An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth DOI Creative Commons

Zhenxian Xu,

Xin Shen,

Sang Ge

et al.

Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 15

Published: July 18, 2024

Introduction As an exceptional geographical entity, the vegetation of Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in south-eastern sector QTP, serving as a transition area from sub-tropical evergreen broadleaf forest high-mountain vegetation. However, there has been limited exploration into predicting temporal and spatial variability cover using anti-interference methods address outliers long-term historical data. Additionally, correlation between these variables environmental factors natural forests with complex terrain rarely analyzed. Methods This study developed advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional cover) accurately evaluate predict time shifts FVC within BNNR, utilizing GEE (Google Earth Engine). satellite data utilized this paper consisted Landsat images spanning 1986 to2020. By integrating methodologies monitor assess trend, Hurst index was employed forecast FVC. Furthermore, association topographic evaluated, partial climatic influences analyzed at pixel level (30×30m). Results discussion Here are results research: (1) Overall, BNNR growth mean value increasing 59.40% 68.67% 2020. (2) TS-MK algorithm showed that percentage decreasing trend 59.03% (significant increase 28.04%) 22.13% decrease 6.42%), respectively. coupling exponent Theil-Sen estimator suggests majority regions projected sustain upward future. (3) Overlaying outcomes revealed changes were notably influenced by elevation. analysis indicated temperature exerts significant influence cover, demonstrating correlation.

Language: Английский

Forest fire probability zonation using dNBR and machine learning models: a case study at the Similipal Biosphere Reserve (SBR), Odisha, India DOI
Rajkumar Guria, Manoranjan Mishra,

Samiksha Mohanta

et al.

Environmental Science and Pollution Research, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 30, 2025

Language: Английский

Citations

1
Forecasting shoreline dynamics and land use/land cover changes in Balukhand-Konark Wildlife Sanctuary (India) using geospatial techniques and machine learning DOI
Manoranjan Mishra, Debdeep Bhattacharyya,

Brihaspati Mondal

et al.

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 975, P. 179207 - 179207

Published: April 7, 2025

Language: Английский

Citations

0
Dynamic shoreline alterations and their impacts on Olive Ridley Turtle (Lepidochelys olivacea) nesting sites in Gahirmatha Marine Wildlife Sanctuary, Odisha (India) DOI
Manoranjan Mishra, Saswati Pati, Suman Paul

et al.

Marine Pollution Bulletin, Journal Year: 2024, Volume and Issue: 202, P. 116321 - 116321

Published: April 3, 2024

Language: Английский

Citations

3
Rapid impact assessment of severe cyclone storm Michaung along coastal zones of Andhra and Tamil Nadu, India: A geospatial analysis DOI
Manoranjan Mishra, Debdeep Bhattacharyya, Rajkumar Guria

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 370, P. 122369 - 122369

Published: Sept. 10, 2024

Language: Английский

Citations

2
Multisensor Integrated Drought Severity Index (IDSI) for assessing agricultural drought in Odisha, India DOI
Rajkumar Guria, Manoranjan Mishra, Richarde Marques da Silva

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2024, Volume and Issue: 37, P. 101399 - 101399

Published: Nov. 13, 2024

Language: Английский

Citations

2
Optimal allocation of distributed energy resources to cater the stochastic E-vehicle loading and natural disruption in low voltage distribution grid DOI Creative Commons
Devender Kumar Saini, Monika Yadav, Nitai Pal

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: July 24, 2024

The everyday extreme uncertainties become the new normal for our world. Critical infrastructures like electrical power grid and transportation systems are in dire need of adaptability to dynamic changes. Moreover, stringent policies strategies towards zero carbon emission require heavy influx renewable energy sources (RES) adoption electric systems. In addition, world has seen an increased frequency natural disasters. These events adversely impact grid, specifically less hardened distribution grid. Hence, a resilient network is demand future fulfill critical loads charging emergency vehicles (EV). Therefore, this paper proposes two-dimensional methodology planning operational phase Initially stochastic modelling EV load been performed duly considering geographical feature commute pattern form probability functions. Thenceforth, assessment earthquakes using damage state classification done model on efficacy proposed tested by simulating urban Indian with mapped DigSILENT PowerFactory integrated supervised learning tools Python. Subsequently 24-h profile before event after have compared analyze impact.

Language: Английский

Citations

1
An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth DOI Creative Commons

Zhenxian Xu,

Xin Shen,

Sang Ge

et al.

Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 15

Published: July 18, 2024

Introduction As an exceptional geographical entity, the vegetation of Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in south-eastern sector QTP, serving as a transition area from sub-tropical evergreen broadleaf forest high-mountain vegetation. However, there has been limited exploration into predicting temporal and spatial variability cover using anti-interference methods address outliers long-term historical data. Additionally, correlation between these variables environmental factors natural forests with complex terrain rarely analyzed. Methods This study developed advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional cover) accurately evaluate predict time shifts FVC within BNNR, utilizing GEE (Google Earth Engine). satellite data utilized this paper consisted Landsat images spanning 1986 to2020. By integrating methodologies monitor assess trend, Hurst index was employed forecast FVC. Furthermore, association topographic evaluated, partial climatic influences analyzed at pixel level (30×30m). Results discussion Here are results research: (1) Overall, BNNR growth mean value increasing 59.40% 68.67% 2020. (2) TS-MK algorithm showed that percentage decreasing trend 59.03% (significant increase 28.04%) 22.13% decrease 6.42%), respectively. coupling exponent Theil-Sen estimator suggests majority regions projected sustain upward future. (3) Overlaying outcomes revealed changes were notably influenced by elevation. analysis indicated temperature exerts significant influence cover, demonstrating correlation.

Language: Английский

Citations

0