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<p>This research work presents a comprehensive assessment of the Astronomical Observation Site (AOS) suitability map using fuzzy logic in a GIS-based environment for the North West Himalayan Mountain (NWHM) region. Multi-temporal climatic data from 2002 to 2022, and remote sensing (RS) data have been used to derive a total of nine selected factors, which are Elevation (EL), Slope (SL), Normalised Difference Vegetation Index (NDVI), Temperature (TEMP), Relative Humidity (RH), Precipitation (PR), Cloud Amount (CL), Aerosol Optical Depth (AOD), and Night-time Light (NTL). All the parameters were normalised using fuzzy membership functions based on their influence on Astronomical Observation (AO). Fuzzy gamma operation was adopted to utilise data uncertainty and interdependency effectively. The gamma integration was performed for nine different gamma values (range: 0–1), and gamma value 0.9 was selected for the development of the final suitability map. The resulting map was reclassified into five categories from very less, less, moderate, suitable, and very suitable, based on natural breaks, and a sixth class represents the waterbodies and permafrost. To validate the performance, a machine learning evaluation technique with the help of the Receiver Operating Characteristic (ROC) curve analysis has been taken into consideration to demonstrate high predictive accuracy for selected different gamma values. The methodology validates the existing sites and locates several unexplored, highly-potential areas for the development of AO. It highlights the effectiveness of fuzzy logic for AOS selection for planning in a complex geographic, climatic, and ecologically sensitive mountain region such as NWHM. The methodology shows flexibility and adaptability for future changes, supporting spatial decision-making.</p>

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Remote Sensing-Based Multi-Criteria Astronomical Site Suitability Mapping in the North West Himalayas

  • 期刊论文

  • 发表日期：

    2026年4月4日

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  • Sumalya Ray,
  • Jai Sukh Paul Singh,
  • Rohan Kumar,
  • Swati Sharma,
  • Md. Omar Sarif

摘要

This research work presents a comprehensive assessment of the Astronomical Observation Site (AOS) suitability map using fuzzy logic in a GIS-based environment for the North West Himalayan Mountain (NWHM) region. Multi-temporal climatic data from 2002 to 2022, and remote sensing (RS) data have been used to derive a total of nine selected factors, which are Elevation (EL), Slope (SL), Normalised Difference Vegetation Index (NDVI), Temperature (TEMP), Relative Humidity (RH), Precipitation (PR), Cloud Amount (CL), Aerosol Optical Depth (AOD), and Night-time Light (NTL). All the parameters were normalised using fuzzy membership functions based on their influence on Astronomical Observation (AO). Fuzzy gamma operation was adopted to utilise data uncertainty and interdependency effectively. The gamma integration was performed for nine different gamma values (range: 0–1), and gamma value 0.9 was selected for the development of the final suitability map. The resulting map was reclassified into five categories from very less, less, moderate, suitable, and very suitable, based on natural breaks, and a sixth class represents the waterbodies and permafrost. To validate the performance, a machine learning evaluation technique with the help of the Receiver Operating Characteristic (ROC) curve analysis has been taken into consideration to demonstrate high predictive accuracy for selected different gamma values. The methodology validates the existing sites and locates several unexplored, highly-potential areas for the development of AO. It highlights the effectiveness of fuzzy logic for AOS selection for planning in a complex geographic, climatic, and ecologically sensitive mountain region such as NWHM. The methodology shows flexibility and adaptability for future changes, supporting spatial decision-making.