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Topic Review
Advanced Agriculture Technology
The agricultural industry is getting more data-centric and requires precise, more advanced data and technologies than before, despite being familiar with agricultural processes. The agriculture industry is being advanced in generating database by various information and advanced communication technologies, such as the Internet of Things (IoT). 
  • 7.7K
  • 25 May 2021
Topic Review
Land Suitability Assessment
Land suitability assessment is a method of land evaluation, which identifies the major limiting factors for planting a particular crop. Land suitability assessment includes qualitative and quantitative evaluation. In the qualitative land suitability evaluations, information about climate, hydrology, topography, vegetation, and soil properties is considered and in quantitative assessment, the results are more detailed and yield is estimated. At present study we prepared land suitability assessment map for rain-fed wheat and barley crops based on FAO "land suitability assessment framework" using parametric method and machine learning algorithms in Kurdistan Province, located in west of Iran. This is a unique study that compared two machine learning-based and traditional-based approaches for mapping current and potential future land suitability classes. Moreover, potential yield of rain-fed wheat and barley crop were computed by FAO model.
  • 6.1K
  • 30 Oct 2020
Topic Review
New Seismotectonic Atlas of Greece
Integration and harmonization of the most recent seismological, geological, tectonic, geophysical and geodetic datasets, with the aim of capturing the potential of ground deformation towards a more reliable evaluation of seismic risk at a national level.
  • 5.9K
  • 20 Nov 2020
Topic Review
Early Flood Warning System
The early-warning model for flash floods is based on a hydrological and geomorphological concept connected to the river basin, with the principle that flash floods will only occur where there is a high potential risk and when rainfall exceeds the threshold. In the model used to build flash-floods risk maps, the parameters of the basin are analyzed and evaluated and the weight is determined using Thomas Saaty’s analytic hierarchy process (AHP). The flash-floods early-warning software is built using open source programming tools. With the spatial module and online processing, a predicted precipitation of one to six days in advance for iMETOS (AgriMedia—Vietnam) automatic meteorological stations is interpolated and then processed with the potential risk maps (iMETOS is a weather-environment monitoring system comprising a wide range of equipment and an online platform and can be used in various fields such as agriculture, tourism and services). The results determine the locations of flash floods at several risk levels corresponding to the predicted rainfall values at the meteorological stations. The system was constructed and applied to flash floods disaster early warning for Thuan Chau in Son La province when the rainfall exceeded the 150 mm/d threshold. The system initially supported positive decision-making to prevent and minimize damage caused by flash floods.
  • 5.4K
  • 27 Jan 2022
Topic Review
Artificial Intelligence in Archaeology
Artificial Intelligence (AI), due to its increasingly powerful predictive capabilities, is showing an increasing trend in attracting widespread interest in many sciences. Archaeologists now can more fully exploit the knowledge from an extensive amount of archaeological data with the use of artificial intelligence in such a way as to make decisions related to appropriate strategies for the preservation and protection of archaeological elements, as well as to decide on the most ideal point excavation in a complex cultural landscape. 
  • 5.1K
  • 30 Nov 2022
Topic Review
Application of Google Earth Engine
Google Earth Engine (GEE) is a cloud computing platform that was launched by Google in 2010. Since then, GEE has demonstrated its capacity of preprocessing and mining of geographic big data. GEE enables cloud computation and is an effective tool for carrying out the analysis of global geospatial big data.
  • 4.0K
  • 08 Oct 2021
Topic Review
Landsat 8 and Landsat 9
With the launch of Landsat 9 in September 2021, an optimal opportunity for in-flight cross-calibration occurred when Landsat 9 flew underneath Landsat 8 while being moved into its final orbit. Since the two instruments host nearly identical imaging systems, the underfly event offered ideal cross-calibration conditions. Using the underfly imagery collected by the instruments to estimate cross-calibration parameters for Landsat 9 for a calibration update scheduled at the end of the on-orbit initial verification (OIV) period was studied. Three types of uncertainty were considered: geometric, spectral, and angular (bidirectional reflectance distribution function—BRDF). Differences caused by geometric uncertainty were found to be negligible for this application. 
  • 3.9K
  • 01 Jun 2022
Topic Review
Precision Spraying
Precision spraying, defined as the targeted spraying, obtains the target information (e.g., size, shape, structure, and canopy density, etc.) of the tree and then apply pesticides as needed. It addresses overdosing or underdosing problem by efficiently applying pesticides to the target area and substantially reducing pesticide usage while maintaining efficacy at preventing crop losses.
