4.5 Article

The Influence of Data Density and Integration on Forest Canopy Cover Mapping Using Sentinel-1 and Sentinel-2 Time Series in Mediterranean Oak Forests

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Ecology

Anthropogenic pressures decrease structural complexity in Caucasian forests of Iran

Kiomars Sefidi et al.

Summary: The study found that high anthropogenic pressure in the Arasbaran Protected Area led to aggregated tree distribution, uniformity in tree sizes, and less heterogeneous forest structure. The indices most sensitive to anthropogenic pressure were diameter differentiation, height differentiation, Gini coefficient, and structural diversity. Regular monitoring of these indices should be integrated into conservation management plans for the area.

ECOSCIENCE (2022)

Article Environmental Sciences

Influence of fuel structure derived from terrestrial laser scanning (TLS) on wildfire severity in logged forests

Nicholas Wilson et al.

Summary: The study found that the connectivity between canopy height and understorey vegetation significantly influences the probability of high severity wildfire, with fire weather being the primary driver of wildfire severity, and also affected by topography.

JOURNAL OF ENVIRONMENTAL MANAGEMENT (2022)

Article Multidisciplinary Sciences

Exploiting time series of Sentinel-1 and Sentinel-2 to detect grassland mowing events using deep learning with reject region

Viacheslav Komisarenko et al.

Summary: This paper presents a method for detecting grassland mowing events using time series of Sentinel-1 and Sentinel-2 optical images through a deep learning model. The proposed model achieves high accuracy by using a rejection mechanism based on a threshold of prediction confidence.

SCIENTIFIC REPORTS (2022)

Article Remote Sensing

Integrated use of Sentinel-1 and Sentinel-2 data and open-source machine learning algorithms for land cover mapping in a Mediterranean region

Giandomenico De Luca et al.

Summary: This paper presents a supervised classification method that integrates SAR and optical data to improve land use/land cover mapping in a Mediterranean forest area. The results show that the integration of SAR improves the classification accuracy compared to using only optical data.

EUROPEAN JOURNAL OF REMOTE SENSING (2022)

Article Forestry

Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 Data

Fardin Moradi et al.

Summary: This study used Sentinel-2 remote sensing data to estimate the aboveground biomass (AGB) of Carpinus betulus trees in the Hyrcanian forests of northern Iran. By comparing different machine learning methods, it was found that the ANN algorithm performed the best in AGB estimation.

FORESTS (2022)

Article Environmental Sciences

Monitoring the Reduced Resilience of Forests in Southwest China Using Long-Term Remote Sensing Data

Hao Jiang et al.

Summary: Global warming-induced increase in drought frequency and severity has negatively impacted forest productivity in Southwest China. This study reveals reduced resilience of the forest to drought, particularly in afforestation areas.

REMOTE SENSING (2022)

Article Environmental Sciences

Positive Unlabelled Learning for Satellite Images'Time Series Analysis: An Application to Cereal and Forest Mapping

Johann Desloires et al.

Summary: Applications that aim to extract a single land type from remotely sensed data are common, but defining the negative class can be difficult. To address this challenge, this study proposes a new framework called PUL-SITS, which utilizes a semi-supervised approach to build a final binary classification model using satellite image time series data. The results demonstrate the effectiveness of the proposed method in dealing with the challenges of positive unlabelled learning scenarios.

REMOTE SENSING (2022)

Article Environmental Sciences

Comparison of Random Forest and Support Vector Machine Classifiers for Regional Land Cover Mapping Using Coarse Resolution FY-3C Images

Tesfaye Adugna et al.

Summary: The type of algorithm used for remote sensing image classification has a significant impact on accuracy. In this paper, the performance of random forest (RF) and support vector machine (SVM) algorithms in large area land cover mapping using coarse-resolution images was compared. The results showed that RF outperformed SVM, especially in mixed class classification and handling large input datasets.

