Long-time series ecological environment quality monitoring and cause analysis in the Dianchi Lake Basin, China

Ecological Indicators, Год журнала: 2023, Номер 148, С. 110084 - 110084

Опубликована: Март 5, 2023

As the core area in transformation of Kunming into an international center city, studying changes ecological environment quality and causes Dianchi Lake Basin is great significance for its future optimization landscape pattern. This study based on Google Earth Engine (GEE) platform to calculate Remote Sensing Ecological Index (RSEI) from 1990 2020. Then we used Mann-Kendall mutation detection obtain time points when significant RSEI occurred. Finally, Geodetector MGWR models were combined analyse driving factors Basin. The results show that: (1) showed increasing trend 2020, with mean value 0.49 0.52. (2) According test, years 1990, 1993, 2006, 2015, 2020 as monitoring over a long series. past 30 was mainly improved state, accounting 49.43%. deterioration areas are located northeastern part Xishan District (north Caohai Lake), southwestern Guandu District, Kunyang Town Jining northern Jincheng Shangsuan Town. (3) single factor that elevation slope have strongest influence RSEI. q-value average annual temperature has changed most, 6th 3rd place. indicates urban heat island effect expansion construction land had greater impact local recent years. multi-factor interaction test shows each enhanced after interaction. (4) regression actual scales action inconsistent, most spatial heterogeneity Percentage cropland area. Based above findings, it can provide data support planning It also provides new means integrating analysis.

Язык: Английский

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The Dynamic Monitoring and Driving Forces Analysis of Ecological Environment Quality in the Tibetan Plateau Based on the Google Earth Engine

Remote Sensing, Год журнала: 2024, Номер 16(4), С. 682 - 682

Опубликована: Фев. 14, 2024

As a region susceptible to the impacts of climate change, evaluating temporal and spatial variations in ecological environment quality (EEQ) potential influencing factors is crucial for ensuring security Tibetan Plateau. This study utilized Google Earth Engine (GEE) platform construct Remote Sensing-based Ecological Index (RSEI) examined dynamics Plateau’s EEQ from 2000 2022. The findings revealed that RSEI Plateau predominantly exhibited slight degradation trend 2022, with multi-year average 0.404. Utilizing SHAP (Shapley Additive Explanation) interpret XGBoost (eXtreme Gradient Boosting), identified natural as primary influencers on Plateau, temperature, soil moisture, precipitation variables exhibiting higher values, indicating their substantial contributions. interaction between temperature showed positive effect RSEI, value increasing rising precipitation. methodology results this could provide insights comprehensive understanding monitoring dynamic evolution amidst context change.

Язык: Английский

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Ecological security pattern based on remote sensing ecological index and circuit theory in the Shanxi section of the Yellow River Basin

Ecological Indicators, Год журнала: 2024, Номер 166, С. 112382 - 112382

Опубликована: Июль 19, 2024

Evaluating the quality and establishing an ecological network are beneficial for maintaining ecosystem health stability optimizing national spatial pattern. This study used morphological pattern analysis (MSPA) remote sensing index (RSEI) to identify sources (ESs) in Shanxi section of Yellow River Basin (SYRB). Comprehensive resistance surface is constructed corrected based on weight. The corridor was identified by Linkage Mapper tool, node barrier points were determined basis minimum cost path theory establish security (ESP) SYRB. 108 ESs identified, with a total area 34,157.42 km2. unevenness distribution obvious concentrated areas higher elevations environmental quality. We 243 corridors (ECs), totaling 3,259.44 km. main land use types ECs cultivated land, forest, grassland. Low-resistance mainly distributed central pearl-shaped basin, connecting two major source east west. high-resistance southern part which had highly fragmented at periphery. 41 pinch points, Mianshan Mountain, plays key role energy exchange between ESs. 26 overlapped ECs, obstructed landscape connectivity. A comprehensive "two zones, one belt, three corridors" ESP established, providing solid theoretical support practical guidance future sustainable development enhanced design

Язык: Английский

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Response of ecological environment quality to land use transition based on dryland oasis ecological index (DOEI) in dryland: A case study of oasis concentration area in Middle Heihe River, China

Ecological Indicators, Год журнала: 2024, Номер 165, С. 112214 - 112214

Опубликована: Июнь 7, 2024

Язык: Английский

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A new approach for the assessment of urban eco-environmental quality based on remote sensing: a case study of Herat City, Afghanistan

Journal of Spatial Science, Год журнала: 2024, Номер unknown, С. 1 - 26

Опубликована: Апрель 5, 2024

This research assesses Herat City's urban ecological degradation in 2000, 2013, and 2021 using Landsat MODIS data. A Mean Remote Sensing Ecological Index (MRESI) is developed by integrating Known Granulation Entropy (KGE) COmprehensive Distance-Based RAnking (COBRA) algorithms. Five elements are considered: humidity, greenness, heat, dryness, AOD. MRESI declined from 0.4544 to 0.4100, indicating deteriorating quality. Spatial increased six nine districts. MRSEI identified as the most representative indicator, effectively reflecting quality of city. approach offers an effective economical method for managing development spatial control.

