The 50-year Landsat collection 2 archive

Science of Remote Sensing, Journal Year: 2023, Volume and Issue: 8, P. 100103 - 100103

Published: Sept. 18, 2023

The Landsat global consolidated data archive now exceeds 50 years. In recognition of the need for consistently processed across satellite series, United States Geological Survey (USGS) initiated collection-based processing entire that was as Collection 1 in 2016. preparation from successfully launched 9, USGS reprocessed 2 2020. This paper describes rationale for, and contents advancements provided by 2, highlights differences between products. Notably, products have improved geolocation and, first time, provides a inventory Level surface reflectance temperature Also used commercial cloud computing architecture via Amazon Web Services (AWS) to efficiently process enable direct access concludes with discussion likely improvements expected 3 Next mission is planned launch early 2030s.

Language: Английский

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Remote sensing of land change: A multifaceted perspective

Remote Sensing of Environment, Journal Year: 2022, Volume and Issue: 282, P. 113266 - 113266

Published: Oct. 7, 2022

The discipline of land change science has been evolving rapidly in the past decades. Remote sensing played a major role one essential components science, which includes observation, monitoring, and characterization change. In this paper, we proposed new framework multifaceted view through lens remote recommended five facets including location, time, target, metric, agent. We also evaluated impacts spatial, spectral, temporal, angular, data-integration domains remotely sensed data on observing, different change, as well discussed some current products. recommend clarifying specific facet being studied reporting multiple or all products, shifting focus from cover to metric agent, integrating social multi-sensor datasets for deeper fuller understanding recognizing limitations weaknesses studies.

Language: Английский

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Improved human greenspace exposure equality during 21st century urbanization

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Oct. 13, 2023

Greenspace plays a crucial role in urban ecosystems and has been recognized as key factor promoting sustainable healthy city development. Recent studies have revealed growing concern about greenspace exposure inequality; however, the extent to which urbanization affects human associated inequalities over time remains unclear. Here, we incorporate Landsat-based 30-meter time-series mapping population-weighted framework quantify changes equality (rather than equity) for 1028 global cities from 2000 2018. Results show substantial increase physical coverage an improvement greenspace, leading reduction inequality past two decades. Nevertheless, observe contrast rate of between Global South North, with faster South, nearly four times that North. These findings provide valuable insights into impact on nature environmental change can help inform future greening efforts.

Language: Английский

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Mapping the presence and distribution of tree species in Canada's forested ecosystems

Remote Sensing of Environment, Journal Year: 2022, Volume and Issue: 282, P. 113276 - 113276

Published: Sept. 29, 2022

Knowledge of tree species is required to inform management, planning, and monitoring forests as well characterize habitat ecosystem function. Remotely sensed data spatial modeling enable mapping presence distribution. Following an assessment identified in the sample-based National Forest Inventory (NFI), we mapped 37 over 650-Mha, forest-dominated ecosystems Canada representing 2019 conditions. Landsat imagery related spectral indices, geographic climate data, elevation derivatives, remote sensing-derived phenology are used predictor variables trained with calibration samples from Canada's NFI using Random Forests machine learning algorithm. Based upon prior knowledge distributions, classification models were implemented on a regional basis, meaning only that expected given region modeled local samples. Modeling resulted class membership probabilities values for each regionally eligible all treed pixels indicator attribution confidence derived distance feature space between two leading classes. Accuracy was conducted independent validation also drawn following same selection rules indicated overall accuracy 93.1% ± 0.1% (95%-confidence interval). Predictor informing geographic, climatic topographic conditions had largest importance models. Nationally, most common black spruce (Picea mariana; 203 Mha or 57.3% area), trembling aspen (Populus tremuloides; 34.7 Mha, 9.8%), lodgepole pine (Pinus contorta; 21.1 5.9%). Regionally, there ecozone-level dominance other species, including subalpine fir (Abies lasiocarpa; Montane Cordillera), western hemlock (Tsuga heterophylla; Pacific Maritime), balsam balsamea; Atlantic Maritime). per-pixel probabilities, assemblages akin those forest inventories can be produced. Further, calibrated reflectance imagery, methods presented herein time series images. The approach uses open variables, making method portable areas availability training data.

Language: Английский

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Advancement of Remote Sensing for Soil Measurements and Applications: A Comprehensive Review

Sustainability, Journal Year: 2023, Volume and Issue: 15(21), P. 15444 - 15444

Published: Oct. 30, 2023

Remote sensing (RS) techniques offer advantages over other methods for measuring soil properties, including large-scale coverage, a non-destructive nature, temporal monitoring, multispectral capabilities, and rapid data acquisition. This review highlights the different detection methods, types, parts, applications of RS in measurements, as well disadvantages measurements properties. The choice depends on specific requirements task because it is important to consider limitations each method, context objective determine most suitable technique. paper follows well-structured arrangement after investigating existing literature ensure well-organized, coherent covers all essential aspects related studying advancement using While several remote are available, this suggests spectral reflectance, which entails satellite tools based its global high spatial resolution, long-term monitoring non-invasiveness, cost effectiveness. Conclusively, has improved property various but more research needed calibration, sensor fusion, artificial intelligence, validation, machine learning enhance accuracy applicability.

