Insights into Boreal Forest Disturbance from Canopy Stability Index DOI Creative Commons
Brendan Mackey, Sonia Hugh, Patrick Norman

и другие.

Land, Год журнала: 2024, Номер 13(10), С. 1644 - 1644

Опубликована: Окт. 9, 2024

The world’s forests are being increasingly disturbed from exposure to the compounding impacts of land use and climate change, in addition natural disturbance regimes. Boreal have a lower level deforestation compared tropical forests, while they higher levels disturbances, accumulated impact forest management for commodity production coupled with worsening fire weather conditions other climate-related stressors is resulting ecosystem degradation loss biodiversity. We used satellite-based time-series analysis two canopy indices—canopy photosynthesis water stress—to calculate an index that maps relative stability canopies Canadian provinces Ontario Quebec. By drawing upon available spatial data on logging, wildfire, insect infestation impacts, we were able attribute causal determinants areas identified as having unstable canopy. slope indices comprise also provided information where recovering prior disturbances. analyses associated datasets interactive web-based mapping app. can be map attribution disturbances human or causes. This assist decision-makers identifying potentially ecologically degraded need restoration those stable priority protection.

Язык: Английский

State of Wildfires 2023–2024 DOI Creative Commons
Matthew W. Jones, Douglas I. Kelley, Chantelle Burton

и другие.

Earth system science data, Год журнала: 2024, Номер 16(8), С. 3601 - 3685

Опубликована: Авг. 13, 2024

Abstract. Climate change contributes to the increased frequency and intensity of wildfires globally, with significant impacts on society environment. However, our understanding global distribution extreme fires remains skewed, primarily influenced by media coverage regionalised research efforts. This inaugural State Wildfires report systematically analyses fire activity worldwide, identifying events from March 2023–February 2024 season. We assess causes, predictability, attribution these climate land use forecast future risks under different scenarios. During 2023–2024 season, 3.9×106 km2 burned slightly below average previous seasons, but carbon (C) emissions were 16 % above average, totalling 2.4 Pg C. Global C record in Canadian boreal forests (over 9 times average) reduced low African savannahs. Notable included record-breaking extent Canada, largest recorded wildfire European Union (Greece), drought-driven western Amazonia northern parts South America, deadly Hawaii (100 deaths) Chile (131 deaths). Over 232 000 people evacuated Canada alone, highlighting severity human impact. Our revealed that multiple drivers needed cause areas activity. In Greece, a combination high weather an abundance dry fuels probability fires, whereas area anomalies weaker regions lower fuel loads higher direct suppression, particularly Canada. Fire prediction showed mild anomalous signal 1 2 months advance, Greece had shorter predictability horizons. Attribution indicated modelled up 40 %, 18 50 due during respectively. Meanwhile, seasons magnitudes has significantly anthropogenic change, 2.9–3.6-fold increase likelihood 20.0–28.5-fold Amazonia. By end century, similar magnitude 2023 are projected occur 6.3–10.8 more frequently medium–high emission scenario (SSP370). represents first annual effort catalogue events, explain their occurrence, predict risks. consolidating state-of-the-art science delivering key insights relevant policymakers, disaster management services, firefighting agencies, managers, we aim enhance society's resilience promote advances preparedness, mitigation, adaptation. New datasets presented this work available https://doi.org/10.5281/zenodo.11400539 (Jones et al., 2024) https://doi.org/10.5281/zenodo.11420742 (Kelley 2024a).

Язык: Английский

Процитировано

37
Insights into mapping tropical primary wet forests in the Amazon Basin from satellite-based time series metrics of canopy stability DOI Creative Commons
Brendan Mackey, Sonia Hugh, Tatiana A. Shestakova

и другие.

Deleted Journal, Год журнала: 2025, Номер 2(1)

Опубликована: Янв. 30, 2025

Язык: Английский

Процитировано

1
Time-Series Data-Driven PM2.5 Forecasting: From Theoretical Framework to Empirical Analysis DOI Creative Commons

Chengqian Wu,

Ruiyang Wang, Siyu Lu

и другие.

