Forecasting actual evapotranspiration without climate data based on stacked integration of DNN and meta-heuristic models across China from 1958 to 2021.

As a non-linear phenomenon that varies along with agro-climatic conditions alongside many other factors, Evapotranspiration (ET) process represents a complexity when be assessed especially if there is a data scarcity in the weather data. However, even under such a data scarcity, the accurate estimates of ET values remain necessary for precise irrigation. So, the present study aims to: i) evaluate the performance of six hybrid machine learning (ML) models in estimating the monthly actual ET values under different agro-climatic conditions in China for seven provinces (Shandong, Jiangsu, Zhejiang, Fujian, Jiangxi, Hubei, and Henan), and ii) select the best-developed model based on statistical metrics and reduce errors between predicted and actual ET (AET) values.

Spatio-temporal evolution and influencing factors of synergizing the reduction of pollution and carbon emissions - Utilizing multi-source remote sensing data and GTWR model.

Grasping current circumstances and influencing components of the synergistic degree regarding reducing pollution and carbon has been recognized as a crucial part of China in response to the protection of the environment and climate mitigation. With the introduction of remote sensing night-time light, CO emissions at multi-scale have been estimated in this study. Accordingly, an upward trend of "CO-PM" synergistic reduction was discovered, which was indicated by an increase of 78.

Petrologic Characteristics and Chemical Structures of Macerals in a Suite of Thermally Altered Coals by Confocal Raman.

Thermally altered coals affect the safety and efficiency of coal mining and utilization, but most studies of thermally altered coal have only focused on the whole coal instead of on different macerals. Thermally altered coals have complex and special maceral components; not only intrinsic macerals but also newly formed macerals such as pyrolytic carbon can be observed. The shape and texture of intrinsic macerals also change significantly after thermal alteration, especially for vitrinite.

Heavy metals in soil-vegetable system around E-waste site and the health risk assessment.

Investigating the farmland quality around electronic waste (E-waste) dismantling site and taking positive measures to ensure local food safety are urgent. Eleven types of vegetables (n = 184) and their corresponding soils were collected from vegetable fields in a city with famous historical e-waste activities in China. Nemerow integrated pollution indices analysis revealed that local vegetable fields suffered from heavy metal pollution to a certain extent, especially with regards to Cd, Cu, and Zn.

An interpretable self-adaptive deep neural network for estimating daily spatially-continuous PM concentrations across China.

Accurate estimation of daily spatially-continuous PM (fine particulate matter) concentration is a prerequisite to address environmental public health issues, and satellite-based aerosol optical depth (AOD) products have been widely used to estimate PM concentrations using statistical-based or machine learning-based models. However, statistical-based models oversimplify the AOD-PM relationships, whereas complex machine learning technologies ignore the spatiotemporal heterogeneity of the predictors and demonstrate shortage in interpretation. Besides, large AOD data gaps resulting in PM estimation biases have been seldom imputed in previous studies, especially at national scales.

The impact of climate changes on the water footprint of wheat and maize production in the Nile Delta, Egypt.

Spatial-temporal information of different water resources is essential to rationally manage, sustainably develop, and optimally utilize water. This study focused on simulating future water footprint (WF) of two agronomically important crops (i.e.

Evaluation of satellite rainfall products for modeling water yield over the source region of Blue Nile Basin.

Rainfall data is a vital input for many ecosystem service modeling in general and hydrological modeling in particular. However, accurate rainfall data with sufficient spatiotemporal distribution is inadequate in the Blue Nile Basin (Ribb watershed) due to uneven distribution of rain gauge networks. Advances in remote sensing science have provided alternative sources of rainfall data with high spatiotemporal resolution.

Mapping the fine-scale spatial pattern of artificial light pollution at night in urban environments from the perspective of bird habitats.

The increase in artificial light at night (ALAN) is a global concern, while the pattern of ALAN pollution inside urban areas has not yet been fully explored. To fill this gap, we developed a novel method to map fine-scale ALAN pollution patterns in urban bird habitats using high spatial resolution ALAN satellite data. First, an ALAN pollution map was derived from JL1-3B satellite images.

Estimating Dynamic Cellular Morphological Properties via the Combination of the RTCA System and a Hough-Transform-Based Algorithm.

The xCELLigence real-time cell analysis (RTCA) system has the potential to detect cellular proliferation, migration, cytotoxicity, adherence, and remodeling. Although the RTCA system is widely recognized as a noninvasive and efficient tool for real-time monitoring of cellular fate, it cannot describe detailed cell morphological parameters, such as length and intensity. Transforming growth factor beta(TGF-β) induced the epithelial-mesenchymal transition (EMT), which produces significant changes in cellular morphology, so we used TGF-β to treat A549 epithelial cells in this study.

Assessing and mapping cultural ecosystem services supply, demand and flow of farmlands in the Hangzhou metropolitan area, China.

Despite research on monitoring and mapping cultural ecosystem services (CESs) increasing exponentially in recent years, our knowledge of the CESs of farmlands is still inadequate, particularly in megacities. Analyzing the CESs of farmlands is a daunting challenge partly due to the lack of appropriate frameworks, and partly because of paucity of information on farmland. In this paper, the maximum entropy (Maxent) model along with agricultural big data were combined to measure and map CESs supply with respect to aesthetics and recreation, within farmlands in the Hangzhou metropolitan area of China between 2010 and 2016.

