Remote Sensing (RS)
Kolsoom Shokrilahizadeh; Hamed Naghavi; Morteza Ghobadi; Rahim Maleknia
Abstract
Extended Abstract
Introduction:
Urban green spaces constitute a pivotal component of urban ecosystems, offering a plethora of ecological benefits and services to cities. Augmenting these green patches within urban landscapes and establishing interconnected ecological networks therein represent viable ...
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Extended Abstract
Introduction:
Urban green spaces constitute a pivotal component of urban ecosystems, offering a plethora of ecological benefits and services to cities. Augmenting these green patches within urban landscapes and establishing interconnected ecological networks therein represent viable strategies to mitigate the adverse repercussions of inadequate urban development while bolstering urban environment resilience. In the past few decades, the landscape ecology paradigm has introduced innovative methodologies aimed at comprehending the intricacies of urban green space dynamics and how landscape configurations wield influence over the environmental processes within cities. This research, consequently, sets out with the intention of quantitatively assessing and dissecting the transformations transpiring within Khorramabad's urban green spaces. It does so by harnessing remote sensing data and leveraging landscape metrics to gain deeper insights into the urban landscape's evolution.
Materials & Methods:
The focus of this research centers on Khorramabad city, which serves as the capital of Lorestan province and holds the distinction of being the province's largest city in terms of both population and geographical expanse. Municipally zoned into three distinct regions, the study unfolds across two main phases. Initially, the endeavor involved the creation of comprehensive synoptic maps capturing Khorramabad city's green spaces. This process relied on satellite imagery, followed by a subsequent phase of scrutinizing these maps through the application of landscape metrics.
To execute this, satellite images from various sensors—namely TM, ETM+, and OLI on Landsat 5, 7, and 8 satellites—were harnessed for the years 1987, 2003, and 2019, respectively. These images underwent meticulous preprocessing, culminating in their classification using the maximum likelihood method within the ENVI software environment. To validate the accuracy of the resultant maps, an error matrix was employed. In order to model the quantitative alterations and patterns within Khorramabad's urban green spaces, landscape metrics were harnessed. Notably, the Fragstat software facilitated the analysis of selected landscape metrics, which encompassed four key measures: class area (CA), number of patches (NP), percent of landscape (PLAND), and mean Euclidean nearest neighbor distance (ENN-MN).
Results:
The analysis of spatial-temporal changes in Khorramabad city's green spaces reveals an evident declining trend in their overall pattern. The outcomes underscore a substantial reduction both in the quantity of green patches and the area they encompass, dwindling from 703.8 hectares in 1987 to 629.88 hectares in 2019. Additionally, the investigation into landscape metrics' composition and distribution underscores an absence of cohesive dispersion on the city-wide scale. Within Khorramabad city, regions 1 and 3 exhibit inadequate green space composition and distribution. The computed metric for Class Area (CA) reflects a decrease from 195.66 hectares in 1987 to 191.63 hectares in 2003, further diminishing to 170.145 hectares by 2019. Correspondingly, the metric for Number of Patches (NP) indicates the lowest count of patches (33) in 1987, which escalated to 122 patches in 2003, and ultimately reaching 183 patches by 2019. Moreover, Proportion of Landscape (PLAND) data highlights that regions 3 and 2 demonstrate the highest (19.45%) and lowest (7.18%) green area proportions, respectively. Notably, the PLAND metric underwent modification from 229.81 meters in 1987 to 88.47 meters in 2003, further diminishing to 78.65 meters in 2019. The findings underscore deficiencies in Khorramabad city's urban green spaces, indicating a lack of favorable conditions for their development.
Conclusion:
The research conducted an assessment of urban green spaces within the urban areas of Khorramabad, utilizing remote sensing data and landscape metrics. The findings indicated a consistent downward trend in the overall extent of green spaces in Khorramabad city over various years. The distribution of green patches within the city was deemed relatively inappropriate, lacking an optimal arrangement. To enhance the status of green spaces, there is a need to establish continuity between discrete green patches and smaller green areas. This study underscores the significance of prioritizing sustainable management for Khorramabad's urban green space, aiming to prevent its degradation. The study's limitation lies in its reliance on medium-resolution Landsat image data. Overcoming this constraint through the incorporation of high-resolution data holds promise, particularly for fragmented green spaces in urban areas.
Geographic Data
Majid Goodarzi; Farkhondeh Hashemi Ghandali
Abstract
Extended AbstractIntroductionUrbanization is a developing phenomenon, and the analysis of the appropriate location and the geographical distribution of urban green space plays a significant role in the development and future of the city. Although in the past, green spaces were primarily manifested in ...