  • 2.4K
  • 24 May 2021
Topic Review
LiDAR-Derived DEM in Flood Applications
Flood occurrence is increasing due to escalated urbanization and extreme climate change; hence, various studies on this issue and methods of flood monitoring and mapping are also increasing to reduce the severe impacts of flood disasters. The advancement of current technologies such as light detection and ranging (LiDAR) systems facilitated and improved flood applications. Since the conventional methods cannot produce high-resolution digital elevation model (DEM) data, which results in low accuracy of flood simulation results, LiDAR data are extensively used as an alternative. This review aims to study the potential and the applications relevant to flood studies from a LiDAR-derived DEM perspective. It also provides insight into the operating principles of different LiDAR systems, system components, and advantages and disadvantages of each system. Furthermore, the challenges and future perspectives regarding DEM LiDAR data for flood mapping and assessment are also discussed. This study demonstrates that LiDAR-derived data are useful in flood risk management, especially in the future assessment of flood-related problems.  
  • 2.3K
  • 04 Aug 2020
Topic Review
Attention Mechanism for Remote Sensing
Machine learning, particularly deep learning (DL), has become a central and state-of-the-art method for several computer vision applications and remote sensing (RS) image processing. Researchers are continually trying to improve the performance of the DL methods by developing new architectural designs of the networks and/or developing new techniques, such as attention mechanisms. Since the attention mechanism has been proposed, regardless of its type, it has been increasingly used for diverse RS applications to improve the performances of the existing DL methods.
  • 2.2K
  • 24 Nov 2021
Topic Review
Hyperspectral Remote Sensing and Plant
Hyperspectral remote sensing provides image data with very high spectral resolution. This high resolution allows subtle differences in plant health to be recognized. Such a multidimensional data space, generated by hyperspectral sensors, has given rise to new approaches and methods for analyzing hyperspectral data.
  • 2.0K
  • 31 Jan 2022
Topic Review
Environmental Monitoring Applications
Concerns about global environmental challenges, such as the alarming increase in pollution of oceans, waterways, land, and air, are becoming more and more prevalent in contemporary society. Environmental pollution has evolved into more than a health concern because of global industrialization and mass consumption patterns; it now represents a danger to whole ecosystems. It is critical to comprehend its causes and mitigation strategies. Adequate and timely environmental data are required for risk forecasting and early warning for environmental disasters.
  • 2.0K
  • 23 Nov 2022
Topic Review
Global Open-Data Remote-Sensing Satellite Missions
The application of global open data remote sensing satellite missions is in the state of rapid growth, ensuring an observation with high spatial and spectral resolution over large areas. Multispectral (Landsat, Sentinel-2, and MODIS), radar (Sentinel-1), and digital elevation model missions (SRTM, ASTER) were analyzed, as the most often used global open data satellite missions, according to the number of scientific research articles published in Web of Science database. Processing methods of these missions’ data consisting of image preprocessing, spectral indices, image classification methods, and modelling of terrain topographic parameters were analyzed and demonstrated. Possibilities of their application in land cover, land suitability, vegetation monitoring, and natural disaster management were evaluated, having high potential in broad use worldwide. Availability of free and complementary satellite missions, as well as the open-source software, ensures the basis of effective and sustainable land use management, with the prerequisite of the more extensive knowledge and expertise gathering at a global scale.
  • 1.8K
  • 12 Nov 2020
Topic Review
The Use of Green Laser in LiDAR Bathymetry
Bathymetric LiDAR technology is a technology used for simultaneous data acquisition regarding the morphology of the bottom of water reservoirs and the surrounding coastal zone, realized from the air, e.g., by plane or drone. Contrary to the air topographic LiDAR, which uses an infrared wavelength of 1064 nm, bathymetric LiDAR systems additionally use a green wavelength of 532 nm. The green laser can penetrate the water, which makes it possible to measure the depth of shallow water reservoirs, rivers, and coastal sea waters within three Secchi depths.
