Search Results (674)

Surface energy partitioning regulates heat and water exchange between land and atmosphere and reflects alpine ecosystem responses to meteorological variation. Using radiation and meteorological data from November 2022 to October 2023, we compared adjacent alpine shrubland (Hulu 1) and alpine meadow (Hulu 2) ecosystems in the Qilian Mountains. Surface energy fluxes were estimated with a combined method based on surface energy balance, then evaluated with eddy covariance measurements. Path models examined direct and indirect environmental effects on turbulent fluxes. Standardized sensitivity coefficients based on evaporative fraction (EF) assessed seasonal responses of energy partitioning to environmental variation. Both ecosystems showed similar seasonal patterns, although flux magnitudes differed. Net radiation (R_n) followed a unimodal annual cycle and averaged 107.69 W m⁻² in the meadow and 89.36 W m⁻² in the shrubland. Sensible heat flux (H) peaked in May, with annual means of 60.22 and 51.68 W m m⁻². Latent heat flux (LE) peaked in July and averaged 49.12 and 38.58 W m m⁻². Soil heat flux (G) varied least, averaging −21.64 and −0.89 W m⁻². Path analysis identified R_n as the strongest control on turbulent fluxes. Its effect on H was weaker in the shrubland (0.92) than in the meadow (0.97), whereas its effect on LE was stronger in the shrubland (0.94) than in the meadow (0.71). Wind speed was positively related to H but negatively related to LE, with a stronger effect on H in the shrubland. Vapor pressure deficit (VPD) was negatively related to H but positively related to LE. Soil water content (SWC) had limited direct effects on turbulent fluxes at both sites. Sensitivity analysis showed higher overall EF sensitivity to environmental variation in the meadow during the growing season (0.510 vs. 0.228). Meadow EF was more sensitive to soil temperature (T_s) and SWC, whereas shrubland EF responded more strongly to VPD. Over the whole period, overall EF sensitivity was higher in the shrubland than in the meadow (0.439 vs. 0.353). These findings show that vegetation type and local environmental conditions jointly shape surface energy balance and energy partitioning in alpine ecosystems. Full article

Solar tracking can increase photovoltaic (PV) energy yield, but its contribution to sustainable electricity depends on more than geometric gain. This structured narrative review evaluates flat-plate and low-concentration PV trackers using an integrated three-layer taxonomy covering mechanical architecture, actuation and drivetrain, and control strategy. Tracker classes are compared in terms of annual energy gain, life-cycle cost, parasitic consumption, land-use efficiency, structural resilience, reliability, maintainability, and deployment maturity. Utility-scale horizontal single-axis trackers using astronomical control, backtracking, supervisory monitoring, and weather-dependent stow provide the most mature balance of energy yield, cost, and operational robustness. Dual-axis systems can offer higher output under high-direct-normal-irradiance conditions but impose greater structural and O&M burdens, while passive fluid-based and shape-memory-alloy concepts remain mainly experimental. The review also examines bifacial and terrain-aware tracking, agrivoltaic dual land use, extreme-weather resilience, tracker-specific availability, artificial intelligence, digital twins, predictive maintenance, and end-of-life considerations. A plant-level decision framework and reporting checklist are proposed to support transparent, project-specific choices that maximize lifetime renewable-energy value while limiting material use, land-use conflict, operational risk, and avoidable life-cycle impacts. Full article

Strawberries are among the most water-sensitive horticultural crops because of their shallow root systems and high transpiration rates, making them particularly vulnerable to rising temperatures, irregular rainfall, and increased vapor pressure deficits under climate change. This review paper synthesizes methods for quantifying water-use efficiency (WUE) in strawberry production, including empirical equations, crop models (AquaCrop, DSSAT, and HYDRUS), and remote sensing approaches. It examines how water use, crop productivity, and WUE respond to environmental conditions and management practices. Earlier studies show that rising temperatures, altered precipitation patterns, and increased atmospheric water demand can often reduce WUE, although responses vary depending on cultivar, management practices, and environmental conditions. In contrast, practices such as deficit irrigation, mulching, and microclimate modification may help maintain water productivity. Remote sensing tools such as the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Surface Energy Balance Algorithm for Land (SEBAL), and Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) are increasingly used to evaluate evapotranspiration, crop condition, and irrigation performance from field to regional scales. Collectively, these approaches improve understanding of strawberry water use and support irrigation management under changing climatic conditions. Full article

