Analysis of Land Surface Temperature Distribution in Response to Land Use Land Cover Change in Agroforestry Dominated Area, Gedeo Zone, Southern Ethiopia

Wendwesen Taddesse Sahile; Gashaw Kibret Goshem; Seid Ali Shifaw; Muh. Rais  Abidin

doi:10.55151/ijeedu.v5i1.98

Wendwesen Taddesse Sahile Department of Land Administration and Surveying, College of Agriculture and Natural Resource Management, Dilla University, Ethiopia
Gashaw Kibret Goshem Department of Land Administration and Surveying, College of Agriculture and Natural Resource Management, Dilla University, Ethiopia
Seid Ali Shifaw Department of Land Administration and Surveying, College of Agriculture and Natural Resource Management, Dilla University, Ethiopia
Muh. Rais Abidin Department of Geography, Universitas Negeri Makassar, South Sulawesi, Indonesia

DOI: https://doi.org/10.55151/ijeedu.v5i1.98

Keywords: Agroforestry, Dark Object Substruction, Gedeo Zone, Sentinel-2A, Support Vector Machine

Abstract

This study examined LST distribution in Ethiopia's agroforestry-dominated Gedeo Zone due to Land Use Land Cover change. For 2005, 2011, 2017, and 2022, 10 m Sentinel 2A and 30 m Landsat images were used to extract and map LST and LULC distribution. The DOS1 method corrected atmospheric errors in all satellite images. LULC change was detected using SVM image classification. The study result revealed that the Agroforestry and Built-up coverage has increased by 1520 sq. km and 2600 sq. km, respectively, from 2005 to 2022. The Bare Land and Farm Land coverage decreased by 1554 sq. km and 2565 sq. km, respectively, in the same period. The LST result has shown that there has been a remarkable variation in the spatial pattern of the LST between 2005 and 2022. The average LST in Agroforestry, Bare Land, Farm Land, and Built-up area has progressively increased over the years, from 19.6°C, 26.0°C, 20.2°C, and 25.58°C in 2005 to 25°C, 32.16°C, 28.23°C, and 30.62 °C in 2022, respectively. While in 2005, the maximum recorded LST did not exceed 37.3°C, by 2022, it had increased by close to 3°C, reaching 40.6°C. The overall result revealed that the average LST in °C has increased from 2005 to 2022. From the result, it was concluded that agroforestry had contributed a lot to LST distribution. LST may not depend on the local LULC change only; other factors like urbanization and global warming could play a significant role in changing LST locally and globally.

References

G. C. Hulley, D. Ghent, F. M. Göttsche, P. C. Guillevic, D. J. Mildrexler, and C. Coll, “Land Surface Temperature,” in Taking the Temperature of the Earth, Elsevier, 2019, pp. 57–127.

G. Hulley and D. Ghent, Taking the temperature of the earth: steps towards integrated understanding of variability and change. Elsevier, 2019.

J. Hofierka, M. Gallay, K. Onačillová, and J. Hofierka Jr, “Physically-based land surface temperature modeling in urban areas using a 3-D city model and multispectral satellite data,” Urban Clim., vol. 31, p. 100566, 2020.

J. Tan, D. Yu, Q. Li, X. Tan, and W. Zhou, “Spatial relationship between land-use/land-cover change and land surface temperature in the Dongting Lake area, China,” Sci. Rep., vol. 10, no. 1, pp. 1–9, 2020.

N. R. Govind and H. Ramesh, “The impact of spatiotemporal patterns of land use land cover and land surface temperature on an urban cool island: a case study of Bengaluru,” Environ. Monit. Assess., vol. 191, pp. 1–20, 2019.

R. S. Defries, L. Bounoua, and G. J. Collatz, “Human modification of the landscape and surface climate in the next fifty years,” Glob. Chang. Biol., vol. 8, no. 5, pp. 438–458, 2002.

L. Bounoua, R. DeFries, G. J. Collatz, P. Sellers, and H. Khan, “Effects of land cover conversion on surface climate,” Clim. Change, vol. 52, pp. 29–64, 2002.

E. Pramova, B. Locatelli, H. Djoudi, and O. A. Somorin, “Forests and trees for social adaptation to climate variability and change,” Wiley Interdiscip. Rev. Clim. Chang., vol. 3, no. 6, pp. 581–596, 2012.

C. Mbow, P. Smith, D. Skole, L. Duguma, and M. Bustamante, “Achieving mitigation and adaptation to climate change through sustainable agroforestry practices in Africa,” Curr. Opin. Environ. Sustain., vol. 6, pp. 8–14, 2014.

S. Sarvade, R. Singh, H. Prasad, and D. Prasad, “Agroforestry practices for improving soil nutrient status,” Pop. Kheti, vol. 2, no. 1, pp. 60–64, 2014.

N. Sharma, B. Bohra, N. Pragya, R. Ciannella, P. Dobie, and S. Lehmann, “Bioenergy from agroforestry can lead to improved food security, climate change, soil quality, and rural development,” Food Energy Secur., vol. 5, no. 3, pp. 165–183, 2016.

T. Thorlakson and H. Neufeldt, “Reducing subsistence farmers’ vulnerability to climate change: evaluating the potential contributions of agroforestry in western Kenya,” Agric. Food Secur., vol. 1, pp. 1–13, 2012.

K. F. Kalaba, P. Chirwa, S. Syampungani, and C. O. Ajayi, “Contribution of agroforestry to biodiversity and livelihoods improvement in rural communities of Southern African regions,” Trop. rainforests agroforests under Glob. Chang. Ecol. socio-economic valuations, pp. 461–476, 2010.

