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Effect of Urban Heat Islands on The Land Use Land Cover Changes Between 2015 and 2020 in Perth Metropolitan

Introduction to Remote Sensing

A remote sensing refers to the science of acquiring information about a particular area from a distance normally from an aircraft or a satellite. The sensors are mounted on the aircraft or satellite from where they detect how heat energy is reflected from the earth. This method of obtaining data was used to conduct a research on effects of urban heat islands on the land use, land cover changes between the year 2015 and 2020 in Perth Metropolitan.

An urban heat island refers to a human distributed urban/metropolitan area that is warmer than its surrounding rural areas (Estoque, 2017). This is majorly caused by human activities, land surfaces modification and waste heat which is generated when using energy as a secondary contributor. It is key to note that in such areas the temperature is usually high at night and low during the day, mostly witnessed during the summer and winter.

Urbanisation is generally seen to be a global phenomenon hence it is likely to continue for millions of decades to come in the developing countries. This has a series of effects on the quality of the environment which include t increase in temperature, quality in air and traffic congestion, this contributes to the climate change in a number of ways including GHG emissions which originates outside the boundaries of the city, energy consumption in the cities, direct emissions which leads to the greenhouse effect and all this changes the earth’s atmosphere and the general surface Albedo. The changes in the chemistry of the earth also has led to a number of changes in the natural soils and ground covers hence has reduced filtration and the absorption functions of the earth in the cities. This has in turn has led to the restriction in the water availability, changed the natural cooling process and also destroyed the vegetation cover. The changes in the urban centres has led to the region becoming warmer than the surrounding regions hence has led to the formulation of an island of higher temperatures.

The urban heat island has a number of effects on the environment which include: increase in the length of growing seasons which therein leads to a decrease in the occurrence of weak tornadoes, increase in the production of pollutants such as the ozone layer which leads to the decrease in the quality of air, a decrease in the quality of water which is caused by the flow of warm water into the surrounding streams which has a great impact on the water as it places great amounts of stress on the ecosystems and lastly it leads to a decrease in the monthly rainfall in the affected Metropolitan area.

Aims and Objectives of Remote Sensing

The aim of this particular research was to assess the nature of growth of urban centres using the remote sensors and the technological land maps of the Metropolitan this research was aimed at analysing the urban heat intensities in different categories and use them in accessing their potential variability of heating hence acquire indications of the policy of urban development in terms of sustainability levels, determine the areas in metropolitan which were most likely to be affected by healthy threats caused by the urban heat, select a research area in the Metropolitan based on socio economic and demographic factors for example income levels, average size of families, socio economic characteristics of a population and then use this type of research in compilation of effective methods of curbing the heat related effects, identify the most beneficial interventions of the Metropolitan area, to coin the risks of the urban heat on the populations and lastly to find out the positive contributions of energy conservations and thermal concepts.

Methods of Acquiring Data and The Workflow

Study Area

The Metropolitan refers to a region which consists of a densely populated urban core with a low populated neighbourhood which shares infrastructure, housing and industries. This area can also include towns and cities which contains rural areas that are economically tied to the urban centre or the urban core. In some cases though few the Metropolitan areas may have a number of centres which are closely of equal value as the Metropolitan itself and they can be able to build by themselves similar attractions as the Metropolitan and gain equal prominence to the urban area. This concept of metropolis was introduced in the year 2006 by Germany professors and since its adoption there has been little or no changes to the concepts in which it was generated with. Usually the Metropolitan has a number of municipalities which have their own jurisdictions and are economic, social and political regions.

Even though remote sensing (ulaby, 2015) is an expensive option, it was the most effective method when efficiency and labour are taken into consideration, it is considered to be cost effective as compared to the other elementary techniques in use. The two methods of remote sensing which are active remote sensing and passive remote sensing. Active remote sensing is the method when signals are emitted by an aircraft or a satellite on space or on air and the reflection of the signals detected by a sensor, it works by emitting energy which is used to scan objects while the sensor detects and measures the reflected radiation which is scattered from the targets (Nikolakopoulos, 2015). The most commonly used active remote sensor is the RADAR (Sinha, 2015) in which it measures the time of delay between the moment of emission and the moment of return of the emissions which is thereby measured by establishing the direction, speed and location of the object on which then emissions hit. While passive remote sensing is the method whereby the remote sensors uses the reflection of the sunlight to detect the sensors, a good example of a passive sensor is the infrared, radiometers, film photography and charge-coupled devices. It is key to note that the remote sensors was used with the maps of the Metropolitan which helped to point out the landscape and acted as a guide in giving the distance between places, mountains, rivers and the whole vegetational cover of the Metropolitan.

The remote sensing has a number of advantages and disadvantages too. The advantages include it allows easy collection of data in a span of resolutions, it is capable of repeating coverage of dynamic themes such as water which are helpful in collection of data, it can easily process and analyse data faster by using a computer, it reduces work done on the field as the data collected is analysed in the laboratory, it can cover large areas this allows diverse regional surveys on a variety of themes and lastly it is relatively cheap when one is constructing a base map. The disadvantages include: when analysing data over small areas remote sensing is fairly an expensive method of data collection, it is an expensive method when one is analysing repeated photographs and lastly remote sensing systems such as radar emit very powerful radiations which affects the phenomenon in question.

The remote sensing has several characteristics (Liu) which help in data collection and they include view whereby the remote sensors can be able to view the surface of the earth at several angles which can reveal different information this helped provide a collection of images of the Metropolitan from a number of angles hence provided a large number of helpful data, the time of capture which is used in the tracking of spatial changes which helps provide useful information hence its essential to note the time of capture of the images as different times provide different information which changes according to the time, the type of radiation which is sensed and can either be radar, infrared or visible light, multiscale, high-dimensional, dynamic-state, non-linear and multi-source. The remote sensors differ in terms of their solution depending on the type of investigation to be carried out hence most of them differ in terms of resolutions, spectrum, revisit cycle, and the modes of imaging.

