Improving on mapping long-term surface water with a novel framework based on the Landsat imagery series.

Surface water plays a crucial role in the ecological environment and societal development. Remote sensing detection serves as a significant approach to understand the temporal and spatial change in surface water series (SWS) and to directly construct long-term SWS. Limited by various factors such as cloud, cloud shadow, and problematic satellite sensor monitoring, the existent surface water mapping datasets might be short and incomplete due to losing raw information on certain dates.

Assessment of sediment transport in Luxiapuqu watershed using RUSLE-TLSD and InSAR techniques: Yarlung Tsangpo River, China.

The Yarlung Tsangpo River Basin is characterized by its intricate topography and a significant presence of erosive materials. These often coincide with heavy localized precipitation, resulting in pronounced hydraulic erosion and geological hazards in mountainous regions. To tackle this challenge, we integrated the RUSLE-TLSD (Revised Universal Soil Loss Equation-Transportation-limited sediment delivery) model with InSAR (Interferometric Synthetic Aperture Radar) data, aiming to explore the sediment transport process and pinpoint hazard-prone sites within mountainous small watershed.

Experimental study of erodible bed scoured by the debris flow in the narrow-steep gully.

In recent years, debris flows have frequently erupted in the narrow-steep gully of the earthquake-hit Wenchuan region, displaying high flow velocities and powerful scouring abilities. However, few scouring studies in the narrow-steep gully have been conducted. A model experiment simulated the debris flow scouring process in a narrow-steep flume, in which several important physical parameters, including the debris flow density (ρ), flume slope (θ), and grain size of the sediment (D), were varied to investigate their influences on the erodible strength.

UNetGE: A U-Net-Based Software at Automatic Grain Extraction for Image Analysis of the Grain Size and Shape Characteristics.

The shape and the size of grains in sediments and soils have a significant influence on their engineering properties. Image analysis of grain shape and size has been increasingly applied in geotechnical engineering to provide a quantitative statistical description for grain morphologies. The statistic robustness and the era of big data in geotechnical engineering require the quick and efficient acquirement of large data sets of grain morphologies.

Morphological environment survey and hydrodynamic modeling of a large bifurcation-confluence complex in Yangtze River, China.

Since the establishment of the world-class Three Gorges Dam (TGD) across the Yangtze River, China, the downstream reach has experienced a long-term adjustment with regard to the river morphology and hydrodynamics, imposing a profound impact on the environmental conditions of human living and aquatic ecosystem. This study presents an investigation on the river channel morphological characteristics and hydrodynamic environment of a large bifurcation-confluence complex downstream of the TGD through detailed field survey and numerical modeling. Results show that the main stem, before being bifurcated into two sub-channels (the North Channel and the South Channel), experiences a meander, leading to the severe bed scouring near the outer bank (pools) resulted from a high flow mass flux and bed shear stress.

Investigation of respirable suspended particulate trend and relevant environmental factors in Hong Kong downtown areas.

As the addressing of high demand of good air quality in urban area, a study on air pollutant dispersion and distribution resulting from vehicular exhaust emission is strongly required. In particular, vehicular exhaust emission has become a major air pollution source in metropolitan city like Hong Kong, which is characterized with the heavy, dense traffic flow and the limited land resources. Respirable suspended particulate (RSP) is one of main pollutants resulted from vehicular exhaust emission in urban area.

Seasonal variation of air pollution index: Hong Kong case study.

Air pollution is an important and popular topic in Hong Kong as concerns have been raised about the health impacts caused by vehicle exhausts in recent years. In Hong Kong, sulphur dioxide SO2, nitrogen dioxide (NO2), nitric oxide (NO), carbon monoxide (CO), and respirable suspended particulates (RSP) are major air pollutants caused by the dominant usage of diesel fuel by goods vehicles and buses. These major pollutants and the related secondary pollutant, e.

Evolving trend and self-similarity of ozone pollution in central Hong Kong ambient during 1984-2002.

The evolving pattern of ozone level in Hong Kong urban air has undergone various changes and corresponds to the regional urban and economic development. We assess such changes by reviewing and analyzing the original ozone pollutant database monitored in central Hong Kong downtown area during the period of 1984-2002. Both fractal analysis and traditional statistical methods are adopted to estimate the ozone evolving characteristics during the studied period.

Potential assessment of a neural network model with PCA/RBF approach for forecasting pollutant trends in Mong Kok urban air, Hong Kong.

The forecasting of air pollutant trends has received much attention in recent years. It is an important and popular topic in environmental science, as concerns have been raised about the health impacts caused by unacceptable ambient air pollutant levels. Of greatest concern are metropolitan cities like Hong Kong.

A study of ozone variation trend within area of affecting human health in Hong Kong.

As far as the impact of air pollutants on human health being concerned, ozone is one of the main pollutants in atmosphere. In particular, the ground level ozone is responsible for a variety of adverse effects on both human being and plant life. To protect the humankind from such adverse health effects, early information and precautions of high ozone level need to be supplied in times.

Prediction of maximum daily ozone level using combined neural network and statistical characteristics.

Analysis and forecasting of air quality parameters are important topics of atmospheric and environmental research today due to the health impact caused by air pollution. As one of major pollutants, ozone, especially ground level ozone, is responsible for various adverse effects on both human being and foliage. Therefore, prediction of ambient ozone levels in certain environment, especially the ground ozone level in densely urban areas, is of great importance to urban air quality and city image.

A preliminary study of ozone trend and its impact on environment in Hong Kong.

As far as the impact of air pollutants on human health being is concerned, ozone (O3) is one of the most pollutant sources, and, in particular, the ground level ozone is responsible for a variety of adverse effects on both human being and plant life. To protect the population from such adverse health effects, early information and precautions about the high ozone level need to be ascertained. In this study, statistical characteristics of ground level ozone is analyzed according to field monitoring data in mixed residential, commercial and industrial areas, e.