Flood hazards and susceptibility detection for Ganga river, Bihar state, India: Employment of remote sensing and statistical approaches

Results in Engineering, Год журнала: 2023, Номер 21, С. 101665 - 101665

Опубликована: Дек. 12, 2023

Climate change and flooding are related issues on the Earth's surface, while numerous lowland areas, especially delta regions, mostly affected by flood hazards. Hence, susceptibility mapping simulation of future effect areas essential for hazard management awareness. The river floodplain Ganga River in Bihar state most due to high annual floods. Floods cause huge economic losses environmental degradation, such as deforestation, riverbank erosion, water quality loss. Thus, vulnerability measurement is a serious concern this area, which involves building proper awareness mitigation strategies achieve sustainable development goals. Remote Sensing (RS) widely applied hydrological issues. statistical approaches, Analytical Hierarchy Process (AHP), Frequency Ratio (FR), Fuzzy-AHP (FAHP) algorithms, were analysis selected plain state. suitable three different approaches 9604.21 km2 9712.48 9598.28 channel not area. flooded maps indicated lands using Google Earth Engine (GEE) years 2977.69 (2020), 10481.63 (2021), 1103.89 (2022), respectively. results current study indicate that area essentially need attention adaptation reduction addition socio-economic variability monsoon regions. Otherwise, floods destroyed cropland, increased food scarcity, caused losses.

Язык: Английский

Analysis of Spatiotemporal Evolution and Driving Forces of Vegetation from 2001 to 2020: A Case Study of Shandong Province, China

Forests, Год журнала: 2024, Номер 15(7), С. 1245 - 1245

Опубликована: Июль 17, 2024

As global climate change intensifies and human activities escalate, changes in vegetation cover, an important ecological indicator, hold significant implications for ecosystem protection management. Shandong Province, a critical agricultural economic zone China, experiences that crucially affect regional regulation biodiversity conservation. This study employed normalized difference index (NDVI) data, combined with climatic, topographic, anthropogenic activity utilizing trend analysis methods, partial correlation analysis, Geodetector to comprehensively analyze the spatiotemporal variations primary driving factors of cover Province from 2001 2020. The findings indicate overall upward particularly areas concentrated activities. Climatic factors, such as precipitation temperature, exhibit positive growth, while land use emerge one key drivers influencing dynamics. Additionally, topography also impacts spatial distribution certain extent. research provides scientific basis management similar regions, supporting formulation effective restoration conservation strategies.

Язык: Английский

Generative adversarial networks with texture recovery and physical constraints for remote sensing image dehazing

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Дек. 28, 2024

The scattering of tiny particles in the atmosphere causes a haze effect on remote sensing images captured by satellites and similar devices, significantly disrupting subsequent image recognition classification. A generative adversarial network named TRPC-GAN with texture recovery physical constraints is proposed to mitigate this impact. This not only effectively removes but also better preserves information original image, thereby enhancing visual quality dehazed image. multi-scale module extract feature images, allowing it capture features from different receptive fields. Simultaneously, an attention designed further guide network's focus towards important information. In addition, restore both global local about Introducing constraint loss function improve allows for preservation characteristics images. Simulation experiments synthetic natural hazy datasets are conducted. results demonstrate that dehazing performance method surpasses other four methods.

Язык: Английский