REMOTE SENSING (2022)

Article Ecology

Disturbance frequency, intensity and forest structure modulate cyclone-induced changes in mangrove forest canopy cover

Jonathan Peereman et al.

Summary: The study found that one-thirds of cyclone disturbances resulted in canopy damage in mangrove forests. Stands exposed to high wind speeds and close to cyclone paths were more severely damaged, while lower damage was found in areas with higher past cyclone frequency. Canopy damage was higher in taller mangrove stands but decreased with higher aboveground biomass. The distance from the cyclone path and maximum wind speed were the most important factors, explaining over 50% of the variation in cyclone damage.

GLOBAL ECOLOGY AND BIOGEOGRAPHY (2022)

Article Forestry

Assessing the effects of large herbivores on the three-dimensional structure of temperate forests using terrestrial laser scanning

Shun Li et al.

Summary: This study used terrestrial laser scanning (TLS) data to quantify the 3D habitat structural characteristics of different forest types in Northeast China affected by forest management or large herbivore activities. The TLS-derived parameters revealed subtle changes in habitat structures below the canopy and are implicated in wildlife habitat selection and fitness.

FOREST ECOLOGY AND MANAGEMENT (2022)

Article Plant Sciences

Comparison of UAV-based LiDAR and digital aerial photogrammetry for measuring crown-level canopy height in the urban environment

Longfei Zhou et al.

Summary: This study compares the performances of UAV-LiDAR and UAV-DAP approaches in measuring crown-level forest canopy height (FCH) in the urban environment. The results show that non-ground coverage is the main factor affecting the accuracy of the DAP approach in measuring urban FCH.

URBAN FORESTRY & URBAN GREENING (2022)

Article Environmental Sciences

Modeling Forest Canopy Cover: A Synergistic Use of Sentinel-2, Aerial Photogrammetry Data, and Machine Learning

Vahid Nasiri et al.

Summary: This study successfully modeled forest canopy cover in the Hyrcanian mixed temperate forest in Northern Iran using a combination of Sentinel-2 data, high-resolution aerial images, and machine learning algorithms. The results showed that vegetation indices were the most important predictors in the models, and the random forest algorithm performed the best while the elastic net algorithm performed the worst in terms of model performance.

REMOTE SENSING (2022)

Article Environmental Sciences

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

Vahid Nasiri et al.

Summary: Accurate and real-time LULC maps are crucial for dynamic Earth monitoring, planning, and management. This study explored the impact of spectral-temporal metrics and composition methods on machine learning classifiers for accurate LULC mapping, finding that seasonal composites outperformed percentile metrics in providing phenological variation information for different LULC classes. This methodology can produce precise LULC maps efficiently through cloud computing platforms and is beneficial for large-scale mapping projects.

REMOTE SENSING (2022)

Article

Classifying Operational Events in Cable Yarding by a Machine Learning Application to GNSS-Collected Data: A Case Study on Gravity-Assisted Downhill Yarding

S.A. Borz et al.

Bulletin of the Transilvania University of Brasov, Series II: Forestry, Wood Industry, Agricultural Food Engineering (2022)

Article

Seasonal Variation of GPS Accuracy and Precision in Forest Road Mapping

E. Abdi et al.

Bulletin of the Transilvania University of Brasov, Series II: Forestry, Wood Industry, Agricultural Food Engineering (2022)

Article Engineering, Civil

The performance of the reformulated Gash rainfall interception model in the Hyrcanian temperate forests of northern Iran

Touba Panahandeh et al.

Summary: This study examines the applicability of the Reformulated Gash Analytical Model (RGAM) for estimating rainfall interception (I) in reforested areas across the Hyrcanian temperate forests in northern Iran. The results show that different tree species have an impact on rainfall interception. The Norway spruce is the most effective species in reducing erosion and surface runoff. Average-based calculations indicate that evergreen needle-leaved forests have lower free throughfall coefficient but higher canopy storage capacity and evaporation rate compared to deciduous broad-leaved forests. The RGAM satisfactorily estimates I for all species except for the Acer velutinum stand.