Low-carbon sustainable development requires a better understanding of how urban land expansion reshapes carbon emission patterns within and across cities. Impervious surface expansion is a visible land use expression of urbanization and a key carrier of energy consumption, industrial activity, and ecological loss. Yet, its cross-city effects on carbon emissions remain insufficiently understood, particularly in highly integrated urban agglomerations. Using a balanced panel of 41 cities in the Yangtze River Delta (YRD), China, from 2008 to 2022, this study combines EDGAR gridded CO₂ emissions, annual land cover data, global and local spatial autocorrelation analysis, and a two-way fixed-effects Spatial Durbin Model (SDM) to examine the local and spillover effects of impervious surface expansion. The results show that impervious surfaces and carbon emissions both evolved from core agglomeration toward peripheral diffusion, while carbon emissions maintained significant positive spatial autocorrelation, with Moran’s I remaining positive and significant throughout the study period. SDM estimates indicate that local impervious surface expansion significantly increases local carbon emissions, whereas the estimated indirect effect on neighboring cities is significantly negative. Effect decomposition confirms a positive direct effect and a negative indirect effect under both inverse-distance and contiguity weight matrices. A rolling-window analysis further shows that the negative spillover effect strengthened over time. These findings demonstrate that urban land hardening should be evaluated not only as a local emission driver but also as a spatially embedded process within regional carbon governance. By linking impervious surface expansion with spatial carbon emission interactions, this study contributes to sustainability research by providing empirical evidence for sustainable urban agglomeration development. Full article

Irrigation water management in arid systems requires spatially distributed estimates of crop evapotranspiration (ET) that fixed crop coefficients cannot provide. The actual ET of flood-irrigated rice (Oryza sativa L.) on the arid northern coast of Peru was mapped with the METRIC surface energy balance model (Mapping EvapoTranspiration at high Resolution with Internalized Calibration) on Google Earth Engine (GEE). Ten cloud-free Landsat 8/9 scenes (January–July 2022) were processed over 113 ha at Ferreñafe (Lambayeque) on the 30 m product grid, onto which the 100 m native thermal observation was resampled, with internal calibration based on automatic anchor-pixel selection and hourly ERA5-Land data. Daily field-mean ET ranged from 4.2 to 8.1 mm d⁻¹, peaking during flooding and establishment and declining towards harvest. Because the same reference $E{T}_o$ underlies the METRIC internal calibration and the FAO-56 estimate, this is a comparison between two modelling approaches rather than an independent validation. Against the FAO-56 reference ET, METRIC showed a positive bias of $+0.65$ mm d⁻¹ (percent bias (PBIAS) $=+13\%$; root mean square error (RMSE) $=1.23$ mm d⁻¹; $r^2=0.57$; $n=9$, after excluding one date with anomalous reanalysis forcing), concentrated during flooding and after harvest, whereas at full canopy cover the two estimates converged. Two global ET products that share neither the METRIC formulation nor the ERA5-Land forcing reproduce the same seasonal decline once the canopy closes ($r=0.63$ and $0.91$) but stay far below in magnitude, as expected from their 500 m pixel. ET did not differ between sowing methods and varied only slightly among cultivars (∼0.3 mm d⁻¹), against marked intra-field variability. The METRIC–GEE workflow offers a low-cost, high-resolution tool for monitoring water use in data-scarce arid rice systems. Full article

Rapid urban-industrial development has intensified surface warming in global cities, including India, posing critical challenges for sustainable urban environments. While advanced AI and remote sensing methods have mapped urban heat patterns, a fundamental thermodynamic understanding of how cities generate, absorb, store, and dissipate heat with the urban land transformation remains underexplored. This study conceptualizes the urban geo-thermodynamics mechanism as a comprehensive framework to quantify urban surface energy exchanges, heat flux dynamics, and thermal responses in the Haldia urban-industrial region (103.84 km²) of eastern India. The analysis employs Landsat-derived impervious surface expansion, land surface temperature (LST), and normalized difference vegetation index (NDVI), NASA POWER radiation fluxes, world settlement footprint 3D structural (2023) and material stock (2024) data, and census-based population records (1991–2021). The integrated mathematical formulations were developed after the remote sensing-GIS-based statistical analysis for the urban energy balance through the Urban Thermodynamic Index (UTI), Urban Heat Retention Efficiency (UHRE), and Urban Cooling Potential (UCP) indices, which were developed from energy balance equations linking net radiation (Q*), anthropogenic flux (${\mathrm{Q}}_{\mathrm{F}}$), sensible and ground heat (${\mathrm{Q}}_{\mathrm{H}}$, ${\mathrm{Q}}_{\mathrm{G}}$), and latent heat flux (${\mathrm{Q}}_{\mathrm{E}}$). The results reveal a 36% increase in UTI and a 28% rise in UHRE between 1991 and 2021, indicating enhanced surface heat accumulation and anthropogenic energy input associated with built-up area and population growth (22.87–53.37 km²) and (1452–2375 person/km²). In contrast, UCP declined by 22%, reflecting reduced evaporative cooling due to vegetation loss, with the regression-based calibration (R² = 0.89; RMSE = 0.74 °C) validating strong correspondence with observed LST. These findings demonstrate a quantifiable link between thermodynamic processes and the transformation of the urban morphological landscape. The proposed mathematical-thermodynamic structure provides a scientific, GIS-based statistical method for urban heat risk assessment, energy-efficient planning, and geo-thermal environmental management, supporting global initiatives toward climate-resilient and sustainable urban development. Full article