A. Raj and S. Chandrawanshi, “Role of agroforestry in poverty alleviation and livelihood support in Chhattisgarh,” South Indian J. Biol. Sci., vol. 2, no. 3, pp. 326–330, 2016.

Z. Mekonnen et al., “Traditional knowledge and institutions for sustainable climate change adaptation in Ethiopia,” Curr. Res. Environ. Sustain., vol. 3, p. 100080, 2021.

T. K. Kanshie, Five thousand years of sustainability?: a case study on Gedeo land use (Southern Ethiopia). Wageningen University and Research, 2002.

T. Abebe, “Determinants of crop diversity and composition in Enset-coffee agroforestry homegardens of Southern Ethiopia,” 2013.

S. Degefa, “Home garden agroforestry practices in the Gedeo zone, Ethiopia: a sustainable land management system for socio-ecological benefits,” Socio-ecological Prod. landscapes seascapes Africa, p. 28, 2016.

M. Negash, E. Yirdaw, and O. Luukkanen, “Potential of indigenous multistrata agroforests for maintaining native floristic diversity in the south-eastern Rift Valley escarpment, Ethiopia,” Agrofor. Syst., vol. 85, pp. 9–28, 2012.

G. M. Foody and A. Mathur, “A relative evaluation of multiclass image classification by support vector machines,” IEEE Trans. Geosci. Remote Sens., vol. 42, no. 6, pp. 1335–1343, 2004.

S. S. Keerthi, O. Chapelle, D. DeCoste, K. P. Bennett, and E. Parrado-Hernández, “Building support vector machines with reduced classifier complexity.,” J. Mach. Learn. Res., vol. 7, no. 7, 2006.

K. S. Kumar, P. U. Bhaskar, and K. Padmakumari, “Estimation of land surface temperature to study urban heat island effect using LANDSAT ETM+ image,” Int. J. Eng. Sci. Technol., vol. 4, no. 2, pp. 771–778, 2012.

J. C. Jiménez-Muñoz, J. A. Sobrino, D. Skoković, C. Mattar, and J. Cristobal, “Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data,” IEEE Geosci. Remote Sens. Lett., vol. 11, no. 10, pp. 1840–1843, 2014.

A. Rajeshwari and N. D. Mani, “Estimation of land surface temperature of Dindigul district using Landsat 8 data,” Int. J. Res. Eng. Technol., vol. 3, no. 5, pp. 122–126, 2014.

M. B. Giannini, O. R. Belfiore, C. Parente, and R. Santamaria, “Land Surface Temperature from Landsat 5 TM images: comparison of different methods using airborne thermal data.,” J. Eng. Sci. Technol. Rev., vol. 8, no. 3, 2015.

Q. Weng, D. Lu, and J. Schubring, “Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies,” Remote Sens. Environ., vol. 89, no. 4, pp. 467–483, 2004.

R. R. Jensen, J. D. Gatrell, D. D. McLean, Q. Weng, and R. C. Larson, “Satellite remote sensing of urban heat islands: current practice and prospects,” Geo-spatial Technol. urban Environ., pp. 91–111, 2005.

D. Skoković et al., “Calibration and Validation of land surface temperature for Landsat8-TIRS sensor,” L. Prod. Valid. Evol., 2014.

Y. Xiong, S. Huang, F. Chen, H. Ye, C. Wang, and C. Zhu, “The impacts of rapid urbanization on the thermal environment: A remote sensing study of Guangzhou, South China,” Remote Sens., vol. 4, no. 7, pp. 2033–2056, 2012.

J. C. Jiménez-Muñoz, J. A. Sobrino, A. Plaza, L. Guanter, J. Moreno, and P. Martínez, “Comparison between fractional vegetation cover retrievals from vegetation indices and spectral mixture analysis: Case study of PROBA/CHRIS data over an agricultural area,” Sensors, vol. 9, no. 02, pp. 768–793, 2009.

B. K. Terfa, N. Chen, D. Liu, X. Zhang, and D. Niyogi, “Urban expansion in Ethiopia from 1987 to 2017: Characteristics, spatial patterns, and driving forces,” Sustainability, vol. 11, no. 10, p. 2973, 2019.

T. S. Shanka, “Characterizing to sustain the agrobiodiversity in the Gedeo Zone, Southern Ethiopia,” in Natural Resources Conservation and Advances for Sustainability, Elsevier, 2022, pp. 581–612.

B. Tsegaye, “Effect of land use and land cover changes on soil erosion in Ethiopia,” Int. J. Agric. Sci. Food Technol., vol. 5, no. 1, pp. 26–34, 2019.

S. B. Wassie, “Natural resource degradation tendencies in Ethiopia: a review,” Environ. Syst. Res., vol. 9, pp. 1–29, 2020.

R. Alkama and A. Cescatti, “Biophysical climate impacts of recent changes in global forest cover,” Science (80-. )., vol. 351, no. 6273, pp. 600–604, 2016.

S. Yin, W. Wu, X. Zhao, C. Gong, X. Li, and L. Zhang, “Understanding spatiotemporal patterns of global forest NPP using a data-driven method based on GEE,” PLoS One, vol. 15, no. 3, p. e0230098, 2020.

N. E. A. Murray, M. B. Quam, and A. Wilder-Smith, “Epidemiology of dengue: past, present and future prospects,” Clin. Epidemiol., pp. 299–309, 2013.

A. Parven et al., “Impacts of disaster and land-use change on food security and adaptation: Evidence from the delta community in Bangladesh,” Int. J. Disaster Risk Reduct., vol. 78, p. 103119, 2022.

A.-A. Kafy et al., “Assessment and prediction of seasonal land surface temperature change using multi-temporal Landsat images and their impacts on agricultural yields in Rajshahi, Bangladesh,” Environ. Challenges, vol. 4, p. 100147, 2021.