Atmosphere, Год журнала: 2025, Номер 16(3), С. 292 - 292

Опубликована: Фев. 28, 2025

PM2.5 in air pollution poses a significant threat to public health and the ecological environment. There is an urgent need develop accurate prediction models support decision-making reduce risks. This review comprehensively explores progress of concentration prediction, covering bibliometric trends, time series data characteristics, deep learning applications, future development directions. article obtained on 2327 journal articles published from 2014 2024 WOS database. Bibliometric analysis shows that research output growing rapidly, with China United States playing leading role, recent increasingly focusing data-driven methods such as learning. Key sources include ground monitoring, meteorological observations, remote sensing, socioeconomic activity data. Deep (including CNN, RNN, LSTM, Transformer) perform well capturing complex temporal dependencies. With its self-attention mechanism parallel processing capabilities, Transformer particularly outstanding addressing challenges long sequence modeling. Despite these advances, integration, model interpretability, computational cost remain. Emerging technologies meta-learning, graph neural networks, multi-scale modeling offer promising solutions while integrating into real-world applications smart city systems can enhance practical impact. provides informative guide for researchers novices, providing understanding cutting-edge methods, systematic paths. It aims promote robust efficient contribute global management protection efforts.

Язык: Английский

Процитировано

1
Transitioning from MODIS to VIIRS Global Water Reservoir Product DOI Creative Commons
Deep Shah, Shuai Zhang, Sudipta Sarkar

и другие.

Scientific Data, Год журнала: 2024, Номер 11(1)

Опубликована: Фев. 15, 2024

Abstract Reservoirs play a crucial role in regulating water availability and enhancing security. Here, we develop NASA’s Visible Infrared Imaging Radiometer Suite (VIIRS) based Global Water Reservoir (GWR) product, consisting of measurements reservoir area, elevation, storage, evaporation rate, loss for 164 large global reservoirs. The dataset is available at 8-day monthly temporal resolutions. Since the Moderate Resolution Spectroradiometer (MODIS) close to end its life, further evaluated consistency between MODIS VIIRS-based GWR ensure continuity 20+ year product. Independent assessment VIIRS storage (8-day) retrievals against in-situ shows an average R 2 = 0.84, RMSE 0.47 km 3 , NRMSE 16.45%. rate has 0.56, 1.32 mm/day, 28.14%. Furthermore, results show good (R ≥ 0.90) MODIS-based product components, confirming that long-term data can be achieved. This provide valuable insights trend analysis, hydrological modeling, understanding hydroclimatic extremes context

Язык: Английский

Процитировано

5
Upscaling Land Surface Fluxes Through Hyper Resolution Remote Sensing in Space, Time, and the Spectrum DOI Creative Commons
Youngryel Ryu

Journal of Geophysical Research Biogeosciences, Год журнала: 2024, Номер 129(10)

Опубликована: Окт. 1, 2024

Abstract Numerous efforts to measure land surface fluxes, from leaf canopy scales, have significantly advanced the field of biogeoscience. However, upscaling these estimates larger spatial and temporal scales remains a challenge. Recent advancements in remote sensing provide new opportunities bridge gaps efforts. In this review, I propose that emerging satellite data can support robust fluxes terms space through constellations low Earth orbit satellites, time geostationary spectrum via optical, thermal, microwave satellites. Lastly, recommend development long‐term network integrating tower‐based hyperspectral, instruments rigorously evaluate process fluxes.

Язык: Английский

Процитировано

5
River Ice Mapping from Landsat-8 OLI Top of Atmosphere Reflectance Data by Addressing Atmospheric Influences with Random Forest: A Case Study on the Han River in South Korea DOI Creative Commons
Hyangsun Han, Tae-Wook Kim, S. D. Kim

и другие.

