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Research Article

Assessing the impact of land use land cover changes on soil moisture and vegetation cover in Southern Punjab, Pakistan using multi-temporal satellite data

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Received 27 Jul 2023, Accepted 01 Apr 2024, Published online: 09 Apr 2024

References

  • Abdullah, A., Masrur, A., Adnan, M., Baky, M., Hassan, Q., & Dewan, A. (2019). Spatio-temporal patterns of land use/land cover change in the heterogeneous coastal region of Bangladesh between 1990 and 2017. Remote Sensing, 11(7), 790. https://doi.org/10.3390/rs11070790
  • Aboelnour, M., & Engel, B. A. (2018). Application of remote sensing techniques and geographic information systems to analyze land surface temperature in response to land use/land cover change in greater Cairo region, Egypt. Journal of Geographic Information System, 10(1), 57–88. https://doi.org/10.4236/jgis.2018.101003
  • Afzal, S., Mubeen, M., Hussain, S., Ali, M., Javeed, H. M. R., Al-Ashkar, I., & Jatoi, W. N. (2023). Modern breeding approaches for climate change. In Climate change impacts on agriculture: Concepts, issues and policies for developing countries (pp. 299–313). Springer International Publishing. https://doi.org/10.1007/978-3-031-26692-8_17.
  • Ahmad, F. (2012). A review of remote sensing data change detection: Comparison of Faisalabad and Multan Districts, Punjab Province, Pakistan. Journal of Geography and Regional Planning, 5(9), 236–251. https://doi.org/10.5897/JGRP11.121
  • Ahmed, M., Aslam, M. A., Hayat, R., Nasim, W., Akmal, M., Mubeen, M., & Ahmad, S. (2022). Nutrient dynamics and the role of modeling. In Building climate resilience in agriculture (pp. 297–316). Springer. https://doi.org/10.1007/978-3-030-79408-8_19.
  • Akhtar, F., Awan, U. K., Tischbein, B., & Liaqat, U. W. (2017). A phenology based geo-informatics approach to map land use and land cover (2003–2013) by spatial segregation of large heterogenic river basins. Applied Geography, 88, 48–61. https://doi.org/10.1016/j.apgeog.2017.09.003
  • Akram, R., Amanet, K., Iqbal, J., Fatima, M., Mubeen, M., Hussain, S., & Fahad, S. (2022b). Climate change, insects and global food production. In S. Fahad, M. Adnan, S. Saud, & L. Nie (Eds.), Climate change and ecosystems (pp. 47–60). CRC Press.
  • Akram, R., Jabeen, T., Bukari, M. A., Wajid, S. A., Mubeen, M., Rasul, F., Hussain, H., Aurangzaib, M., & Nasim, W. (2022a). Research on climate change issues. In W. N. Jatoi, M. Mubeen, A. Ahmad, M. A. Cheema, Z. Lin, & M. Z. Hashmi (Eds.), Building Climate Resilience in Agriculture (pp. 255–268). Springer. https://doi.org/10.1007/978-3-030-79408-8_17
  • Akram, R., Turan, V., Hammad, H. M., Ahmad, S., Hussain, S., Hasnain, A., Maqbool, M. M., Rehmani, M. I. A., Rasool, A., Masood, N., & Mahmood, F. (2018). Fate of organic and inorganic pollutants in paddy soils. In Environmental pollution of paddy soils (pp. 197–214). Springer. https://doi.org/10.1007/978-3-319-93671-0_13.
  • Ali, A., Khalid, A., Butt, M. A., Mehmood, R., Mahmood, S. A., Sami, J., Qureshi, J., Shafique, K., Ghalib, A. K., Waheed, R., Ali, F., Mukhtar, R., & Azhar, M. (2018). Towards a remote sensing and GIS-Based technique to study population and urban growth: A case study of multan. Advances in Remote Sensing, 7(3), 245. https://doi.org/10.4236/ars.2018.73017
  • Ali, A., Khan, M., Nadeem, M. A., Imran, M., Ahmad, S., Amanet, K., & Hanif, A. (2023). Climate change effects on the quality of different crop plants and coping mechanisms. In Climate change impacts on agriculture: Concepts, issues and policies for developing countries (pp. 355–370). Springer International Publishing. https://doi.org/10.1007/978-3-031-26692-8_20.
