Analyzing the Spatial Patterns and Impact Factors of Vegetation Net Primary Productivity and Precipitation Utilization Efficiency in Heilongjiang Province Under Climate Change DOI Open Access
Fangli Dong,

Xingmin Mu,

Fanxiang Meng

et al.

Water, Journal Year: 2024, Volume and Issue: 16(24), P. 3681 - 3681

Published: Dec. 20, 2024

Understanding the spatial patterns and driving mechanisms of net primary productivity (NPP) precipitation utilization efficiency (PUE) is crucial for assessing ecosystem services. This study analyzed variations in NPP PUE Heilongjiang Province from 2001 to 2020, using MOD17A3 products meteorological, topographic, land use data. The distribution seven categories was determined study, namely, cropland, forest, grassland, water, barren, impervious wetland. multi-year averages were 428.96 gC·m−2·a−1 0.74 gC·m−2·mm−1, respectively, with forests showing highest values barren lands lowest. During period, 91.4% increased at an average rate 3.36 gC·m−2·a−1, while exhibited a polarized trend. Changes use, especially conversions involving cropland along climatic factors such as rising temperature, significantly influenced dynamics. These findings provide scientific basis ecological restoration assessment function under changing conditions.

Language: Английский

Exploring the spatiotemporal heterogeneity of vegetation changes in subtropical humid karst region under CO2 fertilization DOI
Meng Chen, Qiuwen Zhou, Dawei Peng

et al.

Journal of Geographical Sciences, Journal Year: 2025, Volume and Issue: 35(1), P. 65 - 87

Published: Jan. 1, 2025

Language: Английский

Citations

1
Seasonal Spatiotemporal Changes in the NDVI and Its Driving Forces in Wuliangsu Lake Basin, Northern China from 1990 to 2020 DOI Creative Commons
Caixia Li, Xiang Jia,

Ruoning Zhu

et al.

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(12), P. 2965 - 2965

Published: June 7, 2023

In the context of global climate change, many studies have focused on interannual vegetation variation trends and their response to precipitation temperature, but ignored effects seasonal variability. This study explored relationship between normalized difference index (NDVI) elements in Wuliangsu Lake Basin area from 1990 2020, quantified impacts human activities dynamics. We used Landsat series data analyze spatial temporal NDVI using trend analysis method, Theil–Sen median, Mann–Kendall test, Hurst index. Then, we meteorological land use quantify residual analysis, correlation methods determine driving forces variations. The results showed that changes presented obvious regional characteristics, with a decreasing southeast northwest Basin. Due warming, start growing season (SOS) is 4.3 days (2001 2010) 6.8 (2011 2020) earlier compared 2000. end (EOS) advanced by 3.6 2010), delayed 8.9 2020). Seasonal (spring, summer, autumn, winter) NDVIs temperature show heterogeneity. Further, grasslands woodlands were vulnerable change activities. Since beginning 21st century, activity was force for improvement Dengkou, west-central, north southwest regions, where ecological instability weak. finding can provide theoretical basis implementation same type restoration projects construction civilization, contribute green sustainable development.

Language: Английский

Citations

14
Spatiotemporal dynamics of vegetation net primary productivity in Chinese ecological function conservation areas: The influences of climate and topography DOI
Xian Liu, Hengkai Li, Yanbing Zhou

et al.

Journal for Nature Conservation, Journal Year: 2025, Volume and Issue: unknown, P. 126846 - 126846

Published: Jan. 1, 2025

Language: Английский

Citations

0
Seasonal variations in the transpiration-to-evapotranspiration ratio and their driving forces in China’s terrestrial ecosystem during 1981–2021 DOI
Bin Wang, Zhongen Niu, Lili Feng

et al.

Journal of Geographical Sciences, Journal Year: 2025, Volume and Issue: 35(4), P. 699 - 715

Published: April 1, 2025

Language: Английский

Citations

0
Forestry Ecosystem Protection from the Perspective of Eco-civilization Based on Self-Attention Using Hierarchical Dilated Convolutional Neural Network DOI Creative Commons
Rui Meng

International Journal of Computational Intelligence Systems, Journal Year: 2024, Volume and Issue: 17(1)

Published: April 22, 2024

Abstract Ensuring the sustainable protection of forestry ecosystems faces numerous challenges. One significant hurdle is constant threat illegal logging and deforestation. Despite various regulations conservation efforts, enforcing these measures can be difficult, particularly in remote or poorly monitored areas. Additionally, increasing global demand for timber other forest products puts immense pressure on ecosystems, leading to overexploitation habitat degradation. In this manuscript, Self-Focused Hierarchical Augmented Convolution Neural Network (SAHD-CNN) optimized with Tasmanian Devil Optimization (TDO) algorithm proposed. Initially data taken from Global Leaf Area Index (LAI) dataset. Afterward input fed Adaptive Distorted Quantum Matched-Filter. The pre-processing output provided effectively classifying Forestry Ecosystem Protection (FEP) high, medium, low. weight parameters SAHD-CNN are using (TD) method. proposed method implemented MATLAB working platform. FEP-SAHDCNN technique attains higher accuracy value 99% than existing techniques such as based Particle swarm (FEP-PSO) Accuracy 65%, Evaluation-based (FEP-EN) 82%, FEP-GRS 79%. Thus, gives optimal methods.

Language: Английский

Citations

2
NPP and Carbon Emissions under Forest Fire Disturbance in Southwest and Northeast China from 2001 to 2020 DOI Open Access
Wenyi Zhang, Yanrong Yang, Cheng Hu

et al.

