Investigation of the relationship between dust storm index, climatic parameters, and normalized difference vegetation index using the ridge regression method in arid regions of Central Iran

Khusfi, Zohre Ebrahimi; Roustaei, Fatemeh; Khusfi, Mohsen Ebrahimi; Naghavi, Somayeh

doi:10.1080/15324982.2019.1694087

Cited by 30 publications

(4 citation statements)

References 84 publications

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“…Touré, et al [35] highlighted the sensitivity of wind erosion to vegetation, showing that even a low cover rate has a strong impact on wind erosion. In Iran, Khusfi et al [36] and Khusfi et al [37] observed a significant negative relationship between the Enhanced Vegetation Index (EVI) and Dust Storm Index (DSI) changes in the spring season. Based on observations and wind tunnel tests, Cheng et al [38] quantitatively established the relationship between the wind erosion rate and its effect on vegetationcovered soil surfaces.…”

Section: Introductionmentioning

confidence: 99%

Grain Size Characteristics of Sediments Found in Typical Landscapes in the Playa of Ebinur Lake, Arid Central Asia

Abuduwaili

2021

Land

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A playa usually refers to a salt desert landscape mainly composed of loose and fine lacustrine sediments. Severe wind erosion on a playa causes the playa to become a source of dust and salt dust and poses a threat to vast areas downwind. Currently, little is known about the impact of wind erosion on the particle size distribution of sediments in different landscapes in the playa. In the present study, six dominant different landscapes in a natural state with the same sedimentary environment in the playa of Ebinur Lake were selected to provide insights into the different characteristics of particle size distribution under the effect of long-term wind erosion. The results reveal that the grain-size composition clearly differed among different landscapes. All samples had a common dominant size group consisting of very fine sand and sand. The very fine sand and sand content of Haloxylon ammodendron desert zone (LS5) was the lowest, while the clay and silt content was the highest at both depths among the six landscapes. The lowest clay and silt fraction and highest sand fraction appeared in the herbal desert zone (LS3) at both depths. Almost all of the sediment samples were of a bimodal distribution mode, with significant differences. The cumulative curve showed a similar S-shape, while the probability cumulative curve showed an inverted S-shape with three subpopulations of granularity characteristics. The smallest mean particle diameter appeared in LS5. The majority of the sediments were moderately to poorly sorted. The mean particle size of the sediments from the six landscapes was significantly different (p < 0.05), while no significant difference was observed among the other three parameters. Generally, it can be inferred that LS5 can reduce wind speed effectively, probably due to the smaller leaves and dense branches of Haloxylon ammodendron, which results in a high level of coverage. The results of the present study will have some implications for the grain size characteristics for changes in intensity in regional wind erosion environment and will also have some basis for wind erosion prevention and control in the playa of Ebinur Lake.

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Section: Introductionmentioning

confidence: 99%

Grain Size Characteristics of Sediments Found in Typical Landscapes in the Playa of Ebinur Lake, Arid Central Asia

Abuduwaili

2021

Land

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“…The ridge regression reduces the model's complexity by a coefficient shrinkage and improves the least-squares error by applying a degree of bias to the regression estimates. The lasso regression (Least Absolute Shrinkage and Selection Operator) works similarly, since it also adds a penalty for non-zero coefficients, but differently from the ridge regression, which penalizes the sum of the squared coefficients (L2 penalty, represented by the first set inside the parenthesis-Equation ( 5)), lasso penalizes the sum of their absolute values (L1 penalty, represented by the second set inside the parenthesis-Equation ( 5)) [70][71][72]. Thus, elastic-net regression combines both lasso and ridge methods by learning from their shortcomings to improve the regularization of these statistical approaches.…”

Section: Methodsmentioning

confidence: 99%

Modeling Carbon Release of Brazilian Highest Economic Pole and Major Urban Emitter: Comparing Classical Methods and Artificial Neural Networks

Debone

Martins

Miraglia

2022

Climate

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Despite the concern about climate change and the associated negative impacts, fossil fuels continue to prevail in the global energy consumption. This paper aimed to propose the first model that relates CO2 emissions of Sao Paulo, the main urban center emitter in Brazil, with gross national product and energy consumption. Thus, we investigated the accuracy of three different methods: multivariate linear regression, elastic-net regression, and multilayer perceptron artificial neural networks. Comparing the results, we clearly demonstrated the superiority of artificial neural networks when compared with the other models. They presented better results of mean absolute percentage error (MAPE = 0.76%) and the highest possible coefficient of determination (R2 = 1.00). This investigation provides an innovative integrated climate-economic approach for the accurate prediction of carbon emissions. Therefore, it can be considered as a potential valuable decision-support tool for policymakers to design and implement effective environmental policies.

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“…38 As demonstrated by consequent data which was reported in papers the number of daily dust events has been gradually increased in the East and Southeast of Iran in the last decade. [39][40][41][42][43] However, it is interesting to note that dust events containing high volumes of PM can transport a high diversity of air-borne pathogens. 44 On the other hand, the presence of numerous mines of lead, zinc, iron, and gold in Kavir desert regions and the activities related to them result in a high exposure to those elements by the nearby urban areas surrounded by those desert areas.…”

Section: Outdoor Air Pollutionmentioning

confidence: 99%

Socio-Environmental Determinants and Human Health Exposures in Arid and Semi-Arid Zones of Iran—Narrative Review

Kalankesh

Rodríguez‐Couto

Alami

et al. 2022

Environ�Health�Insights

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Lifestyle is different in arid and semi-arid zones. However, where people are born and live have a lasting influence on their social and environmental exposure. This review focuses on the, various dimensions of environmental health imbalance inequality especially in significant environmental sources such as (ie, air, water, soil) among provinces that creates a big health gap in the center, East and the Southeast of Iran. Thus, the population of the arid and semi-arid zones of Iran is facing respiratory, cardiovascular, cancer and infection diseases linked to environmental problems such as chemical and microbial pollution due to air pollution and unsafe water sources, respectively. The prevalence of certain types of cancer such as skin, stomach, bladder, prostate and colorectal cancer together with some respiratory and cardiovascular diseases in arid and semiarid zones such as Kerman, Yazd, etc., has been reported in comparison with other provinces frequently. These impacts have effects on multiple levels of health security in those zones. Based on these concerns, we propose key questions that should guide research in the context of the socio environmental science to support science-based management actions in Iran and other similar semi-arid areas worldwide.

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Investigation of the relationship between dust storm index, climatic parameters, and normalized difference vegetation index using the ridge regression method in arid regions of Central Iran

Cited by 30 publications

References 84 publications

Grain Size Characteristics of Sediments Found in Typical Landscapes in the Playa of Ebinur Lake, Arid Central Asia

Grain Size Characteristics of Sediments Found in Typical Landscapes in the Playa of Ebinur Lake, Arid Central Asia

Modeling Carbon Release of Brazilian Highest Economic Pole and Major Urban Emitter: Comparing Classical Methods and Artificial Neural Networks

Socio-Environmental Determinants and Human Health Exposures in Arid and Semi-Arid Zones of Iran—Narrative Review

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