Analysis of the Cooling Effect of Urban Green Spaces in Mitigating Micro-climate Change Using Geospatial Techniques in Adama City, Central Ethiopia

doi:10.21203/rs.3.rs-1095929/v1

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Analysis of the Cooling Effect of Urban Green Spaces in Mitigating Micro-climate Change Using Geospatial Techniques in Adama City, Central Ethiopia

https://doi.org/10.21203/rs.3.rs-1095929/v1

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Nowadays, addressing urban climate in urban planning through mapping has got world-wide attention. Greening urban environment is one of the best mechanisms to combat the effects of micro-climate change. Therefore, this study aims at analyzing the cooling effects of Urban Green Spaces (UGS) in mitigating micro-climate change in Adama City with special emphasis on land surface temperature variation with respective to vegetation cover for the last two decades i.e. from 2000 to 2020. Three different remotely sensed data of Landsat7 ETM+ (2000 and 2010) as well as Landsat8 OLI/TIRS (2020) were used in the study. The consistent land surface temperature data were retrieved from Landsat7 ETM+ and Landsat8 OLI/TIRS using mono window and split window algorithms, respectively. Regression and correlation analysis among Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) were also performed in Statistical Package for Social Science (SPSS V23). The study reveals that the proportion of Urban Green Spaces (UGS) to other land use/land cover particularly, dense vegetation cover were reduced from 29.3Km²(21.20%) in 2000 to 18.17Km² (13.15%) in 2020. The main land dynamic process, which could considerably contribute to the increase in Land Surface Temperature, was the rapid expansion of built-up areas in the study area. The model produced through multiple linear regression analysis clearly indicates that the two urban parameters (built up and green areas) contributed 75.2% of the Land Surface Temperature (LST) variations in Adama City. The cooling efficiency (CE) and the threshold value of efficiency (TVoE) of green space in Adama City were calculated as 5.5 ± 0.5 ha. This finding implies that when Adama City municipality implements urban planning, allocating a green space area of 5.5 ± 0.5 ha reduces surface temperature by about 2.85 ⁰C which is the most efficient to reduce heat effects. The study suggests that strengthening of plan execution capacity, public participation in urban planning and strengthening the development of urban green spaces as an important strategy to mitigate the effects of micro-climate change.

Biogeography

Cooling Efficiency

Land Surface Temperature

Micro-Climate

Normalized Difference Built-up Index

Normalized Difference Vegetation Index

Table 1: Remote sensing images

Image	Path	Raw	Pixel size	Observation date	Sources
Landsat ETM+ 2000	168	54	30*30	18, Jan, 2000	United State Geological Survey
Landsat ETM+ 2010	168	54	30*30	11, Feb, 2010	United State Geological Survey
Landsat OLI/TIRS 2020	168	54	30*30	05, Jan, 2020	United State Geological Survey

Table 2: Data types and sources

No.	Data category	Source	Purpose
1	Temperature data	National Meteorological Agency (NMA), Ethiopia	To validate the value of temperature retrieved from satellite image
2	Adama city shape file	Adama City Municipality	For preparation of result map

Table 3: Software Used for the Study

No	Software	Purpose
1	ArcGIS 10.3	Analyzing and visualization of Spatial data
2	ERDAS 2015	For Image classification and Accuracy Assessment
3	Arc SWAT	Extraction of drainage network
4	Google Earth Pro & GPS	For LULC accuracy assessment
5	SPSS V23	For regression and analysis

Table 4: Variations of LST Values from the year 2000 to 2020

2000			2020		Difference (%)
LST (⁰C)	Area (km²)	Area (%)	Area (Km²)	Area (%)	Difference ( km²)	2000 – 2020
< 22	24.57	17.78	36.72	26.57	12.15	+ 10.42
22 - 26	64.51	46.69	32.84	23.76	-31.67	- 22.93
26 - 30	29.33	21.22	14.04	10.16	-15.29	- 11.06
30 - 34	8.23	5.95	38.97	28.2	30.74	+ 20.62
> 34	11.54	8.35	15.63	11.31	4.09	+ 2.96

Source: Computed from data, (2020).

Table 5: Comparisons of the NDVI values in the year 2000 and 2020

NDVI Values	Landsat ETM+ (2000)	Landsat ETM+ (2010)	Landsat OLI (2020)
Min.	-0.31	-0.265	-0.128
Max.	0.62	0.516	0.456
Mean	0.35	0.28	0.124

Source: Computed from data, (2020)

Table 6: Estimated LST value of selected test Spot (Gooba Hiddii Kebele)

Increase of built-up area by	Estimated mean LST in (°C)	Increase green area by	Estimated mean LST (°C)
25%	35.02	25%	32.98
50%	35.78	50%	31.76
75%	36.54	75%	30.46
100%	37.31	100%	29.16

Source: Computed from data, (2020)

Table 7: Correlations coefficients between LST, NDVI and NDBI

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.	95.0% Confidence Interval for B
Model		B	Std. Error	Beta	t	Sig.	Lower Bound	Upper Bound
	(Constant)	29.437	1.697		17.342	.000	25.701	33.173
	NDBI	117.725	23.624	1.376	4.983	.00042**	65.729	169.721
	NDVI	-19.106	8.386	-.629	-2.278	.044*	-37.564	-.648

a. Dependent Variable: LST

**Indicate that coefficient is statistically significant at p < 0.01 and * indicates that coefficient is statistically significant at p < 0.05.

Table 8: Distribution of LST through Kebeles in Adama City

Kebele	LST_2000 in (⁰C)					LST_2020 in (⁰C)				Difference
	Min	Max	Range	Mean	Min		Max	Range	Mean
Sire Abba Bune	24.68	27.75	3.08	25.77	28.34		31.50	3.16	29.72		3.95
Boriticha	22.88	27.75	4.87	25.18	26.73		30.67	3.93	29.05		3.87
Cheffe	23.78	27.32	3.54	25.32	28.10		30.90	2.81	29.25		3.94
Biqa	20.61	28.19	7.58	25.31	24.37		30.98	6.61	29.40		4.09
Soloke	17.82	30.77	12.94	24.75	25.35		34.82	9.47	29.66		4.91
Harriti	22.43	28.62	6.19	25.09	27.12		32.15	5.03	29.39		4.30
Ketera	22.88	30.34	7.46	26.05	25.65		32.69	7.04	29.13		3.08
Giko	21.52	31.19	9.67	26.27	26.23		34.69	8.46	29.83		3.55
Dembela	20.61	32.88	12.27	28.90	24.13		36.85	12.72	31.54		2.64
Bole	19.22	38.23	19.01	28.21	18.81		38.61	19.80	31.40		3.18
Andode	18.76	33.71	14.96	28.11	25.77		38.34	12.57	33.08		4.97
Gooba Hiddi	21.07	34.55	13.48	29.25	24.41		39.78	15.36	34.26		5.02
Dibibisa	21.52	32.04	10.51	27.32	25.56		38.30	12.75	31.02		3.70
Goro	20.61	32.88	12.27	28.87	21.21		36.43	15.22	31.12		2.25

Source: Computed from satellite data, (2020)

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Analysis of the Cooling Effect of Urban Green Spaces in Mitigating Micro-climate Change Using Geospatial Techniques in Adama City, Central Ethiopia

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