The management of organic waste in high-altitude mining poses a distinctive circularity challenge: waste is generated at sites decoupled from agricultural systems, while the same operations are legally required to revegetate the land they disturb. This study provides, to the best of our knowledge, the first primary-data environmental characterization of a real system that valorizes dining-facility organic waste from a high-altitude mining unit in northern Peru into a solid biofertilizer and a liquid biol, both applied in situ for land reclamation. Unlike methanogenic digesters, the system operates under a lactic (acidogenic) fermentation regime inoculated with effective microorganisms and does not recover biogas. A cradle-to-gate life cycle assessment (ISO 14040/14044) with Monte Carlo uncertainty propagation was combined with a well-established family of five circular economy indicators, adapted to the non-energy-recovery case by redefining the Energy Self-Sufficiency Ratio (ESSR) and the Decarbonization Circularity Indicator (DCI). The principal contribution is methodological: the framework is extended to a circularity archetype that previous, biogas-centered formulations could not represent, showing that a system can close its material and nutrient loops robustly (WVI = 0.97) while the energy loop is absent by design (ESSR = 0). The climate result is conditional and is a first-order greenhouse-gas (GHG) screening balance, not a physical carbon-sequestration claim: under the upper-bound assumption of full fertilizer substitution, the avoided fertilizer credit outweighs non-methane process emissions only below a narrow fugitive-methane threshold (≈0.32 kg CH₄ per ton), a margin that narrows further once agronomic equivalence is discounted. The measured product acidity suggests that this condition is plausible, but, because methane was not measured directly, the low-emission interpretation is presented as a hypothesis requiring confirmation rather than as a demonstrated result. The environmental burden is driven by material and electricity inputs—chiefly the polypropylene containers and grid electricity—rather than by the biological process, which broadens the set of improvement priorities beyond methane management to include capital-good reuse and electricity decarbonization, without implying that methane can be neglected. Full article

Accurate segmentation of clouds and cloud shadows in optical remote sensing imagery is an indispensable preprocessing step for downstream land-surface observation tasks. However, existing methods strike different trade-offs between local detail preservation and global context modeling, yet they still exhibit two major limitations: insufficient interaction during the dual-branch encoding stage, and decoder-side multi-scale fusion that applies uniform operations to all spatial locations, making it unable to distinguish boundary regions, such as thin cloud boundaries and cloud shadow contours, from homogeneous regions, such as thick cloud interiors. To address these issues, we propose SpecGateNet, a fusion network guided by spectral information from a frequency-domain perspective. The core idea is that the Fourier amplitude spectrum of deep features summarizes how much energy is carried by different spatial frequencies, where high-frequency components typically correspond to rapidly varying regions such as boundaries and textures, whereas low-frequency components are more closely associated with smooth regions. Building on this insight, we use an amplitude-derived, phase-free spectral energy cue constructed from the amplitude spectrum, and integrate it with a learnable gating generation network to produce spatially adaptive fusion modulation signals. SpecGateNet is built upon a CNN-Swin Transformer dual-branch encoder and consists of three key components: a Cross-Feature Fusion module (CFF) that enables stage-wise bidirectional interaction, a frequency-domain dynamic filtering bottleneck that enhances global context through input-adaptive frequency-domain filtering, and a Spectral-Guided Fusion decoder (SGF) that generates spatial gates from the amplitude spectrum to adaptively balance high-level semantics and low-level details. Together, the bottleneck filter and SGF constitute a spectral utilization framework that operates at both the encoder and decoder sides. Using only RGB inputs without relying on infrared auxiliary bands, SpecGateNet achieves the highest mIoU among the compared general-purpose baselines under a unified experimental protocol on three public datasets, namely CloudSEN-12, SPARCS-Val, and 38-Cloud, with mIoU scores of 77.80%, 76.75%, and 93.30%, respectively, outperforming the second-best method by 1.33, 5.26, and 1.44 percentage points. Ablation studies confirm that the spectral modules account for 70.1% of the total performance gain, with SGF contributing the largest single-step improvement among individual modules (+1.22%). Full article

