Predicting Microscale Land Use/Land Cover Changes Using Cellular Automata Algorithm on the Northwest Coast of Peninsular Malaysia

Rahaman, Zullyadini A.; Kafy, Abdulla Al; Faisal, Abdullah-Al-; Rakib, Abdullah Al; Jahir, Dewan Md. Amir; Fattah, Md. Abdul; Kalaivani, S.; Rathi, R.; Mallik, Saumik; Rahman, Muhammad Tauhidur

doi:10.1007/s41748-022-00318-w

Cited by 27 publications

(7 citation statements)

References 48 publications

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“…Spatial analysis of the multi-temporal LULC map of Hai Duong Province shows significant changes over the past 30 years . LULC changes occur continuously and are influenced by many This suggests that the LULC changes in the study area may reflect expansion of land used for economic development and urbanization, including the construction of new infrastructure, such as roads, railways, bridges, and industrial zones (Rahaman et al, 2022;Thien et al, 2023a). In addition, climate change may contribute to changes in areas covered by vegetation, barren areas, and bodies of water (Ahmad et al, 2014;Mahmoud and Gan, 2018;Sadiq Khan et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Monitoring Land Surface Temperature Relationship to Land Use and Land Cover in Hai Duong Province, Vietnam

Thien,

Ovsepyan,

Phuong

2024

Environ. Nat. Resour. J.

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This study utilised remote sensing data and ArcGIS 10.8 software to evaluate changes in land use and land cover (LULC) and their effects on land surface temperature (LST) in Hai Duong Province, Vietnam, from 1992 to 2022. Landsat satellite data were pre-processed and classified using supervised methods for the years 1992, 2010, and 2022. In 1992, vegetation cover accounted for 57.89% of land cover, increasing to 84.49% in 2010, but then decreasing again to 66.67% in 2022. In contrast, the built-up area consistently increased, from 2.88% in 1992 to 29.35% in 2022, as most of the barren land present in 1992 became built-up area in 2022. The LST values were calculated from the thermal bands for the years 1992, 2010, and 2022 and ranged from 16.09°C to 34.27°C, 17.04°C to 36.74°C, and 11.03°C to 28.44°C, respectively. In addition, the Normalized Difference Vegetation Index (NDVI) values were calculated using the near-infrared band and the red band, with values ranging from -0.40 to 0.70 over the study period. A linear regression analysis indicated a shift in the correlation between NDVI and LST from positive to negative. This study highlights the significant transformation that occurred in Hai Duong Province due to rapid population density increases, urban growth and infrastructure development, leading to a decline in greenery. These LULC changes can cause severe environmental damage. These research findings will assist policymakers in formulating management strategies and sustainable land-use plans to minimize potential harm and promote sustainable development in the area.

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Section: Discussionmentioning

confidence: 99%

Monitoring Land Surface Temperature Relationship to Land Use and Land Cover in Hai Duong Province, Vietnam

Thien,

Ovsepyan,

Phuong

2024

Environ. Nat. Resour. J.

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“…They were speculating on the future of LULC in light of social and environmental variables and calculating the magnitude of the LULC shift and any potential effects on the regional pattern. Setting up the circumstances for a future LULC intensity [53].…”

Section: Discussionmentioning

confidence: 99%

“…The work by Rahaman and colleagues presented here evaluated the capacity of the SVM and CA algorithms to track (2005-2020) and forecast (2025 and 2035) the future LULC change in Penang, Malaysia. The LULC classes were estimated using Landsat photos, and the CA model was validated using Pearson chi-square values [53].…”

