Fifty years of Landsat science and impacts

Remote Sensing of Environment, Год журнала: 2022, Номер 280, С. 113195 - 113195

Опубликована: Июль 28, 2022

Since 1972, the Landsat program has been continually monitoring Earth, to now provide 50 years of digital, multispectral, medium spatial resolution observations. Over this time, data were crucial for many scientific and technical advances. Prior program, detailed, synoptic depictions Earth's surface rare, ability acquire work with large datasets was limited. The early delivered a series technological breakthroughs, pioneering new methods, demonstrating capacity digital satellite imagery, creating template other global Earth observation missions programs. Innovations driven by have paved way subsequent science, application, policy support activities. economic value knowledge gained through long recognized, despite periods funding uncertainty, resulted in program's continuity, as well substantive ongoing improvements payload mission performance. Free open access data, enacted 2008, unprecedented substantially increased usage led proliferation science application opportunities. Here, we highlight key developments over past that influenced changed our understanding system. Major programmatic impacts realized areas agricultural crop mapping water use, climate change drivers impacts, ecosystems land cover monitoring, changing human footprint. introduction collection processing, coupled free policy, facilitated transition away from single images towards time analyses fostered widespread use science-grade data. launch Landsat-9 on September 27, 2021, advanced planning its successor mission, Landsat-Next, underscore sustained institutional program. Such commitment continuity is recognition both historic impact future potential build upon Landsat's remarkable 50-year legacy.

Язык: Английский

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Land Use and Land Cover Mapping Using Sentinel-2, Landsat-8 Satellite Images, and Google Earth Engine: A Comparison of Two Composition Methods

Remote Sensing, Год журнала: 2022, Номер 14(9), С. 1977 - 1977

Опубликована: Апрель 20, 2022

Accurate and real-time land use/land cover (LULC) maps are important to provide precise information for dynamic monitoring, planning, management of the Earth. With advent cloud computing platforms, time series feature extraction techniques, machine learning classifiers, new opportunities arising in more accurate large-scale LULC mapping. In this study, we aimed at finding out how two composition methods spectral–temporal metrics extracted from satellite can affect ability a classifier produce maps. We used Google Earth Engine (GEE) platform create cloud-free Sentinel-2 (S-2) Landsat-8 (L-8) over Tehran Province (Iran) as 2020. Two methods, namely, seasonal composites percentiles metrics, were define four datasets based on series, vegetation indices, topographic layers. The random forest was classification identifying most variables. Accuracy assessment results showed that S-2 outperformed L-8 overall class level. Moreover, comparison indicated percentile both series. At level, improved performance related their better about phenological variation different classes. Finally, conclude methodology GEE an fast way be

Язык: Английский

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Remote sensing of land change: A multifaceted perspective

Remote Sensing of Environment, Год журнала: 2022, Номер 282, С. 113266 - 113266

Опубликована: Окт. 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.

Язык: Английский

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Integrating GEDI and Landsat: Spaceborne Lidar and Four Decades of Optical Imagery for the Analysis of Forest Disturbances and Biomass Changes in Italy

Sensors, Год журнала: 2022, Номер 22(5), С. 2015 - 2015

Опубликована: Март 4, 2022

Forests play a prominent role in the battle against climate change, as they absorb relevant part of human carbon emissions. However, precisely because forest disturbances are expected to increase and alter forests' capacity carbon. In this context, monitoring using all available sources information is crucial. We combined optical (Landsat) photonic (GEDI) data monitor four decades (1985-2019) Italian forests (11 Mha). Landsat were confirmed source for disturbance mapping, harvestings Tuscany predicted with omission errors estimated between 29% (in 2012) 65% 2001). GEDI was assessed Airborne Laser Scanning (ALS) about 6 Mha forests. A good correlation (r2 = 0.75) Above Ground Biomass Density estimates (AGBD) canopy height ALS reported. provided complementary Landsat. The mission capable mapping disturbances, but not retrieving three-dimensional structure forests, while our results indicate that capturing biomass changes due disturbances. acquires useful only trend quantification regimes also discrimination characterization, which crucial further understanding effect change on ecosystems.

