Impacts of tourism on LULC and LST dynamics in district Buner and Shangla, Pakistan DOI Creative Commons
Waheed Ullah, Khalid Ahmad, Adnan Ahmad Tahir

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 18, 2025

Tourism activities are changing the global landscape pattern. This study attempted to estimate changes in Land Use Cover (LULC) and Surface Temperature (LST) District Buner Shangla, Khyber Pakhtunkhwa (KPK), Pakistan, specifically its tourist spots. Using remote sensing data from satellites (1990–2020) future projections (2035–2050), we applied Artificial Neural Network (ANN) Cellular Automata Markov (CA-Markov) models examine past LULC LST dynamics across two districts including four major spots (Shangla Top as spot one (TS1), Bar Puran (TS2), Shahida Sar (TS3), Daggar (TS4). The classification for whole area indicates that built-up agricultural areas increased with a net change of +0.8% +3.2% Shangla districts, respectively. highest mean was found areas. simulation results indicate an expansion 4.5% 5.8% total areas, above 31 °C will cover 76% 88% 2035 2050, conversion is driven by tourism activities, causing urban heat island effects (UHIs), environmental degradation. analysis shows at while (28 °C) (2035–2050) show TS4 would have (5.67%), (31 65.23 82.20%. These findings provide essential understandings developing long-term policies meant moderate impact region.

Language: Английский

Impacts of tourism on LULC and LST dynamics in district Buner and Shangla, Pakistan DOI Creative Commons
Waheed Ullah, Khalid Ahmad, Adnan Ahmad Tahir

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 18, 2025

Tourism activities are changing the global landscape pattern. This study attempted to estimate changes in Land Use Cover (LULC) and Surface Temperature (LST) District Buner Shangla, Khyber Pakhtunkhwa (KPK), Pakistan, specifically its tourist spots. Using remote sensing data from satellites (1990–2020) future projections (2035–2050), we applied Artificial Neural Network (ANN) Cellular Automata Markov (CA-Markov) models examine past LULC LST dynamics across two districts including four major spots (Shangla Top as spot one (TS1), Bar Puran (TS2), Shahida Sar (TS3), Daggar (TS4). The classification for whole area indicates that built-up agricultural areas increased with a net change of +0.8% +3.2% Shangla districts, respectively. highest mean was found areas. simulation results indicate an expansion 4.5% 5.8% total areas, above 31 °C will cover 76% 88% 2035 2050, conversion is driven by tourism activities, causing urban heat island effects (UHIs), environmental degradation. analysis shows at while (28 °C) (2035–2050) show TS4 would have (5.67%), (31 65.23 82.20%. These findings provide essential understandings developing long-term policies meant moderate impact region.

Language: Английский

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