Detection of illegal wells using advanced GIS analysis through Landsat 8 and Sentinel-2 image fusion in Bastam, Iran
Abstract Identifying unauthorized agricultural wells is a critical issue for the sustainable management of water resources. Unregulated groundwater extraction through illegal wells has resulted in significant environmental challenges, including declining water tables and ecosystem degradation. This...
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Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-91188-5 |
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| author | Ardeshir Sassani Behnaz Bigdeli Seyed Fazlolah Saghravani |
| author_facet | Ardeshir Sassani Behnaz Bigdeli Seyed Fazlolah Saghravani |
| author_sort | Ardeshir Sassani |
| collection | DOAJ |
| description | Abstract Identifying unauthorized agricultural wells is a critical issue for the sustainable management of water resources. Unregulated groundwater extraction through illegal wells has resulted in significant environmental challenges, including declining water tables and ecosystem degradation. This study was conducted in the Bastam region of Shahroud, Iran, utilizing satellite imagery and spatial analysis techniques to address this issue. Satellite images from Landsat 8 and Sentinel-2 were fused using ENVI software, with a focus on preprocessing and image integration. Subsequently, spatial analyses, including proximity and density evaluations, were performed in ArcMap to examine the spatial distribution of wells. Three methods were compared: The weighted sum method, kernel density estimation (KDE) combined with Euclidean distance, and a hybrid approach integrating both techniques. Through technical evaluations using correlation and scatter plot analysis, the hybrid method was identified as the most effective solution. The final output of this method generated a probability map depicting the likelihood of unauthorized wells, represented by a color gradient from green to red. Green areas indicated lower probabilities of unauthorized wells, while red zones highlighted regions with higher risk. The approach was validated using resampling methods, confirming its potential as a reliable tool for identifying unauthorized wells within the study area. |
| format | Article |
| id | doaj-art-bce2cef7cffc4cbcbea57f165e61ad71 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-bce2cef7cffc4cbcbea57f165e61ad712025-08-20T03:13:17ZengNature PortfolioScientific Reports2045-23222025-02-0115111910.1038/s41598-025-91188-5Detection of illegal wells using advanced GIS analysis through Landsat 8 and Sentinel-2 image fusion in Bastam, IranArdeshir Sassani0Behnaz Bigdeli1Seyed Fazlolah Saghravani2Faculty of Civil Engineering, Shahrood University of TechnologyFaculty of Civil Engineering, Shahrood University of TechnologyFaculty of Civil Engineering, Shahrood University of TechnologyAbstract Identifying unauthorized agricultural wells is a critical issue for the sustainable management of water resources. Unregulated groundwater extraction through illegal wells has resulted in significant environmental challenges, including declining water tables and ecosystem degradation. This study was conducted in the Bastam region of Shahroud, Iran, utilizing satellite imagery and spatial analysis techniques to address this issue. Satellite images from Landsat 8 and Sentinel-2 were fused using ENVI software, with a focus on preprocessing and image integration. Subsequently, spatial analyses, including proximity and density evaluations, were performed in ArcMap to examine the spatial distribution of wells. Three methods were compared: The weighted sum method, kernel density estimation (KDE) combined with Euclidean distance, and a hybrid approach integrating both techniques. Through technical evaluations using correlation and scatter plot analysis, the hybrid method was identified as the most effective solution. The final output of this method generated a probability map depicting the likelihood of unauthorized wells, represented by a color gradient from green to red. Green areas indicated lower probabilities of unauthorized wells, while red zones highlighted regions with higher risk. The approach was validated using resampling methods, confirming its potential as a reliable tool for identifying unauthorized wells within the study area.https://doi.org/10.1038/s41598-025-91188-5Agricultural wellsEuclidean distance analysisSatellite image fusionKernel density estimation (KDE)GIS spatial analysisUnauthorized wells detection |
| spellingShingle | Ardeshir Sassani Behnaz Bigdeli Seyed Fazlolah Saghravani Detection of illegal wells using advanced GIS analysis through Landsat 8 and Sentinel-2 image fusion in Bastam, Iran Scientific Reports Agricultural wells Euclidean distance analysis Satellite image fusion Kernel density estimation (KDE) GIS spatial analysis Unauthorized wells detection |
| title | Detection of illegal wells using advanced GIS analysis through Landsat 8 and Sentinel-2 image fusion in Bastam, Iran |
| title_full | Detection of illegal wells using advanced GIS analysis through Landsat 8 and Sentinel-2 image fusion in Bastam, Iran |
| title_fullStr | Detection of illegal wells using advanced GIS analysis through Landsat 8 and Sentinel-2 image fusion in Bastam, Iran |
| title_full_unstemmed | Detection of illegal wells using advanced GIS analysis through Landsat 8 and Sentinel-2 image fusion in Bastam, Iran |
| title_short | Detection of illegal wells using advanced GIS analysis through Landsat 8 and Sentinel-2 image fusion in Bastam, Iran |
| title_sort | detection of illegal wells using advanced gis analysis through landsat 8 and sentinel 2 image fusion in bastam iran |
| topic | Agricultural wells Euclidean distance analysis Satellite image fusion Kernel density estimation (KDE) GIS spatial analysis Unauthorized wells detection |
| url | https://doi.org/10.1038/s41598-025-91188-5 |
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