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Liu R, Li L, Guo L, Jiao L, Wang Y, Cao L, Wang Y. Multi-scenario simulation of ecological risk assessment based on ecosystem service values in the Beijing-Tianjin-Hebei region. ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 194:434. [PMID: 35575942 DOI: 10.1007/s10661-022-10086-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Accepted: 05/02/2022] [Indexed: 06/15/2023]
Abstract
In this study, a framework for ecological risk assessment based on ecosystem service values and risk probability was established. Remote sensing was used to estimate the value of ecosystem services at the regional scale. Considering the natural and anthropogenic factors and using the entropy weight method to assign weights, probability index was constructed. In addition, multiple scenarios based on the ordered weighted averaging (OWA) method were simulated to reduce subjective uncertainty in the assessment. The results showed that the ecosystem service values generated by the gas regulation value accounted for the largest proportion, with a ratio of 46% in the Beijing-Tianjin-Hebei region. From 2005 to 2015, the value of ecosystem services decreased, falling by 2.5 × 107 Yuan. The level of ecological risk was relatively high, with a corresponding area ratio of 32.89%. Spatially, the areas with high risk were concentrated in the southeastern areas, and areas with relatively low risk were distributed in the western and northern areas. This high risk was probably caused by urbanization which was characterized by reduction of farmland and increase in impervious surface. Multi-scenario simulation showed that the areas of unstable ecological risk zones covered 30% and were mainly concentrated in the surroundings of developing cities. In areas of unstable risk distribution, the relationship between development and protection should be considered. This framework increases the reliability and practicability of ecological risk assessment results and has potential application value for regional risk control in the context of urbanization.
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Affiliation(s)
- Ruimin Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Lin Li
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Lijia Guo
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Lijun Jiao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Yifan Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Leiping Cao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Yue Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
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Retrieval of DTM under Complex Forest Stand Based on Spaceborne LiDAR Fusion Photon Correction. REMOTE SENSING 2022. [DOI: 10.3390/rs14010218] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The new generation of satellite-borne laser radar Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) data has been successfully used for ground information acquisition. However, when dealing with complex terrain and dense vegetation cover, the accuracy of the extracted understory Digital Terrain Model (DTM) is limited. Therefore, this paper proposes a photon correction data processing method based on ICESat-2 to improve the DTM inversion accuracy in complex terrain and high forest coverage areas. The correction value is first extracted based on the ALOS PALSAR DEM reference data to correct the cross-track photon data of ICESat-2. The slope filter threshold is then selected from the reference data, and the extracted possible ground photons are slope filtered to obtain accurate ground photons. Finally, the impacts of cross-track photon and slope filtering on fine ground extraction from the ICESat-2 data are discussed. The results show that the proposed photon correction and slope filtering algorithms help to improve the extraction accuracy of forest DTM in complex terrain areas. Compared with the forest DTM extracted without the photon correction and slope filtering methods, the MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) are reduced by 51.90~57.82% and 49.37~53.55%, respectively. To the best of our knowledge, this is the first study demonstrating that photon correction can improve the terrain inversion ability of ICESat-2, while providing a novel method for ground extraction based on ICESat-2 data. It provides a theoretical basis for the accurate inversion of canopy parameters for ICESat-2.
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