-
-
-
Open Access Article
1 - Estimation of wheat area cultivation using Sentinel 2 satellite images (Case study: Sojasroud region, Khodabandeh city, Zanjan province)
Seyed Ahmad Seyed Ahmad Nadia Abbaszadeh Tehrani Milad JanalipourWheat is one of the strategic agricultural products which provides one of the most basic nutritional needs of human societies for Iran and the whole world. Having the right statistics and information of the lands under wheat cultivation and estimating the amount of thei MoreWheat is one of the strategic agricultural products which provides one of the most basic nutritional needs of human societies for Iran and the whole world. Having the right statistics and information of the lands under wheat cultivation and estimating the amount of their production in one crop year can help the planners of agriculture and industry to manage the production and consumption of the mentioned product as effectively as possible. One of the tools that can calculate the level of wheat cultivation in the shortest time and with low cost and appropriate accuracy is the science and technology of remote sensing. In the present study, using a supervised classification of images from several time of Sentinel 2, the area under wheat cultivation and its production rate for the 96-97 crop year has been estimated. Supervised classification with the overall accuracy of 80% and a kappa coefficient of 0.8 has acceptable and suitable results for the identification and separation of wheat from other agricultural crops. Manuscript profile -
Open Access Article
2 - Investigation of forest land use degradation due to dam construction using satellite images processing
mandana azizi Mohammad panahandehIdentify land uses and land use changes to investigate and monitor sensitive areas is essential for sustainable land planning and management. The main objective of this study is to investigate the land use changes caused by the construction of Shafarood Dam in the Hyrca MoreIdentify land uses and land use changes to investigate and monitor sensitive areas is essential for sustainable land planning and management. The main objective of this study is to investigate the land use changes caused by the construction of Shafarood Dam in the Hyrcanian forests in the north of Iran during a 17-year period using Landsat satellite imagery. To do this, three satellite imagery of the years 2000, 2013 and 2017 were used, and the corrections (geometric and atmospheric) were applied on the images and the map of the land use for each section in the region was prepared using the classification method of the maximum likelihood that the produced map have Kappa coefficient more than 86% and usage accuracy of 0.83. After classification, the comparison method was used to monitor the land use changes. The results revealed that in every three years, the most land cover of Shafarood watershed belongs to the forest class and in the next rank belongs to the rangeland class. As a result, the continuous decline of the forest class accured from 63.05 percent to 57.27 and 57.22 percent in the first section for the years 2013 and 2017 respectively. The continuous increase of the rock class (8.15-9.10-10.45) and bare lands (3.5- 4.47-5.08%) confirms it in the study area. Environmental challenges of constructing the Shafaroud dam is another emphasis on the importance of conducting advanced and specialized studies based on ecological methodologies and also increasing the decision makers awareness of Hyrcanian forests complexity which has formed in a very long-time period. Manuscript profile -
Open Access Article
3 - Comparison of support vector machine and artificial neural network classification methods to produce landuse maps (Case study: Bojagh National Park)
Mahsa Abdoli Laktasaraei Maryam Haghighi khomamiNational parks and wildlife shelter are the most important natural heritages; therefore, knowing of quantitative and qualitative changes in their land use plays an essential role in the quality of these areas' management. various algorithms have been developed to classi MoreNational parks and wildlife shelter are the most important natural heritages; therefore, knowing of quantitative and qualitative changes in their land use plays an essential role in the quality of these areas' management. various algorithms have been developed to classify satellite imagery in remote sensing, selecting an appropriate classification algorithm is very important in achieving the accurate results. In this research, a more accurate algorithm was determined by comparing the classification accuracy of two artificial neural network and support vector machine algorithms, and it was used to examine the process of the land use changes. The present study was performed in Boujagh National Park, in the Guilan Province, during the years 2000 to 2017, using satellite imagery ETM and OLI of Landsat 7 and 8. The results of the research revealed that the support vector machine algorithm with overall accuracy and Kappa coefficient of 86.42 and 0.83 respectively for the year 2000 and, 90.65 and 0.88 for the year 2017, classified the satellite images more precisely, in comparison with the artificial neural network algorithm with overall accuracy and Kappa coefficient of 83.71 and 0.80 respectively for the year 2000 and overall accuracy and Kappa coefficient of 89.25 and 0.87 for the year 2017. Therefore, the land use maps of the support vector machine algorithm were used to determine the land use changes. The study of land use change by this method concluded that the areas of the waterbody, sea, grassland and agriculture have decreased and marshland, woody and bare lands classes showed an increase during the study period. Manuscript profile -
Open Access Article
4 - Monitoring and determination of the urban green coverage threshold based on Landsat data, Case study: Zones 1 and 6 from Shiraz city
