scholarly journals Migratory flight on the Pacific Flyway: strategies and tendencies of wind drift compensation

2019 ◽  
Vol 15 (9) ◽  
pp. 20190383
Author(s):  
Patrick B. Newcombe ◽  
Cecilia Nilsson ◽  
Tsung-Yu Lin ◽  
Kevin Winner ◽  
Garrett Bernstein ◽  
...  
Keyword(s):  
Wind Direction ◽  
Remote Sensing Data ◽  
Radar Data ◽  
Migration System ◽  
Migratory Flight ◽  
Preferred Direction ◽  
Northern Latitudes ◽  
The Pacific ◽  
Pacific Flyway ◽  
Complex Relationships

Applications of remote sensing data to monitor bird migration usher a new understanding of magnitude and extent of movements across entire flyways. Millions of birds move through the western USA, yet this region is understudied as a migratory corridor. Characterizing movements in the Pacific Flyway offers a unique opportunity to study complementary patterns to those recently highlighted in the Atlantic and Central Flyways. We use weather surveillance radar data from spring and autumn (1995–2018) to examine migrants' behaviours in relation to winds in the Pacific Flyway. Overall, spring migrants tended to drift on winds, but less so at northern latitudes and farther inland from the Pacific coastline. Relationships between winds and autumn flight behaviours were less striking, with no latitudinal or coastal dependencies. Differences in the preferred direction of movement (PDM) and wind direction predicted drift patterns during spring and autumn, with increased drift when wind direction and PDM differences were high. We also observed greater total flight activity through the Pacific Flyway during the spring when compared with the autumn. Such complex relationships among birds’ flight strategies, winds and seasonality highlight the variation within a migration system. Characterizations at these scales complement our understanding of strategies to clarify aerial animal movements.

scholarly journals Evolution of Surge-Type Glaciers in the Yangtze River Headwater Using Multi-Source Remote Sensing Data

2019 ◽  
Vol 11 (24) ◽  
pp. 2991 ◽  
Author(s):  
Jin Yan ◽  
Mingyang Lv ◽  
Zhixing Ruan ◽  
Shiyong Yan ◽  
Guang Liu
Keyword(s):  
Remote Sensing ◽  
Flow Velocity ◽  
Yangtze River ◽  
Stable State ◽  
Remote Sensing Data ◽  
Radar Data ◽  
Series Data ◽  
The Yangtze River ◽  
Glacier Surges ◽  
Short Time

A surge-type glacier is a special and dangerous type of glacier, which can advance quickly in a short-time with cycles. Glaciers in the Yangtze River headwater are generally acknowledged to be in a stable state. However, not all of those glaciers are stable. In this paper, five glaciers from the Yangtze River headwater glacier were selected as the experimental subjects, and multi-source remote sensing images were used to study and analyze the surge behavior over the past 30 years. Based on the Landsat series data, ERS-2, and ENVISAT radar data, this paper extracts the glacier centerline information, glacial area information, and glacial flow velocity during different time periods from 1988 to 2018, which are used to monitor the active periods of glacier surges. We found three surge-type glaciers in the study area. The glacial characteristics of the three glaciers showed some drastic changes, they can advance quickly nearly 800 m in active periods, their area change can reach 2.0 × 106 m2, and their flow velocity can suddenly increase by dozens of times. Surging periods and the initiated time of the three glaciers are different, which are locked in 1997, 2003, and 1997–1998. All those surges ended within one to two years. We suggest that the surges in this paper are dominated by hydrological conditions.

scholarly journals A Meta-Methodology for Improving Land Cover and Land Use Classification with SAR Imagery

2020 ◽  
Vol 12 (6) ◽  
pp. 961 ◽  
Author(s):  
Marinalva Dias Soares ◽  
Luciano Vieira Dutra ◽  
Gilson Alexandre Ostwald Pedro da Costa ◽  
Raul Queiroz Feitosa ◽  
Rogério Galante Negri ◽  
...  
Keyword(s):  
Remote Sensing Data ◽  
Data Classification ◽  
Test Site ◽  
Radar Data ◽  
Input Image ◽  
Optical Data ◽  
Land Use Classification ◽  
Object Based ◽  
Sar Imagery ◽  
Small Change