  • Ali, M., Mubeen, M., Hussain, N., Wajid, A., Farid, H. U., Awais, M., Hussain, S., Akram, W., Amin, A., Akram, R., & Imran, M. (2019). Role of ICT in crop management. In Agronomic Crops (pp. 637–652). Springer. https://doi.org/10.1007/978-981-32-9783-8_28.
  • Almazroui, M., Masshat, A., Assiri, M., & Butt, M. (2017). Application of landsat data for urban growth monitoring in Jeddah. Earth Systems and Environment, 1(2), 25. https://doi.org/10.1007/s41748-017-0028-4
  • Aredehey, G., Mezgebu, A., & Girma, A. (2018). Land-use land-cover classification analysis of Giba catchment using hyper temporal MODIS NDVI satellite images. International Journal of Remote Sensing, 39(3), 810–821. https://doi.org/10.1080/01431161.2017.1392639
  • Athick, A. A. S. M., & Shankar, K. (2019). Data on land use and land cover changes in AdamaWereda, Ethiopia, on ETM+, TM and OLI- TIRS landsat sensor using PCC and CDM techniques. Data in Brief, 24, 103880. https://doi.org/10.1016/j.dib.2019.103880
  • Athick, A. M. A., Shankar, K., & Naqvi, H. R. (2019). Data on time series analysis of land surface temperature variation in response to vegetation indices in twelve Wereda of Ethiopia using mono window, split window algorithm and spectral radiance model. Data in Brief, 27, 104773. https://doi.org/10.1016/j.dib.2019.104773
  • Ayele, G. T., Tebeje, A. K., Demissie, S. S., Belete, M. A., Jemberrie, M. A., Teshome, W. M., & Teshale, E. Z. (2018). Time series land cover mapping and change detection analysis using geographic information system and remote sensing, Northern Ethiopia. Air, Soil and Water Research, 11, 1178622117751603. https://doi.org/10.1177/1178622117751603
  • Bento, V., Trigo, I., Gouveia, C., & DaCamara, C. (2018). Contribution of land surface temperature (TCI) to vegetation health index: A comparative study using clear sky and all-weather climate data records. Remote Sensing, 10(9), 1324. https://doi.org/10.3390/rs10091324
  • Bhagyanagar, R., Kawal, B. M., Dwarakish, G. S., & Surathkal, S. (2012). Land use/land cover change and urban expansion during 1983–2008 in the coastal area of Dakshina Kannada district, South India. Journal of Applied Remote Sensing, 6(1), 063576. https://doi.org/10.1117/1.JRS.6.063576
  • Cai, M., Ren, C., Xu, Y., Lau, K. K. L., & Wang, R. (2018). Investigating the relationship between local climate zone and land surface temperature using an improved WUDAPT methodology–A case study of Yangtze River Delta, China. Urban Climate, 24, 485–502. https://doi.org/10.1016/j.uclim.2017.05.010
  • Chew, C., Shah, R., Zuffada, C., Hajj, G., Masters, D., & Mannucci, A. J. (2016). Demonstrating soil moisture remote sensing with observations from the UK TechDemoSat‐1 satellite mission. Geophysical Research Letters, 43(7), 3317–3324. https://doi.org/10.1002/2016GL068189
  • Choudhury, D., Das, K., & Das, A. (2018). Assessment of land use land cover changes and its impact on variations of land surface temperature in Asansol-Durgapur development region. Egypt Journal of Remote Sensing and Space Science, 22(2), 203–218. https://doi.org/10.1016/j.ejrs.2018.05.004
  • Cristóbal, J., Jiménez-Muñoz, J., Prakash, A., Mattar, C., Skoković, D., & Sobrino, J. (2018). An improved single-channel method to retrieve land surface temperature from the landsat-8 thermal band. Remote Sensing, 10(3), 431. https://doi.org/10.3390/rs10030431
  • Das, S., & Angadi, D. P. (2020). Land use-land cover (LULC) transformation and its relation with land surface temperature changes: A case study of Barrackpore Subdivision, West Bengal, India. Remote Sensing Applications: Society & Environment, 19, 100322. https://doi.org/10.1016/j.rsase.2020.100322
  • Das, S., & Sarkar, R. (2019). Predicting the land use and land cover change using Markov model: A catchment level analysis of the Bhagirathi-Hugli River. Spatial Information Research, 27(4), 439–452. https://doi.org/10.1007/s41324-019-00251-7
  • Ding, H., & Shi, W. (2013). Land-use/land-cover change and its influence on surface temperature: A case study in Beijing City. International Journal of Remote Sensing, 34(15), 5503–5517. https://doi.org/10.1080/01431161.2013.792966
  • Din, M. S. U., Mubeen, M., Hussain, S., Ahmad, A., Hussain, N., Ali, M. A., & Nasim, W. (2022). World nations priorities on climate change and food security. In Building climate resilience in agriculture (pp. 365–384). Springer. https://doi.org/10.1007/978-3-030-79408-8_22.
