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Change detection, Land cover, Urban expansion Urban growth driven by uncontrolled expansion is one of the greatest problems that reduces the fertile lands in Karbala Governorate, Iraq. This phenomenon is the cause for variety of urban environmental problems such as an increase in local temperature, cost of land, and loss of agricultural produce. Mu...
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Context
Pattern-based spatial analysis provides methods to describe and quantitatively compare spatial patterns for categorical raster datasets. It allows for spatial search, change detection, and clustering of areas with similar patterns.
Objectives
We developed an R package motif as a set of open-source tools for pattern-based spatial analysis....
Citations
... [5] Remote sensing change detection techniques were used to detect the land-use change, they find that there is a significant landuse change has happened, and agricultural land increased by 13.78% due to an increase in population with a high interest in croplands [6]. Noor H. Hamed and others also use remote sensing and multiple images in different periods, a series of image processing steps made to achieve the objective of the study by calculating land cover changes for Karbala City in the period from 1992 to 2013 [7]. Madugundu, R and others studied the investigation of land use land cover in the Drab region -Saudi Arabia in the period from 1980 to 2010 using remote sensing techniques and Landsat images, they approved high land-use changes occurred in the AOI in this period, that may be because of agriculture development from 1980 to 2000 and the urban expansion between 2000 and 2010 [8]. ...
The expansions of cities and continuous urbanization have prepared comprehensive urban plans necessary. The important thing about these plans is to determine their success, efficiency, and feasibility. The expansion of the city comes because of the population increase or investment. When the expansion of cities precedes the updating of its master plans and the development of alternative plans to accommodate these expansions, it is normal that finds irregularities in use and differences between the master plan and real land use. Therefore, the main purpose of this paper is to examine the extent of illegal changes in the current situation in comparison with master plans. Also, the efficiency of artificial neural network models is evaluated to predict illegal land-use changes. The old master plan (1990-2010) and the new one (2010-2030) was used with two high-resolution satellite images dated 2010 and 2018. To determine changes between the status quo and the uses defined in the master plan, the required information tables were completed by field visit with questioner made for Al-hay City. Neural network models were used to evaluate the survey, data was divided into two parts training and testing then a neural network model was performed on them after testing the results using the neural network model, the results present that the accuracy of about 85% for the old master plan and pass 91% for the updated master plan. The largest percentage of differences between the real use and master plan for the year 2010 was in (Religious use, Parking, Gas stations, then government use, green areas, educational use, and residential), but note that the largest percentage of differences between the real use and master plan for the year 2018 were in (Religious use, Athletic use, Green areas, then commercial and governmental uses).
... Bands 4 and 5 were utilized to calculate the NDVI in this investigation, whereas band 10 was employed to determine brightness temperature. Table 1 contains the metadata of the satellite pictures that were utilized in the method [4]. ...
In this research, it has been calculate the LST of Bahr Al-Najaf for the interval 2013-2020 Utilizing OLS image, so, It will get the minimum and maximum LST was in 2014.
... There are many ways of geometric correction that can be classified regarding to the type of processing or data sources. Image to image geometric correction was applied by returning the low resolution image (as source) to the high resolution image which assumed as the base (target) [9] ...
... From 1976 to 1996 vegetation areas expand to more than 160 % and while sand dunes reduced to about 12%, which mean there is a planned treatment at that time, but vegetation returned back to about the same area in 2021 also sand dunes areas expanded from 438 Km² in 1996 to about 990 Km² in 2014 then to more than 1300 Km² in 2021. Figures (7) and (8) All results and discussion can be illustrated carefully by figure (9) which explain the comparison for all items in the four stations of the study in single integrated chart. ...
Abstract. In this study Remote Sensing techniques have been used to investigate soil
degradation in Iraq (alluvial plain) for the period (1976 - 2020) by using different many source
of data such as satellite images (Landsat 1-5 MSS C1 Level, Landsat 4-5 TM C1 Level-1,
Landsat 7, Landsat 8, and sentinel 2) and use more than one software like (ENVI 5.3, ERDAS
Imagine 2015, Arc GIS 10.7, and Blender). This study focusing on determine the main degraded
areas in Iraq, (alluvial plain) chosen because of spread sand dunes. To make the study soberer,
ground trothing achieved to verify the real status of the area and collect the data by field visit.
