مهدی حسنلو

Today, remote sensing is an effective method for identifying drug crops, along with traditional methods such as field visits. This technology has been able to reduce the limitations of traditional methods and become efficient in spending money and energy. Numerous researches have been carried out in the field of identifying and extracting the area under poppy cultivation in the world, and due to the extent of these researches, the variety of data and methods used in them, it is necessary to collect and analyze them in an integrated manner. It can be useful and pave the way for future researches.

The upcoming research collects the previous researches that have been done in the field of identification of poppy cultivation using remote sensing method. After a comprehensive review of the articles, the algorithms used in them have been extracted, and as an example, two selected methods have been implemented in the regions of Afghanistan and Turkey.

Among the existing methods, two selected methods based on supervised and unsupervised classification with two views based on pixels and visual objects, as well as the use of a vegetation index, have been selected for implementation.

The implementation of these methods on areas of Afghanistan›s Helmand province and Gonen region in Turkey has shown that they have been able to with an average accuracy of more than %88 (the accuracy obtained in the studied cases is %83 ,%90.8 ,%80 and %97.8) identify poppy cultivation.

Cultivated saffron (Crocus sativus L.) boasts remarkable commercial value due to its possessing three pivotal metabolites: crocin, picrocrocin, and safranal. The significance of obtaining these metabolites, particularly crocin, from sources other than cultivated saffron has grown substantially, primarily driven by native wild saffron species in Iran. In this ongoing study, High-Performance Liquid Chromatography (HPLC) has been harnessed as a potent analytical tool for the identification of these metabolites in two wild saffron species, Khazar (C. caspius) and Ziba (C. specious), alongside the cultivated variety. Furthermore, bioinformatics tools have been employed to extract nucleotide and protein sequences, thereby facilitating the prediction of protein structures for genes integral to the biosynthesis process of these notable apocarotenoids in an in-silico manner. The research findings have showcased the presence of crocin across all analyzed samples, albeit in varying quantities. Specifically, the crocin content in the cultivated saffron, Ziba, and Khazar species accounted for 26.76%, 2.8%, and 0.74% of dry weight matter, respectively. However, the amount of picrocrocin and safranal metabolites in cultivated species was 8.4 and 0.03 percent, respectively, but there were no detectable amounts of these apocarotenoids in the studied wild species. , The existence of crocin in wild species has made hope for conducting research and searching in wild species for these effective substances and implementing breeding programs or genetic manipulation for the mentioned species.

Agricultural saffron Crocus sativus L. is a medicinal, widely used and expensive plant and has important effective substances: crocin, picrocrocin and safranal, which gives it the characteristics of color, taste and smell. The search for new sources producing the aforementioned apocarotenoids makes the importance of research on it more obvious day by day. Since the country of Iran has diploid wild species with characteristics close to the sterile triploid cultivated species, in the present research, two species of Caspian saffron C. caspius and Zeiba C. Speciosus, along with the cultivated species, were investigated and 6 genes active in the production of the three mentioned effective substances , CCD2, ALDH, PSY, LCY, BCH, UGT74 (and a housekeeping gene TUB as an internal control gene with constant expression in all tissues) in two flower tissues, stigma and perianth (tepal) and in five stages (time) of flowering including: The stages of bud formation (immature bud), bud ready to bloom, newly opened flower, mature flower and old flower were investigated. Using of Real Time PCR, the expression ratio (fold change) to the internal control gene (with logarithm based on 2) was investigated in different genes and different and sometimes similar expression patterns were observed with the gene expression in the cultivated species in both the stigma and stigma tissues. Based on the results obtained in this study and the increase or decrease in the expression of some genes involved in the pathways of apocarotenoids production, at the same time as the growth of the stages from the bud to the senescence stage of the flower, it is expected from the three aforementioned substances or from other apocarotenoids in the metabolom of flowers, cases have been found in the non-triploid species and create approaches for the commercial use of Iranian wild saffron species and pave the way for its commercialization.