  • Forkel, M., Carvalhais, N., Verbesselt, J., Mahecha, M., Neigh, C., & Reichstein, M. (2013). Trend change detection in NDVI time series: Effects of inter-annual variability and methodology. Remote Sensing, 5(5), 2113–2144. https://doi.org/10.3390/rs5052113
  • Gilani, H., Shrestha, H. L., Murthy, M. S. R., Phuntso, P., Pradhan, S., Bajracharya, B., & Shrestha, B. (2015). Decadal land cover change dynamics in Bhutan. Journal of environmental management, 148, 91–100. https://doi.org/10.1016/j.jenvman.2014.02.014
  • Hashim, A. M., Elkelish, A., Alhaithloul, H. A., El-Hadidy, S. M., & Farouk, H. (2020). Environmental monitoring and prediction of land use and land cover spatio-temporal changes: A case study from El-Omayed biosphere reserve, Egypt. Environmental Science and Pollution Research, 27(34), 42881–42897. https://doi.org/10.1007/s11356-020-10208-1
  • Hc, H., Surendra, L., & Srikanth, H. J. (2020). Prioritization of sub-watersheds of the Kanakapura Watershed in the Arkavathi River Basin, Karnataka, India-using Remote sensing and GIS. Geology, Ecology, and Landscapes, 5(2), 149–160. https://doi.org/10.1080/24749508.2020.1846841
  • Hu, Y., Raza, A., Syed, N. R., Acharki, S., Ray, R. L., Hussain, S., Dehghanisanij, H., Zubair, M., & Elbeltagi, A. (2023). Land use/land cover change detection and NDVI estimation in Pakistan’s Southern Punjab province. Sustainability, 15(4), 3572. https://doi.org/10.3390/su15043572
  • Hussain, S. (2018). Land use/land cover classification by using satellite NDVI tool for sustainable water and climate change in Southern Punjab [ M.S. thesis]. COMSATS University Islamabad. https://doi.org/10.13140/RG.2.2.32363.69923
  • Hussain, S. (2022). Managing greenhouse gas emission. In Sarwar, N., Atique-Ur-Rehman, Ahmad, S., & Hasanuzzaman, M. (Eds.), Modern Techniques of rice crop production. Springer. https://doi.org/10.1007/978-981-16-4955-4_27.
  • Hussain, S., Ahmad, A., Wajid, A., Khaliq, T., Hussain, N., Mubeen, M., Farid, H. U., Imran, M., Hammad, H. M., Awais, M., Ali, A., Aslam, M., Amin, A., Akram, R., Amanet, K., & Nasim, W. (2020). Irrigation scheduling for cotton cultivation. In Cotton production and uses (pp. 59–80). Springer. https://doi.org/10.1007/978-981-15-1472-2_5.
  • Hussain, S., Amin, A., Mubeen, M., Khaliq, T., Shahid, M., Hammad, H. M., & Nasim, W. (2022). Climate Smart Agriculture (CSA) Technologies. In Building climate resilience in agriculture (pp. 319–338). Springer. https://doi.org/10.1007/978-3-030-79408-8_20.
