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Topic Review
SARS-CoV-2 Transmission in Livestock Industry and Agro-environment
The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a public health emergency that turns the year 2020–2021 into annus horribilis for millions of people across international boundaries. The interspecies transmission of this zoonotic virus and mutated variants are aided by exposure dynamics of infected aerosols, fomites and intermediate reservoirs. The spike in the first, second and third waves of coronavirus confirms that herd immunity is not yet reached and everyone including livestock is still vulnerable to the infection. Of serious concern are the communitarian nature of agrarians in the livestock sector, aerogenous spread of the virus and attendant cytocidal effect in permissive cells following activation of pathogen recognition receptors, replication cycles, virulent mutations, seasonal spike in infection rates, flurry of reinfections and excess mortalities that can affect animal welfare and food security. As the capacity to either resist or be susceptible to infection is influenced by numerous factors, identifying coronavirus-associated variants and correlating exposure dynamics with viral aerosols, spirometry indices, comorbidities, susceptible blood types, cellular miRNA binding sites and multisystem inflammatory syndrome remains a challenge where the lethal zoonotic infections are prevalent in the livestock industry, being the hub of dairy, fur, meat and egg production. This entry provides insights into the complexity of the disease burden and recommends precision smart-farming models for upscaling biosecurity measures and adoption of digitalised technologies (robotic drones) powered by multiparametric sensors and radio modem systems for real-time tracking of infectious strains in the agro-environment and managing the transition into the new-normal realities in the livestock industry.
  • 668
  • 22 Nov 2021
Topic Review
Background of Hyperspectral Change Detection
Hyperspectral image change detection (HSI-CD) is an interesting task in the Earth’s remote sensing community.  HSI-CD methods are feeble at detecting subtle changes from bitemporal HSIs, because the decision boundary is partially stretched by strong changes so that subtle changes are ignored.
  • 657
  • 01 Jul 2022
Topic Review
Assimilation of Key Data in Land Surface Models
The correction of Soil Moisture (SM) estimates in Land Surface Models (LSMs) is considered essential for improving the performance of numerical weather forecasting and hydrologic models used in weather and climate studies. Along with surface screen-level variables, the satellite data, including Brightness Temperature (BT) from passive microwave sensors, and retrieved SM from active, passive, or combined active–passive sensor products have been used as two critical inputs in improvements of the LSM.
  • 646
  • 22 Feb 2022
Biography
Qihao Weng
Dr. Qihao Weng is a Chair Professor of Geomatics and Artificial Intelligence at the Hong Kong Polytechnic University since July 2021. He worked as the Director of the Center for Urban and Environmental Change (July 2004-2021) and a Professor at Indiana State University, 2001-2021, and was a Senior Fellow at the NASA Marshall Space Flight Center from Dec. 2008 to Dec. 2009. He received his Ph.D
  • 642
  • 10 Aug 2022
Topic Review
Forest Fires on Air Quality in Wolgan Valley
Forests are an important natural resource and are instrumental in sustaining environmental sustainability. Burning biomass in forests results in greenhouse gas emissions, many of which are long-lived. Precise and consistent broad-scale monitoring of fire intensity is a valuable tool for analyzing climate and ecological changes related to fire. Remote sensing and geographic information systems provide an opportunity to improve current practice’s accuracy and performance. 
  • 639
  • 28 Dec 2021
Topic Review
Smart Irrigation
Agriculture consumes an important ratio of the water reserve in irrigated areas. The improvement of irrigation is becoming essential to reduce this high water consumption by adapting supplies to the crop needs and avoiding losses. This global issue has prompted many scientists to reflect on sustainable solutions using innovative technologies, namely Unmanned Aerial Vehicles (UAV), Machine Learning (ML), and the Internet of Things (IoT). These new technologies can be used in the analysis of the water status of crops for better irrigation management, with an emphasis on arboriculture. 
