Spatial Analysis of Urban Thermal Island in Northern Iran (Case Study: Rasht City)

Land surface temperature (LST) is one of the key parameters in hydrology, meteorology, and the surface energy balance.The one-window algorithm of Kim et al. Uses Landsat satellite imagery to model the earth's surface temperature.These trends are validated using meteorological data. Two main and basic factors play a major role in the temporal and spatial trend of the thermal islands of Rasht. These two factors of climate change that have occurred in the last two decades in the region of Gilan province and the city of Rasht. The second factor that has greatly enhanced the effect of the first factor is the human factor that has greatly included other urban factors in Rasht, including urban management and proper urban planning in the province and the city of Rasht. These two factors in the temporal and spatial trend of urban thermal islands have caused thermal islands to rapidly increase the growth of the city and urban population from the urban center to the western and southwestern regions and have very negative effects on land use changes and human areas. It has caused the construction of Rasht city.

Chemical control of water hyacinth by some herbicides and their effect on some aquatic invertebrate

Water Hyacinth (Eichhornia crassipes), regarded as one of worst aquatic weeds in the world, has been an invader in northern Iran, particularly in the Anzali Wetland. Herbicide application as a control method with respect to ecosystem health has been investigated. The effects of three herbicides, glyphosate (Roundup), Glufosinate-ammonium (Basta), and Bispyribac sodium (Nominee) were investigated on water hyacinth and on the survival of five aquatic invertebrates from the Anzali Wetland including Hemiptera, Amphipoda, Odonata, Ostracoda and Daphnia. The treatments consisted of 3 L/ha of glyphosate, 5 L/ha of Glufosinate-ammonium, and 0.3 L/ha of Bispyribac sodium. European Weed Research Council (EWRC) rating scale determining reduction of wet and dry weight of shoot was the basis of assessment to determine the effectiveness of the herbicides in the control of of water hyacinth. All herbicides were effective on water hyacinth while Roundup caused a significant reduction of shoot biomass and scored 98% on the EWRC scale. Bayesian mediation model was used to calculate total and decomposition effect of herbicides on animal groups. Based on the Bayesian mediation model, Basta showed the best performance with lowest probability of a negative effect (PEff<0=0.22). The accuracy of dosages and spraying of herbicides can be considered the most effective in inhibiting water hyacinth and the least destructive to living organisms.

COVID-19 in Pediatrics: Demographic, Clinical, Laboratory, and Radiological Characteristics of Infected Patients With SARS-CoV-2

The COVID-19 disease usually leads to mild infectious disease in children, but some develop serious complications. Here, we describe the characteristics of children with COVID-19 in northern Iran, the Golestan province. Ninety-one confirmed cases were enrolled in the study, aged 0–18 years. Demographic, clinical, comorbidity, laboratory, and radiological data were compared based on the disease severity (admitted to intensive care unit (ICU) or not) and disease outcome (recovered or deceased). Sixteen (17.5%) cases were hospitalized in ICU, and 8/91 (8.8%) deceased. Fever and cough were the most common clinical symptoms. Among all symptoms notified there were no significant differences between severe and milder cases, or between those who deceased and recovered. Failure to thrive (FTT), malignant disease and neurological disease were significantly more prevalent in severe cases as was frequently reported comorbidities. Laterality, ground-glass opacity, and lung consolidation were the most common findings in chest computed tomography. The data confirms that the COVID-19 disease has various presentations in children, and clinical, laboratory, and radiological findings may help predict the development of severe forms of COVID-19 among children.

Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 Data

Due to the challenges brought by field measurements to estimate the aboveground biomass (AGB), such as the remote locations and difficulties in walking in these areas, more accurate and cost-effective methods are required, by the use of remote sensing. In this study, Sentinel-2 data were used for estimating the AGB in pure stands of Carpinus betulus (L., common hornbeam) located in the Hyrcanian forests, northern Iran. For this purpose, the diameter at breast height (DBH) of all trees thicker than 7.5 cm was measured in 55 square plots (45 × 45 m). In situ AGB was estimated using a local volume table and the specific density of wood. To estimate the AGB from remotely sensed data, parametric and nonparametric methods, including Multiple Regression (MR), Artificial Neural Network (ANN), k-Nearest Neighbor (kNN), and Random Forest (RF), were applied to a single image of the Sentinel-2, having as a reference the estimations produced by in situ measurements and their corresponding spectral values of the original spectral (B2, B3, B4, B5, B6, B7, B8, B8a, B11, and B12) and derived synthetic (IPVI, IRECI, GEMI, GNDVI, NDVI, DVI, PSSRA, and RVI) bands. Band 6 located in the red-edge region (0.740 nm) showed the highest correlation with AGB (r = −0.723). A comparison of the machine learning methods indicated that the ANN algorithm returned the best ABG-estimating performance (%RMSE = 19.9). This study demonstrates that simple vegetation indices extracted from Sentinel-2 multispectral imagery can provide good results in the AGB estimation of C. betulus trees of the Hyrcanian forests. The approach used in this study may be extended to similar areas located in temperate forests.

Assessment of Some Toxic Metals in Ziziphora (Ziziphora persica) Obtained from Local Market in Lahijan, Northern Iran

: Heavy metals cause significant issues when people are exposed to many specific types of them. They can cause many disorders and affect the biochemical pathways in the body. Herbs are known as one of the richest sources of modern patented drugs, particularly in Iranian references. Many metals, particularly heavy metals, are toxic. Various studies have shown a higher level of heavy metals than standards in some countries like Iran, Pakistan, Egypt, and Nigeria. A preliminary study was conducted to determine some toxic elements in powdered Ziziphora (Ziziphora persica) collected from the local market in Lahijan city, northern Iran. Twenty random samples were gathered from various markets, and a flame atomic absorption spectrophotometer (FAAS) was used to detect some featured toxic elements, including copper (Cu), cadmium (Cd), lead (Pb), zinc (Zn), and mercury (Hg). The results showed higher Pb, Cd, and Hg levels than standards. Besides, Cu and Zn were detected to be lower than standards.

Drought assessment in paddy rice fields using remote sensing technology towards achieving food security and SDG2

PurposeThis research aims to monitor vegetation indices to assess drought in paddy rice fields in Mazandaran, Iran, and propose the best index to predict rice yield.Design/methodology/approachA three-step methodology is applied. First, the paddy rice fields are mapped by using three satellite-based datasets, namely SRTM DEM, Landsat8 TOA and MYD11A2. Second, the maps of indices are extracted using MODIS. And finally, the trend of indices over rice-growing seasons is extracted and compared with the rice yield data.FindingsRice paddies maps and vegetation indices maps are provided. Vegetation Health Index (VHI) combining average Temperature Condition Index (TCI) and minimum Vegetation Condition Index (VCI), and also VHI combining TCImin and VCImin are found to be the most proper indices to predict rice yield.Practical implicationsThe results serve as a guideline for policy-makers and practitioners in the agro-food industry to (1) support sustainable agriculture and food safety in terms of rice production; (2) help balance the supply and demand sides of the rice market and move towards SDG2; (3) use yield prediction in the rice supply chain management, pricing and trade flows management; and (4) assess drought risk in index-based insurances.Originality/valueThis study, as one of the first research assessing and mapping vegetation indices for rice paddies in northern Iran, particularly contributes to (1) extracting the map of paddy rice fields in Mazandaran Province by using satellite-based data on cloud-computing technology in the Google Earth Engine platform; (2) providing the map of VCI and TCI for the period 2010–2019 based on MODIS data and (3) specifying the best index to describe rice yield through proposing different calculation methods for VHI.