- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Forest structural diversity characterization in Mediterranean landscapes affected by fires using Airborne Laser Scanning data
摘要： Forest fires can change forest structure and composition, and low-density Airborne Laser Scanning (ALS) can be a valuable tool for evaluating post-fire vegetation response. The aim of this study is to analyze the structural diversity differences in Mediterranean Pinus halepensis Mill. forests affected by wildfires on different dates from 1986 to 2009. Several types of ALS metrics, such as the Light Detection and Ranging (LiDAR) Height Diversity Index (LHDI), the LiDAR Height Evenness Index (LHEI), and vertical and horizontal continuity of vegetation, as well as topographic metrics, were obtained in raster format from low point density data. In order to map burned and unburned areas, differentiate fire occurrence dates, and distinguish between old and more recent fires, a sample of pixels was previously selected to assess the existence of differences in forest structure using the Kruskal–Wallis test. Then, k-nearest neighbors algorithm (k-NN), support vector machine (SVM) and random forest (RF) classifiers were compared to select the most accurate technique. The results showed that, in more recent fires, around 70% of the laser returns came from grass and shrub layers, yielding low LHDI and LHEI values (0.37–0.65 and 0.28–0.46, respectively). In contrast, the areas burned more than 20 years ago had higher LHDI and LHEI values due to the growth of the shrub and tree strata. The classification of burned and unburned areas yielded an overall accuracy of 89.64% using the RF method. SVM was the best classifier for identifying the structural differences between fires occurring on different dates, with an overall accuracy of 68.79%. Furthermore, SVM yielded an overall accuracy of 75.49% for the classification between old and more recent fires.
关键词： machine learning,Forest structure,landscape,LIDAR
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) - Valparaiso, Chile (2019.11.13-2019.11.27)] 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) - All-optical Routers Modeled through the Matrix Method with NVidia CUDA Development Framework
摘要： In this letter, we present a novel efficient automated tracing algorithm, called Compound Ray Recorder (CRR), to measure landscape heterogeneity efficiently without any supporting data sets. The main advantages of this method are: 1) the definition of a unified calculation framework for landscape heterogeneity is proposed and 2) no ancillary data are required, and the whole procedure can be automatically performed without any expert support or subjective evaluation. The results of tests using the proposed CRR method with actual satellite data show that it can accurately quantify the level of heterogeneity of a variety of landscapes. By normalizing the image size, the method constructs a unified framework for comparison of different regions or image extents. Meanwhile, the CRR method has been applied to time-series tracing of urban expansion and seasonal changes in the Poyang Lake area, thereby providing a new approach for monitoring landscape changes. Furthermore, heterogeneity changes mapping, and quantitative comparisons between the proposed method and existing methods are also performed.
关键词： landscape heterogeneity,index,Comparisons,heterogeneity changes mapping,time series
更新于2025-09-19 17:13:59
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[IEEE 2019 International Workshop on Fiber Optics in Access Networks (FOAN) - Sarajevo, Bosnia and Herzegovina (2019.9.2-2019.9.4)] 2019 International Workshop on Fiber Optics in Access Networks (FOAN) - Passive Optical Network: Patent Analysis
摘要： We identify research and development trends of Passive Optical Network (PON) technology by performing a competitive patent landscape analysis on a global scale. We use patent landscape analysis to identify patenting activities in different areas of innovation. Looking at large sets of patent data provides a better understanding of several important innovation waves in PON development, with an emphasis on adopted ITU and IEEE standards. In this paper, we also review key PON technology segments, discuss patent filing activity in different world regions, discuss key companies and patent leaders within the PON technology.
关键词： Passive optical network,competitive landscape,patent analysis
更新于2025-09-12 10:27:22
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Predicting Landscapes as Seen from Space from Environmental Conditions
摘要： Satellite images are information rich snapshots of ecosystems and landscapes. In consequence, the features in the images strongly depend on the environmental conditions. Such dependency between climate and landscapes has been regarded since the beginning of earth sciences; however, it has never been taken as literally as in the present study. We adapted a deep learning generative model as a first demonstration of the potential behind deep learning for spatial pattern generation in geoscience. The purpose is to build a conditional Generative Adversarial Network (cGAN) useful to establish the relationship between two loosely linked set of variables that show multitude of complex spatial features such as climate conditions to aerial image. We trained a custom cGAN to generate Sentinel-2 multispectral imagery given a set of climatic and terrain predictors. Results show that the generated imagery shares many characteristics with the real one. In some cases, the quality of the generated imagery is high enough to deceive humans. We envision that such use of deep learning for geoscience could become an important tool to test the effects of climate on landscapes and ecosystems.
