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Topic Review
Deep Learning-Based Change Detection
Change detection based on remote sensing images plays an important role in the field of remote sensing analysis, and it has been widely used in many areas, such as resources monitoring, urban planning, disaster assessment, etc. With the improved spatial resolution of remote sensing images, many deep learning methods have been proposed for aerial and satellite image change detection. Depending on the granularity of the detection unit, these methods can be roughly classified into two main categories : scene-level methods (SLCDs) and region-level methods (RLCDs). These two categories are not necessarily independent of each other, and sometimes, the same change detection process may be present in different methods simultaneously.
  • 1.3K
  • 01 Apr 2022
Topic Review
Weeds in Agricultural Fields
Weeds are significant contributors to the decline in crop yield and quality. Weeds compete with crops in terms of nutrients, water, and sunlight.
  • 1.3K
  • 18 Jan 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. 
  • 1.3K
  • 13 Dec 2021
Topic Review
Machine Learning for Crop Disease
Crop diseases constitute a serious issue in agriculture, affecting both quality and quantity of agriculture production. Disease control has been a research object in many scientific and technologic domains. Technological advances in sensors, data storage, computing resources and artificial intelligence have shown enormous potential to control diseases effectively. A growing body of literature recognizes the importance of using data from different types of sensors and machine learning approaches to build models for detection, prediction, analysis, assessment, etc. However, the increasing number and diversity of research studies requires a literature review for further developments and contributions in this area. 
  • 1.2K
  • 24 Nov 2021
Topic Review
Measurement and Monitoring of TDS and TSS
Total dissolved solids (TDS) and total suspended solids (TSS) have traditionally been analyzed and monitored through field or in situ sampling and laboratory testing generally classified as conventional methods. Field and laboratory measurements include grab sampling, filtering, and evaporating a sample through a fine filter paper followed by drying in an air oven which are collectively known as gravimetric methods. Conventional methods of monitoring of water quality parameters (WQPs) are, however, cost-prohibitive, labor-intensive, time-consuming, and, also not suitable for large-scale analysis.
  • 1.2K
  • 21 Jul 2023
Topic Review
Urban Growth Boundary
With the rapid and unregulated nature of urban expansion occurring in Chattogram, Bangladesh, the adoption of urban growth restriction mechanisms such as the urban growth boundary (UGB) can provide a robust framework necessary to direct the development of built-up areas in a way that curtails the growth in environmentally sensitive areas of the city. UGBs, in simple terms, can be defined as land regulations that have been put into place, in most cases, by the local government to prohibit urban growth and development beyond a defined boundary. The UGBs are designed to protect non-urban land outside the boundary and to promote compact, contiguous, and sustainable urban development. The UGB, as an urban growth policy tool, has been implemented in a wide variety of cities in both the developed and the developing world.
  • 1.2K
  • 20 May 2022
Topic Review
Land Use Land Cover Modeling
Land use land cover (LULC) modeling is considered as the best tool to comprehend and unravel the dynamics of future urban expansion.
  • 1.1K
  • 06 Feb 2023
Topic Review
Measuring Urban Shrinkage
Most of the shrinking cities experience an unbalanced de-urbanization across different urban areas in cities. However, traditional ways of measuring urban shrinkage are focused on tracking population loss at the city level and are unable to capture the spatially heterogeneous shrinking patterns inside a city. Consequently, the spatial mechanism and patterns of urban shrinkage inside a city remain less understood, which is unhelpful for developing accommodation strategies for shrinkage. The smart city initiatives and practices have provided a rich pool of geospatial big data resources and technologies to tackle the complexity of urban systems. Given this context, we propose a new measure for the delineation of shrinking areas within cities by introducing a new concept of functional urban shrinkage, which aims to capture the mismatch between urban built-up areas and the areas where significantly intensive human activities take place. Taking advantage of a data fusion approach to integrating multi-source geospatial big data and survey data, a general analytical framework is developed to construct functional shrinkage measures. Combining geospatial big data with urban land-use functions obtained from land surveys and Points-Of-Interests data, the framework further enables the comparison between cities from dimensions characterized by indices of spatial and urban functional characteristics and the landscape fragmentation; thus, it has the capacity to facilitate an in-depth investigation of fundamental causes and internal mechanisms of urban shrinkage. 
  • 1.1K
  • 05 Nov 2020
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. 
  • 1.0K
  • 21 Mar 2022
Topic Review
Geographic Information System
Geographic information systems (GIS) are composed of software, hardware, data, administrators, and methods for processing and analyzing data.  Creating and sharing spatial data in digital form is not only good practice but is also regulated by specific legal acts. Currently created in map portals and the widely available General Geographic Object Databases offer a reliable, current, and continuous source of spatial information for the entire country, extremely helpful in the planning process at various levels of generalization. The database implemented into the Spatial Information System is its most important element and should constitute a complete and reliable representation of elements of the real world.  GIS systems allow us to formulate models in a structured and formal way to reflect both the current situation and forecast changes that will occur in space when certain conditions are met. The proposed methodology can be used in practical applications:• Preparing planning studies, both regarding spatial policy and local law, as well as in economic planning and shaping the structure of rural space (structure of ownership and structure of use).• The development of thematic spatial information systems related to planning studies and works shaping the rural space.• Reports submitted to EU authorities relating to the utilization of funds dedicated to rural development in the multiannual financial framework and modification of the implemented actions.• The use of renewable energy sources to improve Poland’s energy security.
  • 983
  • 19 Jan 2021
Topic Review
Google Earth Application
Released in 2005 by Google, Google Earth (GE) has become the most popular and successful virtual globe tool. GE has demonstrated its capacity for 3D global representation and visualization of geospatial data from local to global scales.
