos ◽  
Abdelgadir Abuelgasim ◽  
Christos Spyrou ◽  
Ioannis Binietoglou ◽  
Slobodan Nickovic
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Mesoscale Model ◽  
Dust Emission ◽  
Atmospheric Model ◽  
Fine Tuning ◽  
Dust Source ◽  
Dust Sources ◽  
Modis Aod ◽  
Dynamic Source

Abstract. We developed a time-dependent dust source map for the NMME Dust Regional Atmospheric Model (DREAM v1.0) based on the satellite MODIS Normalized Difference Vegetation Index (NDVI). Areas with NDVI <0.1 are classified as active dust sources. The updated modeling system is tested for dust emission capabilities over SW Asia using a mesoscale model grid increment of 0.1∘×0.1∘ for a period of 1 year (2016). Our results indicate significant deviations in simulated aerosol optical depths (AODs) compared to the static dust source approach and general increase in dust loads over the selected domain. Comparison with MODIS AOD indicates a more realistic spatial distribution of dust in the dynamic source simulations compared to the static dust sources approach. The modeled AOD bias is improved from −0.140 to 0.083 for the case of dust events (i.e., for AOD >0.25) and from −0.933 to −0.424 for dust episodes with AOD >1. This new development can be easily applied to other time periods, models, and different areas worldwide for a local fine tuning of the parameterization and assessment of its performance.

scholarly journals Spatio-Temporal Analysis of Vegetation Dynamics as a Response to Climate Variability and Drought Patterns in the Semiarid Region, Eritrea

2019 ◽  
Vol 11 (6) ◽  
pp. 724 ◽  
Author(s):  
Simon Measho ◽  
Baozhang Chen ◽  
Yongyut Trisurat ◽  
Petri Pellikka ◽  
Lifeng Guo ◽  
...  
Keyword(s):  
Climate Variability ◽  
Vegetation Dynamics ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Negative Impact ◽  
Pearson Correlation ◽  
Temporal Analysis ◽  
Semiarid Region ◽  
Ecological Zones ◽  
Spatio Temporal

There is a growing concern over change in vegetation dynamics and drought patterns with the increasing climate variability and warming trends in Africa, particularly in the semiarid regions of East Africa. Here, several geospatial techniques and datasets were used to analyze the spatio-temporal vegetation dynamics in response to climate (precipitation and temperature) and drought in Eritrea from 2000 to 2017. A pixel-based trend analysis was performed, and a Pearson correlation coefficient was computed between vegetation indices and climate variables. In addition, vegetation condition index (VCI) and standard precipitation index (SPI) classifications were used to assess drought patterns in the country. The results demonstrated that there was a decreasing NDVI (Normalized Difference Vegetation Index) slope at both annual and seasonal time scales. In the study area, 57.1% of the pixels showed a decreasing annual NDVI trend, while the significance was higher in South-Western Eritrea. In most of the agro-ecological zones, the shrublands and croplands showed decreasing NDVI trends. About 87.16% of the study area had a positive correlation between growing season NDVI and precipitation (39.34%, p < 0.05). The Gash Barka region of the country showed the strongest and most significant correlations between NDVI and precipitation values. The specific drought assessments based on VCI and SPI summarized that Eritrea had been exposed to recurrent droughts of moderate to extreme conditions during the last 18 years. Based on the correlation analysis and drought patterns, this study confirms that low precipitation was mainly attributed to the slowly declining vegetation trends and increased drought conditions in the semi-arid region. Therefore, immediate action is needed to minimize the negative impact of climate variability and increasing aridity in vegetation and ecosystem services.

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 Temporal Patterns of Precipitation and Vegetation Variability over Zimbabwe during Extreme Dry and Wet Rainfall Seasons

2014 ◽  
Vol 53 (12) ◽  
pp. 2790-2804 ◽  
Author(s):  
Seth Mberego ◽  
Juliet Gwenzi
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Variability ◽  
Temporal Distribution ◽  
Climate Extremes ◽  
Temporal Patterns ◽  
Distribution Patterns ◽  
Dry Spells ◽  
Dry Conditions ◽  
Dry Seasons

