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.
Reza Sarli; Gholamreza Roshan; Stefan Grab
Abstract
Extended Abstract Introduction change monitoring is generally used to evaluate natural processes such as the long-term effects of climate change, which is affected by the interaction of the climatic system’s constructive components such as the biosphere, lithosphere, or factors that control the ...
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Extended Abstract Introduction change monitoring is generally used to evaluate natural processes such as the long-term effects of climate change, which is affected by the interaction of the climatic system’s constructive components such as the biosphere, lithosphere, or factors that control the climate changes outside the climatic system, over a long period of time, as well as the short-term processes that include vegetation sequence and geomorphological processes. Change monitoring is also used to evaluate the effects derived from human activities such as deforestation, agriculture and urban development. Remote sensing is a very useful technology, which can be used to obtain information layers from the soil and vegetation. Materials and Methods Land Cover Product was used to process the MODIS1 Satellite data which is one of the most frequently used products designed relating to MODIS Satellite, and is used annually. This Sensor with 250-500 meter and also 1-kilometer spatial resolution has 36 spectral bands in the range of visible, reflectional infrared and thermal infrared wavelengths, which can well be used for various applications of the surface, the Earth surface, atmosphere and the oceans. MOD12Q1, which is one of the MODIS products, was used to investigate and analyze the profile of the vegetation changes in Mazandaran province using the NDVI and EVI indicators from 2005 to 2017. The related images have been prepared annually with 500-meter resolution and sine coordinate system in the form of a combination of Terra and Aqua data. Given the standards provided by NASA, the changes were investigated using the “decision tree” classification method, and the map for the prediction of its changes was calculated using the Markov Chain Model. The ArcGis software was then used to analyze these changes in order to determine which use of land with what percentage of changes has been allocated to which area. Results and Discussion In 2005, land-uses associated with dense vegetation dominated an area of 398.77 m2. These land-uses include wasteland, dense vegetation and scattered vegetation. The estimation of the changes occurring in the aforementioned land-uses showed that the maximum changes relating to the low density vegetation with an average of 55.62% are in the northwestern and the eastern parts, and the minimum changes relating to the in dense vegetation with an average of 77.21% are in the central parts of the region, respectively. Furthermore, the observations of the images of the year 2005 show that the use of dense vegetation which has turned into low density vegetation in the image of the year 2017, has had the minimum changes. Finally, considering the prediction of the observed changes, it can be concluded that these changes were more related to the altitude range of 1400 m to 2260 m with the slope coefficients of 15% to 99%. The prediction carried out using the Markov Chain also suggests that the low-density land cover, which was over 864/80 km2 in 2017, will turn into barren lands in proportion to the changes occurringin 2022. Conclusion A major part of the vegetation changes in the area is due tothelack of job opportunities, extra labor attraction and the economic poverty of the inhabitants.In addition,the pressure on the meadow fields hasreached its highest limit by ranchers,which has resulted inthe reduction of grasslands. Eventually, it could be stated that the evaluationmethods and modelsof the vegetation changes have their own featuresand no method on its own is usable andappropriate for all cases, hence,the identification of an appropriate method for evaluating thevegetation changesneeds to be examined quantitatively and qualitativelyin order to provide the best result.
Reza Lahmian
Abstract
Extended Abstract
Introduction
Statistics show that more than half of the world's population (54% in 2014) live in urban areas, although there are many differences between countries in terms of urbanization levels. For the first time in history, the urban population exceeded the rural population of ...
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Extended Abstract
Introduction
Statistics show that more than half of the world's population (54% in 2014) live in urban areas, although there are many differences between countries in terms of urbanization levels. For the first time in history, the urban population exceeded the rural population of the world in 2007. One of the most important problems of urban and environmental development is the shortage or lack of natural-regional parks in the center of the cities and in suburbs. Natural and regional parks have social, economic and ecological impacts in terms of the coherent structure which, is considered as a significant criterion for the betterment of the quality of living space and development of the community, with lots of benefits such as obtaining a suitable environment to develop the social coherence, maintain comfort and treat psychological and mental illnesses.Identifying the suitable locations for the natural-regional parks is one of the cases that should be taken into consideration regarding any type of development, including comprehensive plans, civil plans or regional plans. The purpose of this paper is to achieve the spatial organization of Mazandaran province in order to construct and allocate natural and regional parks in the regions of this province using the new scientific methods of spatial analysis in the GIS environment and applying multi-criteria decision-making techniques.
Research Method
The process of this study is descriptive and analytical. Accordingly, the necessary data and criteria, including maps and information layers and satellite imagery were analyzed using ARC GIS 10 and ENVI 5.1 software. In order to weigh,in addition to taking the experts point to the criteria into account, the Marinoni extension in Arc GIS software was used with regard to the hierarchical decision-making process. The main criteria used in this study are natural vegetation, transportation network, welfare and service centers, cultural-educational centers, commercial-residential areas, population centers, industrial areas. As it was mentioned, the information layers were provided for each of the influential factors, and a weight was assigned to each of the layers, and then, appropriate weights were assigned to each of the information layers based on their significance using hierarchical analyzing model to provide the spatial modeling, and the information layers were integrated, and the optimal regions were identified using the provided model.
Results and Discussion
Identifying and selecting the factors influencing the location, are among the significant stages of the study. The more compatible are the identified factors with the land reality, the more satisfactory will be the outcomes of the location. Accordingly, in this study, weights have been assigned to each one of the weights based on the opinions of the experts, using the hierarchical model, and the criterion of the transportation network with relative normalized weight (0.311) has had the most importance among the main criteria.Natural vegetation (with a normalized score of 0.277), population centers (with a normalized score of 0.271), and travelling facilities and services (with a normalized score of 0.120) have been placed in the subsequent ranks, respectively. Accordingly, in this research, with regard to the opinions of the experts, four main criteria of industrial, population centers, commercial-residential, cultural-educational, welfare and services, transportation network and natural vegetation, each one of which includes sub-criteria as well,were taken into consideration .A combination of the AHP process and Fuzzy set was used for analyzing the spatial data, in order to evaluate the selected factors and the Geographic Information System (GIS) as well. As it is seen, areas with a very good desirability in Kalastan have accounted for 6.6%, and areas with the lowest potential for the construction of natural-regional parks in Kalastan constitute 5.5%. Similarly, areas with medium potential and regions with relatively appropriate potential in Kalastan of Mazandaran show an average of 12.4% and 10.1%, respectively. Estimates show that about 129817 hectares of the area of the province are susceptible to creating regional parks, i.e. the area No. 1, which will be a significant amount for the decision-makers and planners in the urban and regional areas in pursuit of achieving sustainable development and protecting the natural environment of this province. In the next regions, the priority of the selection will be with the experts and decision-makers of this field.
Conclusion
The purpose of this research was to identify the areas susceptible to the creation of regional parks in the province of Mazandaran, in order to provide the sustainable financial resources for the management of the province while, protecting the natural resources of the province.
