Object-Based Distinction between Building Shadow and Water in High-Resolution Imagery Using Fuzzy-Rule Classification and Artificial Bee Colony Optimization

Due to the high similarity of the spectra of urban water and building shadows, high-resolution satellite imagery often confuses and wrongly classifies these features. To address this problem, we propose an object-based method for distinguishing building shadow from water using an artificial bee colony algorithm. In the method, four spectral ratio bands are first calculated as additional input parameters for improving the accuracy of segmentation results. During the segmentation, a series of statistical factors, such as spectrum, ratio, and sharp features, are calculated to make up for defects in the high-resolution imagery. Finally, we propose a fuzzy-rule-based classifier to generate extraction rules. The classifier is based on artificial bee colony optimization, which employs the geometric mean (G-mean) as fitness function. The proposed method was carried out on two test sites in Xiamen City. The experimental results based on GF-1 satellite date show that, compared with SVM method, the proposed method improved the overall accuracy of extraction by approximately 6% to 15% and the kappa coefficient values by approximately 0.1 to 0.2. The analysis of the extraction rules also proves that the red/NIR band and the length-width ratio band are significantly influenced by the distinction between building shadow and water

A multi-dimensional integrated approach to assess flood risks on a coastal city, induced by sea-level rise and storm tides

Coastal cities are vulnerable to increasing flood risks caused by the combination of sea-level rise (SLR) and storm tides (STs), due to their low-lying topography and densely distributed assets. Faced with this challenge, comprehensive and integrated flood risk information is vital and fundamental for the planning, implementation and optimization of coastal risk adaptation and management. The goal of this study is to propose an integrated assessment approach to sea-level rise- and storm tide-induced flood risks on a coastal urban system by employing a wide range of indicators across ecological, physical and socio-economic dimensions. To demonstrate its applicability, a case study of Xiamen City, China was performed. The results show that this approach is applicable for assessing the specific flood risks on urban ecological, physical and socio-economic system, respectively. Under 4.75 ∼ 5.86 m extreme sea-level, 11 600 ∼ 17 100 ha land and 440 000 ∼ 720 000 population will be flooded in Xiamen City, with flood risks—measured by monetary—of 858 ∼ 1134 million, 4744 ∼ 10 590 million and 2537 ∼ 4175 million RMB of ecological, physical and economic systems, respectively. Coastal ecosystem will suffer flood risks on ecological services, mainly regulation service; and wetland is the dominant ecosystem that will be affected, which imply urgent needs to wetland conservation. Indirect risk on economy accounts for a large proportion of total risks, and should be given adequate weight in the decision-making process

PM_2.5 Spatiotemporal Evolution and Drivers in the Yangtze River Delta between 2005 and 2015

High concentrations of PM2.5 are a primary cause of haze in the lower atmosphere. A better understanding of the spatial heterogeneity and driving factors of PM2.5 concentrations is important for effective regional prevention and control. In this study, we carried out remote sensing inversion of PM2.5 concentration data over a long time series and used spatial statistical analyses and a geographical detector model to reveal the spatial distribution and variation characteristics of PM2.5 and the main influencing factors in the Yangtze River Delta from 2005 to 2015. Our results show that (1) The average annual PM2.5 concentration in the Yangtze River Delta prior to 2007 displayed an increasing trend, followed by a decreasing trend after 2007 which eventually stabilized; and (2) climate regionalization and geomorphology were the dominant natural factors driving PM2.5 concentration diffusion, while total carbon dioxide emissions and population density were the dominant socioeconomic factors affecting the formation of PM2.5. Natural factors and socioeconomic factors together lead to PM2.5 pollution. These findings provide an interpretation of PM2.5 spatial distribution and the mechanisms influencing PM2.5 pollution, which can help the Chinese government develop effective abatement strategies

Gap analysis of Firmiana danxiaensis, a rare tree species endemic to southern China