Язык: Английский

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Estimating and mapping forest age across Canada's forested ecosystems

Remote Sensing of Environment, Год журнала: 2023, Номер 290, С. 113529 - 113529

Опубликована: Март 15, 2023

Forest age is an important variable for assessments of biodiversity and habitat, sustainable forest land management, as well carbon science modeling. Tree stand are typically measured directly on site, or estimated through visual photo interpretation, with spatially explicit maps not often produced over large areas. Remote sensing enables the generation wall-to wall, disturbance events within satellite record; however, relatively rare landscape in a given year, additional means determining required. As reviewed herein, estimation using optical Earth observation data challenging due to limited spectral link attribute interest, especially forests get older. The temporally dictated multi-method approach outlined herein acknowledges these limitations, by applying that best suited quality information available, depending epoch interest. In this research, we combine three approaches estimate at 30-m spatial resolution Landsat data. first uses change detection protocols detect from 1985 2019, time since used proxy age. second surface reflectance composites identify pixels exhibiting evidence recovery occurred twenty years prior 1985, allowing extension estimates 1965. Finally, understanding linkage between canopy height, inverted allometric equations coupled structure productivity metrics model those show no maximum 150 years, acknowledging uncertainty increases increasing Combining approaches, made every treed pixel found 650 Mha forested ecosystems Canada. Nationwide, mean ≤150 old (representing 94.1% area) was 70 (standard deviation = 32.1 years). For confidence building, were compared reported National Inventory (NFI) both aspatially. Nationally, 5.9% area be older than while 9.5% NFI sample recorded years. median 68 73 regional variability matching expectations related regimes productivity. Spatially provide can inform wide range policy, science, management needs.

Язык: Английский

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Alternative states in the structure of mountain forests across the Alps and the role of disturbance and recovery

Landscape Ecology, Год журнала: 2023, Номер 38(4), С. 933 - 947

Опубликована: Янв. 25, 2023

Abstract Context Structure is a central dimension of forest ecosystems that closely linked to their capacity provide ecosystem services. Drivers such as changing disturbance regimes are increasingly altering structure, but large-scale characterizations structure and disturbance-mediated structural dynamics remain rare. Objectives Here, we characterize patterns in the horizontal vertical mountain forests test for presence alternative states. We investigate factors determining occurrence states role recovery transitions between Methods used spaceborne lidar (GEDI) across European Alps. combined GEDI-derived metrics with Landsat-based maps related topography, climate, landscape configuration, past disturbances. Results found two emerged consistently all types Alps: short, open-canopy (24%) tall, closed-canopy (76%). In absence disturbance, occurred at high elevations, edges, warm, dry sites. Disturbances caused transition conditions approximately 50% cases. Within 35 years after 72% recovered state, except submediterranean forests, where slow long-lasting more likely. Conclusions As climate warming increases disturbances causes thermophilization vegetation, could become likely future. Such restructuring pose challenge management, have lower capacities providing important

Язык: Английский

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Recovery and resilience of European temperate forests after large and severe disturbances

Global Change Biology, Год журнала: 2024, Номер 30(2)

Опубликована: Фев. 1, 2024

Abstract Recent observations of tree regeneration failures following large and severe disturbances, particularly under warm dry conditions, have raised concerns about the resilience forest ecosystems their recovery dynamics in face climate change. We investigated temperate forests Europe after disturbance events (i.e., resulting more than 70% canopy loss patches larger 1 ha), with a range one to five decades since occurred. The study included 143 sites different types management practices that had experienced 28 events, including windthrow (132 sites), fire (six bark beetle outbreaks (five sites). focused on assessing post‐disturbance density, structure, composition as key indicators resilience. compared height‐weighted densities site‐specific pre‐disturbance qualitatively assess potential for structural compositional recovery, overall dominant species, respectively. Additionally, we analyzed ecological drivers post‐windthrow such management, topography, aridity, using series generalized additive models. descriptive results show European been resilient past disturbances concurrent albeit lower high‐severity other agents. Across agents, was greater proportion plots becoming dominated by early‐successional species disturbance. models showed increasing elevation salvage logging negatively affect regeneration, late‐successional while pioneer are affected summer aridity. These findings provide baseline future recent occurrence widespread region anticipation conditions characterized heat drought stress.