The Mississippi River Delta region is of national and international relevance in terms of agriculture, energy, river navigation, and fisheries. Being one of the most engineered rivers in the world, the Mississippi River has been intensively altered over the past 150 years. The river alterations included the construction of dams, levees, diversions, channelization, spillway flood control systems, and many others. These engineering practices have significantly modified the natural hydrology and sediment dynamics of the river and its deltaic region. While these interventions have provided critical benefits such as flood protection, improved navigation, and economic development, they have also led to profound environmental and ecological consequences. The reduction in sediment delivery to the Mississippi River Delta has accelerated land loss, contributing to the disappearance of coastal wetlands at an alarming rate. The land loss has diminished critical habitats for wildlife, reduced storm surge protection for coastal communities, and disrupted the delta’s natural ability to adapt to fast subsidence. The long-term sustainability of the delta is further threatened by the compounding effects of climate change, including rising sea levels, increased storm intensity, and extreme precipitation and drought conditions. This paper examines the effects, consequences, and future risks of the major river engineering practices on the Mississippi River Delta and provides strategic recommendations that balance human needs with changing natural conditions to ensure sustainability. Specific recommendations include river diversion upstream of New Orleans, better strategies to deal with floods and droughts, strategic maintenance or removal of portions of levees, hybrid coastal-inland human migration, improved transportation connections between coast and inland, and better preparation for future ecosystem shifts. This review is needed because river engineering has made the Mississippi River Delta economically vital yet increasingly vulnerable to sediment loss, wetland collapse, saltwater intrusion, flooding, and population decline. By synthesizing these linked natural and human consequences, it provides a timely framework for rethinking delta sustainability under climate change. Full article

To provide reliable impact protection for a flying car power battery pack under stringent lightweight requirements, especially under takeoff, landing, and drop impact scenarios, a biomimetic metamaterial sandwich enclosure inspired by the hierarchical protective architecture of a tortoise carapace is proposed. The enclosure is composed of an outer shell, an internal sandwich core, and an inner plate, through which load diffusion and deformation buffering can be achieved by multilayer structural coordination. Firstly, three core configurations, including conventional honeycomb, a chiral structure with negative Poisson’s ratio (NPR) characteristics, and an NPR concave structure, are comparatively investigated through high-speed impact finite element simulations. The NPR concave structure is regarded as the preferred core configuration due to its more balanced energy absorption behavior and superior deformation stability. Afterwards, the NPR concave structure is embedded into the full battery pack enclosure, and the protective performances of the proposed battery pack are evaluated under representative flying car operating conditions. Compared with those of the conventional honeycomb, the maximum displacement of the proposed battery pack decreases by 49.31% under the takeoff-and-landing overload condition, and the maximum intrusion decreases by 25.94% under the drop impact condition. The results indicate that the tortoise-carapace-inspired metamaterial sandwich structure effectively enhances the deformation resistance and anti-intrusion capability of a flying car battery pack, thereby providing a feasible structural design approach for battery protection in flying car applications. Full article

This study evaluated the individual and interactive effects of straw management, tillage systems, and wheat growth stages on surface energy balance (SEB) dynamics in a semi-arid wheat production system, with particular focus on net radiation (Rn), sensible heat flux (H), latent heat flux (LE), Bowen ratio (β), and energy partitioning (EP). A field experiment was conducted during the 2022–2023 growing season using a split–split plot design with two straw management treatments, four tillage systems, and three growth stages. Surface energy balance components were estimated through field-based micrometeorological measurements. Data were analysed using ANOVA, variance partitioning analysis, and Pearson correlation analysis. All experimental factors significantly affected SEB components, although growth stage represented the dominant source of variability, accounting for 42–58% of total variance. Flowering stage consistently promoted the highest LE values and the lowest β and EP values, indicating enhanced evaporative cooling during maximum crop development. Conservation-oriented tillage systems substantially modified thermal partitioning, with no-tillage (NT) significantly increasing LE and reducing H relative to conventional tillage (CT). The combination of straw incorporation and NT during flowering (IS + NT + S2) produced the highest LE value (129.15 W m⁻²) and one of the lowest H values (18.35 W m⁻²). Bowen ratio progressively decreased from CT (8.57) to NT (1.44), confirming a shift from sensible to latent heat exchange under conservation-oriented management. Crop phenology and conservation-oriented soil management jointly regulated thermal partitioning and evaporative cooling in semi-arid wheat systems. NT combined with straw incorporation substantially enhanced latent heat exchange while reducing sensible heating, particularly during flowering. This study provides novel field-based evidence regarding the combined influence of straw management, tillage systems, and wheat phenology on SEB dynamics under semi-arid conditions, contributing to improved understanding of land–atmosphere interactions and climate-adaptive agricultural management strategies. Full article

