- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
LESS: LargE-Scale remote sensing data and image simulation framework over heterogeneous 3D scenes
摘要： Three-dimensional (3D) radiative transfer modeling of the transport and interaction of radiation through earth surfaces is challenging due to the complexity of the landscapes as well as the intensive computational cost of 3D radiative transfer simulations. To reduce computation time, current models work with schematic landscapes or with small-scale realistic scenes. The computer graphics community provides the most accurate and efficient models (known as renderers) but they were not designed specifically for performing scientific radiative transfer simulations. In this study, we propose LESS, a new 3D radiative transfer modeling framework. LESS employs a weighted forward photon tracing method to simulate multispectral bidirectional reflectance factor (BRF) or flux-related data (e.g., downwelling radiation) and a backward path tracing method to generate sensor images (e.g., fisheye images) or large-scale (e.g. 1 km2) spectral images. The backward path tracing also has been extended to simulate thermal infrared radiation by using an on-the-fly computation of the sunlit and shaded scene components. This framework is achieved through the development of a user-friendly graphic user interface (GUI) and a set of tools to help construct the landscape and set parameters. The accuracy of LESS is evaluated with other models as well as field measurements in terms of directional BRFs and pixel-wise simulated image comparisons, which shows very good agreement. LESS has the potential in simulating datasets of realistically reconstructed landscapes. Such simulated datasets can be used as benchmarks for various applications in remote sensing, forestry investigation and photogrammetry.
关键词： Landscape modeling,Image simulation,Radiative transfer
更新于2025-09-23 15:23:52
-
Recentering the rural: Lidar and articulated landscapes among the Maya
摘要： The concept of the 'rural' may, for the ancient Maya, need 'recentering,' an acknowledgement that 'rurality' as a lifeway insu?ciently describes the integrated landscapes with high pedestrian 'vagility' that were dominated by dynastic centers. Large-scale lidar captures reveal special-purpose facilities for defense, surveillance, possible chocolate plantations under close supervision, orderly if defensible landscapes, agricultural works of landesque scope, and overall regional articulations with variable intensity of settlement. If there were 'rural' zones, they existed in coordination with centers. There was no exclusive dichotomy between inner and outer zones nor were there distinct populations, one acutely centered, the other dispersed. A conurban pattern applies to the evidence, with multiple, overlapping foci, gradients of drop-o?, complex interactions over time, and a continuous use-surface.
关键词： Landscape control,Conurbation,Redefining rurality,Lidar technology,Maya,Pedestrian vagility
更新于2025-09-23 15:23:52
-
Rapid mapping application of vegetated terraces based on high resolution airborne LiDAR
摘要： The aim of this work is to define a methodology for terraced areas survey and rapid mapping in a complex environment, like Ligurian (Northwestern Italy) one, where a remarkable percentage of its surface is estimated as terraced and where the canopy coverage makes their recognition very hard. Methodology steps are the definition of LiDAR survey parameters, morphometric filtering and GIS processing for final mapping. Each phase is oriented to provide a reliable terrace mapping, also practicable in canopy-covered areas due to a particular attention to land cover influence. The work considers a case study (Rupinaro basin) close to Cinque Terre, with a mixed land cover (terraces, forest and urbanized areas). The methodology provided encouraging results detecting 448 ha of terraces, 95% of them located under canopy cover. This finding pointed out that terraces mapping cannot rely only on photo-interpretation, as canopies will hamper their detection. Mapping of these areas, frequently characterized by abandonment, is crucial while identifying potential trigger factors for slope instabilities. This case study highlighted the importance of a carefully planned production chain, that should start from LiDAR survey parameter choice, providing the best input for analysis algorithm and providing the correct identification of terraces.