  • 638
  • 27 Apr 2023
Topic Review
Three-Dimensional Point Cloud Semantic Segmentation for Cultural Heritage
In the cultural heritage field, point clouds, as important raw data of geomatics, are not only three-dimensional (3D) spatial presentations of 3D objects but they also have the potential to gradually advance towards an intelligent data structure with scene understanding, autonomous cognition, and a decision-making ability. The approach of point cloud semantic segmentation as a preliminary stage can help to realize this advancement.
  • 630
  • 09 Mar 2023
Topic Review
Cellular Automata in Modeling and Predicting Urban Densification
The creation of an accurate simulation of future urban growth is considered to be one of the most important challenges of the last five decades that involves spatial modeling within a GIS environment. Even though built-up densification processes, or transitions from low to high density, are critical for policymakers concerned with limiting sprawl, the literature on models for urban study reveals that most of them focus solely on the expansion process. Although the majority of these models have similar goals, they differ in terms of implementation and theoretical assumptions. Cellular automata (CA) models have been proven to be successful at simulating urban growth dynamics and projecting future scenarios at multiple scales.
  • 622
  • 05 Aug 2022
Topic Review
Applications and Outlook of Soil Moisture Products
Soil moisture (SM), the moisture content in the soil, is a crucial component in the hydrological cycle; it links atmospheric precipitation and underground water and is also an important parameter of energy exchange between the land surface and the atmosphere. Consequently, SM is recognized as an essential element in studies aimed at analyzing and understanding Earth system processes, such as climate change and ecological evolution. Specifically, the available water content, which is essential for vegetation growth, is one of the most important components of soil and has crucial guiding significance for agricultural production. Currently, both ground and spaceborne sensors are used to derive the original SM information. Numerous technologies, such as statistical models, data fusion, machine learning, and assimilation approaches, are widely used to improve SM quality. Additionally, SM datasets with high spatial-temporal resolution are valuable for boosting agricultural production in terms of drought and flood monitoring, crop growth analysis, and yield estimation.
  • 589
  • 11 Aug 2022
Topic Review
Urban Remote Sensing with Spatial Big Data
During the past decades, multiple remote sensing data sources, including nighttime light images, high spatial resolution multispectral satellite images, unmanned drone images, and hyperspectral images, among many others, have provided fresh opportunities to examine the dynamics of urban landscapes. In the meantime, the rapid development of telecommunications and mobile technology, alongside the emergence of online search engines and social media platforms with geotagging technology, has fundamentally changed how human activities and the urban landscape are recorded and depicted. The combination of these two types of data sources results in explosive and mind-blowing discoveries in contemporary urban studies, especially for the purposes of sustainable urban planning and development. Urban scholars are now equipped with abundant data to examine many theoretical arguments that often result from limited and indirect observations and less-than-ideal controlled experiments. For the first time, urban scholars can model, simulate, and predict changes in the urban landscape using real-time data to produce the most realistic results, providing invaluable information for urban planners and governments to aim for a sustainable and healthy urban future. 
  • 589
  • 14 Apr 2023
Topic Review
Grain Quality On-Farm
Grains intended for human consumption or feedstock are typically high-value commodities that are marketed based on either their visual characteristics or compositional properties. The combination of visual traits, chemical composition and contaminants is generally referred to as grain quality.
  • 584
  • 27 Apr 2023
Topic Review
Irrigation Information Retrievals
Irrigation represents one of the most impactful human interventions in the terrestrial water cycle. Knowing the distribution and extent of irrigated areas as well as the amount of water used for irrigation plays a central role in modeling irrigation water requirements and quantifying the impact of irrigation on regional climate, river discharge, and groundwater depletion. Obtaining high-quality global information about irrigation is challenging, especially in terms of quantification of the water actually used for irrigation.
  • 574
  • 20 Dec 2021
Topic Review
PCO2 in Inland Waters
The traditional field-based measurements of carbon dioxide (pCO2) for inland waters are a snapshot of the conditions on a particular site, which might not adequately represent the pCO2 variation of the entire lake. However, these field measurements can be used in the pCO2 remote sensing modeling and verification. By focusing on inland waters (including lakes, reservoirs, rivers, and streams), this paper reviews the temporal and spatial variability of pCO2 based on published data. The results indicate the significant daily and seasonal variations in pCO2 in lakes. 
