Evidence map›Paper›PMID 41107354›Full record

ArticleScientific reports2025

Karst remote sensing ecological index KRSEI for monitoring ecological quality in Southwest China.

Xianwu Yang, Haoyang Tian, Yang Wang, Yamei Xue, Jingke Lv, Tingjie Wen

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

6 authors.

Xianwu YangSchool of Geographic Sciences, Xinyang Normal University, Xinyang, 464000, China. xianwu82@163.com.
Haoyang TianSchool of Geographic Sciences, Xinyang Normal University, Xinyang, 464000, China.
Yang WangPipe China Construction Project Management Company, Langfang, 065000, China.
Yamei XueSchool of Geographic Sciences, Xinyang Normal University, Xinyang, 464000, China.
Jingke LvSchool of Geographic Sciences, Xinyang Normal University, Xinyang, 464000, China.
Tingjie WenSchool of Geographic Sciences, Xinyang Normal University, Xinyang, 464000, China.

Funding

National Natural Science Foundation of China 41701449
6 · The paper itself

Abstract

Karst regions are ecologically fragile and highly sensitive to both natural and anthropogenic disturbances, necessitating accurate and quantitative assessments of ecological quality and its driving forces. This study introduces a Karst-Specific Remote Sensing Ecological Index (KRSEI), a novel model tailored to the unique environmental conditions of karst landscapes. Using Guizhou Province in Southwest China as the study area, the KRSEI was applied to MODIS remote sensing data from 2002 to 2022, and further integrated with Theil-Sen-Mann-Kendall (Sen-MK) trend analysis and an optimized parameter geographical detector to explore spatiotemporal patterns and key driving mechanisms of ecological change. The findings reveal that: (1) KRSEI achieves higher information entropy and image contrast than traditional RSEI, effectively reflecting ecological heterogeneity; (2) ecological quality remained moderately stable (KRSEI ≈ 0.6) over two decades, with regions of lower ecological status exhibiting a "rise-decline-rebound" trajectory, and 58.25% of the area showing an improving trend; and (3) vegetation cover, precipitation, and population density were identified as dominant drivers, with most factor interactions showing synergistic (bivariate enhancement) effects. This research offers a robust methodological framework for ecological monitoring in karst regions and provides scientific support for targeted ecological protection and sustainable regional development.

Indexed as

Ecological quality assessmentGeographical detectorKarst ecosystemKRSEISpatiotemporal analysis

Identifiers

PMID41107354
PMCPMC12534547

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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.