关键词： land abandonment,high resolution Digital Terrain Model,rapid mapping,Anthropic landscape,morphometric filtering
更新于2025-09-23 15:23:52
-
[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Capabilities of Lidar- and Satellite Data in Assessing the Drivers of Avian Diversity in a Fragmented Landscape
摘要： In modern landscapes, small habitat patches such as woodlands isolated in an agricultural matrix, can be important refuges for wildlife. However, their value as habitat may be compromised by their size and thus knowledge of how habitat structure influences habitat quality is vital to maximize species diversity. This study examined the factors driving avian diversity in four small woods in an agricultural landscape, and how accurately remote sensing (RS) metrics were able to quantify this. Linear mixed-effect models were used to combine annual breeding bird census data with data of habitat structure from satellite images and airborne lidar. The aims were firstly to examine the drivers of bird diversity, and secondly to reveal the strengths and weaknesses of the compared RS datasets in quantifying them. The results showed that, at first, bird diversity increased significantly towards the edges, being driven in part by vegetation structure. The amount of understorey vegetation was the most significant driver of diversity, due to which lidar-based models outperformed satellite-based ones. In general, lidar metrics correlated strongly with bird diversity, but such relationships were not discovered with satellite image metrics. The results indicate that the drivers of diversity, especially in fragmented woodlands may be too fine-scaled to be studied without sufficient consideration of the structural component of vegetation, which was proven to be attainable from lidar data.
关键词： habitat,fragmentation,lidar,bird diversity,satellite,landscape ecology
更新于2025-09-23 15:22:29
-
Using LiDAR to develop high-resolution reference models of forest structure and spatial pattern
摘要： Successful restoration of degraded forest landscapes requires reference models that adequately capture structural heterogeneity at multiple spatial scales and for specific landforms. Despite this need, managers often lack access to reliable reference information, in large part because field-based methods for assessing variation in forest structure are costly and inherently suffer from limited replication and spatial coverage and, therefore, yield limited insights about the ecological structure of reference forests at landscape scales. LiDAR is a cost-effective alternative that can provide high-resolution characterizations of variation in forest structure among landform types. However, managers and researchers have been reluctant to use LiDAR for characterizing structure because of low confidence in its capacity to approximate actual tree distributions. By calculating bias in LiDAR estimates for a range of tree-height cutoffs, we improved LiDAR's ability to capture structural variability in terms of individual trees. We assessed bias in the processed LiDAR data by comparing datasets of field-measured and LiDAR-detected trees of various height classes in terms of overall number of trees and estimates of structure and spatial pattern in an important contemporary reference forest, the Sierra de San Pedro Martir National Park, Baja California, Mexico. Agreement between LiDAR- and field-based estimates of tree density, as well as estimates of forest structure and spatial pattern, was maximized by removing trees less than 12 m tall. We applied this height cutoff to LiDAR-detected trees of our study landscape, and asked if forest structure and spatial pattern varied across topographic settings. We found that canyons, shallow northerly, and shallow southerly slopes were structurally similar; each had a greater number of all trees, large trees, and large tree clumps than steep southerly slopes and ridges. Steep northerly slopes supported unique structures, with taller trees than ridges and shorter trees than canyons and shallow southerly slopes. Our results show that characterizations of forest structure based on LiDAR-detected trees are reasonably accurate when the focus is narrowed to the overstory. In addition, our finding of strong variation of forest structure and spatial pattern across topographic settings demonstrates the importance of developing reference models at the landscape scale, and highlights the need for replicated sampling among stands and landforms. Methods developed here should be useful to managers interested in using LiDAR to characterize distributions of medium and large overstory trees, particularly for the development of landscape-scale reference models.
关键词： Ecological reference model,Forest structure,Sierra de San Pedro Martir,Spatial pattern,Landscape restoration,Spatial scale,LiDAR
更新于2025-09-23 15:22:29
-
Soil Temperature Variability in Complex Terrain Measured Using Fiber-Optic Distributed Temperature Sensing
摘要： Soil temperature (Ts) exerts critical controls on hydrologic and biogeochemical processes, but the magnitude and nature of Ts variability in a landscape setting are rarely documented. Fiber-optic distributed temperature sensing (DTS) systems potentially measure Ts at high density across a large extent. A fiber-optic cable 771 m long was installed at a depth of 10 cm in contrasting landscape units (LUs) defined by vegetative cover at Upper Sheep Creek in the Reynolds Creek Experimental Watershed (RCEW) and Critical Zone Observatory in Idaho. The purpose was to evaluate the applicability of DTS in remote settings and to characterize Ts variability in complex terrain. Measurement accuracy was similar to other field instruments (±0.4°C), and Ts changes of approximately 0.05°C at a monitoring spatial scale of 1 m were resolved with occasional calibration and an ambient temperature range of 50°C. Differences in solar inputs among LUs were strongly modified by surface conditions. During spatially continuous snow cover, Ts was practically homogeneous across LUs. In the absence of snow cover, daily average Ts was highly variable among LUs due to variations in vegetative cover, with a standard deviation (SD) greater than 5°C, and relatively uniform (SD < 1.5°C) within LUs. Mean annual soil temperature differences among LUs of 5.2°C was greater than those of 4.4°C associated with a 910-m elevation difference within the RCEW. In this environment, effective Ts simulation requires representation of relatively small-scale (<20 m) LUs due to the deterministic spatial variability of Ts.