  • 1.8K
  • 13 Jan 2023
Topic Review
Application of GIS in Agriculture
GIS technology application in agriculture has gained prominence. The main GIS application areas identified included: crop yield estimation, soil fertility assessment, cropping patterns monitoring, drought assessment, pest and crop disease detection and management, precision agriculture, and fertilizer and weed management. GIS technology has the potential to enhance agriculture sustainability by integrating the spatial dimension of agriculture into agriculture policies. In addition, GIS's potential in promoting evidence-informed decision-making is growing. There is, however, a big gap in GIS application in sub-Saharan Africa. With the growing threat of climate change to agriculture and food security, there is an increased need for the integration of GIS in policy and decision-making in improving agriculture sustainability.
  • 1.8K
  • 09 Sep 2022
Topic Review
Remote Sensing and Deep Learning
The advances in remote sensing technologies, hence the fast-growing volume of timely data available at the global scale, offer new opportunities for a variety of applications. Deep learning being significantly successful in dealing with Big Data, is a great candidate for exploiting the potentials of such complex massive data. However, with remote sensing, there are some challenges related to the ground-truth, resolution, and the nature of data that require further efforts and adaptions of deep learning techniques.
  • 1.7K
  • 26 Jan 2021
Topic Review
Image-Based Obstacle Detection Methods
Mobile robots lack a driver or a pilot and, thus, should be able to detect obstacles autonomously. These various image-based obstacle detection techniques include Unmanned Surface Vehicles (USVs), Unmanned Aerial Vehicles (UAVs), and Micro Aerial Vehicles (MAVs). The techniques were divided into monocular and stereo. The former uses a single camera, while the latter makes use of images taken by two synchronised cameras. Monocular obstacle detection methods are discussed in appearance-based, motion-based, depth-based, and expansion-based categories. Monocular obstacle detection approaches have simple, fast, and straightforward computations. Thus, they are more suited for robots like MAVs and compact UAVs, which usually are small and have limited processing power. On the other hand, stereo-based methods use pair(s) of synchronised cameras to generate a real-time 3D map from the surrounding objects to locate the obstacles. Stereo-based approaches have been classified into Inverse Perspective Mapping (IPM)-based and disparity histogram-based methods. Whether aerial or terrestrial, disparity histogram-based methods suffer from common problems: computational complexity, sensitivity to illumination changes, and the need for accurate camera calibration, especially when implemented on small robots.
  • 1.5K
  • 24 Oct 2022
Topic Review
LCM Model
Cellular Automata-Markov chain (CA-Markov) model is a general method that has been widely used to predict LUCC. However, the process of this treditional model is subjective and stochastic, which makes it's modeling capacity limited. For precisely detecting the LUCC and their driving factors, we introduced the Logistic regression method to integrate with the treditional CA-Markov model (Logistic-CA-Markov model, LCM), to improve the preformance of modeling LUCC. This model would hopefully provide theoretical instructions for future land use planning and management, as well as a new methodology reference for LUCC analysis.
  • 1.4K
  • 29 Oct 2020
Topic Review
Multispectral Image
Multispectral imaging captures image data within specific wavelength ranges across the electromagnetic spectrum. The wavelengths may be separated by filters or detected with the use of instruments that are sensitive to particular wavelengths, including light from frequencies beyond the visible light range, i.e. infrared and ultra-violet. Spectral imaging can allow extraction of additional information the human eye fails to capture with its visible receptors for red, green and blue. It was originally developed for military target identification and reconnaissance. Early space-based imaging platforms incorporated multispectral imaging technology to map details of the Earth related to coastal boundaries, vegetation, and landforms. Multispectral imaging has also found use in document and painting analysis. Multispectral imaging measures light in a small number (typically 3 to 15) of spectral bands. Hyperspectral imaging is a special case of spectral imaging where often hundreds of contiguous spectral bands are available.
  • 1.4K
  • 21 Oct 2022
Topic Review
Google Earth Engine and Artificial Intelligence
Remote sensing (RS) plays an important role gathering data in many critical domains (e.g., global climate change, risk assessment and vulnerability reduction of natural hazards, resilience of ecosystems, and urban planning). Retrieving, managing, and analyzing large amounts of RS imagery poses substantial challenges. Google Earth Engine (GEE) provides a scalable, cloud-based, geospatial retrieval and processing platform. GEE also provides access to the vast majority of freely available, public, multi-temporal RS data and offers free cloud-based computational power for geospatial data analysis. Artificial intelligence (AI) methods are a critical enabling technology to automating the interpretation of RS imagery, particularly on object-based domains, so the integration of AI methods into GEE represents a promising path towards operationalizing automated RS-based monitoring programs. 
  • 1.3K
  • 15 Aug 2022
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