Firmiana danxiaensis (F. danxiaensis) is a special native species with a narrow distribution. More than 90 % of the plant species in the genus that F. danxiaensis belongs to are rare species with a narrow distribution. The main distribution area is Mount Danxia, a representative area of China Danxia where many endemic species of the Danxia landform have been bred. We carried out a gap analysis by overlapping the nature reserves with the potential habitat of F. danxiaensis. The results show that: (1) the potential habitat area of F. danxiaensis is 6,255.28 km2 simulated by the Biomod2 ensemble model and 4,114.19 km2 by Maxent, respectively, which accounted for 3.48 % and 2.29 % of the study area, located in Nanxiong county, Shixing county, Renhua county, and Qujiang county; (2) F. danxiaensis prefers areas with the max temperature of the warmest month over 32.5℃, the temperature seasonality between 6000 and 7000, and the occurrence probability of F. danxiaensis was at its highest level when the max temperature of the warmest month reached between 36 and 37 °C, the temperature seasonality was nearly 7000; (3) more than 40 % of the potential habitat of F. danxiaensis was anthropogenically disturbed; (4) in the potential habitat simulated by Maxent, the conservation gap area is 3,390.26 km2, accounting for 82.40 % of the total potential habitat, in the potential habitat simulated by Biomod2 ensemble model, the conservation gap area is 4.899.62 km2, accounting for 78.33 % of the total potential habitat. The protection status of F. danxiensis is poor, with populations of F. danxiaensis in Yingde and Shixing not covered by nature reserves and already subject to serious human disturbance. It is recommended that the structure of existing protected areas be adjusted, the scope of corresponding nature reserves be appropriately expanded, and new nature reserves be added to ensure the sustainable development of F. danxiaensis populations

An Optimized Approach for Extracting Urban Land Based on Log-Transformed DMSP-OLS Nighttime Light, NDVI, and NDWI

Quantitative and accurate urban land information on regional and global scales is urgently required for studying socioeconomic and eco-environmental problems. The spatial distribution of urban land is a significant part of urban development planning, which is vital for optimizing land use patterns and promoting sustainable urban development. Composite nighttime light (NTL) data from the Defense Meteorological Program Operational Line-Scan System (DMSP-OLS) have been proven to be effective for extracting urban land. However, the saturation and blooming within the DMSP-OLS NTL hinder its capacity to provide accurate urban information. This paper proposes an optimized approach that combines NTL with multiple index data to overcome the limitations of extracting urban land based only on NTL data. We combined three sources of data, the DMSP-OLS, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI), to establish a novel approach called the vegetation–water-adjusted NTL urban index (VWANUI), which is used to rapidly extract urban land areas on regional and global scales. The results show that the proposed approach reduces the saturation of DMSP-OLS and essentially eliminates blooming effects. Next, we developed regression models based on the normalized DMSP-OLS, the human settlement index (HSI), the vegetation-adjusted NTL urban index (VANUI), and the VWANUI to analyze and estimate urban land areas. The results show that the VWANUI regression model provides the highest performance of all the models tested. To summarize, the VWANUI reduces saturation and blooming, and improves the accuracy with which urban areas are extracted, thereby providing valuable support and decision-making references for designing sustainable urban development

Spatiotemporal Evolution Characteristics of Urbanization in the Xiamen Special Economic Zone Based on Nighttime-Light Data from 1992 to 2020

In China and elsewhere, urban expansion is directly related to the important issues of social development, economic development, and the sustainable development of the ecological environment. Traditional statistical methods based on administrative regions lack geospatial information, which makes it difficult to analyze and explore in detail the development status and spatial differences of cities. In real time, nighttime light (NTL) remote sensing can reveal the spatial expansion change information of urban built-up areas (UB) on different scales, thus allowing for the analysis of urban spatial patterns and variations in urban development. Based on the long-time sequence NTL data from 1992 to 2020, this work studies the Xiamen Special Economic Zone by using the vegetation-water-adjusted NTL urban index (VWANUI) to extract the urban built-up areas and study the UB expansion patterns, the migration of the urban center of gravity, and intra-city differences. The result is a qualitative and quantitative temporal and spatial evaluation of Xiamen’s economic development characteristics. The results show that the UB of Xiamen expanded 349.219 km2 from 1995 to 2020, mainly concentrated in the period 2005–2020, during which time 79.44% of the expansion of the whole study period occurred. Throughout the study period, the urban center of gravity of Xiamen city shifts 8757.15 m to the northeast at the rate of 350.29 m/year in the direction of 74.88° (the urban center of gravity shifted from the inner island to the outer island). The total brightness of nighttime lights in Xiamen is gradually increasing, indicating that the level of urban economic development continuously improved over the measurement period, that human social activities have strengthened, and that the cross-island development strategy has produced certain results. These results provide data that describe urban development and policy formulation in Xiamen

