Quantifying how topography impacts vegetation indices at various spatial and temporal scales

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 312, P. 114311 - 114311

Published: Aug. 3, 2024

Satellite-derived vegetation indices (VIs) have been extensively used in monitoring dynamics at local, regional, and global scales. While numerous studies explored various factors influencing VIs, a remarkable knowledge gap persists concerning their applicability mountain areas with complex topographic variations. Here we bridge this by conducting comprehensive evaluation of the effects on ten widely VIs. We three strategies, including: (i) an analytic radiative transfer model; (ii) 3D ray-tracing (iii) Moderate Resolution Imaging Spectroradiometer (MODIS) products. The two models provided theoretical results under specific terrain conditions, aiding first exploration interactions both shadow spatial scale MODIS-based quantified discrepancies VIs between MODIS-Terra MODIS-Aqua over flat rugged terrains, providing new insights into real satellite data across different temporal scales (i.e., from daily to multiple years). Our were consistent these revealing key findings. normalized difference index (NDVI) generally outperformed other yet all did not perform well (e.g., mean relative error (MRE) 14.7% for NDVI non-shadow 26.1% areas). impacts exist spatiotemporal For example, MREs reached 28.5% 11.1% 30 m 3 km resolutions, respectively. quarterly annual deviations also increased slope. found topography-induced interannual variations simulated MODIS data. trend Tibetan Plateau 2003 2020 as slope steepened enhanced (EVI) doubled). Overall, sun-target-sensor geometry changes induced topography, causing shadows mountains along obstructions sensor observations, compromised reliability terrains. study underscores considerable particularly effects, scales, highlighting imperative cautious application VIs-based calculation mountains.

Language: Английский

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Development of Fractional Vegetation Cover Change and Driving Forces in the Min River Basin on the Eastern Margin of the Tibetan Plateau

Forests, Journal Year: 2025, Volume and Issue: 16(1), P. 142 - 142

Published: Jan. 14, 2025

Fractional vegetation cover (FVC) is an important indicator of regional ecological environment change, and quantitative research on the spatial temporal distribution FVC trend change great significance to monitoring, evaluation, protection, restoration ecology. This study estimates eastern Tibetan Plateau margin from 2000 2020 using image element dichotomous model based Google Earth Engine platform MODIS-NDVI images. It also investigates changes in this region its drivers Theil–Sen Mann–Kendall tests, autocorrelation analysis, geodetector, machine learning approaches impact. The results indicated a generally erratic rising tendency, with Min River Basin (MRB) near tip having annual average 0.67 growth rate 0.16%. percentage places better reached 60.37%. showed significant positive was clustered. Driver analyses that soil type, DEM, temperature, potential evapotranspiration, land use type were main influencing Plateau. In addition, random forest (RF) outperformed support vector (SVM), backpropagation neural network (BP), long short-term memory (LSTM) regression fitting. summary, shows overall upward trend, has improved significantly over past two decades.

Language: Английский

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A 10 m resolution land cover map of the Tibetan Plateau with detailed vegetation types

Earth system science data, Journal Year: 2024, Volume and Issue: 16(7), P. 3307 - 3332

Published: July 19, 2024

Abstract. The Tibetan Plateau (TP) hosts a variety of vegetation types, ranging from broadleaved and needle-leaved forests at the lower altitudes in mesic areas to alpine grassland higher xeric areas. Accurate detailed mapping distribution on TP is essential for an improved understanding climate change effects terrestrial ecosystems. Yet, existing land cover datasets are either provided low spatial resolution or have insufficient types characterize certain unique ecosystems, such as scree. Here, we produced 10 m map with 12 classes 3 non-vegetation year 2022 (referred TP_LC10-2022) by leveraging state-of-the-art remote-sensing approaches including Sentinel-1 Sentinel-2 imagery, environmental topographic datasets, four machine learning models using Google Earth Engine platform. Our TP_LC10-2022 dataset achieved overall classification accuracy 86.5 % kappa coefficient 0.854. Upon comparing it global products, showed significant improvements terms reflecting local-scale vertical variations southeast region. Moreover, found that scree, which ignored occupied 13.99 region, shrublands, characterized distinct forms (deciduous shrublands evergreen shrublands) largely determined topography missed 4.63 provides solid foundation further analyses need accurate delineation these TP. sample freely available https://doi.org/10.5281/zenodo.8214981 (Huang et al., 2023a) https://doi.org/10.5281/zenodo.8227942 2023b), respectively. Additionally, can be viewed https://cold-classifier.users.earthengine.app/view/tplc10-2022 (last access: 6 June 2024).