JOURNAL OF HYDROLOGY (2022)

Article Forestry

Above-ground biomass estimation in a Mediterranean sparse coppice oak forest using Sentinel-2 data

Fardin Moradi et al.

Summary: This study evaluated the capability of Sentinel-2 satellite data to estimate above-ground biomass in coppice forests of Persian oak in Western Iran. Results indicated that the MLPNN algorithm was the best option for estimating the AGB.

ANNALS OF FOREST RESEARCH (2022)

Article Environmental Studies

Habitat Integrity in Protected Areas Threatened by LULC Changes and Fragmentation: A Case Study in Tehran Province, Iran

Parvaneh Sobhani et al.

Summary: The study analyzed the spatial and temporal changes of habitats in protected areas in Tehran Province, Iran, and found that habitat fragmentation and patch numbers have increased, leading to negative impacts on habitat integrity and spatial patterns.
Article Environmental Sciences

The effectiveness of urban trees in reducing airborne particulate matter by dry deposition in Tehran, Iran

Seyed Mahdi Heshmatol Vaezin et al.

Summary: This study measured and estimated the amount of atmospheric particulate matter (PM) deposition on oriental plane trees in Tehran, Iran, and found that the trees significantly reduce PM concentration at respiratory height.

ENVIRONMENTAL MONITORING AND ASSESSMENT (2021)

Article Environmental Sciences

European Wide Forest Classification Based on Sentinel-1 Data

Alena Dostalova et al.

Summary: The constellation of two Sentinel-1 satellites offers unprecedented SAR data coverage with high spatial and temporal resolution, showing potential for forest mapping and classification at a continental scale in Europe.

REMOTE SENSING (2021)

Article Environmental Sciences

Estimating Forest Structure from UAV-Mounted LiDAR Point Cloud Using Machine Learning

Romain Neuville et al.

Summary: The integration of UAVs with LiDAR technology offers new possibilities for efficient and accurate monitoring of forest stand structures. By improving the HDBSCAN clustering algorithm and utilizing PCA, tree stems can be effectively segmented and their diameters estimated. Results suggest that this methodology can accurately detect tree stems and retrieve tree metrics without the need for site-specific parameters, showcasing potential for minimizing errors and improving tree detection and metrics retrieval.

REMOTE SENSING (2021)

Article Environmental Sciences

How to automate timely large-scale mangrove mapping with remote sensing

Ying Lu et al.

Summary: This study aimed to address the challenges in collecting training samples for large-scale mangrove mapping. By developing an automatic method to collect training samples, introducing two representative one-class classifiers, and comparing various combinations, the study found that the combination of Sentinel-1 and Sentinel-2 yielded the best results.

REMOTE SENSING OF ENVIRONMENT (2021)

Article Environmental Sciences

Machine Learning Classification of Mediterranean Forest Habitats in Google Earth Engine Based on Seasonal Sentinel-2 Time-Series and Input Image Composition Optimisation

Salvatore Pratico et al.

Summary: The sustainable management of natural heritage is a global strategic issue, with remote sensing techniques being used to map, analyze, and monitor natural resources. The research emphasizes the importance of adopting multi-scale and multi-temporal approaches to monitor different vegetation types and species. The Google Earth Engine (GEE) has been proposed as a free cloud-based platform for accessing and processing remotely sensed data at large scales.

REMOTE SENSING (2021)

Article Environmental Sciences

Application of the Random Forest Classifier to Map Irrigated Areas Using Google Earth Engine

James Magidi et al.

Summary: This study utilized random forest algorithm on Google Earth Engine platform to process and classify irrigated areas in Mpumalanga Province, Africa using NDVI to differentiate between irrigated and rainfed areas. Assessment of irrigated areas in 2019 and 2020, along with the impact of Covid-19 pandemic on agriculture, helped in evaluating changes in irrigated areas in smallholder farming areas.