  • Hussain, S., & Karuppannan, S. (2023). Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan. Geology, Ecology & Landscapes, 7(1), 46–58. https://doi.org/10.1080/24749508.2021.1923272
  • Hussain, S., Lu, L., Mubeen, M., Nasim, W., Karuppannan, S., Fahad, S., Tariq, A., Mousa, B. G., Mumtaz, F., & Aslam, M. (2022). Spatiotemporal variation in land use land cover in the response to local climate change using multispectral remote sensing data. The Land, 11(5), 595. https://doi.org/10.3390/land11050595
  • Hussain, S., Mubeen, M., Ahmad, A., Akram, W., Hammad, H. M., Ali, M., Masood, N., Amin, A., Farid, H. U., Sultana, S. R., Fahad, S., Wang, D., & Nasim, W. (2020). Using GIS tools to detect the land use/land cover changes during forty years in Lodhran District of Pakistan. Environmental Science and Pollution Research, 27(32), 39676–39692. https://doi.org/10.1007/s11356-019-06072-3
  • Hussain, S., Mubeen, M., Ahmad, A., Fahad, S., Nasim, W., Hammad, H. M., & Parveen, S. (2021). Study the Effects of COVID-19 in Punjab, Pakistan using space-time scan statistic for policy measures in regional agriculture and food supply chain. https://doi.org/10.21203/rs.3.rs-814098/v1
  • Hussain, S., Mubeen, M., Ahmad, A., Fahad, S., Nasim, W., Hammad, H. M., Parveen, S., Murtaza, B., Tahir, M., & Parveen, S. (2023). Using space–time scan statistic for studying the effects of COVID-19 in Punjab, Pakistan: A guideline for policy measures in regional agriculture. Environmental Science and Pollution Research, 30(15), 42495–42508. https://doi.org/10.1007/s11356-021-17433-2
  • Hussain, S., Mubeen, M., Ahmad, A., Majeed, H., Qaisrani, S. A., Hammad, H. M., Amjad, M., Ahmad, I., Fahad, S., Ahmad, N., & Nasim, W. (2022). Assessment of land use/land cover changes and its effect on land surface temperature using remote sensing techniques in Southern Punjab, Pakistan. Environmental Science and Pollution Research, 30(44), 99202–99218. https://doi.org/10.1007/s11356-022-21650-8
  • Hussain, S., Mubeen, M., Akram, W., Ahmad, A., Habib-Ur-Rahman, M., Ghaffar, A., Amin, A., Awais, M., Farid, H. U., Farooq, A., & Nasim, W. (2020). Study of land cover/land use changes using RS and GIS: A case study of Multan district, Pakistan. Environmental Monitoring and Assessment, 192(1), 2. https://doi.org/10.1007/s10661-019-7959-1
  • Hussain, S., Mubeen, M., Jatoi, W. N., Tahir, M., Ahmad, S., Farid, H. U., & Abbas, B. (2023). Sustainable development goals and governments’ roles for social protection. In Climate change impacts on agriculture: Concepts, issues and policies for developing countries (pp. 209–222). Springer International Publishing. https://doi.org/10.1007/978-3-031-26692-8_12.
  • Hussain, S., Mubeen, M., & Karuppannan, S. (2022). Land use and land cover (LULC) change analysis using TM, ETM+ and OLI landsat images in district of Okara, Punjab, Pakistan. Physics and Chemistry of the Earth, 126, 103117. https://doi.org/10.1016/j.pce.2022.103117
  • Hussain, S., Mubeen, M., Nasim, W., Fahad, S., Ali, M., Ehsan, M. A., & Raza, A. (2023). Investigation of irrigation water requirement and evapotranspiration for water resources management in Southern Punjab, Pakistan. Sustainability, 15(3), 1768. https://doi.org/10.3390/su15031768
  • Hussain, S., Qin, S., Nasim, W., Bukhari, M. A., Mubeen, M., Fahad, S., Raza, A., Abdo, H. G., Tariq, A., Mousa, B. G., Mumtaz, F., & Aslam, M. (2022). Monitoring the dynamic changes in vegetation cover using spatio-temporal remote sensing data from 1984 to 2020. Atmosphere, 13(10), 1609. https://doi.org/10.3390/atmos13101609
  • Hussain, S., Raza, A., Abdo, H. G., Mubeen, M., Tariq, A., Nasim, W., Majeed, M., Almohamad, H., & Al Dughairi, A. A. (2023). Relation of land surface temperature with different vegetation indices using multi-temporal remote sensing data in Sahiwal region, Pakistan. Geoscience Letters, 10(1), 33. https://doi.org/10.1186/s40562-023-00287-6
  • Huyen, N. T., Tu, L. H., Liem, N. D., Tram, V. N. Q., Minh, D. N., & Loi, N. K. (2016). Assessing impacts of land use and climate change on soil and water resources in the Srepok Watershed, Central Highland of Vietnam. Policy Brief Series, 2016, 1–4. https://doi.org/10.13140/RG.2.2.28700.08326
  • Islam, M. S., Fahad, S., Hossain, A., Chowdhury, M. K., Iqbal, M. A., Dubey, A., & Sabagh, A. E. (2021). Legumes under drought stress: plant responses, adaptive mechanisms, and management strategies in relation to nitrogen fixation. In S. Fahad, O. Sönmez, S. Saud, D. Wang, C. Wu, M. Adnan, M. Arif, & Amanullah, (Eds.), Engineering tolerance in crop plants against abiotic stress (pp. 179–207). CRC Press.