Per-point classification is a traditional method for remote sensing data classification, and for radar data in particular. Compared with optical data, the discriminative power of radar data is quite limited, for most applications. A way of trying to overcome these difficulties is to use Region-Based Classification (RBC), also referred to as Geographical Object-Based Image Analysis (GEOBIA). RBC methods first aggregate pixels into homogeneous objects, or regions, using a segmentation procedure. Moreover, segmentation is known to be an ill-conditioned problem because it admits multiple solutions, and a small change in the input image, or segmentation parameters, may lead to significant changes in the image partitioning. In this context, this paper proposes and evaluates novel approaches for SAR data classification, which rely on specialized segmentations, and on the combination of partial maps produced by classification ensembles. Such approaches comprise a meta-methodology, in the sense that they are independent from segmentation and classification algorithms, and optimization procedures. Results are shown that improve the classification accuracy from Kappa = 0.4 (baseline method) to a Kappa = 0.77 with the presented method. Another test site presented an improvement from Kappa = 0.36 to a maximum of 0.66 also with radar data.

scholarly journals Evaluation of the Moisture Sources in two Extreme Landfalling Atmospheric River Events using an Eulerian WRF-Tracers tool

2017 ◽  
Author(s):  
Jorge Eiras-Barca ◽  
Francina Dominguez ◽  
Huancui Hu ◽  
A. Daniel Garaboa-Paz ◽  
Gonzalo Miguez-Macho
Keyword(s):  
Cross Sections ◽  
North Atlantic ◽  
Cold Front ◽  
Wrf Model ◽  
Atmospheric River ◽  
The North ◽  
Northern Latitudes ◽  
The Pacific ◽  
Low Level Jet ◽  
Tropical Moisture

Abstract. A new 3D Tracer tool is coupled to the WRF model to analyze the origin of the moisture in two extreme Atmospheric River (AR) events: the so-called Great Coast Gale of 2007 in the Pacific Basin, and the Great Storm of 1987 in the North Atlantic. Results show that between 80 % and 90 % of the moisture advected by the ARs, as well as between 70 % and 80 % of the associated precipitation have a tropical or subtropical origin. Local convergence transport is responsible for the remaining moisture and precipitation. The ratio of tropical moisture to total moisture is maximized as the cold front arrives to land. Vertical cross sections of the moisture suggest that the maximum in humidity does not necessarily coincide with the Low-Level Jet (LLJ) of the extratropical cyclone. Instead, the amount of tropical humidity is maximized in the lowest atmospheric level in southern latitudes, and can be located above, below or ahead the LLJ in northern latitudes in both analyzed cases.

The Pacific Flyway of the Golden Plover

The Auk ◽  
1949 ◽  
Vol 66 (1) ◽  
pp. 87-88 ◽  
Author(s):  
F. W. Preston
Keyword(s):  
The Pacific ◽  
Pacific Flyway ◽  
Golden Plover

Application of optical and radar data for lineaments mapping in Kerdous inlier of the Anti Atlas belt, Morocco

2021 ◽  
Author(s):  
Amine Jellouli ◽  
Abderrazak El Harti ◽  
Zakaria Adiri ◽  
Mohcine Chakouri ◽  
Jaouad El Hachimi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Radar Data ◽  
Ore Deposits ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Alos Palsar ◽  
Geological Map ◽  
Color Composite ◽  
Manual Extraction

<p>Lineament mapping is an important step for lithological and hydrothermal alterations mapping. It is considered as an efficient research task which can be a part of structural investigation and mineral ore deposits identification. The availability of optical as well as radar remote sensing data, such as Landsat 8 OLI, Terra ASTER and ALOS PALSAR data, allows lineaments mapping at regional and national scale. The accuracy of the obtained results depends strongly on the spatial and spectral resolution of the data. The aim of this study was to compare Landsat 8 OLI, Terra ASTER, and radar ALOS PALSAR satellite data for automatic and manual lineaments extraction. The module Line of PCI Geomatica software was applied on PC1 OLI, PC3 ASTER and HH and HV polarization images to automatically extract geological lineaments. However, the manual extraction was achieved using the RGB color composite of the directional filtered images N - S (0°), NE - SW (45°) and E - W (90°) of the OLI panchromatic band 8. The obtained lineaments from automatic and manual extraction were compared against the faults and photo-geological lineaments digitized from the existing geological map of the study area. The extracted lineaments from PC1 OLI and ALOS PALSAR polarizations images showed the best correlation with faults and photo-geological lineaments. The results indicate that the lineaments extracted from HH and HV polarizations of ALOS PALSAR radar data used in this study, with 1499 and 1507 extracted lineaments, were more efficient for structural lineament mapping, as well as the PC1 OLI image with 1057 lineaments.</p><p><strong>Keywords</strong> Remote Sensing . OLI. ALOS PALSAR . ASTER . Kerdous Inlier . Anti Atlas</p>

scholarly journals A Review of the Application of Remote Sensing Data for Abandoned Agricultural Land Identification with Focus on Central and Eastern Europe