The coastline is considered as the boundary between water and land. coasts are one of the most important environmental effects that directly affect human life. Rising sea levels due to global warming have made coastal cities among the areas under threat. Therefore, management and planning to prevent coastal erosion is one of the important issues that should be considered. In this research, we have studied the changes of shoreline using sentinel-1 satellite images in mazandaran province, the coast between the cities of chalous and tonekabon. For this purpose, two images on 15/01/2019 and 01/09/2021 have been used and the desired images have been taken from the google earth engine system. In the pre-processing step of the images, we corrected the height error of the study area and adjusted the speckle noise. The edge of the shore was discovered with the otsu threshold in the images. Finally, Digital Shoreline analysis system (DSAS) was used to calculate the amount of sedimentation and erosion of the coast by EPR technique. In 87% of the coast of this transects, we have witnessed coastal erosion. The average amount of erosion is about 7 meters per year.

In order to study in shallow coastal areas, free Landsat 8 image with relatively high radiometric resolution and the presence of two bands, coastal blue and blue is suitable. In this study, in addition to Landsat satellite imagery, hydrographic data has also been used. In order to increase the accuracy and reduce the error, tried as much as possible the passing time of the Landsat 8 sensor close to the acquisition terrain date. The purpose of this study is bathymetry of the southeastern part of the Caspian Sea using the PCA algorithm on the pre-processed visible region. In this study, the FLAASH and Dark Object Subtract (DOS) atmospheric corrections were applied separately to visible bands. The obtained depth results by applying PCA transformation to these two types atmospheric correction is investigated. PCA algorithm is implemented in four different forms. Statistical parameters R^2, RMSE, and NRMSE are calculated between obtained data by PCA and hydrographic data in two types of atmospheric correction. The results show that in both of atmospheric correction, the accuracy of estimated depth by PCA is increased when four or three PCA components are introduced as algorithm inputs compared with only two or one PCA components are used. As well as, the use of four components, the accuracy of DOS in bathymetry with values of R2=0.91, RMSE=0.3,and NRMSE=0.05 has shown a better result in comparison to FLAASH correction's values R2=0.87, RMSE=0.38, and NRMSE=0.06.

In recent years, use of non-metric imaging sensors is becoming increasingly common in unmanned vehicles. This can be considered as an alternative to terrestrial mapping. Due to the limitations such as dimension, system weight, and the nature of UAV platform, it is not possible to use high volume and heavy metric sensors. Consequently, most sensors used in UAV platforms are light weight non-metric cameras. Determining the values of the internal parameters of the sensor is important in monitoring the variations of these sensors and improving the triangulation results of these images. Therefore, laboratory geometric calibration for these sensors under similar operating conditions produces better results in later stages. Our station is capable of performing calibration observations and also the calculations of a wide range of non-metric cameras and is currently serving in related organizations with ability to evaluate the accuracy of calibration results.

Soil salinity is considered to be a major cause of desertification and destruction of environmental resources in arid and semi-arid regions. Due to the importance of conserving natural resources and also the increasing trend of soil salinity during the last few years, determining the extent of salinity spread and its severity in affected areas is especially important. Using the potential of high resolution satellite imagery and remote sensing techniques is one of the most effective ways for detecting salinity in salt affected regions. Among different satellite sensors, satellites which provide large scale multispectral satellite imageries with high spatial and spectral resolution have a high potential for assessing salinization and mapping soil salinity in study regions.

Accordingly, this paper aims to map different salinity levels in an area in Kuh-Sefid district (Qom Province), which is highly affected by salinity, using Sentinel-2 recent imageries. For this purpose, field study was conducted and salinity level was measured for several soil samples randomly collected from the site. Different salinity indicators, like salinity and vegetation indices, LST, and Digital Elevation Model of the site produced based on SRTM elevation data were also extracted from corresponding satellite images. These indicators were then used for mapping salinity levels in Kuh-Sefid district. Principal Component Analysis was used to gain the largest amount of available information and reduce the dimensionality of data cube. Based on the performed analysis, different supervised classification algorithms were used to map salinity levels and divide the site into five distinct salinity classes - normal, slightly saline, moderately saline, highly saline, and extremely saline. 