Remote Sensing, Год журнала: 2024, Номер 16(17), С. 3187 - 3187

Опубликована: Авг. 29, 2024

Accurate river ice mapping is crucial for predicting and managing floods caused by jams the safe operation of hydropower water resource facilities. Although satellite multispectral images are widely used mapping, atmospheric contamination limits their effectiveness. This study developed models Han River in South Korea using atmospherically uncorrected Landsat-8 Operational Land Imager (OLI) reflectance data, addressing influences with a Random Forest (RF) classification approach. The RF-based were implementing various combinations input variables, incorporating top-of-atmosphere (TOA) reflectance, normalized difference indices snow, water, bare ice, factors such as aerosol optical depth, vapor content, ozone concentration from Moderate Resolution Imaging Spectroradiometer observations, well surface elevation GLO-30 digital model. RF model all variables achieved excellent performance snow-covered snow-free an overall accuracy kappa coefficient exceeding 98.4% 0.98 test samples, higher than 83.7% 0.75 when compared against reference maps generated manually interpreting under conditions. corrected was also developed, but it showed very low conditions heavily contaminated vapor. Aerosol depth content identified most important variables. demonstrates that despite contamination, can be effectively monitoring applying machine learning auxiliary data to mitigate effects.

Язык: Английский

Процитировано

3
Can real-time NDVI observations better constrain SMAP soil moisture retrievals? DOI
Sijia Feng, Lun Gao, Jianxiu Qiu

и другие.

Remote Sensing of Environment, Год журнала: 2025, Номер 318, С. 114569 - 114569

Опубликована: Янв. 4, 2025

Язык: Английский

Процитировано

0
Comparative analysis of global urban land surface phenology between the MODIS and VIIRS products and extraction methods DOI

Peiyi Yin,

Xuecao Li, Janne Heiskanen

и другие.

Journal of Environmental Management, Год журнала: 2025, Номер 375, С. 124326 - 124326

Опубликована: Янв. 29, 2025

Язык: Английский

Процитировано

0
Inland Water Body Fraction Map for Canada and Adjacent Regions at 250-m Spatial Resolution DOI Creative Commons

Shaheen Ghayourmanesh,

Alexander P. Trishchenko,

Calin Ungureanu

и другие.

Canadian Journal of Remote Sensing, Год журнала: 2025, Номер 51(1)

Опубликована: Фев. 6, 2025

We present a novel raster dataset of surface inland water body fraction over Canada and neighbouring regions, including the northern parts United States, as well Greenland, Iceland, northeastern sector Russia, at 250-m spatial resolution. It was derived from Global Surface Water (GSW) (version 5) using two-step resampling to ensure an accurate replication original data consistency in terms extent resolution with Long-Term Satellite Data Records Moderate Resolution Imaging Spectroradiometer (MODIS) Visible Infrared Radiometer Suite (VIIRS) sensors. Additional input several coastline vector shape databases were utilized refine delineation waterbodies land-ocean interface. The resulting is 8-bit signed integer map, where each pixel represents either or land/ocean mask. Positive values indicate bodies within Canada, while negative represent areas outside Canada. This provides more precise up-to-date tool for medium-resolution studies aligning closely satellite imagery similar freely available through Government Canada's Open Portal.

Язык: Английский

Процитировано

0
Synchronous Atmospheric Correction of Wide-Swath and Wide-Field Remote Sensing Image from HJ-2A/B Satellite DOI Creative Commons
Honglian Huang, Yuxuan Wang, Xiao Liu

и другие.

Remote Sensing, Год журнала: 2025, Номер 17(5), С. 884 - 884

Опубликована: Март 1, 2025

The Chinese HuanjingJianzai-2 (HJ-2) A/B satellites are equipped with advanced sensors, including a Multispectral Camera (MSC) and Polarized Scanning Atmospheric Corrector (PSAC). To address the challenges of atmospheric correction (AC) for MSC’s wide-swath, wide-field images, this study proposes pixel-by-pixel method incorporating Bidirectional Reflectance Distribution Function (BRDF) effects. approach uses synchronous parameters from PSAC, an lookup table, semi-empirical BRDF model to produce surface reflectance (SR) products through radiative, adjacency effect, corrections. corrected images showed significant improvements in clarity contrast compared pre-correction minimum increases 55.91% 35.63%, respectively. Validation experiments Dunhuang Hefei, China, demonstrated high consistency between SR ground-truth data, maximum deviations below 0.03. For types not covered by ground measurements, comparisons Sentinel-2 yielded 0.04. These results highlight effectiveness proposed improving image quality accuracy, providing reliable data support applications such as disaster monitoring, water resource management, crop monitoring.

Язык: Английский

Процитировано

0