Extraction, processing, production and display of geographic data
Qadir Ashournejad
Abstract
Extended AbstractIntroductionRemote sensing is considered as the most important source of spatial data in the current era, which we witness its increasing development in different dimensions. The release of global products of these data in recent years with the aim of easier access and use by experts ...
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Extended AbstractIntroductionRemote sensing is considered as the most important source of spatial data in the current era, which we witness its increasing development in different dimensions. The release of global products of these data in recent years with the aim of easier access and use by experts in geospatial science is one of the dimensions of this development. The land cover product is one of these products that is used more than other remote sensing products. When presenting these products, their qualitative and quantitative characteristics, including their global accuracy, are also published. Expressing the accuracy of these products globally makes it necessary and necessary to re-evaluate their accuracy regionally for the users of these products in different regions of the world.Materials & MethodsIn this research, the accuracy of the European Space Agency's Copernicus Global Land Service (CGLS), GlobeLand30 and Esri's land cover product were evaluated for regional use in the north of Iran - Mazandaran province. After calculating the area of the classes for each of the land cover products, Pearson's correlation coefficient was used to calculate the correlation between them. For quantitative evaluation, the error matrix was used as one of the most common ways to evaluate the accuracy of land cover products. This method is based on the comparison of classified data and ground reality data. Also, the categorized random sampling method was used to select 1329 evaluation samples in Mazandaran province. For visual evaluation, three areas with dimensions of 6 x 6 km were selected.Results & DiscussionThe regional accuracy evaluation of the studied products shows opposite results compared to the global accuracy of these products. Based on the global accuracy reported for the studied products, the highest accuracy is calculated for the Esri product at 86%, followed by GlobeLand30 and CGLS at 83-85 and 80%. Meanwhile, based on the regional accuracy obtained from the results of this research, the highest regional accuracy for the CGLS product has been calculated at 84% and then for GlobeLand30 and Esri products at 81 and 75%. In evaluating the regional accuracy of the classes, all three studied products (CGLS, GlobeLand30 and Esri) have acceptable accuracy (above 90%) in the classes of snow and ice (100, 100 and 100%), forest (90, 95 and 98 percent), water (96, 94 and 90 percent) and impervious surface (94, 91 and 90 percent). For the agricultural class, accuracy equal to 92, 69 and 84% was obtained for CGLS, GlobeLand30 and Esri land covers.In the 3 classes of shrubland, Impervious surface and wetland, the accuracy results are less than other classes for all three land cover products and in the amount of (29, 0 and 13 percent), (65, 66 and 42 percent) and (67, 38 and 0 percent).Conclusion By evaluating and comparing the regional accuracy of three CGLS products, GlobeLand30 and Esri, this research answered the question of whether the accuracy stated in global land cover products can be trusted for regional studies and planning. The results show that the regional accuracy of CGLS, GlobeLand30, and Esri are 84, 81, and 75 percent, respectively, compared to their global accuracy (80, 83, 85, and 86 percent). These results show the difference obtained for the Esri product more than the two products CGLS and GlobeLand30. Meanwhile, the remote sensing data used for the Esri product (Sentinel-2 data) and its pixel size (10 meters) are of higher quality and quantity than the other two products. In fact, these results show that only paying attention to the type of data used and the global accuracy is not enough to use products in regional scales and requires evaluations before using them.In addition, by evaluating the classes of each product and comparing them, the need for this evaluation before using these products seems necessary. The results showed that in the evaluation of the regional accuracy of the classes, all three studied products had an accuracy of over 90% in the classes of snow and ice, forest, water areas and human construction. For the agricultural land class, accuracy equal to 92, 69 and 84% was obtained for CGLS, GlobeLand30 and Esri land covers. In the 3 classes of shrubland, herbaceous cover and wetland, the results show lower accuracy than other classes for all three land cover products. Significant results were also obtained in the visual evaluation, and it seems necessary to pay attention to this evaluation before the applications where it is important to pay attention to a particular class.
Mohammad Rahim Rahnama; Mohammad Ajza Shokouhi; behnam ata
Abstract
Extended abstract Introduction Cities are always influenced by various forces and factors. They are transformed by social changes, demographic displacements, economic changes, and technological innovations. As the population grows, activities and investments are greatly expanded and the ...
