Evidence map›Paper›PMID 39987173›Full record

ArticleScientific reports2025

Detection of illegal wells using advanced GIS analysis through Landsat 8 and Sentinel-2 image fusion in Bastam, Iran.

Ardeshir Sassani, Behnaz Bigdeli, Seyed Fazlolah Saghravani

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ardeshir SassaniFaculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran. ardeshirsassani@shahroodut.ac.ir.
Behnaz BigdeliFaculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran.
Seyed Fazlolah SaghravaniFaculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Agricultural wellsEuclidean distance analysisGIS spatial analysisKernel density estimation (KDE)Satellite image fusionUnauthorized wells detection

Identifiers

PMID39987173
PMCPMC11846939

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.