Energy balance models using remote sensing imagery can provide reliable, cost-effective estimates of actual evapotranspiration (ET_a) over large areas. This study evaluated the Analytical Land Atmosphere Radiometer Model (ALARM), a one-source energy balance model, for estimating ET_a in Mediterranean orchard systems. The model was applied to almond, olive, citrus, and pomegranate orchards during the 2019–2020 growing seasons using MODIS imagery. Calibration and validation were performed against ET_a estimates from the SIMDualKc and HYDRUS-1D models. Sensitivity analysis showed canopy-related parameters had the greatest influence on ET_a estimates. ALARM successfully reproduced seasonal ET_a dynamics for almond, citrus, and pomegranate orchards, achieving R² values ≥ 0.74 and normalized RMSE ≤ 34.1%. Performance was weaker for olive orchards (R² = 0.47–0.85; NRMSE = 32.4–50.2%), where ET_a was overestimated due to inadequate representation of deficit irrigation. The coarse spatial resolution of MODIS imagery also required an empirical adjustment parameter (β = 0.50–0.92) to address mixed land-cover conditions within pixels. Despite these limitations, ALARM proved promising for large-scale water resource assessments, although its suitability for detailed field-scale irrigation management remains limited. Full article

Mountain transition zones are highly sensitive to environmental change, yet the nonlinear coupling between topography and hydroclimate in controlling vegetation Net Primary Productivity (NPP) remains insufficiently constrained. Here, we reconstructed a 2003–2025 annual NPP time series for the West Qinling Mountains using a Carnegie–Ames–Stanford Approach (CASA)-based workflow that integrated Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation products, fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis for land (ERA5-Land) meteorological data, Shuttle Radar Topography Mission (SRTM) topography, and an Aridity Index (AI) dataset. Product-based validation against the annual MOD17A3HGF dataset indicated strong agreement, with a 23-year mean spatial Spearman correlation of 0.823 and a mean annual Pearson correlation of 0.773. The reconstructed dataset showed that 98.50% of the study area experienced increasing NPP, including 50.26% with significant increases, and the domain-wide mean Sen slope reached approximately 3.08 g C m⁻² yr⁻¹. Factor detection further showed that radiation (q = 0.253), elevation (q = 0.252), and temperature (q = 0.249) were the dominant single controls, whereas Aridity–Temperature (q = 0.367) and Elevation–Aridity (q = 0.367) represented the strongest interactions. The concentration of the strongest gains in gentle-slope and moderate-aridity settings suggests that vegetation recovery is maximized where topographic buffering and water-energy balance are jointly optimized. These results strengthen the interpretation of NPP dynamics in mountainous climate-transition environments and provide a basis for spatially targeted ecological restoration, regional carbon-budget assessment, and climate adaptation planning. Full article