Data was analyzed based on five supervised classification algorithms, including Minimum Distance, Mahalanobis, Parallelepiped, Maximum Likelihood, and Support Vector Machine (SVM). Results indicated that the best accuracy in mapping salinity classes was obtained from SVM classifier, with overall accuracy of 92.218 and Kappa coefficient of 0.894. The results also revealed that Maximum Likelihood Classifier with overall accuracy of 90.718 has a high potential for discriminating saline surfaces and producing salinity map. In addition, more than 62% of soil types in this region are categorized in moderate, high and extreme salinity classes, which indicates that the area is highly at risk. 

Evaluating the results of salinity classes shows that the eastern areas of Kuh-Sefid are relatively more severely affected by salinity. This is due to vicinity of Qom Salt Lake and drawing of saline soil into surrounding areas. If this process continues, it will lead to loss of soil fertility and crop productivity in this region over the next few years. Due to their potential in detecting soil salinity and providing large-scale maps of salinity levels, multispectral Sentinel-2 imageries are considered to be a powerful tool in soil reclamation programs and land management studies.

Coral reef communities face unprecedented pressures at local, regional and global scales as a consequence of climate change and anthropogenic disturbance. Remote sensing, from satellites or aircraft, is possibly the only means to measure the effects of such stresses at appropriately large spatial scales. Coral reefs are indicators of environmental, climate and sea surface change which shows the reefs damages. For this purpose, an algorithm that includes relation between those variables was used. Australia’s Heron reef island is considered to be studied. In order to modeling the coral reef health condition by support vector regression (SVR), water and coral important spectral indexes and features was found using landsat-8. From this method, the SVR is achieved the high performance for modeling the statistical problem .In this study we used genetic algorithm (GA) and sequential feature selection (SFS) for selecting suitable features in order to estimate model. The results for the testing data in this area of best model is [RMSE= 0.53 and R² =0.983] that show the high SVR performance.

Rocky sanctuaries are the most valuable works of Iranian architecture, that have been formed over a long period of time, and due to the continuity of traditions or slowness of the transformation process, their exact date is difficult. Among them “Kohulu Mechid” is the rocky sanctuary in the city of Maragheh, East Azarbaijan, which, no coherent studies have been conducted around it yet. This research seeks to provide dates and more acceptable practices for this sanctuary, through a comparative study and a review of some of the details, though deep and accurate research needs archaeological speculation and science. However, according to available evidence and based on the present research, this rocky structure was created during the Ilkhanid period and the nature of its usage, religious sanctuary , is proposed for non-Islamic religions, including Buddhists and Christianity, that is called mosque with religious reforms in later periods and its user modification.

Soil salinity is one of the serious environmental hazard and agriculture problems in arid and semiarid areas. Monitoring and assessing this phenomenon in affected areas is restricted and has been associated with poor results in optical remote sensing. Using potential of radar remote sensing can be effective approach for detecting salinization in salt affected areas due to the sensitivity of signal to dielectric properties of the target. The dielectric constant, which is considered as inherent characteristics of the surface, impacts the radar backscattering coefficient and is an important factor for simulating the radar backscattering coefficient. This paper deals with modeling the backscattering coefficient of salt affected soils by evaluating its dielectric constant behavior. For this purpose, semi-empirical model, which proposed by Wang were used and dielectric constant was estimated in both real and imaginary parts, as a function of salinity and volumetric soil moisture content for different types of soil texture in different frequencies. We also used two backscattering models, Dubois and Oh, to simulate backscattering coefficient of the Sentinel-1 data in VV and VH polarization. The results showed that real part of dielectric constant is influenced by soil moisture and increases with amount of water content up to 50. Imaginary part is also influenced by both salinity and moisture content and increase up to 40. The results also indicated that both real and imaginary parts of dielectric constant decrease sharply with increasing frequency, which reveal the necessity of using low frequencies to detect salt affected soils due to its higher sensitivity to salinity and moisture content in these frequencies. Evaluating the results of simulating the backscattering coefficients in VV and VH polarization, showing the RMSE=2.9554, Bias=-1.5138 for Dubois model in VV polarization and RMSE=2.0704, Bias=0.9839 for Oh model in VH polarization. It can be concluded that used models have great potential for modeling radar backscattering in salt affected soils.