Removal and recovery of perchlorate from fireworks production wastewater through ion exchange and biological reduction processes.

Ion exchange is often used to remove perchlorate from various wastewaters. This study evaluated the performance of four representative anion exchange resins for removing perchlorate from wastewater. Perchlorate was recovered from the regenerant brine concentrate and further treated through biological methods.

Change in water column total chlorophyll-a in the Mediterranean revealed by satellite observation.

Chlorophyll-a (Chl-a) is a crucial pigment in algae and macrophytes, which makes the concentration of total Chl-a in the water column (total Chl-a) an essential indicator for estimating the primary productivity and carbon cycle of the ocean. Integrating the Chl-a concentration at different depths (Chl-a profile) is an important way to obtain the total Chl-a. However, due to limited cost and technology, it is difficult to measure Chl-a profiles directly in a spatially continuous and high-resolution way.

Error-Reduced Digital Elevation Model of the Qinghai-Tibet Plateau using ICESat-2 and Fusion Model.

The Qinghai-Tibet Plateau (QTP) holds significance for investigating Earth's surface processes. However, due to rugged terrain, forest canopy, and snow accumulation, open-access Digital Elevation Models (DEMs) exhibit considerable noise, resulting in low accuracy and pronounced data inconsistency. Furthermore, the glacier regions within the QTP undergo substantial changes, necessitating updates.

Solar photovoltaic program helps turn deserts green in China: Evidence from satellite monitoring.

Solar energy is considered one of the key solutions to the growing demand for energy and to reducing greenhouse gas emissions. Thanks to the relatively low cost of land use for solar energy and high power generation potential, a large number of photovoltaic (PV) power stations have been established in desert areas around the world. Despite the contribution to easing the energy crisis and combating climate change, large-scale construction and operation of PV power stations can change the land cover and affect the environment.

A global record of annual terrestrial Human Footprint dataset from 2000 to 2018.

Human Footprint, the pressure imposed on the eco-environment by changing ecological processes and natural landscapes, is raising worldwide concerns on biodiversity and ecological conservation. Due to the lack of spatiotemporally consistent datasets of Human Footprint over a long temporal span, many relevant studies on this topic have been limited. Here, we mapped the annual dynamics of the global Human Footprint from 2000 to 2018 using eight variables that reflect different aspects of human pressures.

Estimation of the spatial distribution of heavy metal in agricultural soils using airborne hyperspectral imaging and random forest.

Hyperspectral imaging, with the hundreds of bands and high spectral resolution, offers a promising approach for estimation of heavy metal concentration in agricultural soils. Using airborne imagery over a large-scale area for fast retrieval is of great importance for environmental monitoring and further decision support. However, few studies have focused on the estimation of soil heavy metal concentration by airborne hyperspectral imaging.

Assessing the Spatiotemporal Variation and Impact Factors of Net Primary Productivity in China.

In this study, the net primary productivity (NPP) in China from 2001 to 2012 was estimated based on the Carnegie-Ames-Stanford Approach (CASA) model using Moderate Resolution Imaging Spectroradiometer (MODIS) and meteorological datasets, and the accuracy was verified by a ChinaFLUX dataset. It was found that the spatiotemporal variations in NPP present a downward trend with the increase of latitude and longitude. Moreover, the influence of climate change on the evolution of NPP shows that NPP has had different impact factors in different regions and periods over the 12 years.

Spatiotemporal Pattern of PM Concentrations in Mainland China and Analysis of Its Influencing Factors using Geographically Weighted Regression.

Based on annual average PM gridded dataset, this study first analyzed the spatiotemporal pattern of PM across Mainland China during 1998-2012. Then facilitated with meteorological site data, land cover data, population and Gross Domestic Product (GDP) data, etc., the contributions of latent geographic factors, including socioeconomic factors (e.

An Adaptive Weighting Algorithm for Interpolating the Soil Potassium Content.

The concept of spatial interpolation is important in the soil sciences. However, the use of a single global interpolation model is often limited by certain conditions (e.g.

Ensemble learning for spatial interpolation of soil potassium content based on environmental information.

One important method to obtain the continuous surfaces of soil properties from point samples is spatial interpolation. In this paper, we propose a method that combines ensemble learning with ancillary environmental information for improved interpolation of soil properties (hereafter, EL-SP). First, we calculated the trend value for soil potassium contents at the Qinghai Lake region in China based on measured values.

Estimation of heavy metal concentrations in reclaimed mining soils using reflectance spectroscopy.

A selection of soil samples from reclaimed mining areas were prepared to establish the quantitative inversion models of the soil heavy metal (As, Zn, Cu, Cr, and Pb) concentrations. The concentrations of the soil heavy metals and the visible and near-infrared spectra of the soil samples were obtained in a darkroom. Firstly, smoothing processing was used to smooth the noise in the original spectra, and the spectral transformation techniques of first derivative (FD), continuum removal (CR), and standard normal variate (SNV) were used to promote the model stability and the accuracy of the prediction.

Multiple classifier system for remote sensing image classification: a review.

Over the last two decades, multiple classifier system (MCS) or classifier ensemble has shown great potential to improve the accuracy and reliability of remote sensing image classification. Although there are lots of literatures covering the MCS approaches, there is a lack of a comprehensive literature review which presents an overall architecture of the basic principles and trends behind the design of remote sensing classifier ensemble. Therefore, in order to give a reference point for MCS approaches, this paper attempts to explicitly review the remote sensing implementations of MCS and proposes some modified approaches.

Adaptive affinity propagation with spectral angle mapper for semi-supervised hyperspectral band selection.

Band selection is a commonly used approach for dimensionality reduction in hyperspectral imagery. Affinity propagation (AP), a new clustering algorithm, is addressed in many fields, and it can be used for hyperspectral band selection. However, this algorithm cannot get a fixed number of exemplars during the message-passing procedure, which limits its uses to a great extent.

[Hyperspectral remote sensing image classification based on radical basis function neural network].

Based on the radial basis function neural network (RBFNN) theory and the specialty of hyperspectral remote sensing data, the effective feature extraction model was designed, and those extracted features were connected to the input layer of RBFNN, finally the classifier based on radial basis function neural network was constructed. The hyperspectral image with 64 bands of OMIS II made by Chinese was experimented, and the case study area was zhongguancun in Beijing. Minimum noise fraction (MNF) was conducted, and the former 20 components were extracted for further processing.

[The analysis of error sources for SAM and its improvement algorithms].

Based on the analysis of the error sources for spectral anglemapping (SAM), several key elements are pointed out, i.e. the change of wave band location, the change of the attribution ratio, the random change of attribution, and the whole translation of wave band.

[Spectral feature-based hyperspectral RS image retrieval].

Oriented to the demands of vast RS information management for RS image retrieval, the applications of spectral features are discussed by taking hyperspectral RS image as an example. It is proposed that spectral features-based retrieval includes two modes: retrieval based on point mask an dpolygon mask. The most key issues in retrieval are spectral features extraction andsimilarity measure.