Forests, Journal Year: 2023, Volume and Issue: 14(5), P. 999 - 999

Published: May 12, 2023

With climate change, frequent forest fires and prolonged fire period occur all over the world. Moreover, carbon emission from affects cycle of ecosystem. However, this effect varies by region with no uniform conclusions, fewer comparative studies exist on such differences between regions. In paper, net primary productivity (NPP) data MOD17A3 were used as an important parameter absorption, along MODIS spot MCD14DL burned area MCD64A1. Forest lost under interference in northeast southwest natural areas China was studied to explore role process its unlike regions China. Here, means kernel density analysis M-K trend test, characteristics China’s forests calculated. disturbance quantified reference factor list. We show that (1) total number spots 2001 2020 1.06 × 105, 1.28 times Northeast only 67.84% northeast. (2) The emissions 37,559.94 Gg, 10.77% larger than forest, CH4 CO2 13.52% 11.29% respectively. showed a downward trend, R2 = 0.16 (p < 0.1), while it remained basically unchanged southwest. contribution changed types, shown as: evergreen needleleaf (14.98%) > broadleaf (10.81%) deciduous (6.52%) (5.22%). (3) From 2020, premise NPP both manifested upward trends, significant 0.42 0.05), increased 0.37 0.05). It negative correlation emissions, had China, loss occurred Southwest general, different characteristics, NPP, which represents uptake, differences. impact study can provide some ideas effects change.

Language: Английский

Citations

6
The impact of land uses on the diversity and farmers' preferences for woody species in the selected highlands of Ethiopia DOI
Fekadu Hailu, Abayneh Derero, Abebayehu Aticho

et al.

Agroforestry Systems, Journal Year: 2024, Volume and Issue: 98(6), P. 1681 - 1702

Published: March 21, 2024

Language: Английский

Citations

1
Research on the Spatio-Temporal Changes of Vegetation and Its Driving Forces in Shaanxi Province in the Past 20 Years DOI Open Access
Ming Shi, Fei Lin, Xia Jing

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(23), P. 16468 - 16468

Published: Nov. 30, 2023

(1) Background: Vegetation is an important component of ecosystems. Investigating the spatio-temporal dynamic changes in vegetation various Shaanxi Province regions crucial for preservation local ecological environment and sustainable development. (2) Methods: In this study, KNDVI index over 20-year period from 2003 to 2022 was calculated using MODIS satellite image data that received Google Earth Engine (GEE). Sen MK trend analysis as well partial correlation were then utilized examine patterns change regions. This paper selected meteorological factors, such potential evapotranspiration (PET), precipitation (PRE), temperature (TMP); human activity land-use type population density; terrain surface elevation, slope direction, gradient, influencing factors research area order analyze driving forces changes. These analyzed a geo-detector. (3) Results: The presented growth 2022, improvement 189,756 km2, accounting 92.15% total area. Among them, significantly improved 174,262 84.63% area, slightly 15,495 square kilometers, 7.52% (4) Conclusions: strengthening bivariate nonlinear enhancement main interaction types affecting combination includes PRE ∩ PET TMP PET. Therefore, climate conditions force Province. supported by are maintaining region’s natural ecosystem.

Language: Английский

Citations

3
An Analysis of Runoff Variation in a Small Basin in the Loess Plateau: Identifying the Variation Causes and Implications for Sustainable Water Management DOI Open Access
Wenqing Li,

Guohua He,

Yong Zhao

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(12), P. 9651 - 9651

Published: June 16, 2023

Analyzing the characteristics and causes of runoff variation in a typical small basin is beneficial for ecological restoration Loess Plateau. This study employed series statistical methodologies to examine meteorological changes underlying surface evolution Qishui River Basin (QRB). To differentiate impacts climate change human activities on variation, we applied Choudhury–Yang formula Double Mass Curve (DMC) method. Subsequently, by incorporating future watershed protection strategies various SSP scenarios, utilized Soil Water Assessment Tool simulate while employing DMC identify variation. The results suggested that activity has slightly greater impact than reducing during historical period, with only 1% difference. However, this will as becomes increasingly significant. Human such afforestation have dual effects, encompassing positive effects improving water quality mitigating soil erosion, well negative consequences diminishing local availability exacerbating drought. Effective policies should be implemented, involving use appropriate tree species planting methods, finding an value forest area, monitoring evaluation, etc., order ensure are aligned broader social, economic, environmental goals QRB. These findings provide valuable guidance policy-makers developing management changes.

Language: Английский

Citations

2
Remote Sensing Identification of Picea schrenkiana var. tianschanica in GF-1 Images Based on a Multiple Mixed Attention U-Net Model DOI Open Access
Jian Zheng, Donghua Chen,

Hanchi Zhang

et al.

Forests, Journal Year: 2024, Volume and Issue: 15(11), P. 2039 - 2039

Published: Nov. 19, 2024

Remote sensing technology plays an important role in woodland identification. However, mountainous areas with complex terrain, accurate extraction of boundary information still faces challenges. To address this problem, paper proposes a multiple mixed attention U-Net (MMA-U-Net) semantic segmentation model using 2015 and 2022 GF-1 PMS images as data sources to improve the ability extract features Picea schrenkiana var. tianschanica forest. The architecture serves its underlying network, feature is improved by adding hybrid CBAM replacing original skip connection DCA module accuracy segmentation. results show that on remote dataset images, compared other models, increased 5.42%–19.84%. By statistically analyzing spatial distribution well their changes, area was 3471.38 km2 3726.10 2022. Combining predicted DEM data, it found were most distributed at altitude 1700–2500 m. method proposed study can accurately identify provides theoretical basis research direction for forest monitoring.

Language: Английский

Citations

0