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Dam reservoir extraction from remote sensing imagery using tailored metric learning strategies
[article]
2022
arXiv
pre-print
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To address this data gap, a promising approach is to perform automated dam reservoir extraction based on globally available remote sensing imagery. ...
For the latter step, prior-guided metric learning with triplets from clusters is injected into the classification model to optimize the image embedding space in a fine-grained level based on reservoir ...
Dam reservoir extraction from remote sensing imagery using tailored metric learning strategies Arnout van Soesbergen * , Zedong Chu * , Miaojing Shi † , Member, IEEE, and Mark Mulligan Abstract-Dam reservoirs ...
arXiv:2207.05807v1
fatcat:fob33hl6xvffjftrmh7mdqrn3a
Aerial Imagery Feature Engineering Using Bidirectional Generative Adversarial Networks: A Case Study of the Pilica River Region, Poland
2021
Remote Sensing
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To accomplish this goal, a modified version of the big bidirectional generative adversarial network (BigBiGAN) has been trained on a fine-tailored orthophoto imagery dataset covering the area of the Pilica ...
The feature engineering use case, on the other hand, has been presented in a real research scenario that involved splitting the orthophoto into a set of patches, encoding the patch set into the GAN latent ...
The rapid development of remote sensing technology supported by a significant improvement in access to remote sensing imagery [1] led to an increased interest in the potential use of the collected material ...
doi:10.3390/rs13020306
fatcat:jiq57xnoejeltpbtnlvubvjwle
Modeling and Validation of Environmental Suitability for Schistosomiasis Transmission Using Remote Sensing
2015
PLoS Neglected Tropical Diseases
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The model was developed for Burkina Faso using a habitat suitability index (HSI). The plausibility of remote sensing habitat variables was validated using field measurements. ...
on regularly updated remote sensing data. ...
Acknowledgments The Schistosoma infection prevalence data were derived from the open-access Global Neglected Tropical Disease (GNTD) database (http://www.gntd.org). ...
doi:10.1371/journal.pntd.0004217
pmid:26587839
pmcid:PMC4654500
fatcat:flpnzp7vlfdtfnirv2rmaghavq
Realizing ecosystem-safe hydropower from dams
2020
Renewables: Wind, Water, and Solar
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For data-limited regions, remote sensing-based temperature estimation algorithm was established using thermal infrared band of Landsat ETM+ over multiple dams. ...
for hydropower operation (reservoir level, powered/spillway release, storage), forecast reservoir inflow and air temperature for a dam site with in situ thermal measurements. ...
Reservoir temperature from satellite remote sensing The Landsat 7 satellite imagery was utilized to extract the water surface temperature along the reaches upstream and downstream of the dam. ...
doi:10.1186/s40807-020-00060-9
pmid:32647609
pmcid:PMC7325499
fatcat:ffg377pe6vewbki6fc7clkfvve
Disaster Monitoring of Satellite Image Processing Using Progressive Image Classification
2023
Computer systems science and engineering
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The PICA creates tailoring and adjustments obtained from satellite images before training and post-disaster aerial image data patches. ...
The analysis of remote sensing image areas is needed for climate detection and management, especially for monitoring flood disasters in critical environments and applications. ...
Therefore, we analyzed image data from remote sensing satellite for recognizing the changes in forest cover. ...
doi:10.32604/csse.2023.023307
fatcat:ba26d566ffhdxjqxjzzdeaxlf4
Quantifying the Impacts of the 2020 Flood on Crop Production and Food Security in the Middle Reaches of the Yangtze River, China
2022
Remote Sensing
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This study shows that with modern remote sensing techniques, stakeholders can obtain critical estimates of large-scale disaster events much earlier than other indicators, such as disaster field surveys ...
This study uses satellite imagery and geospatial data to examine the impact of floods over the main planting areas for double-cropping rice and grain crops in the middle reaches of the Yangtze River. ...
Acknowledgments: The authors acknowledge support from the Ministry of Science and Technology (MOST) of Taiwan under the codes MOST 110-2111-M-008-008. ...
doi:10.3390/rs14133140
fatcat:ujzcd5eepbfdzdl7ua7xxajlxm
Applications of Unmanned Aerial Systems (UASs) in Hydrology: A Review
2021
Remote Sensing
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from UAS-borne data, (iv) the associated advantages and limitations, and (v) knowledge gaps and future prospects of UASs application in hydrology. ...
With unparalleled spatial and temporal resolutions and product-tailoring possibilities, UAS are contributing to the acquisition of large volumes of data on water bodies, submerged parameters and their ...
Acknowledgments: The authors want to thank the support received from the plan "Programa de Fomento e Impulso de la Investigación y Transferencia" of the University of Cádiz. ...
doi:10.3390/rs13071359
fatcat:en3b3kcksbg7xjoksug2eqqylu
Advances and challenges in the water sciences in Brazil: a community synthesis of the XXIII Brazilian Water Resources Symposium
2020
Revista Brasileira de Recursos Hídricos
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We analyzed more than 250 papers and presentations of 16 special sessions covering topics of Climate Variability and Change, Disasters, Modeling, Large Scale Hydrology, Remote Sensing, Education, and Water ...