Язык: Английский

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Development and implementation of a stand-level satellite-based forest inventory for Canada

Forestry An International Journal of Forest Research, Год журнала: 2024, Номер 97(4), С. 546 - 563

Опубликована: Янв. 5, 2024

Abstract Satellite data are increasingly used to provide information support forest monitoring and reporting at varying levels of detail for a range attributes spatial extents. Forests dynamic environments benefit from regular assessments capture status changes both locally over large areas. can products relevant science management on basis (e.g. annually) land cover, disturbance (i.e. date, extent, severity, type), recovery quantification return trees following disturbance), structure volume, biomass, canopy stand height), with generated areas in systematic, transparent, repeatable fashion. While pixel-based outcomes typical based upon satellite inputs, many end users continue require polygon-based inventory information. To meet this need have context such as tree species assemblages, we present new work-flow produce novel spatially explicit, stand-level satellite-based (SBFI) Canada applying image segmentation approaches generate unique stands (polygons), which the fundamental unit management-level inventories. Thus, SBFI offers aggregate generalize other sets. has developed National Terrestrial Ecosystem Monitoring System (NTEMS) that utilizes medium resolution imagery, chiefly Landsat, annually characterize Canada’s forests pixel level 1984 until present. These NTEMS datasets populate polygons regarding current cover type, dominant species, or total biomass) well dynamics polygon been subject change, when, by what, if so, how is recovering). Here, outline drivers monitoring, set aimed meeting these needs, follow demonstrate concept 650-Mha extent forest-dominated ecosystems. In so doing, entirety ecosystems (managed unmanaged) were mapped using same data, attributes, temporal representation. Moreover, use allows generation composition, biomass wood volume stand-scale format familiar landscape managers suitable strategic planning. The methods, presented here portable regions input sources, national available via open access.

Язык: Английский

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Impact of topography and climate on post-fire vegetation recovery across different burn severity and land cover types through random forest

Ecological Informatics, Год журнала: 2024, Номер 82, С. 102757 - 102757

Опубликована: Авг. 8, 2024

Wildfires significantly disturb ecosystems by altering forest structure, vegetation ecophysiology, and soil properties. Understanding the complex interactions between topographic climatic conditions in post-wildfire recovery is crucial. This study investigates interplay topography, climate, burn severity, years after fire on across dominant land cover types (evergreen forest, shrubs, grassland) Pacific Northwest region. Using Moderate Resolution Imaging Spectroradiometer (MODIS) data, we estimated calculating incremental Enhanced Vegetation Index (EVI) change during post-fire years. A machine learning algorithm, random (RF), was employed to map relationships input features (elevation, slope, aspect, precipitation, temperature, fire) target (incremental EVI recovery) for each type. Variable importance analysis partial dependence plots were generated understand influence of individual features. The observed predicted values showed good matches, with R2 0.99 training 0.89–0.945 testing. found that climate variables, specifically precipitation most important overall, while elevation played significant role among factors. Partial revealed lower tended cause a reduction varying temperature ranges types. These findings can aid developing targeted strategies management, considering responses different topographic, climatic, severity

Язык: Английский

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Landsat assessment of variable spectral recovery linked to post-fire forest structure in dry sub-boreal forests

ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2024, Номер 208, С. 121 - 135

Опубликована: Янв. 18, 2024

Forest disturbances such as wildfires can dramatically alter forest structure and composition, increasing the likelihood of ecosystem changes. Up-to-date accurate measures post-disturbance recovery in managed forests are critical, particularly for silvicultural planning. Measuring live dead vegetation post-fire is challenging because areas impacted by wildfire may be remote, difficult to access, and/or dangerous survey. The difficulties monitoring compounded global increase frequency severity disturbances, expansion disturbed also increases number size requiring monitoring. Methods that safely, efficiently, extensively differentiate silviculturally beneficial coniferous growth from barren ground or deciduous shrubs necessary inform management. Satellite imagery detect burn patterns, but changes post fire due complex responses. To overcome this challenge, study combines spectral trajectory a time series historical Landsat with field remotely piloted aircraft (RPA) lidar (light detection ranging) data examine lodgepole pine (Pinus contorta) dominated sub-boreal after high-severity fires 2006 central British Columbia, Canada. Distinct trajectories were identified using data-clustering combination seven indices, varying magnitude rate. associated each distinct was analyzed 430 ha spatially explicit (e.g., basal area, stem counts) composition percent coniferous) derived 26 coincident plots high density RPA (>200 points/m2) data. By comparing measures, we found most abundant cluster coincided area 0.62 m2/ha, densities (>5000 stems/ha) abundance trees (>95 % coniferous). Around 10 landscape relatively (>20 %) addition very conifer (>8000 stems/ha). identifying structural characteristics unique trajectories, highlight combined value satellite image providing detailed characterization relevant forests.

Язык: Английский

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