  • Karan, S. K., Samadder, S. R., & Maiti, S. K. (2016). Assessment of the capability of remote sensing and GIS techniques for monitoring reclamation success in coal mine degraded lands. Journal of Environment Management, 182, 272–283. https://doi.org/10.1016/j.jenvman.2016.07.070
  • Karuppasamy, M. B., Natesan, U., Karuppannan, S., Chandrasekaran, L. N., Hussain, S., Almohamad, H., Dughairi, A. A. A., Al-Mutiry, M., Alkayyadi, I., & Abdo, H. G. (2022). Multivariate urban air quality assessment of indoor and outdoor environments at Chennai metropolis in South India. Atmosphere, 13(10), 1627. https://doi.org/10.3390/atmos13101627
  • Kazmi, D. H., Afzaal, M., Mubeen, M., Hussain, S., & Jatoi, W. N. (2023). Unpredictable weather and agriculture-based economy of developing countries. In Climate change impacts on agriculture: Concepts, issues and policies for developing countries (pp. 65–78). Springer International Publishing. https://doi.org/10.1007/978-3-031-26692-8_4.
  • Khaliq, M. A., Javed, M. T., Hussain, S., Imran, M., Mubeen, M., Nasim, W., Fahad, S., Karuppannan, S., Al-Taisan, W. A., Almohamad, H., Al Dughairi, A. A., Al-Mutiry, M., Alrasheedi, M., & Abdo, H. G. (2022). Assessment of heavy metal accumulation and health risks in okra (Abelmoschus Esculentus L.) and spinach (Spinacia Oleracea L.) fertigated with wastwater. International Journal of Food Contamination, 9(1), 11. https://doi.org/10.1186/s40550-022-00097-2
  • Khan, I., Javed, T., Khan, A., Lei, H., Muhammad, I., Ali, I., & Huo, X. (2019). Impact assessment of land use change on surface temperature and agricultural productivity in Peshawar-Pakistan. Environmental Science and Pollution Research, 26(32), 33076–33085. https://doi.org/10.1007/s11356-019-06448-5
  • Kharazmi, R., Tavili, A., Rahdari, M. R., Chaban, L., Panidi, E., & Rodrigo-Comino, J. (2018). Monitoring and assessment of seasonal land cover changes using remote sensing: A 30-year (1987–2016) case study of Hamoun Wetland, Iran. Environmental Monitoring and Assessment, 190(6), 356. https://doi.org/10.1007/s10661-018-6726-z
  • Kidane, M., Tolessa, T., Bezie, A., Kessete, N., & Endrias, M. (2019). Evaluating the impacts of climate and land use/land cover (LU/LC) dynamics on the hydrological responses of the Upper Blue Nile in the Central Highlands of Ethiopia. Spatial Information Research, 27(2), 151–167. https://doi.org/10.1007/s41324-018-0222-y
  • Majeed, M., Tariq, A., Anwar, M. M., Khan, A. M., Arshad, F., Mumtaz, F., Farhan, M., Zhang, L., Zafar, A., Aziz, M., Abbasi, S., Rahman, G., Hussain, S., Waheed, M., Fatima, K., & Shaukat, S. (2021). Monitoring of land use–land cover change and potential causal factors of climate change in Jhelum District, Punjab, Pakistan, through GIS and multi-temporal satellite data. The Land, 10(10), 1026. https://doi.org/10.3390/land10101026
  • Masood, N., Akram, R., Fatima, M., Mubeen, M., Hussain, S., Shakeel, M., & Nasim, W. (2022). Insect pest management under climate change. In Building climate resilience in agriculture (pp. 225–237). Springer. https://doi.org/10.1007/978-3-030-79408-8_15.