REMOTE SENSING (2021)

Article Environmental Sciences

Monitoring Key Forest Structure Attributes across the Conterminous United States by Integrating GEDI LiDAR Measurements and VIIRS Data

Khaldoun Rishmawi et al.

Summary: Accurate information on global forest distribution and 3D structure is crucial for assessing forest biomass stocks and future terrestrial Carbon sink projections. The GEDI LiDAR sensor provides unprecedented sampling of forest structural properties, with VIIRS data successfully extrapolating GEDI measurements for wall-to-wall forest structure maps in the conterminous US. Validation results demonstrate the robustness of the VIIRS data for monitoring forest structural changes over large areas.

REMOTE SENSING (2021)

Article Chemistry, Multidisciplinary

Integration of Sentinel 1 and Sentinel 2 Satellite Images for Crop Mapping

Shilan Felegari et al.

Summary: This study combines radar data and optical images to identify crop types in the Tarom region. By using Sentinel 1 and Sentinel 2 images, a classification map was created to achieve high accuracy and reliable information in crop identification.

APPLIED SCIENCES-BASEL (2021)

Article Forestry

Spatial Variability and Optimal Number of Rain Gauges for Sampling Throughfall under Single Oak Trees during the Leafless Period

Omid Fathizadeh et al.

Summary: This study revealed significant spatial variability of throughfall under Brant's oak trees in the Zagros region of Iran during the leafless season, suggesting the benefits of using relatively elongated troughs for sampling. The 29 throughfall collectors used in the study were found to be sufficient to robustly estimate tree-scale throughfall values within a 10% error of the mean at the 95% confidence level, highlighting the challenges in individual tree-level measurement.

FORESTS (2021)

Article Environmental Sciences

Assessing the Effect of Training Sampling Design on the Performance of Machine Learning Classifiers for Land Cover Mapping Using Multi-Temporal Remote Sensing Data and Google Earth Engine

Shobitha Shetty et al.

Summary: Machine learning classifiers, particularly Random Forest, were evaluated for their performance in Land Use and Land Cover (LULC) mapping using multi-temporal satellite remote sensing data. Different sampling methods were found to have varying impacts on the classification results, with Stratified Proportional Random Sampling (SRS(Prop)) favoring major classes, Stratified Equal Random Sampling (SRS(Eq)) providing good accuracies for minority classes, and Stratified Systematic Sampling (SSS) performing well for areas with large intra-class variability. Random Forest outperformed other machine learning classifiers with a confidence level of over 95%, while Support Vector Machine and Classification and Regression Trees showed similar performance. Relevance Vector Machine achieved good results with limited training samples.

REMOTE SENSING (2021)

Article Environmental Sciences

Fusion of Sentinel-1 and Sentinel-2 data in mapping the impervious surfaces at city scale

Binita Shrestha et al.

Summary: Urbanization leads to the development of impervious surfaces in open spaces and agricultural fields, affecting natural water infiltration and causing flooding and water pollution. This study utilizes satellite data and classifiers to assess impervious surface growth trends in Lahore from 2015 to 2021, aiming to develop a reliable mapping method for environmental management in the city.

ENVIRONMENTAL MONITORING AND ASSESSMENT (2021)

Article Remote Sensing

A method for predicting large-area missing observations in Landsat time series using spectral-temporal metrics

Zhipeng Tang et al.

Summary: A new method called MOPSTM is proposed to fill missing observations in Landsat data, which shows better performance in accurately predicting missing data compared to other algorithms, especially in nearly cloud-free conditions.

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2021)

Article Remote Sensing

Countrywide mapping of trees outside forests based on remote sensing data in Switzerland

Eylul Malkoc et al.

