Landsat 8‐observed water quality and its coupled environmental factors for urban scenery lakes: A case study of West Lake

Abstract

Urban scenery lakes are not only popular sites for recreation, water sport, and visit of citizens and tourists, but also function for urban water drainage and storage, and hence, their water quality is a sensitive indicator of urban aquatic environment. This study focused on two important water quality parameters, TSM (total suspended matter) and CDOM (colored dissolved organic matter) in West Lake, a world famous urban scenery lake in Hangzhou, China. Based on Landsat 8 images, remote sensing inversion models for TSM and CDOM in West Lake were compared and the best ones were determined using exponential functions and green/red band ratios. Results show that the accuracy of TSM models is relatively better while CDOM models performed relatively poor, indicating that empirical estimation of CDOM for inland complex waters remains a challenge. The Landsat 8‐derived results in West Lake from 2013 to 2017 show that TSM presented diverse distributions in different sections and months/seasons—the relatively high‐concentration TSM was usually found in the north section and during spring festivals, holidays and summer vacations. These spatiotemporal patterns demonstrate the evidence that TSM in West Lake was highly linked to anthropogenic impacts, such as tourist visits, commercial activities, and urban drainage projects in Hangzhou. The relations between TSM and precipitation were also examined, but no significant correlations were found, showing that the impacts of rainfall on water quality of urban lakes are complicated, and using remote sensing for such studies is still with limitations. Practitioner points Water quality (TSM and CDOM) of urban scenery lakes is highly influenced by urban tourist activities. Precipitation and TSM have not found significant relations in urban scenery lakes. An exponential model based on Landsat 8’s bands 3 and 4 is good for TSM estimation. CDOM estimation remains a challenge for water color remote sensing in urban scenery lakes.

Uncertainty Analysis of Remote Sensing Pretreatment for Biomass Estimation on Landsat OLI and Landsat ETM+

“…In the current study, the uncertainty in both models significantly decreased, indicating that the atmospheric correction effectively improved estimation accuracy and reduced the uncertainty of biomass estimation using Landsat. Zhu et al [91] proposed that improved atmospheric correction and surface reflectance removal schemes may decrease the uncertainty generated by water surface. Based on our results, we conclude that the improved atmospheric correction method is the most effective for further reduction of uncertainty during biomass estimation.…”

Sentinel 2 analysis of turbidity retrieval models in inland water bodies: The case study of Jordanian dams

“…[36,37] Two-band ratio algorithms used the ratio between green and red, [38][39][40] blue and red, [41] NIR and vegetation rededge (VRE), [42] and NIR and red. [43] In this work, the previously developed algorithms found in the literature were adopted to the corresponding Sentinel 2 bands.…”

Identificación del marco jurídico en protección al ambiente y responsabilidad social en México

“…Los modelos de trasferencia de radiación implementados en teledetección son factibles económicamente para el estudio del comportamiento de las superficies acuáticas a largo plazo ( Sandoval-Rivera et al, 2022;Zhu et al, 2020). Estas, proporcionan información sobre cambios en las superficies acuáticas, rasgos hidrológicos de superficies en los entonos de agua permanente, periodos de deserción y contaminación hídrica (Cavallo et al, 2021;Upadhyay & Patel, 2022;Yang et al, 2022).…”