A5070647965- Remote Sensing in Agriculture
- Remote-Sensing Image Classification
- Fire effects on ecosystems
- Fuzzy Logic and Control Systems
- Remote Sensing and LiDAR Applications
- Neural Networks and Applications
- Remote Sensing and Land Use
- Advanced Chemical Sensor Technologies
- Smart Agriculture and AI
- Advanced Image and Video Retrieval Techniques
- Evolutionary Algorithms and Applications
- Advanced Image Fusion Techniques
- Atmospheric and Environmental Gas Dynamics
- Species Distribution and Climate Change
- Forest ecology and management
- Music and Audio Processing
- Metaheuristic Optimization Algorithms Research
- Fire Detection and Safety Systems
- Land Use and Ecosystem Services
- Rice Cultivation and Yield Improvement
- Flood Risk Assessment and Management
- Photoacoustic and Ultrasonic Imaging
- Forest Ecology and Biodiversity Studies
- Medical Image Segmentation Techniques
- AI in cancer detection
Aristotle University of Thessaloniki
2015-2024
Federation of Greek Mariculture
2019-2022
This paper presents a review of concepts related to wildfire risk assessment, including the determination fire ignition and propagation (fire danger), extent which may spatially overlap with valued assets (exposure), potential losses resilience those (vulnerability). is followed by brief discussion how these can be integrated connected mitigation adaptation efforts. We then operational systems in place various parts world. Finally, we propose an system being developed under FirEUrisk...
This paper presents and evaluates multitemporal LAI estimates derived from Sentinel-2A data on rice cultivated area identified using time series of Sentinel-1A images over the main European districts for 2016 crop season. study combines information conveyed by into a high-resolution retrieval chain. Rice was detected an operational multi-temporal rule-based algorithm, were obtained inverting PROSAIL radiative transfer model with Gaussian process regression. Direct validation performed in...
Abstract. Over the past 2 decades, several global burned area products have been produced and released to public. However, accuracy assessment of such largely depends on availability reliable reference data that currently do not exist a scale or whose production require high level dedication project resources. The important lack for validation is addressed in this paper. We provide Burned Area Reference Database (BARD), first publicly available database created by compiling existing BA...
The ever increasing need for accurate burned area mapping has led to a number of studies that focus on improving the accuracy and effectiveness. In this work, we investigate influence derivative spectral spatial features accurately recently areas using VHR IKONOS imagery. Our analysis considers both pixel object-based approaches, two advanced image techniques: (a) an efficient feature selection method based Fuzzy Complementary Criterion (FuzCoC) (b) Support Vector Machine (SVM) classifier....
This paper proposes the use of a genetic fuzzy-rule-based classification system for land cover from hyperspectral images. The proposed classifier, namely, Feature Selective Linguistic Classifier, is constructed through three-stage learning process. first stage produces preliminary fuzzy rule base in an iterative fashion. During this stage, local feature selection scheme employed, designed to guide evolution, evaluation deterministic information about relevance each with respect its ability....
The ERMES agromonitoring system for rice cultivations integrates EO data at different resolutions, crop models, and user-provided in situ a unified system, which drives two operational downstream services monitoring. first is aimed providing information concerning the behavior of current season regional/rice district scale, while second dedicated to provide farmers with field-scale useful support more efficient environmentally friendly practices. In this contribution, we describe main...
The knowledge of rice nitrogen (N) requirements and uptake capacity are fundamental for the development improved N management. This paper presents empirical models predicting agronomic traits that relevant to yield (Oryza sativa L.) through remotely sensed data. Multiple linear regression were constructed at key growth stages (at tillering booting), using as input reflectance values vegetation indices obtained from a compact multispectral sensor (green, red, red-edge, near-infrared channels)...
This study investigates the effectiveness of combining multispectral very high resolution (VHR) and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one each image, using output support vector machine (SVM). The classification result from image is then resampled to multispectral’s spatial sources combined simple yet efficient operator. Thus, complementary information provided...