2019 ◽  
Vol 11 (23) ◽  
pp. 2759 ◽  
Author(s):  
Tomáš Goga ◽  
Ján Feranec ◽  
Tomáš Bucha ◽  
Miloš Rusnák ◽  
Ivan Sačkov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
World Literature ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Field Research ◽  
Radar Data ◽  
Expert Assessment ◽  
Biomass Estimation ◽  
Agricultural Abandonment ◽  
Expert Analysis

This study aims to analyze and assess studies published from 1992 to 2019 and listed in the Web of Science (WOS) and Current Contents (CC) databases, and to identify agricultural abandonment by application of remote sensing (RS) optical and microwave data. We selected 73 studies by applying structured queries in a field tag form and Boolean operators in the WOS portal and by expert analysis. An expert assessment yielded the topical picture concerning the definitions and criteria for the identification of abandoned agricultural land (AAL). The analysis also showed the absence of similar field research, which serves not only for validation, but also for understanding the process of agricultural abandonment. The benefit of the fusion of optical and radar data, which supports the application of Sentinel-1 and Sentinel-2 data, is also evident. Knowledge attained from the literary sources indicated that there exists, in the world literature, a well-covered problem of abandonment identification or biomass estimation, as well as missing works dealing with the assessment of the natural accretion of biomass in AAL.

scholarly journals Postseismic Restoration of the Ecological Environment in the Wenchuan Region Using Satellite Data

2018 ◽  
Vol 10 (11) ◽  
pp. 3990 ◽  
Author(s):  
Zhibin Huang ◽  
Min Xu ◽  
Wei Chen ◽  
Xiaojuan Lin ◽  
Chunxiang Cao ◽  
...  
Keyword(s):  
Remote Sensing Data ◽  
Radar Data ◽  
Ecological Environment ◽  
Mountain Area ◽  
State Response ◽  
Lancang River ◽  
Before And After ◽  
Gray Correlation ◽  
Geological Information ◽  
Pressure State

Using Landsat remote-sensing data combined with geological information extracted from ALOS and Sentinel-1A radar data, the ecological environment was evaluated in the years 2007, 2008, 2013, and 2017 through gray correlation analysis on the basis of the construction of the pressure-state-response model. The main objective of this research was to assess the ecological environment changes in Wenchuan County before and after the earthquake, and to provide reference for future social development and policy implementation. The grading map of the ecological environment was obtained for every year, and the ecological restoration status of Wenchuan County after the earthquake was evaluated. The results showed that the maximum area cover at a “safe” ecological level was over 46.4% in 2007. After the 2008 earthquake, the proportion of “unsafe” and “very unsafe” ecological levels was 40.0%, especially around the Lancang River and the western mountain area in Wenchuan County. After five years of restoration, ecological conditions were improved, up to 48.0% in the region. The areas at “critically safe” and above recovered to 85.5% in 2017 within nine years after the deadly Wenchuan earthquake of May 12, 2008. In this paper, we discuss the results of detailed analysis of ecological improvements and correlation with the degrees of pressure, state, and response layers of the Pressure-State-Response (PSR) model.

scholarly journals NN-Based Prediction of Sentinel-1 SAR Image Filtering Efficiency

Geosciences ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 290 ◽  
Author(s):  
Rubel ◽  
Lukin ◽  
Rubel ◽  
Egiazarian
Keyword(s):  
Neural Network ◽  
Image Quality ◽  
Real Life ◽  
Remote Sensing Data ◽  
Radar Data ◽  
Quality Metrics ◽  
Radar Images ◽  
Filtering Efficiency ◽  
Trained Neural Network ◽  
Synthetic Aperture Radars

Images acquired by synthetic aperture radars are degraded by speckle that prevents efficient extraction of useful information from radar remote sensing data. Filtering or despeckling is a tool often used to improve image quality. However, depending upon image and noise properties, the quality of improvement can vary. Besides, a quality can be characterized by different criteria or metrics, where visual quality metrics can be of value. For the case study of discrete cosine transform (DCT)based filtering, we show that improvement of radar image quality due to denoising can be predicted in a simple and fast way, especially if one deals with particular type of radar data such as images acquired by Sentinel-1. Our approach is based on application of a trained neural network that, in general, might have a different number of inputs (features). We propose a set of features describing image and noise statistics from different viewpoints. From this set, that contains 28 features, we analyze different subsets and show that a subset of the 13 most important and informative features leads to a very accurate prediction. Test image generation and network training peculiarities are discussed. The trained neural network is then tested using different verification strategies. The results of the network application to test and real-life radar images are presented, demonstrating good performance for a wide set of quality metrics.

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