关键词： landscape units,complex terrain,vegetative cover,fiber-optic cable,snow cover,spatial variability,Soil temperature,distributed temperature sensing
更新于2025-09-23 15:22:29
-
Method for Mapping Rice Fields in Complex Landscape Areas Based on Pre-Trained Convolutional Neural Network from HJ-1 A/B Data
摘要： Accurate and timely information about rice planting areas is essential for crop yield estimation, global climate change and agricultural resource management. In this study, we present a novel pixel-level classi?cation approach that uses convolutional neural network (CNN) model to extract the features of enhanced vegetation index (EVI) time series curve for classi?cation. The goal is to explore the practicability of deep learning techniques for rice recognition in complex landscape regions, where rice is easily confused with the surroundings, by using mid-resolution remote sensing images. A transfer learning strategy is utilized to ?ne tune a pre-trained CNN model and obtain the temporal features of the EVI curve. Support vector machine (SVM), a traditional machine learning approach, is also implemented in the experiment. Finally, we evaluate the accuracy of the two models. Results show that our model performs better than SVM, with the overall accuracies being 93.60% and 91.05%, respectively. Therefore, this technique is appropriate for estimating rice planting areas in southern China on the basis of a pre-trained CNN model by using time series data. And more opportunity and potential can be found for crop classi?cation by remote sensing and deep learning technique in the future study.
关键词： mapping rice ?elds,convolutional neural network,time series of vegetation index,complex landscape,transfer learning
更新于2025-09-23 15:21:01
-
[IEEE 2019 26th International Workshop on Active-Matrix Flatpanel Displays and Devices (AM-FPD) - Kyoto, Japan (2019.7.2-2019.7.5)] 2019 26th International Workshop on Active-Matrix Flatpanel Displays and Devices (AM-FPD) - Carbon Heating Tube Rapid Heating System for Fabricating Silicon Solar Cells
摘要： In this letter, we present a novel ef?cient automated tracing algorithm, called Compound Ray Recorder (CRR), to measure landscape heterogeneity ef?ciently without any supporting data sets. The main advantages of this method are: 1) the de?nition of a uni?ed 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 uni?ed 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2025-09-23 15:19:57
-
Reduced-dimensional perovskite photovoltaics with homogeneous energy landscape
摘要： Reduced-dimensional (quasi-2D) perovskite materials are widely applied for perovskite photovoltaics due to their remarkable environmental stability. However, their device performance still lags far behind traditional three dimensional perovskites, particularly high open circuit voltage (Voc) loss. Here, inhomogeneous energy landscape is pointed out to be the sole reason, which introduces extra energy loss, creates band tail states and inhibits minority carrier transport. We thus propose to form homogeneous energy landscape to overcome the problem. A synergistic approach is conceived, by taking advantage of material structure and crystallization kinetic engineering. Accordingly, with the help of density functional theory guided material design, (aminomethyl) piperidinium quasi-2D perovskites are selected. The lowest energy distribution and homogeneous energy landscape are achieved through carefully regulating their crystallization kinetics. We conclude that homogeneous energy landscape significantly reduces the Shockley-Read-Hall recombination and suppresses the quasi-Fermi level splitting, which is crucial to achieve high Voc.
关键词： homogeneous energy landscape,open circuit voltage loss,Reduced-dimensional perovskite,photovoltaics,Shockley-Read-Hall recombination
更新于2025-09-19 17:13:59
-
[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Signal-Dependent Noise for B-Modulation NFT-Based Transmission
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： Comparisons,index,heterogeneity changes mapping,time series,landscape heterogeneity
更新于2025-09-19 17:13:59