Language: Английский

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Need and vision for global medium-resolution Landsat and Sentinel-2 data products

Remote Sensing of Environment, Journal Year: 2023, Volume and Issue: 300, P. 113918 - 113918

Published: Nov. 27, 2023

Language: Английский

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Coastline extraction using remote sensing: a review

GIScience & Remote Sensing, Journal Year: 2023, Volume and Issue: 60(1)

Published: Aug. 10, 2023

Coastlines are important basic geographic elements and mapping their spatial attribute changes can help monitor, model manage coastal zones. Traditional studies focused on the accuracy of extraction methods evolution characteristics coastlines. Thanks to advances in remote sensing for earth observations, recent coastline reveal detailed ocean-land interaction changes. In this review, we aim identify key milestones using by associating emergence major research topics with occurrence multiple application fields, data sources, algorithms. Specifically, define coastlines that be applied different summarize products, analyze principles, advantages disadvantages methods. On basis, discussed development direction challenges involved. This study provides practical insights incorporated into future approaches technologies.

Language: Английский

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A global database of historic glacier lake outburst floods

Earth system science data, Journal Year: 2023, Volume and Issue: 15(7), P. 2983 - 3000

Published: July 12, 2023

Abstract. Ongoing atmospheric warming has accelerated glacier mass loss in many mountain regions worldwide. Glacier lakes trap part of the glacial meltwater and have increased by about 50 % number area since 1990s. Some these may empty catastrophically pose hazards to communities, infrastructure, habitats. Such lake outburst floods (GLOFs) caused millions dollars damages fatalities are one concerns future changes magnitude, frequency, impacts processes a shrinking cryosphere. Consistently compiled inventories thus vital assess regional local trends GLOF occurrence, hazard, risk. To this end, we studied 769 literature internet sources developed standardized database with 57 attributes that describe quantify location, dam type, size, timing, GLOFs nine glaciated regions. Our inventory also includes details before after for 391 cases manually mapped from optical satellite images 1984. In total, 3151 reported occurred 27 countries between 850 2022 CE. Most been NW North America (26 %) Iceland (19 %). However, reporting density our varies. During 20th century alone, yearly documented 6-fold. Less than one-quarter all feature hydrodynamic characteristics such as flood peak discharge or volume estimates damage. more doubles previous global inventory, though gaps remain. data collection process emphasizes support experts contributing previously undocumented cases, recommend applying protocols when new cases. The on historic is archived at https://doi.org/10.5281/zenodo.7330344 (Lützow Veh, 2023a) regularly updated http://glofs.geoecology.uni-potsdam.de/ (last access: 9 May 2023).

Language: Английский

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Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region

Ecological Informatics, Journal Year: 2024, Volume and Issue: 82, P. 102732 - 102732

Published: July 22, 2024

Accurately estimating aboveground biomass (AGB) in forest ecosystems facilitates efficient resource management, carbon accounting, and conservation efforts. This study examines the relationship between predictors from Landsat-9 remote sensing data several topographical features. While provides reliable crucial for long-term monitoring, it is part of a broader suite available technologies. We employ machine learning algorithms such as Extreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), Random Forest (RF), alongside linear regression techniques like Multiple Linear (MLR). The primary objectives this encompass two key aspects. Firstly, research methodically selects optimal predictor combinations four distinct variable groups: (L1) data, fusion Vegetation-based indices (L2), integration with Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) (L3) combination best (L4) derived L1, L2, L3. Secondly, systematically assesses effectiveness different to identify most precise method establishing any potential field-measured AGB variables. Our revealed that (RF) model was utilizing OLI SRTM DEM predictors, achieving remarkable accuracy. conclusion reached by assessing its outstanding performance when compared an independent validation dataset. RF exhibited accuracy, presenting relative mean absolute error (RMAE), root square (RRMSE), R2 values 14.33%, 22.23%, 0.81, respectively. XGBoost subsequent choice RMAE, RRMSE, 15.54%, 23.85%, 0.77, further highlights significance specific spectral bands, notably B4 B5 Landsat 9 capturing spatial distribution patterns. Integration vegetation-based indices, including TNDVI, NDVI, RVI, GNDVI, refines mapping precision. Elevation, slope, Topographic Wetness Index (TWI) are proxies representing biophysical biological mechanisms impacting AGB. Through utilization openly accessible fine-resolution employing algorithm, demonstrated promising outcomes identification predictor-algorithm mapping. comprehensive approach offers valuable avenue informed decision-making assessment, ecological monitoring initiatives.

Language: Английский

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Characteristics and changes of glacial lakes and outburst floods

Nature Reviews Earth & Environment, Journal Year: 2024, Volume and Issue: 5(6), P. 447 - 462

Published: May 21, 2024

Language: Английский

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