Against the backdrop of global climate change and carbon neutrality strategies, land use carbon emissions have become a prominent topic amid regional efforts toward low-carbon transformation. However, existing studies on land-use carbon emissions have predominantly focused on humid and economically developed regions, while the unique carbon metabolism pathways of arid oasis–desert ecosystems, which are characterized by extremely low environmental carrying capacity and high sensitivity to land-use disturbance, remain largely unexplored. This study takes the oasis urban cluster in the Tarim Basin in southern Xinjiang Uygur Autonomous Region as the research object. This region belongs to a typical oasis–desert composite ecosystem, with a simple structure and low environmental carrying capacity (reflected by sparse vegetation cover < 20%, annual precipitation < 100 mm, extremely limited water resources, and high sensitivity to land disturbance). Its carbon metabolism pathway (i.e., the dynamic balance between carbon sources and sinks induced by land-use change) is fundamentally different from that in humid areas, and thus merits dedicated investigation. This study selects the period from 2000 to 2020 as the research period, which completely covers the acceleration period of urbanization and agricultural expansion in the Tarim Basin oasis urban cluster since the advancement of China’s Western Development Initiative. The data have a temporal resolution of 5 years (samples in 2000, 2005, 2010, 2015, 2020) and a spatial resolution of 30 m for land use and prefecture level for socio-economic indicators. Based on this, to fill the above-mentioned research gap, a research framework integrating the carbon emission coefficient accounting method, landscape pattern index, spatial autocorrelation analysis and geographic detector is adopted. Specifically, this study aims to systematically quantify the spatio-temporal evolution of land use carbon emissions and identify the most robust driving factors in the Tarim Basin oasis urban cluster by integrating multiple models, an approach that has not been previously applied to arid oasis regions. The research results show: (1) Based on the carbon emission coefficient method, total carbon emissions increased from 1.4455 million tons to 22.364 million tons, following a ‘slow-then-fast’ trajectory. In terms of temporal evolution, the study period can be further divided into three sub-stages: 2000–2005 (slow diffusion, with emission center skewed toward the northern energy-intensive zone), 2005–2015 (rapid restructuring, characterized by a ‘unipolar surge’ in Aksu and spread to the central oasis belt), and 2015–2020 (high-intensity stabilization, forming a cross-regional emission belt). Meanwhile, the land use structure has undergone a significant transformation. Construction land and cultivated land have continued to expand, while ecological land has significantly shrunk, resulting in a complex transformation pattern of oasis–desert ecotone. (2) The overall landscape became increasingly fragmented and diversified, the integrity of ecological space was damaged, and the regional carbon sink function was weakened. (3) The spatial autocorrelation analysis indicates that the spatial distribution of carbon emissions shows a heterogeneous pattern, forming a high-emission concentration area centered around Aksu-Bayingol. However, the global Moran’s I index is negative (such as −0.171 in 2020, p > 0.05), suggesting that carbon emissions have not formed a significant spatial clustering. (4) Carbon emissions are dominated by human and economic factors, and the interaction of factors is significant. The geographic detector identifies population density (average q value 0.904) and the proportion of construction land (average q value 0.858) as the key determinants of spatial variation in carbon emissions, reflecting the sensitive response of the human-nature system of arid zones to the urbanization process. These findings not only clarify the spatio-temporal features and driving forces of land use carbon emissions in the Tarim Basin oasis urban cluster, but also provide a replicable analytical framework for carbon-emission research in other arid and semi-arid regions worldwide. Based on these findings, we discuss the unique driving mechanisms of carbon emissions in arid regions, conclude that construction land expansion and population density are the dominant factors, and recommend a three-tier zoning governance system (carbon source control zone, carbon sink enhancement zone, coordinated development zone) for low-carbon spatial planning in arid areas. Full article

Evapotranspiration (ET) estimation in desert-oasis ecotones remains challenging due to sparse meteorological observations and the coarse spatial resolution of satellite remote sensing, which limit the ability to resolve highly heterogeneous surface conditions. To address this issue, this study develops a high-resolution ET estimation framework by integrating unmanned aerial vehicle (UAV)-based thermal infrared remote sensing with a three-temperature (3T) model in the Hexi Corridor. UAV-derived land surface temperature (LST) at meter-scale resolution, together with meteorological and vegetation data, was used to drive the model and generate high-resolution ET maps. The model’s performance was validated spatially against the Surface Energy Balance Algorithm for Land (SEBAL) model and at the point-scale against a two-source model. The results show that: (1) The 3T model effectively captured the spatial gradient of decreasing ET from cropland (3–10.69 mm d⁻¹), through shelterbelts (3–6 mm d⁻¹), to desert areas (<3 mm d⁻¹). (2) Spatial validation against the SEBAL model was conducted using stratified pixel-wise comparisons across four land-cover types over 14 UAV transects, showing strong agreement (R² = 0.90–0.95; RMSE = 0.22–0.43 mm d⁻¹). The model achieved highest accuracy in cropland (R² = 0.92; RMSE = 0.24 mm d⁻¹), with slight overestimation in shelterbelts. (3) Point-scale validation against the two-source model yielded an MAE of 0.38 mm d⁻¹. This study demonstrates the effectiveness of combining UAV thermal infrared data with the 3T model for high-resolution ET simulation in complex ecological transition zones, offering a promising technical approach for ecohydrological monitoring and water resource assessment in arid regions. Full article