Language: Английский

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Enhancing resilience against geological hazards and soil erosion through sustainable vegetation management: A case study in Shaanxi Province

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 423, P. 138687 - 138687

Published: Sept. 6, 2023

Language: Английский

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Landscape Heterogeneity Drives the Growth of Invasive Acacia Melanoxylon in Humid Forests in Kenya (Nabkoi and Timboroa Forests)

American Journal of Agriculture and Forestry, Journal Year: 2025, Volume and Issue: 13(1), P. 49 - 59

Published: Feb. 26, 2025

Invasion of forest by Acacia species is widespread in many terrestrial environments. However, their response to variation environmental conditions has received less attention. This study determined the influence landscape heterogeneity on growth Australian Blackwood (<i>Acacia melanoxylon</i>) tow tropical highland humid forests (Nabkoi Forest and Timboroa Forest) Kenya. Sampling was done laying three-500 m long transect, followed overlaying three plots 0.1 ha. plot (10 × 10 m) longitudinally at 235 intervals. Tree density, diameter breast height (DBH) > 1.3 m, tree density were measured each plot. The established that one sites capable supporting a larger number trees (in terms density) whose DBH height) constrained while other site supports low fast-growing acacia. DBH, acacia responded heterogeneity. invasive significantly (<I>P</I> < 0.05) affected altitude (-ve), slope (+ve), aspect (+ve). current demonstrates altitude, slope, influenced <i>A. melanoxylon</i> studied forest. To gain insight how these gradients affect without compounding factors, future studies should be conducted under controlled conditions.

Language: Английский

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Treeline remote sensing: from tracking treeline shifts to multi‐dimensional monitoring of ecotonal change

Remote Sensing in Ecology and Conservation, Journal Year: 2023, Volume and Issue: 9(6), P. 729 - 742

Published: June 19, 2023

Abstract Remote sensing applications have a long history in treeline research. Recent reviews examined the topic mainly from methodological point of view. Here, we propose question‐oriented review remote ecology to relate methodologies key ecological metrics and identify knowledge gaps promising areas for future We performed meta‐analysis assess role as tool measuring spatial patterns dynamics alpine Arctic ecotone globally. assessed geographic distribution, scale analysis, relationships between techniques through co‐occurrence mapping multivariate statistics. Our analysis revealed that only 10% studies applied tools, often associated with keyword ‘climate change’. Monitoring adopted coarser resolutions over longer temporal extents comparison other studies. A multiscale multi‐sensor approach was implemented just 19% papers. Long‐term research commonly relied on aerial oblique photography measure shifts photointerpretation within multidisciplinary framework. More recent were quantified using greenness trends derived pixel‐based classification satellite images. Many short‐term focused delineating tree object‐based uncrewed vehicle (UAV) images or LiDAR data. Over past decade, high‐resolution low‐cost UAV has emerged an interesting opportunity fill gap local‐scale coarse‐resolution sensors. Additionally, would strongly benefit frameworks integrate field environmental science. The multi‐dimensional structural complexity treelines typically responds drivers multiple scales thus is best described approaches.

Language: Английский

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How Do Climate and Latitude Shape Global Tree Canopy Structure?