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Extended AbstractIntroductionUrbanization is a developing phenomenon, and the analysis of the appropriate location and the geographical distribution of urban green space plays a significant role in the development and future of the city. Although in the past, green spaces were primarily manifested in the beautification and appearance of urban areas, nowadays, for several reasons, it is considered as a breathing space of the cities. The growth of industry and the increase in population in cities have led to speculative constructions that do not pay enough attention to health issues, provision of sufficient light and healthy air, and leisure spaces in buildings. Moreover, the necessity of creating new urban land use to meet the ever-increasing needs of urban dwellers has gradually reduced the share of urban green space, which is the consequence of limiting the access of urban dwellers to nature. But for some reason, at the beginning of the 20th century, the urban man showed a renewed attention to nature and green spaces, which manifests itself in creating functional gardens instead of recreational gardens that respond to the new needs of citizens. The present study aims to Rank the influencing factors to locate urban green spaces in Masjed Soleyman city. Materials & Methods The present applied study employed an analytical-descriptive method. Reliable internal and external sources related to the subject were reviewed, and in some cases, field studies and referrals to related organizations were conducted for data collection. In this research, the DEMATEL-ANP-integrated approach was employed, and the criteria weights were calculated. Then, the layer of each weight was entered into the Arc GIS software.Results & DiscussionAs the research findings show, 14 criteria are involved in the optimal location of urban green spaces in Masjid Suleiman, distance to commercial centers, distance to waste and empty lands, distance to administrative centers, distance to medical centers, distance to educational centers, distance to existing green spaces, distance to industrial centers, distance to urban facilities and equipment, distance to military centers, distance to religious centers, distance to communication paths, and density.ConclusionThe results of this study showed the priority of the mentioned 14 indicators in order from low to high: proximity to residential centers (0.09263, rank 1), proximity to educational centers (0.07428, rank 2), proximity to cultural centers (0.07268, rank 3), population density (0.07154 and rank 4), proximity to communication ways (0.07092, rank 5), proximity to religious centers (0.06979, rank 6), proximity to existing green spaces (0.06967, rank 7), proximity to medical centers (0.06934, rank 8), proximity to commercial centers (0.06923, rank 9), proximity to urban facilities and equipment (0.06902, rank 10), proximity to military centers (0.06874, rank 11), proximity to administrative centers (0.06761, rank 12), proximity to industrial centers (0.06729, rank 13) and proximity to empty and barren land (0.06726, rank 14).
Spatial planning with regard to military defense
Mahshad Bagheri; Amir Ansari; Azadeh Kazemi; Mahmoud Bayat; Sahar Heidari Masteali
Abstract
Extended Abstract
Introduction
Proper distribution of urban green space is one of the most important issues in urban planning and especially in management of urban green space. In other words, the physical expansion of cities destroys surrounding natural environments and arable lands. It also results ...
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Extended Abstract
Introduction
Proper distribution of urban green space is one of the most important issues in urban planning and especially in management of urban green space. In other words, the physical expansion of cities destroys surrounding natural environments and arable lands. It also results in fundamental changes in ecological structure and functionof urban landscape, along with gradual changesin spatial structure and patterns of this landscape (Wang et al., 2008). Since ecosystem processes depends on its structure, landscape metrics have been accepted as a very useful tool for expressing the structure of urban green space and its human-causedchanges (Hessburg et al., 2013).There has always been discussion onacceptable per capita green space or changes in green space over time and place. Iranian cities are no exception in this regard, thougheven a city enjoying a high ratio of green space per capita may still lack enough green space per capita in some districts. This suggests the necessity of investigating various measures and avoiding studies limited to per capita green space and urban forestry. (Botequilha and Ahren, 2002). If as an ecological structure,green space is proportional to populationcomposition and distribution, ecological performance and land use type of an urban area, it can have important ecological functions. Since most studies on urban green space have primarily focused onfinding a proper location, calculating appropriate per capita green space and introducing suitable species for green space, investigatingthe spatial distribution of urban green spaceseems to be of great importance. Therefore, the present study seeks to investigate the spatial pattern and distribution of public green space in Khomein using a landscape approach.
Materials and methods
Study area
The study area, Khomein, is bounded by agricultural lands and gardens in its northeast, west, and partly in its south. Only the main area of urban texture is located on barren lands (Abbasi et al., 1986). The study area includes four districts of Khomeinin which the pattern of green space distribution isinvestigated.
Methods
Sentinel-2 images were used in the present study. Satellite images were processed and then, their geographical effects were extracted inthe first step of classification. Different indices were defined for each patch of the image and using supervised method, images were classified into four classes of agricultural lands, barren lands, urban parks and residential areas in accordance with the training data. Visual method was used to improve classification results. In this method, classification results are matched with the imagesand possible errors are rectified. Google Earth was used to evaluate the accuracy of results obtained from classification of satellite images. In the next step,the base map of the present study was produced and then, the layer containing urban parkswas integrated with the layers prepared for four districts of Khomein. It should be noted that the present study focuses on urban parks prepared by the municipality for public use and does not include other urban green spaceareas such as the green belt or private gardens, etc.