Section: Related Workmentioning

confidence: 99%

Modeling Land Use Change in Sana’a City of Yemen with MOLUSCE

Alshari

Gawali

2022

Journal of Sensors

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This study provided insight into the size of the difference between the actual and predicted changes in Landsat 8 satellite imagery for the case study Sana’a of Yemen. The LULC classification was created using data available in 2005, 2010, 2015, and 2020. It used the MOLUSCE tool for predicting land changes for the predicted for 2010, 2015, 2020, 2025, and 2030. The objectives of this study are 1) To compare the actual and predicted land changes in 2010,2015 and 2020. 2) To analyze and verify the tool’s performance (MOLUSCE). 3) To identify the size of effect which evented land changes in 2015 on land changes in 2020,2025 and 2030. The results were: 1/the effects of land changes in 2010 showed the accuracy and reliability of MOLUSCE for predicting land changes due to the low difference between the actual and predicted 2010 before the conflict in the region. 2/the actual changes for 2015 were negative and did not support the logical trend toward progress where it is natural that the human element progresses to the increasing construction. 3/identify prediction changes for (2020,2025,2030) are affected by events conflict, which showed in the results of the 2015 images.

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“…Considering the simulated years 2030 and 2040, in 50 years (1990-2040), built-up areas and water bodies will increase by 9.32% and 4.47%, respectively, with a significant decrease in dense vegetation, agricultural land, and other land uses by 5.65%, 10.58%, and 0.34%, respectively (Figure 15). Other South Asian cities' urban areas area grew in the same way over the past two to three decades, with the loss of vegetation cover, such as Delhi, Patna, Lucknow, Kolkata, and Mangalore in India [21,23,80,81], or Cumillia, Dhaka, and Rajsahi of Bangladesh [69,71,82], and Kathmandu of Nepal [83]. Several things led to urbanisation, such as the growth of the population, the political and economic climate, and the movement of people from rural areas into cities, which leads to extensive construction work for the development of infrastructure at a higher rate, and population density also keeps on increasing in northeastern parts of India (Jyotishman, et al, 2011) [84].…”

Section: Change In Lulcmentioning

confidence: 99%

Impacts of Land Use and Land Cover Changes on Land Surface Temperature over Cachar Region, Northeast India—A Case Study

Ashwini

Sil

2022

Sustainability

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The promptness of industrialisation and expanding urbanisation to achieve targets of economics are resulting in the transfiguration of permeable surfaces into impervious ones through LULC adaptation, leaving a herculean footprint on the ecosystem. The LULC escalates land surface temperature (LST), which further stimulates urban heat islands (UHIs), ultimately remaining in tune with high levels of air pollution, energy use, and corresponding health hazards. The present evaluation first used Landsat TM/OLI satellite data to identify the labyrinth of the LULC rotation and, secondly, gauged its effects on the LST in the Cachar district of Assam, India, for the years 1990, 2000, 2010, and 2020. It embraces Cellular Automata (CA) and GIS methodologies to pull out the urbanization pattern and its ramifications in various LULC brackets of Cachar, India. It also embraces spatiotemporal LULC monitoring (1990–2020) and urban growth modelling (2030–2040). From the period 1990 to 2020, satellite-based LULC showed a net urban expansion of 269.43 km2 (7.13% increase). Some correlations were developed to show the relationship between spatial indices such as NDVI, NDBI, and NDWI with Land Surface Temperature (LST). Resultantly, a positive relation exists between LST and NDBI, but a negative correlation prevails between LST and NDVI, as well as NDWI. This evaluation will be of service to urban and environmental planners, providing them with detailed knowledge on how land cover is changing uniquely in northeast India.

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Predicting Microscale Land Use/Land Cover Changes Using Cellular Automata Algorithm on the Northwest Coast of Peninsular Malaysia

Cited by 27 publications

References 48 publications

Monitoring Land Surface Temperature Relationship to Land Use and Land Cover in Hai Duong Province, Vietnam

Monitoring Land Surface Temperature Relationship to Land Use and Land Cover in Hai Duong Province, Vietnam

Modeling Land Use Change in Sana’a City of Yemen with MOLUSCE

Impacts of Land Use and Land Cover Changes on Land Surface Temperature over Cachar Region, Northeast India—A Case Study

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