  • 979
  • 11 Oct 2021
Topic Review
UAV-Based Forest Health Monitoring
Technological advances have led to the increasing use of unmanned aerial vehicles (UAVs) for forestry applications. One emerging field for drone application is forest health monitoring (FHM). Common approaches for FHM involve small-scale resource-extensive fieldwork combined with traditional remote sensing platforms. UAVs have shown that they can meet the demands of flexible operation and high spatial resolution. This is also reflected in a rapidly growing number of publications using drones to study forest health. 
  • 973
  • 27 Jul 2022
Topic Review
Unmanned Aerial Robots’ Applications in Agriculture
The most common role of drones in agriculture is to assess and monitor crops. For this, remote sensing is carried out, but this task is not enough when agricultural applications become more widespread. For this, autonomous mobile robots such as drones and other UAVs with technologically different features are designed for various agricultural purposes.
  • 954
  • 26 Jan 2022
Topic Review
Machine Learning Model in HSI-AD
In the field of remote sensing, hyperspectral image (HSI) is a ground image collected by advanced sensor technology and imaging system mounted on satellites or other aircraft. Anomaly detection (AD) is a very important sub-branch in machine learning and has important applications in computer vision, data mining, and natural language processing (NLP). HSI-AD refers to the identification of pixels whose spectral characteristics in an image are significantly different from adjacent or global background pixels.
  • 934
  • 05 May 2022
Topic Review
Rainfall Measurement by Commercial Microwave Links
As one of the most critical elements in the hydrological cycle, real-time and accurate rainfall measurement is of great significance to flood and drought disaster risk assessment and early warning. Using commercial microwave links (CMLs) to conduct rainfall measure is a promising solution due to the advantages of high spatial resolution, low implementation cost, near-surface measurement, and so on.
  • 911
  • 29 Jun 2022
Topic Review
Process-oriented mining method for marine abnormal variation
Marine anomaly variations (MAVs) refers to an abnormal decrease or increase of marine environmental parameters, which covers a specified spatial domain and lasts for a specified temporal duration, e.g., the monthly mean variation of sea surface temperature and the seasonal variation of sea surface height. These variations have evolution properties from production through development to death, which plays a significant role on exploring the evolution mechanism of marine environment and the mechanism. As few considering temporal evolution relationship, traditional spatiotemporal mining methods have great challenges in analyzing these MAVs. Thus, this paper takes the process semantics of MAVs to design the process-oriented mining workflow, and to explore the spatiotemporal patterns of MAVs.
  • 902
  • 29 Oct 2020
Topic Review
Remote Sensing Land Surface Temperature-Based ET Algorithms
Evapotranspiration (ET) is a process that includes evaporation from the surface, such as open water bodies, soil and vegetation, and transpiration as the water released mostly by the plant leaves transported from the root system. ET is a key factor in the hydrological cycle, since it describes the mechanism and energy needed to transport the liquid water stored in the soil-watershed-canopy system to the atmosphere, converted into water vapour.  Remote sensing technology is a globally consistent and economically feasible means to estimate ET values at regional and meso-scales on the Earth’s surface, since the approach directly links surface radiances and the components of the surface energy balance. Over the past, combined use of satellite remote sensing data from optical and thermal infrared sensors has provided substantial progress in the estimation of ET. Based on the concept of surface energy balance and net radiation, most remote sensing models have estimated ET for application studies such as water consumption, water resources planning and management over watersheds or modeling ecological processes and analyzing biophysical characteristics of landscape.
  • 885
  • 02 Aug 2022
Topic Review
Remote Sensing for Detection of Plant Water Stress
In the context of climate change, the occurrence of water stress in forest ecosystems, which are solely dependent on precipitation, has exhibited a rising trend, even among species that are typically regarded as drought-tolerant. Remote sensing techniques offer an efficient, comprehensive, and timely approach for monitoring forests at local and regional scales. These techniques also enable the development of diverse indicators of plant water status, which can play a critical role in evaluating forest water stress.
  • 881
  • 07 Jul 2023
Topic Review
Thundercloud Features in Different Regions
A comparison of thundercloud characteristics in different regions of the world was conducted. The clouds studied developed in India, China and in two regions of Russia. Several field projects were discussed. Cloud characteristics were measured by weather radars, the SEVERI instrument installed on board of the Meteosat satellite, and lightning detection systems. The statistical characteristics of the clouds were tabulated from radar scans and correlated with lightning observations. Thunderclouds in India differ significantly from those observed in other regions. The relationships among lightning strike frequency, supercooled cloud volume, and precipitation intensity were analyzed. In most cases, high correlation was observed between lightning strike frequency and supercooled volume. 
  • 877
  • 23 Aug 2021
Topic Review
BDS-3 Integrity Concept
Compared to the BeiDou regional navigation satellite system (BDS-2), the BeiDou global navigation satellite system (BDS-3) carried out a brand new integrity concept design and construction work, which defines and achieves the integrity functions for major civil open services (OS) signals such as B1C, B2a, and B1I. The integrity definition and calculation method of BDS-3 are introduced. The fault tree model for satellite signal-in-space (SIS) is used, to decompose and obtain the integrity risk bottom events. In response to the weakness in the space and ground segments of the system, a variety of integrity monitoring measures have been taken. On this basis, the design values for the new B1C/B2a signal and the original B1I signal are proposed, which are 0.9 × 10−5 and 0.8 × 10−5, respectively. The hybrid alarming mechanism of BDS-3, which has both the ground alarming approach and the satellite alarming approach, is explained. At last, an integrity risk analysis and verification work were carried out using the operating data of the system in 2019. The results show that the actual operation of the system is consistent with the conceptual design, which satisfies the integrity performance promised by BDS-3 in the ICAO SAPRs.
  • 875
  • 24 Nov 2021
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