Язык: Английский

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Advancing ecological quality assessment in China: Introducing the ARSEI and identifying key regional drivers

Ecological Indicators, Год журнала: 2024, Номер 163, С. 112109 - 112109

Опубликована: Май 15, 2024

Accurate analysis of regional ecological quality and its drivers is crucial for the sustainable development human society. The remote sensing eco-index (RSEI) has been widely used to monitor changes in many countries or regions, but it ignores problem declining air caused by economic population growth. Consequently, an improved remotely sensed index (ARSEI) was developed evaluate China's environment incorporating aerosol optical depth (AOD) into system. Additionally, a random forest regression model rank importance indexes ARSEI. Furthermore, geographical detector utilized assess impact natural socioeconomic factors on spatial heterogeneity ARSEI six geographic regions China, identifying their primary drivers. research findings revealed following: (1) There are similarities differences order indicators across regions. (2) values significantly increased 24.70% areas, primarily Northeast Plain, Loess Plateau, Tarim Basin, while they decreased 5.35% mainly Qinghai-Tibetan northern part Tianshan Mountains, eastern coastal cities, central urban agglomerations. (3) Rainfall vegetation conditions main affecting environmental Three-North region (XB, HB DB). In southern (XN, ZN HD) cover land use change, density PM2.5 concentrations were greater than influence climate factors. interaction factors, including PM2.5, had results this study can provide data support coordinated ecosystems socioeconomics.

Язык: Английский

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Relationship of construction land expansion and ecological environment changes in the Three Gorges reservoir area of China

Ecological Indicators, Год журнала: 2023, Номер 157, С. 111209 - 111209

Опубликована: Ноя. 11, 2023

With the rapid development of urbanization, disorderly construction land expansion takes up too much ecological space, leading to exacerbation regional internal ecosystem. Therefore, exploring coordinated relationship between and environment change has become a key issue for sustainable development. Based on remote sensing technology, evaluation system in Three Gorges Reservoir area was constructed. The spatial–temporal evolution from 1995 2020 their coordination were analyzed, they divided into coupling types. research shows following findings: Firstly, year 2020, comprehensive value reached 0.8635, an increase more than 8 times compared 1995, indicating significant trend expansion. Secondly, remained 0.4 0.6 continued good direction. And improving indicators expanded difference quality Area. Thirdly, coupled model increased 0.0534 0.7951 which is low-level slow-growing state, social economic does not completely depend destroying quality. Finally, three types are divided: protection type, tandem consumable type. Differentiated regulation strategies suggestions also proposed.

Язык: Английский

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Evolution and Spatiotemporal Response of Ecological Environment Quality to Human Activities and Climate: Case Study of Hunan Province, China

Remote Sensing, Год журнала: 2024, Номер 16(13), С. 2380 - 2380

Опубликована: Июнь 28, 2024

Human beings are facing increasingly serious threats to the ecological environment with industrial development and urban expansion. The changes in environmental quality (EEQ) their driving factors attracting increased attention. As such, simple effective monitoring processes must be developed help protect environment. Based on RSEI, we improved data dimensionality reduction method using coefficient of variation method, constructing RSEI-v Landsat MODIS data. RSEI-v, quantitatively monitored characteristics EEQ Hunan Province, China, its spatiotemporal response human activities climate factors. results show following: (1) RSEI perform similarly characterizing quality. calculated is a positive indicator EEQ, but not. (2) high values concentrated eastern western mountainous areas, whereas low central plains. (3) A total 49.40% area was experiencing substantial areas significant decreases (accounting for 2.42% area) were vicinity various cities, especially Changsha–Zhuzhou–Xiangtan agglomeration. increases 16.97% forests. (4) decreases, accounting more than 60% area, mainly affected by activities. surrounding Changsha Hengyang experienced noteworthy EEQ. where precipitation temperature areas. This study provides valuable reference protection.

Язык: Английский

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Spatiotemporal analysis of ecological benefits coupling remote sensing ecological index and ecosystem services index

Ecological Indicators, Год журнала: 2024, Номер 166, С. 112420 - 112420

Опубликована: Авг. 2, 2024

Язык: Английский

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Analysis of Ecological Environment in the Shanxi Section of the Yellow River Basin and Coal Mining Area Based on Improved Remote Sensing Ecological Index

Sensors, Год журнала: 2024, Номер 24(20), С. 6560 - 6560

Опубликована: Окт. 11, 2024

As a major coal-producing area, the Shanxi section of Yellow River Basin has been significantly affected by coal mining activities in local ecological environment. Therefore, an in-depth study evolution this region holds great scientific significance and practical value. In study, Basin, including its planned was selected as research subject. An improved remotely sensed index model (NRSEI) integrating (RSEI) net primary productivity (NPP) vegetation constructed utilizing Google Earth Engine platform. The NRSEI time series data from 2003 to 2022 were calculated, Sen + Mann-Kendall analysis method employed comprehensively assess environment quality evolutionary trends area. findings paper indicate following data: (1) contribution first principal component is more than 70%, average correlation coefficient higher 0.79. effectively integrates information multiple indicators enhances applicability regional evaluation. (2) Between 2022, showed overall upward trend, with value experiencing phases fluctuation, increase, decline, stabilization. values non-coal areas consistently remained those areas. (3) Over 60% have conditions, especially (4) impact on significant within 6 km radius, while effects gradually diminish 10 range. This not only offers reliable methodology for evaluating large scale over long but also guiding restoration sustainable development

Язык: Английский

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