It is also time for us to be aligned with the international water science community and to use our experiences to actively contribute to the tackling of global water issues. ...
In this sense, some works proposed methods for the analyses of in situ bathymetric information and also including remote sensing imagery and altimetry Brêda et al., 2019a; Buffon et al., 2019 . ...
doi:10.1590/2318-0331.252020200136
fatcat:wwi7os5yjvgrtcgi3hu7utyk5y
Mini-UAV-based Remote Sensing: Techniques, Applications and Prospectives
[article]
2018
arXiv
pre-print
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., which make it an effective complement to other remote-sensing platforms and a cost-effective means for remote sensing. ...
We hope this paper will provide remote-sensing researchers an overall picture of recent UAV-based remote sensing developments and help guide the further research on this topic. ...
Remote sensing data with ultra-high spatial resolution (e.g. centimeter-level) plays significant roles in some fine-scale remote sensing applications, such as railway monitoring, dam/bridge crack detection ...
arXiv:1812.07770v2
fatcat:l4tdfpr55jbjvhxzi47lwrs2re
Google Earth Engine and Artificial Intelligence (AI): A Comprehensive Review
2022
Remote Sensing
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Remote sensing (RS) plays an important role gathering data in many critical domains (e.g., global climate change, risk assessment and vulnerability reduction of natural hazards, resilience of ecosystems ...
Retrieving, managing, and analyzing large amounts of RS imagery poses substantial challenges. Google Earth Engine (GEE) provides a scalable, cloud-based, geospatial retrieval and processing platform. ...
To explore how CV algorithms and ML models can be used together on GEE, the authors in [226] combined the existing Cloud-Score algorithm with a SVM to detect clouds in imagery ranging from Amazon tropical ...
doi:10.3390/rs14143253
fatcat:2bxizm4gg5ettkw4vnkl5cdaea
Knowledge Extracted from Copernicus Satellite Data
2019
Zenodo
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The proposed methodology uses new paradigms from Recurrent Neural Networks and Generative Adversarial Networks, supported by Bayesian and Information Bottleneck concepts. References 1. ...
By applying an already established active learning approach based on a Support Vector Machine with relevance feedback [2], we can limit ourselves to a limited number of typical satellite images to extract ...
Remote sensing imagery is most widely used for water resources in remote area and monotonious regions. Several techniques were used to extract the glaciers lake surface using Landsat imagery. ...
doi:10.5281/zenodo.3941573
fatcat:zzifwgljifck5bpjnboetsftfu
Tackling Climate Change with Machine Learning
[article]
2019
arXiv
pre-print
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From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. ...
We call on the machine learning community to join the global effort against climate change. ...
The authors gratefully acknowledge support from National Science Foundation grant 1803547, the Center for Climate and Energy Decision Making through a cooperative agreement between the National Science ...
arXiv:1906.05433v2
fatcat:ykmqsivkbfcazaz3wl5f7srula
Earth Environmental Monitoring Using Multi-Temporal Synthetic Aperture Radar: A Critical Review of Selected Applications
2021
Remote Sensing
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Microwave remote sensing has widely demonstrated its potential in the continuous monitoring of our rapidly changing planet. ...
The analyzed literature is categorized on the base of the approach adopted and the data exploited and discussed in light of the downstream remote sensing market. ...
Acknowledgments: The authors sincerely thank Airbus Defense and Space UK and Catapult SA for providing NovaSAR data from the commissioning phase. ...
doi:10.3390/rs13040604
fatcat:zgqmk5chjbc7hio5l6serraeym
Rehabilitating Valley Floors to a Stage 0 Condition: A Synthesis of Opening Outcomes
2022
Frontiers in Environmental Science
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This approach to rehabilitation is valley scale, rendering traditional monitoring strategies that target single-thread channels inadequate to capture pre- and post-project site conditions, thus motivating ...
Recent years have seen a shift toward "process-based restoration" that is intended to reestablish compromised ecogeomorphic processes resulting from site- or watershed-scale degradation. ...
Vegetation Conditions Shallow groundwater has potential to influence emergent vegetation conditions that can be assessed using remotely sensed imagery. ...
doi:10.3389/fenvs.2022.892268
doaj:bf4de1ed46234c318863cc9565494487
fatcat:ki54m3ajmnhn5lhbsp2r5swcyq
Policy Innovation and Governance for Irrigation Sustainability in the Arid, Saline San Joaquin River Basin
2020
Sustainability
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to address salinity impairments to the use of the San Joaquin River (SJR) as an irrigation water supply. ...
RTSM is a concept that requires access to continuous flow and electrical conductivity data from sensor networks located along the San Joaquin River and its major tributaries and a simulation model-based ...
The SEBAL (surface energy balance algorithm for land) was one of the early applications of remote sensing that used LANDSAT imagery to estimate daily evapotranspiration rates at the field scale (30 m) ...
doi:10.3390/su12114733
fatcat:wqskjinujva4bch4de4qgi4sby
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