GISD30: global 30 m impervious-surface dynamic dataset from 1985 to 2020 using time-series Landsat imagery on the Google Earth Engine platform

Earth system science data, Journal Year: 2022, Volume and Issue: 14(4), P. 1831 - 1856

Published: April 14, 2022

Abstract. Accurately mapping impervious-surface dynamics has great scientific significance and application value for research on urban sustainable development, the assessment of anthropogenic carbon emissions global ecological-environment modeling. In this study, a novel automatic method combining advantages spectral-generalization automatic-sample-extraction strategies was proposed, then an accurate 30 m dynamic dataset (GISD30) 1985 to 2020 produced using time-series Landsat imagery Google Earth Engine cloud computing platform. Firstly, training samples corresponding reflectance spectra were automatically derived from prior land-cover products after employing multitemporal compositing relative radiometric normalization. Then, spatiotemporal adaptive classification models, trained with migrated impervious surfaces transferred pervious-surface in each epoch every 5∘×5∘ geographical tile, applied map surface period. Furthermore, spatiotemporal-consistency correction presented minimize effects independent errors improve consistency dynamics. Our model achieved overall accuracy 90.1 % kappa coefficient 0.865 23 322 validation samples. Cross-comparisons five existing further indicated that our GISD30 product best performance capturing spatial distributions various landscapes. The statistical results doubled past 35 years, 5.116×105 km2 10.871×105 2020, Asia saw largest increase area compared other continents, total 2.946×105 km2. Therefore, it concluded is promising could provide vital support monitoring regional or urbanization as well related applications. generated paper free access at https://doi.org/10.5281/zenodo.5220816 (Liu et al., 2021b).

Language: Английский

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Exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on GTWR and MGWR: The case of Nanjing, China

Ecological Indicators, Journal Year: 2022, Volume and Issue: 143, P. 109333 - 109333

Published: Aug. 22, 2022

Landscape pattern significantly impacts habitat quality, especially in cities undergoing rapid urbanization, where landscape patterns are changing dramatically. However, the spatial and temporal driving mechanisms of on quality still unclear, proposed methods Geographically Temporally Weighted Regression (GTWR) Multiscale Geographic (MGWR) provide possibilities for exploration these mechanisms. This study was conducted Nanjing from 2001 to 2020. indices indicating aggregation, connectivity, diversity compactness were calculated using Fragstats The computed Integrated Valuation Ecosystem Services Tradeoffs (InVEST) model. By combining two new measurement models, GTWR MGWR, explored. results show that (1) as Nanjing’s land under construction has expanded, decreased significantly, overall fluctuated drastically. (2) MGWR well-suited such analysis important insights. (3) Overall, aggregation negatively associated with areas low-quality habitat. Increased connectivity low substrates had a positive effect increase proximity habitat, while opposite true high zones. (4) As urbanization level increases, negative effects expand, do diversity. (5) extent influence ranked largest smallest: compactness, diversity, intensity is reversed. Based findings, reference point urban planners provided plan sustainable rational manner. It also provides means integrating into ecology.

Language: Английский

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LGHAP: the Long-term Gap-free High-resolution Air Pollutant concentration dataset, derived via tensor-flow-based multimodal data fusion

Earth system science data, Journal Year: 2022, Volume and Issue: 14(2), P. 907 - 927

Published: Feb. 24, 2022

Abstract. Developing a big data analytics framework for generating the Long-term Gap-free High-resolution Air Pollutant concentration dataset (abbreviated as LGHAP) is of great significance environmental management and Earth system science analysis. By synergistically integrating multimodal aerosol acquired from diverse sources via tensor-flow-based fusion method, gap-free optical depth (AOD) with daily 1 km resolution covering period 2000–2020 in China was generated. Specifically, gaps AOD imageries Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra were reconstructed based on set tensors satellites, numerical analysis, situ air quality measurements integrative efforts spatial pattern recognition high-dimensional gridded image analysis knowledge transfer statistical mining. To our knowledge, this first long-term high-resolution China, which spatially contiguous PM2.5 PM10 concentrations then estimated using an ensemble learning approach. Ground validation results indicate that LGHAP are good agreement observations Aerosol Robotic Network (AERONET), R 0.91 RMSE equaling 0.21. Meanwhile, estimations also agreed well ground measurements, values 0.95 0.94 RMSEs 12.03 19.56 µg m−3, respectively. The provides suite maps high to better examine changes over past 2 decades, three major variation periods haze pollution revealed. Additionally, proportion population exposed unhealthy increased 50.60 % 2000 63.81 2014 across reduced drastically 34.03 2020. Overall, generated has potential trigger multidisciplinary applications observations, climate change, public health, ecosystem assessment, management. AOD, PM2.5, datasets publicly available at https://doi.org/10.5281/zenodo.5652257 (Bai et al., 2021a), https://doi.org/10.5281/zenodo.5652265 2021b), https://doi.org/10.5281/zenodo.5652263 2021c), Monthly annual can be https://doi.org/10.5281/zenodo.5655797 2021d) https://doi.org/10.5281/zenodo.5655807 2021e), Python, MATLAB, R, IDL codes provided help users read visualize these data.