To study the spatial distribution of green space, measures of land cover were calculated and analyzed in each of the four districts. Geographic Information System (GIS) and Landscape Measurement Analysis Program (FRAGSTATS) were among the tools used to calculate and measure landusein the present study. Landscape metrics used in the present study included:
Landscape Shape Index (LSI) which measures the area of the largest patch in a class divided by the total area of that landscape (multiplied by 100 to convert to percent)
Euclidean Nearest Neighbor distance (ENN) which is the average distance between patches in a class. Meter is used as the standard unit of measurement for this index.
Perimeter /Area Ratio (PARA) which is the ratio of the perimeter of the patch (m) to its area (m2). This measure lacks a specific unit and for PARA> 0 it is without a limit.
Number of Patches (NP) equals the number of patchesof the corresponding patch type (class).
Shape Index:sum of patches’ perimeter divided by the square root of the area of the patch (ha) for each class (class surface) or the entire patch (land surface). This index iscalculated for circle standard (polygon), or square standard (grid) and divided by the number of patches.
Largest Patch Index (LPI) which measures the area of the largest patch in a class divided by the total area of the landscape (multiplied by 100 to convert to percent)
Mean Patch Size (MPS) which measures the average size of a patchin the landscape.
Results and Discussion
District 3 ranked highest and district 1 ranked lowest in ENN indexindicating that urban green space patches in this district were closer together, while green space patches in the third district were limited and far apart from each other. Regarding LPI index, the second district ranked thehighest and the third district ranked the lowest indicating that the largest urban parks in this districtwere much smaller than other districts. Other district had a relatively acceptable statusin this respect. In MPS index, district 2 with 697 patches ranked highest and district 1 with 564 patches ranked lowest indicating that average green space patches in district 1 were smaller. This was also confirmed by maps prepared based on other metrics.Regarding the LSI index, district 1 ranked highest and district 2 ranked lowest, while districts 3 and 4 had a similar status in this measure. The first district had the highest number of patches (NP), while the third district had the lowest NP. The highestPARA ratio was observed in District 1, and the lowestin District 4, while districts 3 and 2 ranked near the middle. In Landscape shape index which increases with the heterogeneity of patches,district 1 (with 13.12) ranked highest and District 3(6.64) ranked lowestwhiledistricts 2 and 4 ranked near the middle.This indicates the heterogeneous shape of green space patches in district 1, while showing that patches of green space in district 3 are very simple and homogeneous.Finally it should be noted that calculating landscape metrics for the four districts ofKhomein indicated a very low per capita green space in this city and also absence of a proper and equitable spatial distribution.
Conclusions
Calculatinglandscape metrics in the four districts of Khomeinindicated thatcompared to other districts, district 1, located in the southern part of the city, has a more desirable status in indices such as PARA, LSI, NP, and ENN. At the same time, district 3, located in the southeastern part of the city, has the least appropriate status regarding these metrics indicating the necessity of a comprehensive analysis of green space areas in this district in near future. Urban managers and planners need to focus on this district and its green space, and if possible find appropriate sites for future green space areas in this district.Although the status of districts 2 and 4, located in the west and north of the cityrespectively, were not very desirable, theyranked higher than districts 3in NP, LPI, and MPS. Using GIS in combination with satellite imagery, and land use metrics provided an innovative way to study the gradual spatial changes in urban green space. Results of landscape metrics analysis indicated an unbalanced distribution of land use in the four urban districts in this study.
Alireza Ma'man push; Reza Tofangsaaz
Volume 20, Issue 79 , November 2011, , Pages 74-77
Abstract
The physical development of cities is a dynamic and continuous process that, if unplanned and rapid, will endanger urban systems. Undoubtedly, green space and urban environment are amongst the most important factors in the sustainability of natural and human life in modern urbanization. In addition to ...
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The physical development of cities is a dynamic and continuous process that, if unplanned and rapid, will endanger urban systems. Undoubtedly, green space and urban environment are amongst the most important factors in the sustainability of natural and human life in modern urbanization. In addition to the aesthetic role, the green space of the city will be of great help in moderating the air. Meanwhile, the issue of development combined with the need to expand the green space and its locating in the city is inevitable in the future of urban development. The city of Isfahan has been recognized as one of the most important and beautiful cities in Iran and a place to attract domestic and foreign tourists. One of the main reasons for this is the passage of Zayandeh Rood through the city, which has endowed the city with freshness and greenery. Regular urban greenery mapping, in addition to the huge cost involved, is also time consuming. Urban green space mapping by satellite imagery, being up-to-date and enjoying time series, is less costly and of higher speed, and can achieve the desired results by performing necessary processes on satellite images using related softwares. In this investigation, the city of Isfahan has been studied in terms of the urban area and the green space expansion, as well as the trend of population growth and per capita green space during the two years of 1923 and 2007 using existing maps and satellite imagery. Furthurmore, its adaptaion has been analyzed by the GIS analyst system, as well as the development of urban green space, the expansion of the city and its changes.