Summary: The study aims to fill the spatial information gap of Trees Outside Forests (TOF) resources at the national scale through an automated mapping approach based on the UNFAO-FRA definitions. Results show varying accuracy across different regions in Switzerland, with the application of biophysical thresholds influencing error types. The final TOF map produced by the approach covers the entire country, surpasses existing information, and meets management and reporting needs while allowing for biomass, carbon sequestration potential, and species distribution derivation.

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2021)

Article Environmental Sciences

Recurrent-based regression of Sentinel time series for continuous vegetation monitoring

Anatol Garioud et al.

Summary: SenRVM is a new multi-sensor approach to regress SAR time series towards NDVI, utilizing a deep Recurrent Neural Network architecture to provide accurate results in optical temporal resolution.

REMOTE SENSING OF ENVIRONMENT (2021)

Article Forestry

The Role of Canopy Cover Dynamics over a Decade of Changes in the Understory of an Atlantic Beech-Oak Forest

Mercedes Valerio et al.

Summary: The understory of temperate forests contains most of the plant species diversity in the ecosystem, which is maintained by canopy gap formation promoting spatiotemporal heterogeneity. Gap dynamics influence the species composition and richness of understory vegetation through changes in light availability and leaf litter cover, impacting the stability of these communities over a decade.

FORESTS (2021)

Article Environmental Sciences

A Forest Monitoring System for Tanzania

Elikana John et al.

Summary: Tropical forests provide essential ecosystem services but are under pressure. Tanzania is experiencing significant forest cover changes, with limited monitoring due to lack of knowledge and tools. A comprehensive forest monitoring system using Earth Observation data can help combat biodiversity loss.

REMOTE SENSING (2021)

Article Environmental Studies

Estimating Forest Canopy Cover by Multiscale Remote Sensing in Northeast Jiangxi, China

Xiaolan Huang et al.

Summary: This research focused on estimating tree canopy cover in south China using multiscale remote sensing. The study established a relationship between tree canopy cover and woody NDVI, and developed a model for estimating tree canopy cover. The developed model showed high predictability and accuracy for large scale estimation of tree canopy cover using high-resolution data.
Article Environmental Sciences

Comparing Support Vector Machines and Maximum Likelihood Classifiers for Mapping of Urbanization

Bhagawat Rimal et al.

JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING (2020)

Article Environmental Sciences

Incorporating LiDAR metrics into a structure-based habitat model for a canopy-dwelling species

Joan C. Hagar et al.

REMOTE SENSING OF ENVIRONMENT (2020)

Review Environmental Sciences

A review of vegetation phenological metrics extraction using time-series, multispectral satellite data

Linglin Zeng et al.

REMOTE SENSING OF ENVIRONMENT (2020)

Article Multidisciplinary Sciences

Near Real-Time Wildfire Progression Monitoring with Sentinel-1 SAR Time Series and Deep Learning

Yifang Ban et al.

SCIENTIFIC REPORTS (2020)

Article Geography, Physical

Evaluation of Sentinel-1 & 2 time series for predicting wheat and rapeseed phenological stages

Audrey Mercier et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2020)

Article Environmental Sciences

Rapid generation of global forest cover map using Landsat based on the forest ecological zones

Xiaomei Zhang et al.

JOURNAL OF APPLIED REMOTE SENSING (2020)

Review Geography, Physical

Google Earth Engine for geo-big data applications: A meta-analysis and systematic review

Haifa Tamiminia et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2020)

Article Environmental Sciences

Detection of sub-canopy forest structure using airborne LiDAR

Lukas R. Jarron et al.

REMOTE SENSING OF ENVIRONMENT (2020)

Review Environmental Sciences

Sentinel-2 Data for Land Cover/Use Mapping: A Review

Darius Phiri et al.

REMOTE SENSING (2020)

Article Environmental Sciences

Toward Operational Mapping of Woody Canopy Cover in Tropical Savannas Using Google Earth Engine

Julius Y. Anchang et al.