  • Mohammed, A. A. A. S., Shankar, K., & Hasan, R. N. (2019). Data on time series analysis of land surface temperature variation in response to vegetation indices in twelve Wereda of Ethiopia using mono window, split window algorithm and spectral radiance model. Data in Brief, 27, 104773. https://doi.org/10.1016/j.dib.2019.104773
  • Mubeen, M., Bano, A., Ali, B., Islam, Z. U., Ahmad, A., Hussain, S., Fahad, S., & Nasim, W. (2021). Effect of plant growth promoting bacteria and drought on spring maize (Zea mays L.). Pakistan Journal of Botany, 53(2), 731–739. https://doi.org/10.30848/PJB2021-2(38)
  • Mukherjee, F., & Singh, D. (2020). Assessing land use–land cover change and its impact on land surface temperature using LANDSAT data: A comparison of two urban areas in India. Earth Systems and Environment, 4(2), 385–407. https://doi.org/10.1007/s41748-020-00155-9
  • Nasim, W., Amin, A., Fahad, S., Awais, M., Khan, N., Mubeen, M., Wahid, A., Rehman, M. H., Ihsan, M. Z., Ahmad, S., Hussain, S., Mian, I. A., Khan, B., & Jamal, Y. (2018). Future risk assessment by estimating historical heat wave trends with projected heat accumulation using SimCLIM climate model in Pakistan. Atmospheric Research, 205, 118–133. https://doi.org/10.1016/j.atmosres.2018.01.009
  • Nayak, D. P., & Fulekar, M. H. (2017). Coastal geomorphological and land use and land cover study on some sites of Gulf of Kachchh, Gujarat, West Coast of India using multi-temporal remote sensing data. International Journal of Advanced Remote Sensing and GIS, 6(1), 2192–2203. https://doi.org/10.23953/cloud.ijarsg.273
  • Naz, S., Fatima, Z., Iqbal, P., Khan, A., Zakir, I., Ullah, H., & Ahmad, S. (2022). An introduction to climate change phenomenon. In Building climate resilience in agriculture (pp. 3–16). Springer. https://doi.org/10.1007/978-3-030-79408-8_1.
  • Naz, A., & Rasheed, H. (2017). Modeling the rice land suitability using GIS and multi-criteria decision analysis approach in Sindh, Pakistan. Journal of Basic & Applied Sciences, 13, 26–33. https://doi.org/10.6000/1927-5129.2017.13.05
  • Olmanson, L. G., Brezonik, P. L., Finlay, J. C., & Bauer, M. E. (2016). Comparison of landsat 8 and landsat 7 for regional measurements of CDOM and water clarity in lakes. Remote Sensing of Environment, 185, 119–128. https://doi.org/10.1016/j.rse.2016.01.007
  • Omran, E. S. E. (2012). Detection of land-use and surface temperature change at different resolutions. Journal of Geographic Information System, 4(3), 189. https://doi.org/10.4236/jgis.2012.43024
  • Orimoloye, I. R., Mazinyo, S. P., Nel, W., & Kalumba, A. M. (2018). Spatiotemporal monitoring of land surface temperature and estimated radiation using remote sensing: Human health implications for East London, South Africa. Environmental Earth Sciences, 77(3), 77. https://doi.org/10.1007/s12665-018-7252-6
  • Pal, S., & Ziaul, S. (2017). Detection of land use and land cover change and land surface temperature in English Bazar urban centre. Egypt Journal of Remote Sensing and Space Science, 20(1), 125–145. https://doi.org/10.1016/j.ejrs.2016.11.003
  • Rahman, S., & Mesev, V. (2019). Change vector analysis, Tasseled Cap, and NDVI-NDMI for measuring land Use/Cover changes caused by a sudden short-term severe drought: 2011 Texas event. Remote Sensing, 11(19), 2217. https://doi.org/10.3390/rs11192217
  • Rahman, M. T. U., Tabassum, F., Rasheduzzaman, M., Saba, H., Sarkar, L., Ferdous, J., & Islam, A. Z. (2017). Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh. Environmental Monitoring and Assessment, 189(11), 565. https://doi.org/10.1007/s10661-017-6272-0
