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Topic Review
Removal of Dyestuffs from Effluents onto Biochar
Processing significant amounts of dye effluent discharges into receiving waters can supply major benefits to countries that are affected by the water crisis and anticipated future stress in many areas in the world. When compared to most conventional adsorbents, biochars can provide an economically attractive solution. In comparison to many other textile effluent treatment processes, adsorption technology provides an economical, easily managed, and highly effective treatment option.
  • 585
  • 20 Jun 2022
Topic Review
Remote Sensing, Geophysics, and Modeling in Precision Agriculture
Remote sensing provides information about the soil surface (or even a few centimeters below), while near-surface geophysics can characterize the subsoil. Results from the methods mentioned above can be used as an input model for soil and/or soil/water interaction modeling. The soil modeling offers a better explanation of complex physicochemical processes in the vadose zone. 
  • 353
  • 25 Apr 2022
Topic Review
Remote Sensing Technique in Rice Weed Detection
Remote sensing technology aims to monitor and capture the earth’s information without making direct contact and destroying it. The utilization of the electromagnetic spectrum, ranging from visible to microwave for measuring the earth’s properties, is the main idea behind remote sensing technology. Machine learning (ML) and deep learning (DL) remote sensing techniques have successfully produced a high accuracy map for detecting weeds in crops using RS platforms. Therefore, this technology positively impacts weed management in many aspects, especially in terms of the economic perspective. The implementation of this technology into agricultural development could be extended further. 
  • 1.1K
  • 13 Dec 2021
Topic Review
Remote Sensing of Urban Vegetation
Green space is increasingly recognized as an important component of the urban environment yet inventorying urban vegetation is a costly and time-consuming process. Various types of remote sensing can be used in the automated mapping of urban vegetation. 
  • 745
  • 21 Mar 2022
Topic Review
Remote Sensing of Geomorphodiversity Linked to Biodiversity
Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring of traits and trait variations of geomorphology and its processes, from the local to the continental scale. RS technologies can record geomorphic traits, their diversity and variations, from which the other four geomorphodiversity characteristics are derived. However, compared to in situ measurements, RS approaches can only record certain parts of these geomorphic traits and their variations. This is because capturing geomorphic traits and diversity using RS approaches is limited by various constraints, namely: (1) the characteristics and spatial-temporal distribution of geomorphic traits; (2) the characteristics of geomorphological processes; as well as (3) the RS sensor characteristics, the chosen RS platforms and the characteristics of RS data-processing and classification information. These constraints and limitations define the detectability, feasibility, accuracy, depth of information, repeatability, and, thus, standards disability in monitoring the five geomorphic characteristics using RS approaches.
  • 424
  • 20 May 2022
Topic Review
Remote Sensing Monitoring Approaches
Meteorological disaster monitoring is an important research direction in remote sensing technology in the field of meteorology, which can serve many meteorological disaster management tasks. The key issues in the remote sensing monitoring of meteorological disasters are monitoring task arrangement and organization, meteorological disaster information extraction, and multi-temporal disaster information change detection. To accurately represent the monitoring tasks, it is necessary to determine the timescale, perform sensor planning, and construct a representation model to monitor information. On this basis, the meteorological disaster information is extracted by remote sensing data-processing approaches. Furthermore, the multi-temporal meteorological disaster information is compared to detect the evolution of meteorological disasters. Due to the highly dynamic nature of meteorological disasters, the process characteristics of meteorological disasters monitoring have attracted more attention. Although many remote sensing approaches were successfully used for meteorological disaster monitoring, there are still gaps in process monitoring. In future, research on sensor planning, information representation models, multi-source data fusion, etc., will provide an important basis and direction to promote meteorological disaster process monitoring.
  • 424
  • 19 Apr 2022
Topic Review
Remote Sensing in Wind Erosion Studies
Remote sensing (RS) has revolutionized field data collection processes and provided timely and spatially consistent acquisition of data on the terrestrial landscape properties. The study of wind erosion involves a range of research techniques, such as laboratory and field measurements, modelling, and the use of remote sensing (RS) technologies.
  • 332
  • 22 Aug 2023
Topic Review
Remote Sensing in Water Quality Parameters Monitoring
Remote sensing (RS) applications offer the opportunity for decisionmakers to quantify and monitor water quality parameters (WQPs) on a spatiotemporal scale effectively. The use of RS for water quality monitoring has been explored in many studies using empirical, analytical, semi-empirical, and machine-learning algorithms. RS spectral signatures have been applied for the estimation of WQPs using two categories of RS, namely, microwave and optical sensors. Optical RS, which has been heavily applied in the estimation of WQPs, is further grouped as spaceborne and airborne sensors based on the platform they are on board. The choice of a particular sensor to be used in any RS application depends on various factors including cost, and spatial, spectral, and temporal resolutions of the images.
  • 354
  • 19 Apr 2023
Topic Review
Remote Sensing in Coastal Areas
Coastal areas are regions of remarkable relevance for humans, providing essential components for social and economic development from the local to the national scale. To preserve the economic and ecological sustainability of the coastal environment, the scientific community has been pushing for the use of integrated observation systems aimed at monitoring such susceptible areas. Remote sensing data can complement traditional field measurements, ensuring almost continuous synoptic coverage with a good trade-off between spatial and temporal resolution, thus allowing for a timely characterization of coastal environment dynamics. In particular, the availability of a multi-temporal historical series of remote sensing data can provide useful information on the spatiotemporal variability of hydrological (sea surface currents, river runoff/discharge), biological (phytoplankton blooms, primary productivity) and physical (temperature, salinity, and turbidity) properties of coastal waters as well as on human-induced land cover mutations (deforestation, surface urban islands).  This Special Issue seeks to collect high-quality papers focused on satellite-based applications for monitoring coastal areas, continental shelves and estuarine ecosystems.
  • 697
  • 29 Oct 2020
Topic Review
Remote Sensing Image Feature Learning Approaches
Deep learning approaches are gaining popularity in image feature analysis and in attaining state-of-the-art performances in scene classification of remote sensing imagery. There is an increase of remote sensing datasets with diverse scene semantics; this renders computer vision methods challenging to characterize the scene images for accurate scene classification effectively.
  • 201
  • 21 Jun 2023
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