FRONTIERS IN ENVIRONMENTAL SCIENCE (2020)

Article Ecology

The role of forest canopy cover in habitat selection: insights from the Iberian lynx

A. Gaston et al.

EUROPEAN JOURNAL OF WILDLIFE RESEARCH (2019)

Article Forestry

Using LiDAR to develop high-resolution reference models of forest structure and spatial pattern

Haley L. Wiggins et al.

FOREST ECOLOGY AND MANAGEMENT (2019)

Article Environmental Sciences

Mapping pan-European land cover using Landsat spectral-temporal metrics and the European LUCAS survey

Dirk Pflugmacher et al.

REMOTE SENSING OF ENVIRONMENT (2019)

Editorial Material Environmental Sciences

Google Earth Engine Applications

Onisimo Mutanga et al.

REMOTE SENSING (2019)

Article Environmental Sciences

A Remote Sensing Based Method to Detect Soil Erosion in Forests

Hanqiu Xu et al.

REMOTE SENSING (2019)

Article Environmental Sciences

Estimating aboveground biomass and forest canopy cover with simulated ICESat-2 data

Lana L. Narine et al.

REMOTE SENSING OF ENVIRONMENT (2019)

Article Engineering, Electrical & Electronic

High-Performance Time-Series Quantitative Retrieval From Satellite Images on a GPU Cluster

Jia Liu et al.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2019)

Article Environmental Sciences

Characterizing global forest canopy cover distribution using spaceborne lidar

Hao Tang et al.

REMOTE SENSING OF ENVIRONMENT (2019)

Review Forestry

On promoting the use of lidar systems in forest ecosystem research

Martin Beland et al.

FOREST ECOLOGY AND MANAGEMENT (2019)

Article Remote Sensing

Estimation of canopy cover in dense mixed-species forests using airborne lidar data

Tauri Arumae et al.

EUROPEAN JOURNAL OF REMOTE SENSING (2018)

Article Plant Sciences

Air pollution removal by urban forests in Canada and its effect on air quality and human health

David J. Nowak et al.

URBAN FORESTRY & URBAN GREENING (2018)

Article Agriculture, Multidisciplinary

Integration of high resolution remotely sensed data and machine learning techniques for spatial prediction of soil properties and corn yield

Sami Khanal et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)

Article Forestry

The impact of road disturbance on vegetation and soil properties in a beech stand, Hyrcanian forest

Azade Deljouei et al.

EUROPEAN JOURNAL OF FOREST RESEARCH (2018)

Article Computer Science, Artificial Intelligence

SVM or deep learning? A comparative study on remote sensing image classification

Peng Liu et al.

SOFT COMPUTING (2017)

Article Environmental Sciences

Landsat-based classification in the cloud: An opportunity for a paradigm shift in land cover monitoring

G. Azzari et al.

REMOTE SENSING OF ENVIRONMENT (2017)

Review Remote Sensing

Remote Sensing Technologies for Enhancing Forest Inventories: A Review

Joanne C. White et al.

CANADIAN JOURNAL OF REMOTE SENSING (2016)

Review Remote Sensing

Remote Sensing Technologies for Enhancing Forest Inventories: A Review

Joanne C. White et al.

CANADIAN JOURNAL OF REMOTE SENSING (2016)

Review Geography, Physical

Support vector machines in remote sensing: A review

Giorgos Mountrakis et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2011)

Review Computer Science, Artificial Intelligence

Classification and regression trees

Wei-Yin Loh

WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY (2011)

Article Geosciences, Multidisciplinary

Analysis and characterization of the vertical accuracy of digital elevation models from the Shuttle Radar Topography Mission

G Falorni et al.

JOURNAL OF GEOPHYSICAL RESEARCH-EARTH SURFACE (2005)

Article Remote Sensing

Support vector machines for classification in remote sensing

M Pal et al.

INTERNATIONAL JOURNAL OF REMOTE SENSING (2005)

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)