  • Rani, M., Kumar, P., Pandey, P. C., Srivastava, P. K., Chaudhary, B. S., Tomar, V., & Mandal, V. P. (2018). Multi-temporal NDVI and surface temperature analysis for urban heat Island inbuilt surrounding of sub-humid region: A case study of two geographical regions. Remote Sensing Applications: Society & Environment, 10, 163–172. https://doi.org/10.1016/j.rsase.2018.03.007
  • Rizvi, S. H., Fatima, H., Alam, K., & Iqbal, M. J. (2020). The surface urban heat Island Intensity and Urban Expansion: A comparative analysis for the coastal areas of Pakistan. Environment, Development and Sustainability, 23(4), 5520–5537. https://doi.org/10.1007/s10668-020-00828-5
  • Romaguera, M., Vaughan, R. G., Ettema, J., Izquierdo-Verdiguier, E., Hecker, C. A., & van der Meer, F. D. (2018). Detecting geothermal anomalies and evaluating LST geothermal component by combining thermal remote sensing time series and land surface model data. Remote Sensing of Environment, 204, 534–552. https://doi.org/10.1016/j.rse.2017.10.003
  • Sabagh, A. E., Hossain, A., Islam, M. S., Iqbal, M. A., Fahad, S., Ratnasekera, D., & Llanes, A. (2020). Consequences and mitigation strategies of heat stress for sustainability of soybean (Glycine max L. Merr.) Production under the Changing Climate. In Plant Stress Physiology. IntechOpen. https://doi.org/10.5772/intechopen.92098.
  • Sadiq Khan, M., Ullah, S., Sun, T., Rehman, A. U. R., & Chen, L. (2020). Land-use/land-cover changes and its contribution to urban heat Island: A Case Study of Islamabad, Pakistan. Sustainability, 12(9), 3861. https://doi.org/10.3390/su12093861
  • Safder, Q. (2019). Assessment of urbanization and urban sprawl analysis through remote sensing and GIS: A case study of Faisalabad, Punjab, Pakistan. The International Journal of Academic Research in Business & Social Sciences, 9(4). https://doi.org/10.6007/IJARBSS/v9-i4/5811
  • Sahana, M., Ahmed, R., & Sajjad, H. (2016). Analyzing land surface temperature distribution in response to land use/land cover change using split window algorithm and spectral radiance model in sundarban biosphere reserve, India. Modeling Earth Systems and Environment, 2(2), 81. https://doi.org/10.1007/s40808-016-0135-5
  • Saha, A., Patil, M., Goyal, V. C., & Rathore, D. S. (2018). Assessment and impact of soil moisture index in agricultural drought estimation using remote sensing and GIS techniques. Multidisciplinary Digital Publishing Institute Proceedings, 7(1), 2.
  • Saleem, M. S., Ahmad, S. R., & Javed, M. A. (2020). Impact assessment of urban development patterns on land surface temperature by using remote sensing techniques: A case study of Lahore, Faisalabad and Multan district. Environmental Science and Pollution Research, 27(32), 39865–39878. https://doi.org/10.1007/s11356-020-10050-5
  • Sinha, P., Kumar, L., & Reid, N. (2012). Three-date landsat thematic mapper composite in seasonal land-cover change identification in a mid-latitudinal region of diverse climate and land use. Journal of Applied Remote Sensing, 6(1), 063595. https://doi.org/10.1117/1.JRS.6.063595
  • Tan, J., Yu, D., Li, Q., Tan, X., & Zhou, W. (2020). Spatial relationship between land-use/land-cover change and land surface temperature in the Dongting Lake area, China. Scientific Reports, 10(1), 1–9. https://doi.org/10.1038/s41598-020-66168-6
  • Tariq, S., Mubeen, M., Hammad, H. M., Jatoi, W. N., Hussain, S., Farid, H. U., & Fahad, S. (2023). Mitigation of climate change through carbon farming. In Climate change impacts on agriculture: Concepts, issues and policies for developing countries (pp. 381–391). Springer International Publishing. https://doi.org/10.1007/978-3-031-26692-8_22.
