Remote Sensing Monitoring and Evaluation of Water Source Environmental Quality in Sanya

We addressed rising drinking water risks in tropical tourism catchments by selecting Sanya as a representative case and developing an integrated 10–16 m remote sensing framework (Sentinel-2, GF-1) with a fuzzy evaluation, combining NDVI, WET, and NDBSI, K–T + NDVI eutrophication mapping, and event-sensitive RUSLE (30 m DEM, nonlinear LS, monthly NDVI-driven C, localized R). Land use mapping shows orchards at 736.46 km2 (38.37%) and tourism land at 2.64% (mostly golf), with 86.52% overall accuracy (Kappa 0.84). Basin-wide, 91% of the area experiences slight–mild erosion, intensified near reservoirs; relative to forests (FVC > 80%), orchards (FVC 60–70%) have a 3.2× higher median erosion risk (IQR 2.8–3.6, 95% CI 2.7–3.7). On 10–25° slopes during flood seasons, orchard pesticide/nutrient runoff indices rise 28–46%, and in the Dalong watershed, high-erosion orchard pixels co-locate with pesticide residues by 62% (95% CI 58–66%). Tourism is associated with elevated nearshore chlorophyll-a (Chl-a); the area is generally mesotrophic (0.25–0.75 mg/L), with localized nearshore hotspots > 1.0 mg/L; across monthly composites, nearshore Chl-a exceeds center waters by 130–210%, and in the Dalong Reservoir, the shoreline-to-center ratio is 2.3–3.1 (median 2.7, 95% CI 2.1–3.3) during 2023–2024 flood seasons. Overall, this source-to-sink framework supports forward-looking governance of drinking water sources under dual monsoon and tourism pressures.

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Publication Details

Journal
Urban Science
Published
2025-09-16
DOI
https://doi.org/10.3390/urbansci9090376
Primary Topic
Remote-Sensing Image Classification
Type
article
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article

Remote Sensing Monitoring and Evaluation of Water Source Environmental Quality in Sanya

Bo Zhong, Changlong Li, Dongping Xu, Junjun Wu
Urban Science
Remote-Sensing Image Classification
article

Remote Sensing Monitoring and Evaluation of Water Source Environmental Quality in Sanya

Bo Zhong, Changlong Li, Dongping Xu, Junjun Wu
article en

Abstract

We addressed rising drinking water risks in tropical tourism catchments by selecting Sanya as a representative case and developing an integrated 10–16 m remote sensing framework (Sentinel-2, GF-1) with a fuzzy evaluation, combining NDVI, WET, and NDBSI, K–T + NDVI eutrophication mapping, and event-sensitive RUSLE (30 m DEM, nonlinear LS, monthly NDVI-driven C, localized R). Land use mapping shows orchards at 736.46 km2 (38.37%) and tourism land at 2.64% (mostly golf), with 86.52% overall accuracy (Kappa 0.84). Basin-wide, 91% of the area experiences slight–mild erosion, intensified near reservoirs; relative to forests (FVC > 80%), orchards (FVC 60–70%) have a 3.2× higher median erosion risk (IQR 2.8–3.6, 95% CI 2.7–3.7). On 10–25° slopes during flood seasons, orchard pesticide/nutrient runoff indices rise 28–46%, and in the Dalong watershed, high-erosion orchard pixels co-locate with pesticide residues by 62% (95% CI 58–66%). Tourism is associated with elevated nearshore chlorophyll-a (Chl-a); the area is generally mesotrophic (0.25–0.75 mg/L), with localized nearshore hotspots > 1.0 mg/L; across monthly composites, nearshore Chl-a exceeds center waters by 130–210%, and in the Dalong Reservoir, the shoreline-to-center ratio is 2.3–3.1 (median 2.7, 95% CI 2.1–3.3) during 2023–2024 flood seasons. Overall, this source-to-sink framework supports forward-looking governance of drinking water sources under dual monsoon and tourism pressures.

Urban ScienceVol. 9(9)
Chinese Academy of Sciences (CN), Guangzhou Vocational College of Science and Technology (CN), Aerospace Information Research Institute (CN), Guangzhou College of Commerce
Openalex Percentile: Top 63%
Remote-Sensing Image Classification
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Remote Sensing Monitoring and Evaluation of Water Source Environmental Quality in Sanya — Bo Zhong, Changlong Li, et al. · Urban Science (2025) | TGRS Research Map | TGRS