Forests, Journal Year: 2025, Volume and Issue: 16(3), P. 432 - 432

Published: Feb. 27, 2025

Understanding global patterns of tree canopy height and density is essential for effective forest management conservation planning. This study examines how these attributes vary along latitudinal gradients identifies key climatic drivers influencing them. We utilized high-resolution remote sensing datasets, including a 10 m resolution dataset aggregated to 1 km computational efficiency, derived from ground-based measurements. To quantify the relationships between structure environmental factors, we applied nonlinear regression models climate dependency analyses, incorporating bioclimatic variables WorldClim dataset. Our finding that latitude exerts dominant but asymmetric control on density, with tropical regions exhibiting strongest correlations. Tree follows quadratic pattern, explaining 29.3% variation, this relationship most pronounced in tropics (−10° 10° latitude, R2 = 91.3%), where warm humid conditions promote taller forests. Importantly, effect differs by hemisphere, Southern Hemisphere (R2 67.1%) showing stronger dependence than Northern 35.3%), indicating asymmetry growth dynamics. exhibits similar trend weaker predictive power 7%); however, within tropics, explains 90.6% underscoring strong constraints biodiverse ecosystems. Among isothermality (Bio 3) identified as determinant 50.8%), suggesting stable temperature fluctuations foster strongly influenced mean diurnal range 2, 36.3%), emphasizing role daily thermal variability distribution. Precipitation-related factors 14 Bio 19) moderately explain (~33%) (~25%), reinforcing moisture availability structuring advances ecology research integrating data robust climate-driven modeling, revealing previously undocumented hemispheric asymmetries biome-specific dependencies. These findings improve offer new insights strategies, particularly vulnerable change.

Language: Английский

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A Feature-Reinforced Ensemble Learning Framework for Space-Based DEM Correction

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(8), P. 1337 - 1337

Published: April 9, 2025

Near-global Digital Elevation Model (DEM) products generated through space-based radar techniques have become a basic data source for variety range of applications. However, these DEM often contain typical errors such as vegetation bias and topography-related errors, which impede their practical utility. Despite the development numerous correction methods based on mathematical fitting artificial neural networks over recent decades, reliably correcting large-scale spaceborne radar-derived DEMs remains an open challenge due to issues like underfitting or overfitting. This paper introduces novel framework called Feature-Reinforced Ensemble Learning (FREEL) designed specifically DEMs. Within this FREEL framework, feature derivation module reinforcement are integrated enhance original input features. Subsequently, adaptive weighting variant DeepForest algorithm is proposed emphasize critical features improve training robustness, even with limited data. The Shuttle Radar Topographic Mission (SRTM) Hunan Province, China, characterized by diverse surface terrain coverage, were selected evaluate framework. results indicate that accuracy SRTM corrected using improved 40%, surpassing several machine learning baseline algorithms average 45% 23%, respectively. method provides more robust solution near-global products.

Language: Английский

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Vegetation Phenological Differences Between Polar‐ and Equatorial‐Facing Slopes in the Three Rivers Source Region, Tibetan Plateau

Geophysical Research Letters, Journal Year: 2024, Volume and Issue: 51(5)

Published: Feb. 28, 2024

Abstract Vegetation growth is influenced by the microclimate driven aspects, as evident in asymmetric vegetation greenness on polar‐facing slopes (PFS) and equatorial‐facing (EFS). However, it remains uncertain whether aspects influence phenology. To address this question, we defined aspect‐induced phenological differences between PFS EFS from 2019 to 2022 within each 3 × km 2 grid, using average metrics extracted Sentinel‐2 data. We found that start of growing season (SOS) occurs earlier cold humid regions, but arid areas, has an SOS. The end (EOS) consistently occurred later due radiation limitations autumn Employing space‐for‐time approach, observed distribution climate space could potentially indicate trends different slope orientations future. Our study provides valuable insights into topographic regulation

Language: Английский

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Spatiotemporal pattern of post-earthquake vegetation recovery in a mountainous catchment in southwestern China

Natural Hazards, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 20, 2024

Language: Английский

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