Analysis on ecological status and spatial–temporal variation of Tamarix chinensis forest based on spectral characteristics and remote sensing vegetation indices

Wang, Jin; Han, Ping; Zhang, Yanhua; Li, Jinyu; Xu, Linxu; Shen, Xue; Yang, Zhiyong; Xu, Shixiao; Li, Guangxue; Chen, Feiyong

doi:10.1007/s11356-022-18678-1

Cited by 6 publications

(2 citation statements)

References 34 publications

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“…With the continuous development of society, there is gradually more attention on natural eco-environment quality and higher requirements on the timeliness, continuance, standard, scale and technical specification of the eco-environment quality monitoring and evaluation. Without doubt, this also offers opportunities for the application of remote sensing technology in the eco-environment quality monitoring and evaluation [1]. Until now, the objectives of the environmental quality monitoring and evaluation most belong to large to medium scale, but less on small scale, which regards the partial area as a unit.…”

Section: Introductionmentioning

confidence: 99%

Eco-Environmental Effect Evaluation of Tamarix chinesis Forest on Coastal Saline-Alkali Land Based on RSEI Model

Wang

Chen

2022

Sensors

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Taking representative Tamarix chinensis forest in the national-level special protection zone for ocean ecology of Changyi city in Shandong province of China as the objective, this research studied how to use remote sensing technology to evaluate natural eco-environment and analyze spatiotemporal variation. In the process of constructing the index system of ecological environment effect evaluation based on RSEI (Remote Sensing Ecological Index) model, AOD (Aerosol Optical Depth), Salinity, Greenness, Wetness, Heat and Dryness, which can represent the ecological environment of the reserve, were selected as the corresponding indexes. In order to accurately obtain the value of the RSEI of the study area and to retain the information of the original indexes to the greatest extent, the SPCA (spatial principal components analysis) method was applied in this research. Finally, the RSEI was applied to evaluate the ecological and environmental effects and to analyze the spatial characteristics and spatiotemporal evolution of the study area. The results not only provide scientific evidence and technical guidance for the protection, transformation and management of the Tamarix chinensis forest in the protection zone but also push the development of the universal model of the ecological environment quality with a remote sensing evaluation index system at a regional scale.

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Section: Introductionmentioning

confidence: 99%

Eco-Environmental Effect Evaluation of Tamarix chinesis Forest on Coastal Saline-Alkali Land Based on RSEI Model

Wang

Chen

2022

Sensors

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“…Several remote sensing indices have been developed to quantify ecological conditions (Pettorelli et al, 2005;Jiang et al, 2021;Pravalie et al, 2022). Among them, the normalized difference vegetation index (NDVI) and other vegetation indices are the single indexes most commonly used in ecological studies (Stefanov and Netzband, 2005;Wang et al, 2022). There are also several other single indicators that perform well in eco-environmental assessment, such as the permanent vegetation fraction (PVF; (Ivits et al, 2009), which has been used to assess the ecological status and dynamics of the Andalusian riparian zone.…”

Section: Introductionmentioning

confidence: 99%

Ecological environmental quality assessment of Chinese estuarine wetlands during 2000–2020 based on a remote sensing ecological index

et al. 2022

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Coastal estuarine wetlands are important transition zones between rivers and oceans and are extremely rich in biodiversity. In recent years in China, large-scale reclamation and development of coastal cities have imposed serious pressures on coastal ecosystems. Thus, assessing the ecological quality of estuarine wetlands is extremely important for sustainable development. Our study focuses on four typical estuarine wetlands at the mouths of the Yangtze, Yellow, Liaohe and PearRivers. Their ecological quality between 2000 and 2020 was assessed using a remote sensing ecological index (RSEI), which was derived from several remote sensing indexes processed via the online Google Earth Engine platform. From 2000 to 2020, the RSEIs of coastal wetland increased from 0.42 to 0.63 in the Liao River estuary, 0.27 to 0.45 in the Pearl River estuary and from 0.47 to 0.54 in the Yangtze River estuary, and decreased from 0.56 to 0.49 in the Yellow River estuary. The spatial distribution in ecological environmental quality was significantly clustered. High-high clusters occurred mainly in areas of lush vegetation, while low-low clusters were mostly found in built-up areas or coastal zones. Aquacultural and built-up areas had negative impacts on the ecological environment, while vegetation cover had a positive influence. The quality of the ecological environment within these wetlands has gradually improved due to the environmental management policies of national and local governments. This approach to evaluating the ecological quality of estuarine wetlands using the RSEI and Google Earth Engine provides critical information to inform sustainable development policy.

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Using remote sensing data to evaluate the ecological restoration in Taiyuan from the SDGs perspective

Yuan,

Jia,

Xia

et al. 2023

International Journal of Digital Earth

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Analysis on ecological status and spatial–temporal variation of Tamarix chinensis forest based on spectral characteristics and remote sensing vegetation indices

Cited by 6 publications

References 34 publications

Eco-Environmental Effect Evaluation of Tamarix chinesis Forest on Coastal Saline-Alkali Land Based on RSEI Model

Eco-Environmental Effect Evaluation of Tamarix chinesis Forest on Coastal Saline-Alkali Land Based on RSEI Model

Ecological environmental quality assessment of Chinese estuarine wetlands during 2000–2020 based on a remote sensing ecological index

Using remote sensing data to evaluate the ecological restoration in Taiyuan from the SDGs perspective

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