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Extended abstract Introduction Cities are always influenced by various forces and factors. They are transformed by social changes, demographic displacements, economic changes, and technological innovations. As the population grows, activities and investments are greatly expanded and the physical system of the cities undergoes fundamental changes.Along with the rapid urbanization process, a large amount of natural lands, such as forests and wetlands, has turned into agricultural land and residential areas. Quick land use changes have had profound effects on natural and human environments. For example, agricultural developments and structures lead to deforestation, soil erosion, water basin degradation, and biodiversity loss and pollution. In addition, changes in the use of agricultural land and the acceleration of urbanization have led to an increase in impenetrable levels, which has led to the development of a transport network and the accumulation of non-disturbing contaminations associated with surface runoff. Due to these great effects, the detection and anticipation of land use changes has become an important topic in environmental management and land use planning. At their initial stagesof formation, most of the cities in Iran were established near or in the middle of thehigh-quality agricultural lands with the purpose of using high-quality soil foragriculture and then, these lands were gradually buried under the cities throughdevelopment of villages and changing into cities and then development of thecities. Accordingly agricultural activities were inevitably receded to the poorlands. Materials & Methods To access fundamental maps for analysis of data and use of different methods to achieve the goal of this study, satellite images related to the years 1987,2000 and 2010 are used. Topographic maps of 1:50000 scales obtained from the army geographical organization are used for geometric correction. At this stage, geometric correction was performed on the images using image sensor TM of the year 2010 image-vector, which were geo-referenced. To perform this task, 42ground control points with appropriate distribution in road junctions, water channels, etc. were used. In this research, to process data, make models, and analyze the output, land cover maps produced in the years 1987 and 2014 as inputs of the LCM model, were selected to analyze the changes in the region and predict land use changes in the year 1404. The LCM model requires two maps covering lands belonging to different times as inputs. In this study, Gains and losses, net changes, unchanged regions, transitions from each user to another in different classes of land cover, were mapped to the model analysis section of the model.ENVI, IDRISI Selva and ARCGIS10 were used to categorize the uses of most-probability-models and methods and finally Ca_Markov model was used to predict and calculate changes in 2025, 2035 and 2045. Results & Discussion Multi-temporal images used in this study were used in mapping land coverafter geometric corrections. With regard to existing images and maps and the condition of the area under investigation and field visit for mapping land cover, five types of applications are discovered for land namely, residential lands,irrigated lands, rain-fed lands, sterile lands, parks and gardens. Altogether, during this time (27years), agricultural and residential land cover has increased and sterile land and rain-fed land cover has decreased. Agricultural lands consume a huge amount of water due to exploiting water from deep holes and land overuse that has turned rain-fed lands and sterile lands into water-fed and residential lands. As the table of predicting areas indicates, the greatest increase of about 1744/74 hectares belongs to agricultural lands and 1741/79 hectares belong to the urban lands which includes: residential lands, trade centers, military areas, hospitals, higher education institutes, etc. The least change which is 274/18 hectares, belong to parks and gardens in and around the cities. The most decline of 2261/59 hectares, is observed in sterile lands. Of the total net changes, one can conclude that urban use has increased and all land cover has become largely urbanized, as well as water lands with the rise and development of deep wells. The need to preserve these lands from the physical development of the city in this direction is essential in order to develop the sustainable development of the city. There are many undeveloped lands in the old days due to the lack of water and the lack of facilities. The advancement of agriculture, turned these lands into agricultural lands. Today, landless areas are mostly on the suburbs or around the cities. This is mainly because of the farmers who leave their lands in a state of desert in hope of urban development to gain huge profits.This is the case where the city of Gonbad-e-Kavoos is not an exception to this rule. Parks and Gardens also have a rational increase in the city, therefore, in urban development projects, parks have been created but the size of the gardens is very low in the city of Gonbad-e-Kavoos. By predicting the changes in usages, it is concluded that the most changes will take place in urban usages and rain-fed and sterile lands with dramatic increase and decrease respectively.As the population of the city of Gonbad- e-Kavoosgrows, some steps should be taken to develop the spatial area of the city so as to prevent the destruction of fertile lands for the sake of human construction. Conclusion In this study, the effect of physical expansion of Gonbad-e-Kavoos city on agricultural lands is investigated. Findings indicate that during 45 years, around 1880 hectares of fertile farmlands surrounding the city are destroyed. The main reason behind this destruction is the horizontal expansion of the city. Hence, one of the fundamental bases of sustainable urban development is the increase of city density. It is concluded that horizontal expansion of the city is totally in contradiction to sustainable development and it leads to more instability of the city.
Ali Shojaeeian; Sadegh Mokhtari Chelche; Leila Keshtkar; Esmaeil Soleymani rad
Abstract
Nowadays, remote sensing data is able to provide the latest information for the study of land cover and land uses. These images are of high importancedue to the presentation of timely information, diversity of forms, being digital and the possibility of processing in the preparation of user maps.Determining ...
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Nowadays, remote sensing data is able to provide the latest information for the study of land cover and land uses. These images are of high importancedue to the presentation of timely information, diversity of forms, being digital and the possibility of processing in the preparation of user maps.Determining the land cover will be of great help to the area managers to make decisions. In this regard, the purpose of this researchis to compare the efficiency of parametric (least distant and box) and nonparametric (supporting vector machine) methods in land cover classification by using Landsat 8 satellite images in part of Dezful city. The nature of this research has been developmental-practical and its method has been descriptive-analytical. For this purpose, satellite data including Landsat 8 satellite images (13/8/2013) were prepared and analyzed using ENVI software. The efficiency of each classification method was investigated by calculating the two general accuracy and kappa coefficient. The results of the comparison of the methods used in the research showed that the SVM algorithm, especially the three linear, radial and polynomial kernels, had a better and more desirable accuracy than the parametric methods with 97.15%, 95.89% and 95.63% respectively. This study confirms the efficiency and more desirable capability of SVM algorithms in the classification of remote sensing images compared with parametric methods.