关键词： GAN,climate,deep learning,satellite imagery,Sentinel 2,landscape ecology
更新于2025-09-10 09:29:36
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Measuring and Monitoring Urban Sprawl of Jaipur City using Remote Sensing and GIS
摘要： The world’s population increased drastically and forced people to migrate from rural area to major cities in search of basic amenities. The majority of the World’s population are already living in the major cities and it is continuously increasing. The increase in population forced the major cities to expand. Expansion of cities acclaimed more unplanned settlement that leads unplanned growth. This is a global phenomenon that has a direct impact on natural resources. It is the biggest challenge for urban planners to achieve sustainable development. Developing countries like India, where the population is increasing at an alarming pace, require more attention towards this problem. In this study, an attempt has been made to measure and monitor urban sprawl in Jaipur (Capital, State of Rajasthan, India). Built-up area with corresponding population has been analysed over a period of 41 years (1972-2013). Remotely sensed images of 1972-2013 (MSS, TM and ETM+) have been classified using Supervised Maximum Likelihood Classification (MLC) for digital image processing. Shannon’s entropy has been used to quantify the degree of urban sprawl, and eight landscape metrics have also been used to quantify urban sprawl and its pattern.
关键词： Remote Sensing,GIS,Shannon’s Entropy,Urban Sprawl,Landscape Metrics
更新于2025-09-10 09:29:36
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The inverse perovskite BaLiF <sub/>3</sub> : single-crystal neutron diffraction and analyses of potential ion pathways
摘要： Doped barium lithium tri?uoride has attracted attention as component for scintillators, luminescent materials and electrodes. With lithium and ?uoride, it contains two possibly mobile species, which may account for its ionic conductivity. In this study, neutron diffraction on oxide-containing BaLiF3 single-crystals is performed at up to 636.2(cid:2)C. Unfortunately, ion-migration pathways could not be mapped by modelling anharmonic ion displacement or by inspecting the scattering-length density that was reconstructed via maximum-entropy methods. However, analyses of the topology and bond-valence site energies derived from the high-temperature structure reveal that the anions can migrate roughly along the edges of the LiF6 coordination octahedra with an estimated migration barrier of (cid:3)0.64 eV (if a vacancy permits), whereas the lithium ions are con?ned to their crystallographic positions. This ?nding is not only valid for the title compound but for ion migration in all perovskites with Goldschmidt tolerance factors near unity.
关键词： bond-valence energy landscape,topological analysis,high-temperature neutron diffraction,maximum-entropy methods,fluoroperovskite
更新于2025-09-10 09:29:36
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Small-Angle Neutron Scattering Reveals Energy Landscape for Rhodopsin Photoactivation
摘要： Knowledge of the activation principles for G-protein-coupled receptors (GPCRs) is critical to development of new pharmaceuticals. Rhodopsin is the archetype for the largest GPCR family, yet the changes in protein dynamics that trigger signaling are not fully understood. Here we show that rhodopsin can be investigated by small-angle neutron scattering (SANS) in fully protiated detergent micelles under contrast matching to resolve light-induced changes in the protein structure. In SANS studies of membrane proteins, the zwitterionic detergent [(Cholamidopropyl)dimethylammonio]-propanesulfonate (CHAPS) is advantageous because of the low contrast difference between the hydrophobic core and hydrophilic head groups as compared to alkyl glycoside detergents. Combining SANS results with quasielastic neutron scattering (QENS) reveals how changes in volumetric protein shape are coupled (slaved) to the aqueous solvent. Upon light exposure rhodopsin is swollen by penetration of water into the protein core, allowing interactions with effector proteins in the visual signaling mechanism.
关键词： Detergent,Neutron Scattering,Hydration,GPCR,Protein Dynamics,Vision,Membrane Proteins,Energy landscape,Slaving,Rhodopsin
更新于2025-09-10 09:29:36
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Remote Sensing and Landscape Metrics for Evaluation of Secondary Vegetation Patterns in the Forest Fragmentation in an Area of the Brazilian Amazon
摘要： Deforestation in the Amazon biome has caused an intense process of fragmentation of its forests. This paper aims to evaluate secondary vegetation patterns in the forest fragmentation in an area of Brazilian Amazon, using remote sensing products and landscape metrics. The calculation of the metrics was performed using the Patch Analyst tool[1], a free extension of ArcGis?, which has the ability to quantify the composition and spatial configuration of a scenario, which can be presented by a remote sensing map or image. Preliminary results have shown that secondary vegetation contributed to improve the vegetation patches mean shape index (MSI), however, it is responsible for increasing the level of fragmentation in the study area.
关键词： Secondary Vegetation,Amazon,Landscape Metrics,Remote Sensing,Forest Fragmentation
更新于2025-09-09 09:28:46