Language: Английский

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How does heterogeneous environmental regulation affect net carbon emissions: Spatial and threshold analysis for China

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 330, P. 117161 - 117161

Published: Jan. 3, 2023

Language: Английский

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Landscape ecological risk assessment and its driving factors of multi-mountainous city

Ecological Indicators, Journal Year: 2023, Volume and Issue: 146, P. 109823 - 109823

Published: Jan. 5, 2023

Urban land has been expanding under the background of rapid urbanization, which leads to increasingly prominent problem regional ecological security in multi-mountainous cities. In order scientifically formulate use policies and maintain pattern, it is necessary assess landscape risk (LER), explore its influencing factors, simulate LERs different scenarios future. This study takes Guiyang, a typical mountainous city karst area southwest China, as area. Based on three-phase remote sensing images, pattern index Geodetector method (GDM) were used LER corresponding driving factors from 2000 2020, PLUS model was urban development 2030. The results showed: (1) average (LERI) 2000, 2010, 2020 0.0341, 0.0320, 0.0304, respectively. shows that overall Guiyang low gradually decreases over time. (2) significant positive spatial autocorrelation, but autocorrelation with city. (3) From main LER, impact social growing (4) change 2030 varies significantly scenarios, among up zone natural scenario largest, followed by farmland protection scenario, priority smallest. will provide scientific basis reference for planning cities, planning, formulation relevant policies.

Language: Английский

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Do adaptive policy adjustments deliver ecosystem-agriculture-economy co-benefits in land degradation neutrality efforts? Evidence from southeast coast of China

Environmental Monitoring and Assessment, Journal Year: 2023, Volume and Issue: 195(10)

Published: Sept. 15, 2023

Language: Английский

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Cropland abandonment in China: Patterns, drivers, and implications for food security

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 418, P. 138154 - 138154

Published: July 18, 2023

Language: Английский

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GLC_FCS30D: the first global 30 m land-cover dynamics monitoring product with a fine classification system for the period from 1985 to 2022 generated using dense-time-series Landsat imagery and the continuous change-detection method

Earth system science data, Journal Year: 2024, Volume and Issue: 16(3), P. 1353 - 1381

Published: March 15, 2024

Abstract. Land-cover change has been identified as an important cause or driving force of global climate and is a significant research topic. Over the past few decades, land-cover mapping progressed; however, long-time-series land-cover-change monitoring data are still sparse, especially those at 30 m resolution. In this study, we describe GLC_FCS30D, novel dynamics dataset containing 35 subcategories covering period 1985–2022 in 26 time steps (maps were updated every 5 years before 2000 annually after 2000). GLC_FCS30D developed using continuous detection all available Landsat imagery based on Google Earth Engine platform. Specifically, first take advantage change-detection model full series observations to capture points changed pixels identify temporally stable areas. Then, apply spatiotemporal refinement method derive globally distributed high-confidence training samples from these Next, local adaptive classification models used update information for pixels, temporal-consistency optimization algorithm adopted improve their temporal stability suppress some false changes. Further, product validated 84 526 validation 2020. It achieves overall accuracy 80.88 % (±0.27 %) basic system (10 major types) 73.04 (±0.30 LCCS (Land Cover Classification System) level-1 (17 types). Meanwhile, two third-party time-series datasets United States Europe Union also collected analyzing variations, results show that offers terms variation across mean accuracies 79.50 (±0.50 81.91 (±0.09 over regions. Lastly, draw conclusions about dataset; namely, forest cropland variations have dominated 37 years, net loss forests reached 2.5 million km2, gain area approximately 1.3 km2. Therefore, accurate land-cover-dynamics benefits its diverse system, high spatial resolution, long span (1985–2022); thus, it will effectively support promote sustainable development analysis. The via https://doi.org/10.5281/zenodo.8239305 (Liu et al., 2023).

Language: Английский

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Trade-offs and synergistic relationships of ecosystem services under land use change in Xinjiang from 1990 to 2020: A Bayesian network analysis

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 858, P. 160015 - 160015

Published: Nov. 8, 2022

Language: Английский

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Analyzing “economy-society-environment” sustainability from the perspective of urban spatial structure: A case study of the Yangtze River delta urban agglomeration

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 96, P. 104691 - 104691

Published: June 3, 2023

Language: Английский

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