Evapotranspiration inversion using a two-sources Model coupling multiscale data fusion and interpolation methods

Research in Cold and Arid Regions, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

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NDVI time-series data reconstruction for spatial-temporal dynamic monitoring of Arctic vegetation structure

Geo-spatial Information Science, Год журнала: 2024, Номер unknown, С. 1 - 19

Опубликована: Апрель 26, 2024

Spatial-temporal dynamics monitoring of Arctic vegetation structure (i.e. distribution range tundra and forest) is great significance for evaluating global warming effect. Currently, time-series relies primarily on the Normalized Difference Vegetation Index (NDVI), which derived from optical remote sensing images. However, because factors such as long revisit period satellites impact climate, observations are severely lacking in region. This results NDVI data highly discontinuous difficult to reflect actual variations structure, traditional reconstruction method would usually fail severe missing conditions. Therefore, this study developed a Time Series Reconstruction considering Periodic Trend (TSR-PT), specifically alleviating observation condition It can separate phenological change trend incomplete time series NDVI, borrow information neighboring unchanged years compensate current years, based learned inter-annual intra-annual correlation. We explore its usability variation Vorkuta region (transition zone taiga Circle) MODIS data. found that proposed TSR-PT able reconstruct with reasonable feature even rate reaches over 70%, falsely constructed by filtering or fitting method, suppress them 0.038 terms RMSE; besides, we find since 21-century, trees have continued increase encroach original ecosystem, caused largely structural change, believe promote research.

Язык: Английский

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A New Evapotranspiration-Based Drought Index for Flash Drought Identification and Monitoring

Remote Sensing, Год журнала: 2024, Номер 16(5), С. 780 - 780

Опубликована: Фев. 23, 2024

Flash droughts, a type of extreme event characterized by the sudden onset and rapid intensification drought conditions with severe impacts on ecosystems, have become more frequent in recent years due to global warming. The index is an effective way monitor mitigate its negative impact human production life. This study presents new flash identification monitoring method based evapotranspiration-based index, i.e., evaporative stress percentile (ESP). ESP-based considers both rate each phase development, which allows it be used quantitative assessment characteristics including detailed information onset, termination, intensity. ESP evaluated using soil moisture (SMP) derived from GLDAS-Noah data. results show that there was good agreement between SMP across most China, correlation coefficient values above 0.8 MAE below 10 percentile/week. then identify droughts China compared Precipitation Anomaly Percentage (PAP) for three cases typical events different regions land covers. It demonstrates robustness detecting geographical regions, cover types, climatic characteristics. applied characterize historical 1979–2018 occur frequently transitional climate zone humid arid Northern China. contributes better understanding development supports decision-makers providing early warnings droughts.

Язык: Английский

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Urban Ecological Quality Assessment Based on Google Earth Engine and Driving Factors Analysis: A Case Study of Wuhan City, China

Sustainability, Год журнала: 2024, Номер 16(9), С. 3598 - 3598

Опубликована: Апрель 25, 2024

Ecological quality is a critical factor affecting the livability of urban areas. Remote sensing technology enables rapid assessment ecological (EQ), providing scientific theoretical support for maintenance and management ecology. This paper evaluates analyzes EQ its driving factors in city Wuhan using remote data from five periods: 2001, 2006, 2011, 2016, 2021, supported by Google Earth Engine (GEE) platform. By employing principal component analysis, Sensing Index (RSEI) was constructed to assess spatiotemporal differences City. Furthermore, study utilized optimal parameter-based geographical detector model analyze influence such as elevation, slope, aspect, population density, greenness, wetness, dryness, heat on RSEI value 2021 further explored impact changes precipitation temperature Wuhan. The results indicate that (1) analysis shows greenness wetness positively affect Wuhan’s EQ, while dryness have negative impacts; (2) reveals 2001 showed trend initial decline followed improvement, with classification grades evolving poor average good better; (3) all nine indicators certain Wuhan, ranking NDVI > NDBSI LST WET elevation density GDP slope aspect; (4) annual non-significant EQ. has improved recent years, but comprehensive still requires enhancement.

Язык: Английский

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Reconstructing daytime and nighttime MODIS land surface temperature in desert areas using multi-channel singular spectrum analysis

Ecological Informatics, Год журнала: 2024, Номер unknown, С. 102830 - 102830

Опубликована: Сен. 1, 2024

Язык: Английский

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The HANTS-fitted RSEI constructed in the vegetation growing season reveals the spatiotemporal patterns of ecological quality

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Июнь 26, 2024

Yuxi, located in China's central plateau of Yunnan, is grappling with ecological and environmental challenges as it continues to develop its economy. While quality assessment serves the foundation for protection, pivotal have reliable long-term methods assessing status support informed decision-making protection. Reliable order facilitate protection are applied. This study utilized Landsat data reconstruct four indices (greenness, wetness, dryness, heat) during vegetation growth Yuxi from 2000 2020 that employs Harmonic Analysis Time Series (HANTS) method. Subsequently, annual Remote Sensing Ecological Index (RSEI) was computed by using reconstructed evaluate Yuxi. Additionally, spatiotemporal patterns determinants Yuxi's unveiled through Sen's slope estimator Mann-Kendall test (Sen + MK) trend analysis, spatial auto-correlation geographical detectors applied year-by-year RSEI data. The findings paper indicate accuracy significantly influenced season, suggesting constructing model season crucial. Moreover, HANTS optimization method effectively enhances used model, leading smoother more continuous filling missing difference between original falls within range - 0.15 0.15. has an average 0.54 emphasis a moderate level comprehensive quality. Compared river valley plains, mountainous areas higher, presents distinct center-edge pattern. From 2020, exhibited fluctuations, slight overall improvement. Land use patterns, particularly forestry land impervious surfaces, identified main drivers these changes. research offers valuable insights scientific related sustainable development