Bands G, B, R, and IR from LANDSAT-3 in 1976, 1996 and 2014, the same bands used from
Sentinel-2 dated 2021. Unsupervised classification made for images of 1976 and 1996 then
supervised classification did for images in 2014 and 2021. The classification was carried out
using ERDAS Imagine V.2015 software and areas of the main land uses in the study area were
calculated. The results indicate that there is a big problem in the base year 1976, this problem
almost disappeared in the second station of work 1996, but it returned back after that through the
results for the years 2014 and 2021.
... Spatial analysis is an important tool for support decision making process [5,6,7]. Regarding the suitability analysis for finding suitable locations for establishing a sports city, many studies have been conducted, in this part we will describe the relevant studies. ...
A fuzzy logic algorithm and spatial analysis methods are presented to propose suitable locations for a sports city in Iraq. GIS overlay analysis has been applied based on the fuzzy logic algorithm and data input extracted from the spatial analysis process. The proposed methodology has combined an intelligence multi-criteria analysis and GIS modelling to support the process of decision making. In recent times, many cities have clustered new sports infrastructures in concentrated areas to create a sports city. Al Hillah City as one of the biggest cities in the center of Iraq, because of many components' countryside relocation and natural expansion of population, and other has been distinguished; extreme population expansion and lastly evolution in need of planning in some inner-city areas and places. Consequently, designated areas in terms of premier spatial allocation and appropriate location for users of general services; sports services that are rapid, on time, and at ease access to them are essential that are not considered. A small-scale recognition has spent on critical aspects of sports utilization for land measure and appropriately locating. This issue has been minimized the premier performance of these spaces and creates problems for the city and its citizens. The premier performance of these spaces has been minimized because of the above-mentioned issue, which creates difficulties for the city and its residents. This research conducted based on the integration between Fuzzy logic algorithm and GIS techniques, spatial analysis tools in ArcGIS software were utilized to implement this method. The results showed that the most suitable areas include three areas that are located on the northwest and the south of the study area. On the other hand, the largest area located on the northwest location respect to Al-Hillah city, the center of Babylon Province, which is considered the proposed area to construct sports city. This study will be useful for decision-makers and stockholders by reducing cost, time, and efforts through decreasing field works.
... There are many ways of geometric correction that can be classified regarding to the type of processing or data sources. Image to image geometric correction was applied by returning the low resolution image (as source) to the high resolution image which assumed as the base (target) [9] ...
... From 1976 to 1996 vegetation areas expand to more than 160 % and while sand dunes reduced to about 12%, which mean there is a planned treatment at that time, but vegetation returned back to about the same area in 2021 also sand dunes areas expanded from 438 Km² in 1996 to about 990 Km² in 2014 then to more than 1300 Km² in 2021. Figures (7) and (8) All results and discussion can be illustrated carefully by figure (9) which explain the comparison for all items in the four stations of the study in single integrated chart. ...
In this study Remote Sensing techniques have been used to investigate soil degradation in Iraq (alluvial plain) for the period (1976 - 2020) by using different many source of data such as satellite images (Landsat 1-5 MSS C1 Level, Landsat 4-5 TM C1 Level-1, Landsat 7, Landsat 8, and sentinel 2) and use more than one software like (ENVI 5.3, ERDAS Imagine 2015, Arc GIS 10.7, and Blender). This study focusing on determine the main degraded areas in Iraq, (alluvial plain) chosen because of spread sand dunes. To make the study soberer, ground trothing achieved to verify the real status of the area and collect the data by field visit. Bands G, B, R, and IR from LANDSAT-3 in 1976, 1996 and 2014, the same bands used from Sentinel-2 dated 2021. Unsupervised classification made for images of 1976 and 1996 then supervised classification did for images in 2014 and 2021. The classification was carried out using ERDAS Imagine V.2015 software and areas of the main land uses in the study area were calculated. The results indicate that there is a big problem in the base year 1976, this problem almost disappeared in the second station of work 1996, but it returned back after that through the results for the years 2014 and 2021.