hadi abdolazimi Hosein RoostaChanging the use of urban green cover over time can create various environmental hazards for the citizens of a city. Due to the importance of the subject, the present study intends to investigate the temporal and spatial changes of green cover in areas 1 and 6 of Shiraz MoreChanging the use of urban green cover over time can create various environmental hazards for the citizens of a city. Due to the importance of the subject, the present study intends to investigate the temporal and spatial changes of green cover in areas 1 and 6 of Shiraz metropolis using Landsat satellite images during five decades (1972 to 2019). For this purpose, after performing radiometric and atmospheric corrections, maps resulting from plant indices including NDVI, SAVI, OSAVI as well as the maximum likelihood algorithm were prepared in ENVI5 software and classified and evaluated in Spatial Information System (GIS). The results of this study showed that the area of the green cover in region 1 has decreased in terms of hectares in NDVI, SAVI, OSAVI indices respectively and also in the maximum likelihood algorithm has decreased from 1394 to 428, from 789 to 421, from 815 to 419, from 1402 to 439, respectively and in region 6 was decreased from 1374 to 858 (NDVI), from 1160 to 862 (SAVI), from 1149 to 884 hectares (OSAVI) and in the algorithm, the maximum likelihood of similarity has decreased from 1393 to 855 hectares. Investigation of threshold values of plant indices to identify urban green cover showed that the range of threshold values in NDVI was variable from 0.2 to 0.3, in SAVI was variable from 0.44 to 0.47 and in OSAVI was variable from 0.34 to 0.36 and using Pearson test in SPSS software, correlation coefficient values between NDVI, SAVI, OSAVI, maximum likelihood algorithm and the studied years were significant at the 1% level. The results of this test also indicated that there was no significant difference between the results of these methods in this study. This reduction of green cover is considered a serious danger for the citizens of Shiraz. Manuscript profile -
Open Access Article
5 - Investigation and prediction on Forests Covers Changes Using Fuzzy Object-Based Satellite Image Classification and CA-Markov (case study: City of Romeshkan)
Rahman Zandi Hajar Shehabi Ebrahim AkbariForest is a valuable heritage and one of the important factors in the ecosystem of each area that in addition to using and exploiting them, they should be preserved. Zagros’ forests, especially in Lorestan province due to negligence have been destroyed throughout past y MoreForest is a valuable heritage and one of the important factors in the ecosystem of each area that in addition to using and exploiting them, they should be preserved. Zagros’ forests, especially in Lorestan province due to negligence have been destroyed throughout past years. The aim of this research is to investigation, detect and modeling Romeshkan’s forests’ cover changes. To do this, first changes that were taken place between 1987-2017 were extracted by satellite Landsat images and using Fuzzy Object-Based classification method, then, were classified in 5 classes (Agriculture, Forest, Range, water and Residential). Finally, classification results show that there is a sharp decrease of forested areas (81.17 km2) and an increase of Range and Farmlands over past 30 years in the forest area. In a period of 1987-2002 forest cover of the study area had not faced major changes, but most of the rangelands turned to farmlands. While in the second period from 2002 onwards forest cover dramatically dipped and its area decreased from 122.58 km2 to 43.42 km2 in 2017, which the rate of forest covers decrement was around 79.16 km2. Moreover, in order to predict forest cover changes in the future CA-Markov model was applied that indicates 10.70% of current forest covers will be reduced in 2030, and the main changes will be occurred between forest classes to farmlands and rangelands classess by 6.901 and 9.172 km2, respectively. Manuscript profile -
Open Access Article
6 - Determination of Potato Crop Cultivation in Hamedan Province, Using time series Satellite Images IRSP6
Ali shahbazi Loghman khodakrami kamran nasirahmadiThe aim of this study is to detect and quantify the cultivated area of potato fields in Hamadan Province using remote sensing methods and a time series of satellite photos. As a result, Awifs time-series imaging was used to determine the potato cropping area. For this p MoreThe aim of this study is to detect and quantify the cultivated area of potato fields in Hamadan Province using remote sensing methods and a time series of satellite photos. As a result, Awifs time-series imaging was used to determine the potato cropping area. For this purpose, pictures were taken at three different times when the potato plant turned green and yellow. Processing such as preparation, atmospheric and geometric correction, vegetation index, and unsupervised classification were performed on the images using appropriate training sites for supervised classification. Following the integration of these two layers, the studied area under the cropping map was prepared using the phase classification method. Additionally, by using the vegetation indices NDVI and SAVI, the area under cropping for the three main crop yields is determined first using the threshold level technique and in three temporal intervals. The kapa coefficient for potato under cropping area determined by phase classification, NDVI, and SAVI was 90, 87, and 85%, respectively. In 1998, the potato cropping area was determined to be 38740, 36728, and 36614 acres, respectively. This study clearly shows that the phase classification method and Awif data time series can be used to recognize and estimate potato under cropping area with acceptable precision and that vegetation indices distinguish potato under cropping area faster. Manuscript profile
List of Articles Classification
-
The rights to this website are owned by the Raimag Press Management System.
Copyright © 2017-2024