Advancements in technology and innovation for sustainable agriculture: Understanding and mitigating greenhouse gas emissions from agricultural soils

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 347, P. 119147 - 119147

Published: Sept. 28, 2023

Language: Английский

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Spatial and temporal variation of ecological quality in northeastern China and analysis of influencing factors

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 423, P. 138650 - 138650

Published: Sept. 4, 2023

Language: Английский

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Investigating the nexus between energy, socio-economic factors and environmental pollution: A geo-spatial multi regression approach

Gondwana Research, Journal Year: 2024, Volume and Issue: 130, P. 308 - 325

Published: March 1, 2024

Language: Английский

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Analysis of the Spatiotemporal Characteristics and Influencing Factors of the NDVI Based on the GEE Cloud Platform and Landsat Images

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(20), P. 4980 - 4980

Published: Oct. 16, 2023

Vegetation is an important type of land cover. Long-term, large-scale, and high-precision vegetation monitoring great significance for ecological environment investigation regional sustainable development in protected areas. This paper develops a long-term remote sensing method by calculating the normalized difference index (NDVI) based on Google Earth Engine (GEE) cloud platform Landsat satellite images. First, images GEE, spatiotemporal distribution map NDVI accurately drawn. Subsequently, classified, time trend analysis conducted mean graphs, transition matrices, etc. Then, combined with Moran’s I, high/low clusters, other methods, spatial pattern characteristics are analyzed. Finally, climate factors, terrain anthropologic factors considered comprehensively. An affecting evolution performed. Taking Zhoushan Island, China, as example, experiment conducted, results reveal that (1) average exhibits decreasing from 1985 to 2022, 0.53 0.46 2022. (2) Regarding transitions, high areas (0.6–1) exhibit most substantial shift toward moderately values (0.4–0.6), covering area 83.10 km2. (3) There obvious agglomeration phenomenon Island. The high-high clusters significant hot spots predominantly concentrated island’s interior regions, while low-low cold mainly situated along coastal (4) DEM, slope, temperature have greater influence among single 2015. differences between DEM precipitation, slope aspect population, gross domestic product (GDP). temperature, population three sets strong interaction. study provides data support scientific management resources Island island region.

Language: Английский

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Detection of cotton leaf curl disease’s susceptibility scale level based on deep learning

Journal of Cloud Computing Advances Systems and Applications, Journal Year: 2024, Volume and Issue: 13(1)

Published: Feb. 26, 2024

Abstract Cotton, a crucial cash crop in Pakistan, faces persistent threats from diseases, notably the Cotton Leaf Curl Virus (CLCuV). Detecting these diseases accurately and early is vital for effective management. This paper offers comprehensive account of process involved collecting, preprocessing, analyzing an extensive dataset cotton leaf images. The primary aim this to support automated disease detection systems. We delve into data collection procedure, distribution dataset, preprocessing stages, feature extraction methods, potential applications. Furthermore, we present preliminary findings our analyses emphasize significance such datasets advancing agricultural technology. impact factors on plant growth significant, but intrusion as Disease (CLCuD) caused by Gemini (CLCuV), poses substantial threat yield. Identifying CLCuD promptly, especially areas lacking critical infrastructure, remains formidable challenge. Despite research dedicated agriculture, deep learning technology continues play role across various sectors. In study, harness power two models, specifically Convolutional Neural Network (CNN). evaluate models using distinct datasets: one publicly available Kaggle other proprietary collection, encompassing total 1349 images capturing both healthy disease-affected leaves. Our meticulously curated categorized five groups: Healthy, Fully Susceptible, Partially Resistant, Resistant. Agricultural experts annotated based their expertise identifying abnormal patterns appearances. Data augmentation enhances precision model performance, with features extracted training testing efforts. Notably, CNN outperforms achieving impressive accuracy rate 99% when tested against dataset.

Language: Английский

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Machine learning insights into PM2.5 changes during COVID-19 lockdown: LSTM and RF analysis in Mashhad

Environmental Monitoring and Assessment, Journal Year: 2024, Volume and Issue: 196(5)

Published: April 15, 2024

Language: Английский

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Predicting ambient PM2.5 concentrations via time series models in Anhui Province, China

Environmental Monitoring and Assessment, Journal Year: 2024, Volume and Issue: 196(5)

Published: April 30, 2024

Language: Английский

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Utilizing convolutional neural networks (CNN) and U-Net architecture for precise crop and weed segmentation in agricultural imagery: A deep learning approach

Big Data Research, Journal Year: 2024, Volume and Issue: 36, P. 100465 - 100465

Published: May 1, 2024

Language: Английский

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Multiobjective Optimization of the Economic Efficiency of Biodegradable Plastic Products: Carbon Emissions and Analysis of Geographical Advantages for Production Capacity

Sustainability, Journal Year: 2025, Volume and Issue: 17(7), P. 2874 - 2874

Published: March 24, 2025

The objective of this study was to address the limitations biodegradable plastics—low economic benefits and marketing difficulties. To end, analyzed production processes two plastics: polylactic acid (PLA) polybutylene adipate terephthalate (PBAT). Based on analysis, economic, technical, environmental improvement indicators were constructed, an optimization model with three objectives profit, carbon emission cost, process risk established. In study, we embedded improved NSGA-III algorithm obtain Pareto optimal solution set. We also proposed entropy-weighted efficiency index (EWEI) for analysis transport advantages based distribution plastics production, road density, regional prices. With a line capacity 10,000 tons 8% discount rate, 10-year return PBAT products 7,039,931.23 yuan higher than that PLA products. profit 488.92 per ton production. However, exhibited carbon-emission cost products, especially risk, by 0.11%. East China region has obvious geographical advantages, but Southwest is constrained in presence mountainous terrain. Therefore, it imperative optimize China’s overall industrial layout plastics, strengthen acquisition support sustainable promotion market, effectively minimize pollution caused traditional plastics.

Language: Английский

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Parcel-scale crop planting structure extraction combining time-series of Sentinel-1 and Sentinel-2 data based on a semantic edge-aware multi-task neural network

International Journal of Digital Earth, Journal Year: 2025, Volume and Issue: 18(1)

Published: April 28, 2025

Language: Английский

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