  • Ullah, S., Tahir, A., Akbar, T., Hassan, Q., Dewan, A., Khan, A., & Khan, M. (2019). Remote sensing-based quantification of the relationships between land use land cover changes and surface temperature over the lower Himalayan region. Sustainability, 11(19), 5492. https://doi.org/10.3390/su11195492
  • Usman, M., Liedl, R., Shahid, M. A., & Abbas, A. (2015). Land use/land cover classification and its change detection using multi-temporal MODIS NDVI data. Journal of Geographical Sciences, 25(12), 1479–1506. https://doi.org/10.1007/s11442-015-1247-y
  • Waleed, M., Mubeen, M., Ahmad, A., Habib-Ur-Rahman, M., Amin, A., Farid, H. U., Hussain, S., Ali, M., Qaisrani, S. A., Nasim, W., Javeed, H. M. R., Masood, N., Aziz, T., Mansour, F., & EL Sabagh, A. (2022). Evaluating the efficiency of coarser to finer resolution multispectral satellites in mapping paddy rice fields using GEE implementation. Scientific Reports, 12(1), 13210. https://doi.org/10.1038/s41598-022-17454-y
  • Xu, L., Li, B., Yuan, Y., Gao, X., Zhang, T., & Sun, Q. (2016). Detecting different types of directional land cover changes using MODIS NDVI time series dataset. Remote Sensing, 8(6), 495. https://doi.org/10.3390/rs8060495
  • Yamamoto, Y., & Ishikawa, H. (2020). Influence of urban spatial configuration and sea breeze on land surface temperature on summer clear sky days. Urban Climate, 31, 100578. https://doi.org/10.1016/j.uclim.2019.100578
  • Yang, X., Yang, Q., Zhu, H., Wang, L., Wang, C., Pang, G., Du, C., Mubeen, M., Waleed, M., & Hussain, S. (2023). Quantitative evaluation of soil water and wind erosion rates in Pakistan. Remote Sensing, 15(9), 2404. https://doi.org/10.3390/rs15092404
  • Yuan, X., Longhui, L., Xi, C., & Hao, S. (2015). Effects of precipitation intensity and temperature on NDVI-based grass change over Northern China during the period from 1982 to 2011. Remote Sensing, 7(8), 10164–10183. https://doi.org/10.3390/rs70810164
  • Zahoor, S. A., Ahmad, S., Ahmad, A., Wajid, A., Khaliq, T., Mubeen, M., Hussain, S., Din, M. S. U., Amin, A., Awais, M., & Nasim, W. (2019). Improving water use efficiency in agronomic crop production. In Agronomic crops (pp. 13–29). Springer. https://doi.org/10.1007/978-981-32-9783-8_2.
  • Zaidi, S. M., Akbari, A., Abu Samah, A., Kong, N. S., Gisen, A., & Isabella, J. (2017). Landsat-5 time series analysis for land use/land cover change detection using NDVI and semi-supervised classification techniques. Polish Journal of Environmental Studies, 26(6), 2833–2840. https://doi.org/10.15244/pjoes/68878
  • Zhang, Z., Liu, S., Wei, J., Xu, J., Guo, W., Bao, W., Jiang, Z., & Zhu, L. (2016). Mass change of glaciers in muztag ata–KongurTagh, Eastern Pamir, China from 1971/76 to 2013/14 as derived from remote sensing data. PLoS One, 11(1), e0147327. https://doi.org/10.1371/journal.pone.0147327
  • Zoungrana, B., Conrad, C., Amekudzi, L., Thiel, M., Da, E., Forkuor, G., & Löw, F. (2015). Multi-temporal landsat images and ancillary data for land use/cover change (LULCC) detection in the Southwest of Burkina Faso, West Africa. Remote Sensing, 7(9), 12076–12102. https://doi.org/10.3390/rs70912076
  • Zoungrana, B. J., Conrad, C., Thiel, M., Amekudzi, L. K., & Da, E. D. (2018). MODIS NDVI trends and fractional land cover change for improved assessments of vegetation degradation in Burkina Faso, West Africa. Journal of Arid Environments, 153, 66–75. https://doi.org/10.1016/j.jaridenv.2018.01.005