Accurate canopy base height (CBH) information is essential for forest and fire managers since it constitutes a key indicator of seedling growth, wood quality health as well necessary input in behavior prediction systems such FARSITE, FlamMap BEHAVE. The present study focused on the potential airborne LiDAR data analysis to estimate plot-level CBH dense uneven-aged structured complex terrain. A comparative two widely employed methods was performed, namely voxel-based approach regression...
Recent technical and jurisdictional advances, together with the availability of low-cost platforms, have facilitated implementation unmanned aerial vehicles (UAVs) in individual tree detection (ITD) applications. UAV-based photogrammetry or structure from motion is an example such a technique, but requires detailed pre-flight planning order to generate desired 3D-products needed for ITD. In this study, we aimed find most optimal flight parameters (flight altitude image overlap) processing...
A class of pipelined recurrent fuzzy neural networks (PRFNNs) is proposed in this paper for nonlinear adaptive speech prediction. The PRFNNs are modular structures comprising a number modules that interconnected chained form. Each module implemented by small-scale network (RFNN) with internal dynamics. Due to nesting, the offer desirable attributes, including decomposition modeling task, enhanced temporal processing capabilities, and multistage dynamic inference. Tuning PRFNN adaptable...
Rice is the major staple crop worldwide, whereas fertilization practices include mainly application of synthetic fertilizers. A novel compost was developed using 74% rice industrial by-products (rice bran and husks) tested in cultivation Greece’s main producing area. Field experimentation conducted two consecutive growing seasons (2017 2018) comprised six treatments, including four rates (C1: 80, C2: 160, C3: 320 kg ha−1 nitrogen all split application, C4: 160 single application), a...
Monitoring post-fire vegetation response using remotely-sensed images is a top priority for management. This study investigated the potential of very-high-resolution (VHR) GeoEye on detecting field-measured burn severity forest fire that occurred in Evros (Greece) during summer 2011. To do so, we analysed role topographic conditions and severity, as measured field immediately after (2011) one year (2012) Composite Burn Index (CBI) explaining response, which VHR satellite imagery. determine...
Surface fuel load (SFL) constitutes one of the most significant components and is used as an input variable in fire behavior prediction systems. The aim present study was to investigate potential discrete-return multispectral Light Detection Ranging (LiDAR) data reliably predict SFL a coniferous forest characterized by dense overstory complex terrain. In particular, linear regression analysis workflow employed with separate combined use LiDAR-derived structural pulse intensity information...
A local search-based version of the so-called genetic sequential image segmentation (GeneSIS) algorithm is presented in this paper, for classification remotely sensed images. The new method combines properties GeneSIS framework with principles region growing algorithms. Localized operates on a fine-segmented obtained after preliminary watershed transformation. Segmentation proceeds by iterative expansions emanating from object cores, i.e., connected components marked watersheds. At each...
The Sentinel-2 satellites are providing an unparalleled wealth of high-resolution remotely sensed information with a short revisit cycle, which is ideal for mapping burned areas both accurately and timely. However, the high detail volume provided actually encumbers automation process, at least level required to map systematically wildfires on national level. This paper proposes fully automated methodology burn scars using data. Information extracted from pair images, one pre-fire post-fire,...
In this paper we propose an image-based approach for in-vivo assessment of IVUS images. The method discriminates plaque components into four classes: calcium, necrotic core, fibrous and fibro-fatty. We employ the frames characterized by virtual histology (VH) tissue labeling. As a result, avoid demerits visual assessments observers while at same time longitudinal resolution VH is increased. To describe textural properties classes five different features are extracted from computed using...
In this paper, we propose an integrated framework of the recently proposed Genetic Sequential Image Segmentation (GeneSIS) algorithm. GeneSIS segments image in iterative manner, whereby at each iteration, a single object is extracted via genetic algorithm-based extraction method. This module evaluates fuzzy content candidate regions, and through effective fitness function design provides objects with optimal balance between coverage, consistency smoothness. exhibits number interesting...
Efficient forest fire management is a key element for alleviating the catastrophic impacts of wildfires. Overall, effective response to events necessitates adequate planning and preparedness before start season, as well quantifying environmental in case Moreover, estimation danger provides crucial information required optimal allocation distribution available resources. The Greek National Observatory Forest Fires (NOFFi)—established by Forestry Service collaboration with Laboratory...