Identifying the effects of land use change on sediment export: Integrating sediment source and sediment delivery in the Qiantang River Basin, China.

Dramatic land use change caused by the rapid economic development in China has impacted the sediment export dynamics in the large basin. However, how land use change affects sediment export is still poorly understood. This study provided an integrated analysis of the relationships in a "three-level" chain linked as follows: "land use change → changes in sediment source and sediment delivery → sediment export change" for a better understanding.

Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy.

Accurately quantifying the variation of urban green space is the prerequisite for fully understanding its ecosystem services. However, knowledge about the spatiotemporal dynamics of urban green space is still insufficient due to multiple challenges that remain in mapping green spaces within heterogeneous urban environments. This paper uses the city of Hangzhou to demonstrate an analysis methodology that integrates sub-pixel mapping technology and landscape analysis to fully investigate the spatiotemporal pattern and variation of hierarchical urban green space patches.

Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs.

It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006-2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis.

Identification of nitrogen, phosphorus, and potassium deficiencies in rice based on static scanning technology and hierarchical identification method.

Establishing an accurate, fast, and operable method for diagnosing crop nutrition is very important for crop nutrient management. In this study, static scanning technology was used to collect images of a rice sample's fully expanded top three leaves and corresponding sheathes. From these images, 32 spectral and shape characteristic parameters were extracted using an RGB mean value function and using the Regionprops function in MATLAB.

Monitoring urban greenness dynamics using multiple endmember spectral mixture analysis.

Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents' quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010.

Identification and assessment of potential water quality impact factors for drinking-water reservoirs.

Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection.

[Voiding urosonography with SonoVue and fluoroscopic voiding cystourethrography in evaluation of vesicoureteral reflux: a comparative study].

Objective: To assess the value of voiding urosonography (VUS) with SonoVue in evaluation of vesicoureteral reflux.

Methods: Thirty-six pediatric patients (72 pyeloureter units [PUUs]) suspected of vesicoureteral reflux underwent both VUS and fluoroscopic voiding cystourethrography (VCUG). The sensitivity of VUS and VCUG and their consistency in detecting vesicoureteral reflux as well as in grading vesicoureteral reflux were compared.

[Diagnosis study of rice leaf under phosphorus insufficiency based on spectral features of scan image and pattern recognition].

Insufficiency of phosphorus could greatly effect rice production, thus it is significant to adopt quick and nondestructive diagnosis of phosphorus content. The present paper focused on first expanded leaves with different phosphorus fertilization levels, comprehensively extracted 26 features' spectral information such as color, texture and shape etc. Single feature index analysis was conducted.

[Leaf characteristics extraction of rice under potassium stress based on static scan and spectral segmentation technique].

The timing, convenient and reliable method of diagnosing and monitoring crop nutrition is the foundation of scientific fertilization management. However, this expectation cannot be fulfilled by traditional methods, which always need excessively work on sampling, detection and analysis and even exhibit lagging timing. In the present study, stable images for potassium-stressed leaf were acquired using stationary scanning, and object-oriented segmentation technique was adopted to produce image objects.

[Application of mutual information to variable selection in diagnosis of phosphorus nutrition in rice].

The present study obtained data of rice canopy spectrum, and P and chlorophyll content at typical growth stages with different rates of P supply by means of solution experiment. The effects of P treatments on leaf P and chlorophyll content were analyzed statistically using LSD's multiple comparison at a probability of 0.05; By mutual information (MI) variable selection procedure, the optimal spectral variables were identified at 536, 630, 1040, 551 and 656 nm, and their corresponding mutual information values were 1.

[Diagnoses of rice nitrogen status based on characteristics of scanning leaf].

In the present research, the scanner was adopted as the digital image sensor, and a new method to diagnose the status of rice based on image processing technology was established. The main results are as follows: (1) According to the analysis of relations between leaf percentage nitrogen contents and color parameter, the sensitive color parameters were abstracted as B, b, b/(r+g), b/r and b/g. The leaf position (vertical spatial variation) effects on leaf chlorophyll contents were investigated, and the third fully expanded leaf was selected as the diagnosis leaf.

[Detecting land use change using PCA-enhancement and multi-source classifier from SPOT images].

Concomitant with the rapid global urbanization process, land use change detection has been the focus and "hot spot" of global change research all the time. In the present study, the rigorous orthorectification was first applied to the SPOT-5 data to guarantee precise geometric correction and image registration. Afterwards, a methodology integrating PCA-enhancement and multi-source classifier was adopted to detect the land use changes in urban area.

[Cotton identification and extraction using near infrared sensor and object-oriented spectral segmentation technique].

The real-time, effective and reliable method of identifying crop is the foundation of scientific management for crop in the precision agriculture. It is also one of the key techniques for the precision agriculture. However, this expectation cannot be fulfilled by the traditional pixel-based information extraction method with respect to complicated image processing and accurate objective identification.

[Habitat factor analysis for Torreya grandis cv. Merrillii based on spatial information technology].

Torreya grandis cv. Merrillii, a tertiary survival plant, is a rare tree species of significant economic value and expands rapidly in China. Its special habitat factor analysis has the potential value to provide guide information for its planting, management, and sustainable development, because the suitable growth conditions for this tree species are special and strict.