Язык: Английский

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A river runs through it: Robust automated mapping of riparian woodlands and land surface phenology across dryland regions

Remote Sensing of Environment, Год журнала: 2024, Номер 305, С. 114056 - 114056

Опубликована: Март 1, 2024

Riparian woodlands in drylands are critically important to human society, global biodiversity, and regional water energy budgets. These sensitive ecosystems have experienced substantial degradation over the last several decades from climatic change direct activity. Nevertheless, quantifying long-term dryland riparian remains a major challenge, much uncertainty exists their remaining extent, historical breadth, likely future trajectories. Dryland landscapes show large, fine-scale spatial heterogeneity seasonal greenness patterns, driven part by variation availability. occur where is concentrated landscape, either as aboveground streamflow or subsurface groundwater. In arid semi-arid climates, this renders them phenologically distinctive upland ecosystems. However, despite importance distinctiveness, there currently no automated methods for delineating across extents cloud. Here we designed implemented cloud-based algorithm retrieve land surface phenology patterns multispectral satellite imagery conducted sensitivity analyses using real simulated data demonstrate that approach robust MODIS, Sentinel-2, Landsat realistic ranges of noise cloud cover. We then series random forest vegetation classifiers integrate phenological spectral information, vegetative structure LiDAR, topography LiDAR Shuttle Radar Topography Mission. three local study sites generalized our model run regionally southwestern United States, with balanced accuracy woodland class ranging 94.5% 97.5% when validated datasets. Generally, information proved more than any other source mapping woodlands, which showed stability interannual did types. To knowledge, ours first regional, annual, automatically-generated updated paving way improved modeling management efforts on watershed scales. also provide one operational, exclusively extract Landsat, sensors, providing framework studies investigating aspects seasonality globe.

Язык: Английский

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Investigating the Response of Vegetation to Flash Droughts by Using Cross-Spectral Analysis and an Evapotranspiration-Based Drought Index

Remote Sensing, Год журнала: 2024, Номер 16(9), С. 1564 - 1564

Опубликована: Апрель 28, 2024

Flash droughts tend to cause severe damage agriculture due their characteristics of sudden onset and rapid intensification. Early detection the response vegetation flash is utmost importance in mitigating effects droughts, as it can provide a scientific basis for establishing an early warning system. The commonly used method determining time drought, based on index or correlation between precipitation anomaly growth anomaly, leads late irreversible drought vegetation, which may not be sufficient use analyzing earning. evapotranspiration-based (ET-based) indices are effective indicator identifying monitoring drought. This study proposes novel approach that applies cross-spectral analysis ET-based index, i.e., Evaporative Stress Anomaly Index (ESAI), forcing vegetation-based Normalized Vegetation (NVAI), response, both from medium-resolution remote sensing data, estimate lag vitality status An experiment was carried out North China during March–September period 2001–2020 using products at 1 km spatial resolution. results show average water availability estimated by over 5.9 days, shorter than measured widely (26.5 days). main difference phase lies fundamental processes behind definitions two methods, subtle dynamic fluctuation signature signal (vegetation-based index) correlates with (ET-based versus impact indicated negative NDVI anomaly. varied types irrigation conditions. rainfed cropland, irrigated grassland, forest 5.4, 5.8, 6.1, 6.9 respectively. Forests have longer grasses crops deeper root systems, mitigate impacts droughts. Our method, innovative earlier impending impacts, rather waiting occur. information detected stage help decision makers developing more timely strategies ecosystems.

Язык: Английский

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Globally increased cropland soil exposure to climate extremes in recent decades

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Март 7, 2025

Cropland soil quality is fundamental to nutrient-rich food production and cropland management strategies are decisive for sustainable agriculture. However, inappropriate agricultural practices often lead persistent exposure air sunlight, which largely increases the losses of microorganisms organic carbon, particularly under climate extremes. Here, we provide a satellite-based mapping daily occurrence across global croplands from 2001 2022 evaluate associated degradation risks caused by extreme events. We find that 57% experienced reduction in duration past two decades (23% significant at p < 0.05), mainly located India, United States, China, while 43% an increasing trend (11% 0.05). On average, decreased five days during 2001–2022. Yet, despite overall duration, 86% soils increasingly subjected extremes (30% The areas exposed tend have higher carbon levels than with decreasing exposure, indicating intensified risk soils. Our study offers insights into its vulnerability change, providing evidence support improvements land practices.

Язык: Английский

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Time series satellite remote sensing reveals annual distribution, composition, and trajectory of tidal wetlands in the Yellow River Delta

Estuarine Coastal and Shelf Science, Год журнала: 2025, Номер unknown, С. 109264 - 109264

Опубликована: Март 1, 2025

Язык: Английский

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