  • 552
  • 31 Jan 2022
Topic Review
STEPLand Framework
This contribution assesses a new term that is proposed to be established within Land Change Science: Spatio-TEmporal Patterns of Land (‘STEPLand’). It refers to a specific workflow for analyzing land-use/land cover (LUC) patterns, identifying and modeling driving forces of LUC changes, assessing socio-environmental consequences, and contributing to defining future scenarios of land transformations. Researchers define this framework based on a comprehensive metaanalysis of 250 selected articles published in international scientific journals from 2000 to 2019. The empirical results demonstrate that STEPLand is a consolidated protocol applied globally, and the large diversity of journals, disciplines, and countries involved shows that it is becoming ubiquitous. The main characteristics of STEPLand are provided and discussed, demonstrating that the operational procedure can facilitate the interaction among researchers from different fields, and communication between researchers and policy makers.
  • 549
  • 29 Jul 2022
Topic Review
Microseismic Monitoring and Analysis with Cutting-Edge Technology
Microseismic monitoring is a useful enabler for reservoir characterization without which the information on the effects of reservoir operations such as hydraulic fracturing, enhanced oil recovery, carbon dioxide, or natural gas geological storage would be obscured. The global energy demand is projected to increase. To meet the increasing energy demand requires new technologies to exploit unconventional reserves. Similarly, calls for climate actions such as carbon geosequestration, hydrogen generation, and geological hydrogen storage will require an improvement in reservoir characterization methods.
  • 546
  • 02 Aug 2022
Topic Review
Geographic Information System Applied to Sustainability Assessments
The conceptual variations and divergences that permeate the debate on sustainability end up directly reflecting the choice of sustainability assessment (SA) processes, providing different methodological approaches. Among them, some researchers have pointed out challenges, but also opportunities to use geospatial data, techniques, and tools as resources to be explored in sustainability assessments.
  • 546
  • 25 Nov 2022
Topic Review
Shoreline Mapping Using Airborne LiDAR
Since the shorelines are important geographical boundaries, monitoring shoreline change plays an important role in integrated coastal management. With the evolution of remote sensing technology, many studies have used optical images to measure and to extract shoreline. However, some factors limit the use of optical imaging on shoreline mapping. Considering that airborne LiDAR data can provide more accurate topographical information, they are used to map shorelines. There are two major types of airborne LiDAR systems that are commonly used in shoreline area surveys: the airborne laser topographic scanning system (ALT) and the airborne laser bathymetric scanning system (ALB).
  • 530
  • 20 Feb 2023
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.
  • 529
  • 20 May 2022
Topic Review
Precision Oliviculture
Precision oliviculture (PO) is having an increasing scientific interest and impact on the sector. Its implementation depends on various technological developments: sensors for local and remote crop monitoring, global navigation satellite system (GNSS), equipment and machinery to perform site-specific management through variable rate application (VRA), implementation of geographic information systems (GIS), and systems for analysis, interpretation, and decision support (DSS). 
  • 520
  • 26 May 2022
Topic Review
Weakly Supervised Object Detection for Remote Sensing Images
To account for the lack of fine-grained annotations, such as object bounding boxes, several object detection methods have been developed that leverage only coarse-grain annotations (especially image-level labels indicating only the presence or absence of an object). This approach is called inexact Weak Supervision and introduces a new branch of Object Detection called Weakly Supervised Object Detection. Given an image, Remote Sensing Fully Supervised Object Detection (RSFSOD) aims to locate and classify objects based on Bounding Boxes annotations. Differently from RSFSOD, Remote Sensing Weakly Supervised Object Detection aims to precisely locate and classify object instances in Remote Sensing Images using only image-level labels or other types of coarse-grained labels (e.g., points or scribbles) as ground truth. 
  • 478
  • 24 Nov 2022
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