AbstractClimatic variability over southern Africa is a well-recognized phenomenon, yet knowledge about the temporal variability of extreme seasons is lacking. This study investigates the intraseasonal progression of extreme seasons over Zimbabwe using precipitation and normalized difference vegetation index (NDVI) data covering the 1981–2005 period. Results show that the greatest deficits/surpluses of precipitation occur during the middle of the rainfall season (January and February), and the temporal distribution of precipitation during extreme dry seasons seems to shift earlier than that of extreme wet seasons. Furthermore, anomalous wet (dry) conditions were observed prior to the development of extreme dry (wet) seasons. Impacts of precipitation variations on vegetation lag by approximately 1–2 months. The semiarid southern region experiences more variability of vegetation cover than do the northern and eastern regions. Three distinct temporal patterns of dry years were noted by considering the maximum NDVI level, the mid-postseason NDVI condition, and nested dry spells. The findings of this study emphasize that climate extremes ought not to be simply understood in terms of total seasonal precipitation, because they may have within them some nested distribution patterns that may have a strong influence on primary production.

scholarly journals Removal of Contaminated Pixels from the Desert Target for AVHRR Vicarious Calibration

2009 ◽  
Vol 26 (7) ◽  
pp. 1354-1366 ◽  
Author(s):  
Fangfang Yu ◽  
Xiangqian Wu
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Dust Storms ◽  
Screening Methods ◽  
Vegetation Growth ◽  
Vicarious Calibration ◽  
Calibration Device ◽  
Libyan Desert ◽  
Cloud Screening

Abstract Desert-based vicarious calibration plays an important role in generating long-term reliable satellite radiances for the visible and near-infrared channels of the Advanced Very High Resolution Radiometer (AVHRR). Lacking an onboard calibration device, the AVHRR relies on reflected radiances from a target site, for example, a large desert, to calibrate its solar reflective channels. While the radiometric characteristics of the desert may be assumed to be stable, the reflected radiances from the target can occasionally be affected by the presence of clouds, sand storms, vegetation, and wet surfaces. These contaminated pixels must be properly identified and removed to ensure calibration performance. This paper describes an algorithm for removing the contaminated pixels from AVHRR measurements taken over the Libyan Desert based on the characteristics of consistent normalized difference vegetation index (NDVI) land-cover stratification. An NDVI histogram-determined threshold is first applied to screen pixels contaminated with vegetation in each individual AVHRR observation. The resulting analyses show that the vegetation growth inside the desert target has a negligibly small impact on the AVHRR operational calibration results. Two criteria based on the maximum NDVI compositing technique are then employed to remove pixels contaminated with clouds, severe sand storms, and wet sand surfaces. Compared to other cloud-screening methods, this algorithm is capable of not only identifying high-reflectance clouds, but also removing the low reflectance of wet surfaces and the nearly indifferent reflectance of severe dust storms. The use of clear pixels appears to improve AVHRR calibration accuracy in the first 3–4 yr after satellite launch.

scholarly journals SPATIO-TEMPORAL SIMULATION AND ANALYSIS OF REGIONAL ECOLOGICAL SECURITY BASED ON LSTM

2017 ◽  
Vol IV-4/W2 ◽  
pp. 153-160 ◽  
Author(s):  
C. Gong ◽  
L. Qi ◽  
L. Heming ◽  
H. Karimian ◽  
M. Yuqin
Keyword(s):  
Deep Learning ◽  
High Speed ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Net Primary Productivity ◽  
Learning Ability ◽  
Scientific Management ◽  
Positive Trend ◽  
Ecological Deficit ◽  
Spatio Temporal

Region is a complicated system, where human, nature and society interact and influence. Quantitative modeling and simulation of ecology in the region are the key to realize the strategy of regional sustainable development. Traditional machine learning methods have made some achievements in the modeling of regional ecosystems, but it is difficult to determine the learning characteristics and to realize spatio-temporal simulation. Deep learning does not need prior identification of training characteristics, have excellent feature learning ability, can improve the accuracy of model prediction, so the use of deep learning model has a significant advantage. Therefore, we use net primary productivity (NPP), atmospheric optical depth (AOD), moderate-resolution imaging spectrometer (MODIS), Normalized Difference Vegetation Index (NDVI), landcover and population data, and use LSTM to do spatio-temporal simulation. We conduct spatial analysis and driving force analysis. The conclusions are as follows: the ecological deficit of northwestern Henan and urban communities such as Zhengzhou is higher. The reason of former lies in the weak land productivity of the Loess Plateau, the irrational crop cultivation mode. The latter lies in the high consumption of resources in the large urban agglomeration; The positive trend of Henan ecological development from 2013 is mainly due to the effective environmental protection policy in the 12th five-year plan; The main driver of the sustained ecological deficit growth of Henan in 2004-2013 is high-speed urbanization, increasing population and goods consumption. This article provides relevant basic scientific support and reference for the regional ecological scientific management and construction.

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