Recent Developments to the SimSphere Land Surface Modelling Tool for the Study of Land-Atmosphere Interactions.

Soil-Vegetation-Atmosphere Transfer (SVAT) models are a promising avenue towards gaining a better insight into land surface interactions and Earth's system dynamics. One such model developed for the academic and research community is the SimSphere SVAT model, a popular software toolkit employed for simulating interactions among the layers of vegetation, soil, and atmosphere on the land surface. The aim of the present review is two-fold: (1) to deliver a critical assessment of the model's usage by the scientific and wider community over the last 15 years, and (2) to provide information on current software developments implemented in the model.

Snow Cover Response to Climatological Factors at the Beas River Basin of W. Himalayas from MODIS and ERA5 Datasets.

Glaciers and snow are critical components of the hydrological cycle in the Himalayan region, and they play a vital role in river runoff. Therefore, it is crucial to monitor the glaciers and snow cover on a spatiotemporal basis to better understand the changes in their dynamics and their impact on river runoff. A significant amount of data is necessary to comprehend the dynamics of snow.

Exploring the spatial patterns of soil salinity and organic carbon in agricultural areas of Lesvos Island, Greece, using geoinformation technologies.

The salt-affected soils national map of Greece was recently made available within the initiative of the Global Soil Partnership (GSP) of Food and Agriculture Organization of the United Nations FAO. The present study explores the development of higher resolution soil property maps included in this national scale product adopting a modified version of the FAO methodology and a logistic regression (LR) method based on ground and satellite data. Furthermore, it also investigates the correlation between saline soils and soil organic carbon (SOC) using geospatial analysis methods.

The impact of COVID-19 pandemic on air pollution: a global research framework, challenges, and future perspectives.

As a result of extreme modifications in human activity during the COVID-19 pandemic, the status of air quality has recently been improved. This bibliometric study was conducted on a global scale to quantify the impact of the COVID-19 pandemic on air pollution, identify the emerging challenges, and discuss the future perspectives during the course of the ongoing COVID-19 pandemic. For this, we have estimated the scientific production trends between 2020 and 2021 and investigated the contributions of countries, institutions, authors, and most prominent journals metrics network analysis on the topic of COVID-19 combined with air pollution research spanning the period between January 01, 2020, and June 21, 2021.

Synergistic Evaluation of Passive Microwave and Optical/IR Data for Modelling Vegetation Transmissivity towards Improved Soil Moisture Retrieval.

Vegetation cover and soil surface roughness are vital parameters in the soil moisture retrieval algorithms. Due to the high sensitivity of passive microwave and optical observations to Vegetation Water Content (), this study assesses the integration of these two types of data to approximate the effect of vegetation on passive microwave Brightness Temperature () to obtain the vegetation transmissivity parameter. For this purpose, a newly introduced index named Passive microwave and Optical Vegetation Index () was developed to improve the representativeness of and converted into vegetation transmissivity through linear and nonlinear modelling approaches.

Pollution characteristics and human health risk assessments of toxic metals and particle pollutants via soil and air using geoinformation in urbanized city of Pakistan.

Toxic metals and particle pollutants in urbanized cities have significantly increased over the past few decades mainly due to rapid urbanization and unplanned infrastructure. This research aimed at estimating the concentration of toxic metals and particle pollutants and the associated risks to public health across different land-use settings including commercial area (CA), urban area (UA), residential area (RA), and industrial area (IA). A total of 47 samples for both soil and air were collected from different land-use settings of Faisalabad city in Pakistan.

Investigating connections between COVID-19 pandemic, air pollution and community interventions for Pakistan employing geoinformation technologies.

Several major cities that witnessed heavy air pollution by particulate matter (PM) concentration and nitrogen dioxide (NO) have contributed to high rate of infection and severity of the coronavirus disease (COVID-19) pandemic. Owing to the negative impact of COVID-19 on health and economy, it is imperative to predict the pandemic trend of the COVID-19 outbreak. Pakistan is one of the mostly affected countries by recent COVID-19 pandemic in terms of COVID-cases and economic crises.

Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan.

Information on the spatiotemporal variability of respirable suspended particulate pollutant matter concentrations, especially of particles having size of 2.5 μm and climate are the important factors in relation to emerging COVID-19 cases around the world. This study aims at examining the association between COVID-19 cases, air pollution, climatic and socioeconomic factors using geospatial techniques in three provincial capital cities and the federal capital city of Pakistan.

Heavy Metal Soil Contamination Detection Using Combined Geochemistry and Field Spectroradiometry in the United Kingdom.

Technological advances in hyperspectral remote sensing have been widely applied in heavy metal soil contamination studies, as they are able to provide assessments in a rapid and cost-effective way. The present work investigates the potential role of combining field and laboratory spectroradiometry with geochemical data of lead (Pb), zinc (Zn), copper (Cu) and cadmium (Cd) in quantifying and modelling heavy metal soil contamination (HMSC) for a floodplain site located in Wales, United Kingdom. The study objectives were to: (i) collect field- and lab-based spectra from contaminated soils by using ASD FieldSpec 3, where the spectrum varies between 350 and 2500 nm; (ii) build field- and lab-based spectral libraries; (iii) conduct geochemical analyses of Pb, Zn, Cu and Cd using atomic absorption spectrometer; (iv) identify the specific spectral regions associated to the modelling of HMSC; and (v) develop and validate heavy metal prediction models (HMPM) for the aforementioned contaminants, by considering their spectral features and concentrations in the soil.

An Operational In Situ Soil Moisture & Soil Temperature Monitoring Network for West Wales, UK: The WSMN Network.

This paper describes a soil moisture dataset that has been collecting ground measurements of soil moisture, soil temperature and related parameters for west Wales, United Kingdom. Already acquired in situ data have been archived to the autonomous Wales Soil Moisture Network (WSMN) since its foundation in July 2011. The sites from which measurements are being collected represent a range of conditions typical of the Welsh environment, with climate ranging from oceanic to temperate and a range of the most typical land use/cover types found in Wales.

A comparison of Spectral Angle Mapper and Artificial Neural Network classifiers combined with Landsat TM imagery analysis for obtaining burnt area mapping.

Satellite remote sensing, with its unique synoptic coverage capabilities, can provide accurate and immediately valuable information on fire analysis and post-fire assessment, including estimation of burnt areas. In this study the potential for burnt area mapping of the combined use of Artificial Neural Network (ANN) and Spectral Angle Mapper (SAM) classifiers with Landsat TM satellite imagery was evaluated in a Mediterranean setting. As a case study one of the most catastrophic forest fires, which occurred near the capital of Greece during the summer of 2007, was used.