... Satellite images such as Landsat images have significant abilities in the monitoring of UHI impacts on dense urban areas (Yusuf 2014;Tan 2013 ;Hamed 2020).Mono-Window method have provided simple and effective outputs that used for evaluating the interaction between land surface and earth's atmosphere temperature (Qin 2001).UHI also influences the welfare and health of human beings. the study conducted by Oke et, al 1982 indicated that the difference between urban and their surrounded rural areas in term of land surface temperature up to 15 ˚Climate changes and UHI are greatly linked in two aspects. ...
Recently, COVID-19 pandemic has swept the world left many victims as well as heavy casualties in the global economic system. As a result, governments have applied some necessary actions such as curfew and restricted mobility between cities, in order to control the spread of COVID-19 pandemic. However, these actions can decrease the traffic congestions within megacities leading to cleaner air and lower temperature. On the other hand, these actions have negative impacts on tourism in congested cities like Karbala and Najaf.Nowadays, urban climatic phenomena within holy cities have attracted researchers. The aim of this study is the evaluation of Urban Climate in term of temperature before and during COVID-19 pandemic period by using Landsat images and GIS techniques. Final findings showed a difference between Land surface temperature before and during COVID-19, which reached about 9 C° within built-up areas and bare lands. While this difference showed a relatively slight decrease within vegetated areas and waterbodies reached about 2 C°. This indicated that built-up areas and bare lands have been mainly affected by governmental restrictions during COVID-19 compared to other areas. Our analysis indicated that the temperature of the surface in urban areas has decreased during COVID-19 compared to the period before COVID-19. The proposed method can pave the way for planners and decision-makers to evaluate other holy cities in terms of the environment and recent disasters like the COVID-19 pandemic.
The growth of cities around the world creates difficulties for governments due to the strain it puts on resources and the negative impact on the environment and living conditions for residents. The Kirkuk Governorate has experienced significant urban growth in recent years, causing various environmental, economic, and social issues. the study aims to monitor the growth of Kirkuk Governorate from 1990-2020 using multi-spectral Landsat images to better understand urban development. Landsat-5 TM for 1990, Landsat-7 ETM+ for 2000, Landsat-5 TM for 2010, and Landsat-8 OLI for 2020 were used for this study. The Supervised Maximum Likelihood algorithm was utilized to categorize images into urban and non-urban areas, with accuracy rates ranging from 91.25% to 96.66% between 1990 and 2020. Post-classification change detection analysis was also conducted to observe changes in urban growth, revealing that the studied city expanded from 46.96 km2 to 193.25 km2 over 30 years. Over the past thirty years, the urban area of Kirkuk Governorate has increased while the non-urban area has decreased. This is due to factors such as population growth, political changes, and economic development. This study provides valuable information about this urban growth and can be used as a foundation for future studies on the region's socioeconomic and environmental changes.
In this study, the land surface temperature (LST) of the western region of Najaf was calculated over the period 2016-2020 using the operational L Imagery OLI pictures, hence the lowest and highest LST values 45°Cwere obtained in 2016. Introduction Local and global surface energy and water balances are influenced by land surface temperature (LST). LST may be retrieved from space-based thermal infrared (TIR) data using a number of different methods that have been established. The LST retrieval is still difficult because of the ill-posed issue. LST retrieval techniques based on satellite TIR data are reviewed [1].We were able to develop a model that would automatically repeat the technique using OLS pictures 2016 and the Model Maker, making it simple to create a tool for pixel computations. Obtaining LST is a time-consuming and error-prone process in the absence of the tool. It is possible to use this tool with a variety of programmers that can do pixel calculations on a picture. When it comes to LANDSAT 8, an LST retrieval method has already been developed, but an easier-to-use tool is needed. A similar examination was conducted with LANDSAT 8 data, although LANDSAT 8 data was not. For LST, the fourth (red wavelength/micrometers, 0.64-0.67),