Research status, trends, and mechanisms of biochar adsorption for wastewater treatment: a scientometric review

Abstract In the last decade, biochar application research has emerged as a hot topic in water treatment studies, which made biochar adsorption one of the primary wastewater treatment strategies. This paper presents a global bibliometric analysis of 2673 publications from the Web of Science database, spanning 2011–2022. For a comprehensive understanding of the research status and trends in biochar adsorption for wastewater treatment, the advanced quantitative and visual analysis tools (i.e., CiteSpace and ArcGIS) were employed. The results showed that China emerged as the leading country with the most published articles. The key research area is on the magnetic adsorption of biochar in wastewater. The articles summarized in the review demonstrated unequivocally that biochar can treat a wide range of wastewater even though the adsorption mechanisms of biochar on heavy metals, inorganic salts and organic pollutants in wastewater are not entirely consistent. The review further analyzes the factors affecting the performance of biochar in adsorbing pollutants from wastewater and the improvement measures of biochar functional characteristics, proposing the future research directions focusing on the improvement of the adsorption capacity of biochar products. The information synthesis and discussion would provide valuable insights on the historical, current, and future trends in biochar research, beneficial to solve the practical problems of water pollution and improve the quality of the environment

Using Unmanned Aerial Vehicle Remote Sensing and a Monitoring Information System to Enhance the Management of Unauthorized Structures

In this research, we investigated using unmanned aerial vehicle (UAV) photographic technology to prevent the further expansion of unauthorized construction and thereby reduce postdisaster losses. First, UAV dynamic aerial photography was used to obtain dynamic digital surface model (DSM) data and elevation changes of 2–8 m as the initial sieve target. Then, two periods of dynamic orthophoto images were superimposed for human–computer interaction interpretation, so we could quickly distinguish buildings undergoing expansion, new construction, or demolition. At the same time, mobile geographic information system (GIS) software was used to survey the field, and the information gathered was developed to support unauthorized construction detection. Finally, aerial images, interpretation results, and ground survey information were integrated and released on WebGIS to build a regulatory platform that can achieve accurate management and effectively prevent violations

Three decades of changes in water environment of a large freshwater Lake and its relationship with socio-economic indicators

Tai Lake (Ch: Taihu) has attracted international attention forcyanobacteria blooms. However, the drivers of cultural eutrophication, especially long-term socio-economic indicators have been little researched. The results of research demonstrate how socioeconomic development affected quality of water and how it has been improved by anthropogenic activities. This study described variability in indicators of water quality in Tai Lakeand investigated thedrivers. Significant relationships existed between concentrations of annual mean total nitrogen (TN), total phosphorous (TP), chemical oxygen demand (COD) and biological oxygen demand (BOD), and population, per capital gross domestic production (CDP) and sewage discharge (p < 0.05). However, mechanisms causing change varied among TN, TP, COD and BOD. Before 2000, the main contributors to increases in concentrations of TN were human population, GDP and volumes of domestic sewage discharges. After 2000, discharges of industrial sewage become the primary contributor. After 1998, the regressions of annual mean TN, TP and COD on per capital GDP, population and domestic sewage discharge were reversed compared to the former period. Since 1999, an apparent inverted U-shaped relationship between environmental pollution and economic development has developed, which indicated that actions taken by governments have markedly improved quality of water in Tai Lake. The statistical relationship between BOD and per capital GDP didn't conform to the Kuznet curve. The Ushaped Kuznet curve may offer hope for the future that with significant environmental investments a high GDP can be reached and maintained without degradation of the environment, especially through appropriate management of industrial sewage discharge. (C) 2018 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V