The most common type of remote sensor used in monitoring land surfaces is the Landsat TM and ETM+. At 30-m resolution the two types of remote sensors can be able to capture signals of vegetation and land covers while at 60-m they can be able to capture the resolution of surface temperature (Rawat, 2015). At 36 spectral bands the remote sensors can be able to detect the dynamics of land covers including the thermal conditions of between 250-1000-m spatial resolutions over large surface areas. In conducting this study in Metropolitan the outcome was integrated into three different types of data bases. The three types of data bases are situ data measurements, census data and lastly the remote sensing data.

The process included retrieving the temperature of the land surface which was meant due to the urbanisation factor, direct detection of ground data which was done starting from the meteorological station and lastly there was the registration of correct spectral values which included calculating the fraction of green vegetation and the temp of land surface but this process excluded MODIS data products as the data provided from the MODIS had already been provided by the provider of data. The census data was formulated mainly to include the built up area, the gross domestic product (GDP) and the population and was used in the analysation of the urbanisation rate and the economic levels. The meteorological data measurements which were averaged daily for a period of one year were recorded using the in situ measurement formula which made it easier for the researchers to easily identify the annual trends.

Findings of Remote Sensing

The results from the research included the following: The first was an indication of a change in land cover from the urban centres to the forest was due to the great daytime and night time temperature. The land cover images which were divided into six cover types which were low reflectance, forest, water, bare earth, high reflection and the grassland reflected the influences of the surface thermal properties which were unique values and were attributed to the Landsat (30x30 meter squared).The second finding was an increase in percentage of the grassland, urban albedo, increased forest percentage and the bare earth which was associated with the lowering of the LST and this was an indication of higher temperatures during daytime in that particular span of years( 2015-2020). In the year 2016, the amount of heat was naturally warmer than 2019 however, it was noted that an average I n the land cover indicated a high inter- annual variation.

The third finding was an increase in the difference of the daytime SUHII (Surface urban heat island intensity) across the Metropolitan while during the night the SUHII difference was high in the outer sides of the urban pixels which was highly associated with the change in the land cover. This differences were identified by taking into consideration the per pixel methodology and used it to identify the change in SUHII between the year 2015 and 2020. The SUHII for the given span of years was computed and measured with both the high and the low land covers while considering the annual differences of the average forests. The fourth finding showed that the low urban albedo between the years produced the highest levels of temperature in the night across all the four seasons which include winter, summer, autumn and spring. This conclusion was made by comparing the amount of land cover from the year 2015-2019 in both the night time LST and the day time LST and of the investigated land covers the urban albedo forests and the bare earth grassland forests (Zhou, 2018) replicated during the night time, the low urban albedo to the forest consistently across the years produced the highest temperature of 0.88 degrees Celsius annually hence it being the highest.

The fifth finding was the distribution of the SUHII at night positively correlated with the difference in the amounts of albedo and the amounts of the light during the night between the rural sides of Metropolitan and the urban areas of the metropolitan while the day time distribution of SUHII correlated negatively across all the cities which had a difference in the amounts of vegetation cover and also this factor included the amounts if activities between the rural areas of the Metropolitan and the urban areas. Lastly the research found out that the areas in the Metropolitan which were covered with urban vegetation had a number of benefits which included a reduced amount of urban heat, improved human health and the general well-being of the surrounding population, improved bio diversity and lastly there was quality in the surrounding air and low amounts of wastes which meant that the surrounding streams had clean waters.

Conclusion on Remote Sensing

From the above discussion its key to note that there is no possibility of controlling and planning urbanisation. Urbanisation in turn leads to a number of effects which can include increase in the temperature of the surfaces of the areas with a high range of ecological value hence this leads to a negative effect on the natural resources. From observing the temperature of the surfaces of Metropolitan between the years 2015-2020 it indicates that in areas where there are high rates of business levels which includes towns and places of trading(markets) there is an indication of high rates of temperatures. It is also key to note that low vegetation cover and high rates of density are located in this particular areas. The albedo maps also show that the mostly congested areas contain moderate albedos and this areas are mostly the urban centres. The lowly populated areas which are mostly the rural areas are cool and covered with green vegetation which Implies that this places are not affected by the urban heats this is mostly due to the concentration in water bodies as well as low amounts of impact which are caused by urban developments. The results also show that high temperatures of the city and urban development without taking into consideration their effect on the UHI leads to a number of negative effects on the qualities of life of the urban population hence in order to curb this effects their needs to be a developed and working strategy of management which aims at protecting the natural vegetation and natural resources

References for Remote Sensing

Estoque, R. C. (2017). Monitoring surface urban heat island formation in a tropical mountain city using Landsat data. journal of photogrammetry and remote sensing, 18-29.

Liu, P. (n.d.). A survey of remote-sensing biga data. frontiers in environmental science, 45.

Nikolakopoulos, K. G. (2015). Active landslide monitoring using remote sensing data,GPS measurements and cameras on board. in earth resources and environmental remote sensing.

Rawat, J. S. (2015). Monitoring land use/ cover change using remote sensing and gis techniques. The egyptian journal of remote sensing and space science, 77-84.

Sinha, S. J. (2015). a review of radar remote sensing for biomass estimation. international journal of environmental science and technology, 1779-1792.

ulaby, F. &. (2015). radar and radiometric remote sensing.

Zhou, D. B. (2018). Remote sensing of the urban heat island effect in a highly populated area . 415-429.

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