搜索结果: 1-15 共查到“林学 Classification”相关记录32条 . 查询时间(0.334 秒)
Optimal Input Features for Tree Species Classification in Central Europe Based on Multi-Temporal Sentinel-2 Data
tree species classification Sentinel-2 multi-temporal Wienerwald biosphere reserve
2024/1/23
Detailed knowledge about tree species composition is of great importance for?forest?management. The two identical European Space Agency (ESA) Sentinel-2 (S2) satellites provide data with unprecedented...
Airborne LiDAR Intensity Correction Based on a New Method for Incidence Angle Correction for Improving Land-Cover Classification
airborne LiDAR intensity correction LiDAR intensity
2023/12/6
Light detection and range (LiDAR) intensity is an important feature describing the characteristics of a target. The direct use of original intensity values has limitations for users, because the same ...
Astrape: A System for Mapping Severe Abiotic Forest Disturbances Using High Spatial Resolution Satellite Imagery and Unsupervised Classification
astrapeforest disturbanceSentinel-2planetdoveimage segmentation RSGISLibjenksXGBoost
2023/12/6
Severe forest disturbance events are becoming more common due to climate change and many forest managers rely heavily upon airborne surveys to map damage. However, when the damage is extensive, airbor...
Single Tree Classification Using Multi-Temporal ALS Data and CIR Imagery in Mixed Old-Growth Forest in Poland
tree species classification airborne laser scanning (ALS) colour-infrared (CIR) aerial images multi-temporal data individual tree random forest (RF)
2023/12/5
Tree species classification is important for a variety of environmental applications, including biodiversity monitoring, wildfire risk assessment, ecosystem services assessment, and sustainable forest...
Climate-Based Regionalization and Inclusion of Spectral Indices for Enhancing Transboundary Land-Use/Cover Classification Using Deep Learning and Machine Learning
machine learning ratio-based indices orthogonal indices Koppen–Geiger climate regionalization landscape change remote sensing landcover
2023/12/4
Accurate land use and cover data are essential for effective land-use planning, hydrological modeling, and policy development. Since the Okavango Delta is a transboundary Ramsar site, managing natural...
Classification of Mediterranean Shrub Species from UAV Point Clouds
Unmanned Aerial Vehicles (UAV) Digital Aerial Photogrammetry (DAP) machine learning deep learning point cloud labelling Mediterranean forest
2023/12/4
odelling fire behaviour in forest fires is based on meteorological, topographical, and vegetation data, including species’ type. To accurately parameterise these models, an inventory of the area of an...
Site Quality Classification Models of Cunninghamia Lanceolata Plantations Using Rough Set and Random Forest West of Zhejiang Province, China
Cunninghamia lanceolata plantations site quality classification models site quality evaluation rough set random forest
2023/12/1
The site quality evaluation of plantations has consistently been the focus in matching tree species with sites. This paper studied the site quality of Chinese fir (Cunninghamia lanceolata) plantations...
Enhancing the Accuracy and Temporal Transferability of Irrigated Cropping Field Classification Using Optical Remote Sensing Imagery
irrigated field classification Landsat NDVI time series Gaussian mixture model interannual climate variability regional analysis
2023/12/1
Mapping irrigated areas using remotely sensed imagery has been widely applied to support agricultural water management; however, accuracy is often compromised by the in-field heterogeneity of and inte...
A Hybrid Classification of Imbalanced Hyperspectral Images Using ADASYN and Enhanced Deep Subsampled Multi-Grained Cascaded Forest
hyperspectral image imbalanced data oversampling adaptive synthetic sampling tree-based classifier subsampling deep multi-grained cascade forest
2023/11/29
Hyperspectral image (HSI) analysis generally suffers from issues such as high dimensionality, imbalanced sample sets for different classes, and the choice of classifiers for artificially balanced data...
Classification of Toona Sinensis Young Leaves Using Machine Learning And UAV-Borne Hyperspectral Imagery
Classification Toona Sinensis Young Leaves
2023/6/2
Rapid and accurate distinction between young and old leaves of Toona sinensis in the wild is of great significance to the selection of T. sinensis varieties and the evaluation of relative yield. In th...
Spectrometric Classification of Bamboo Shoot Species by Comparison of Different Machine Learning Methods
Spectrometric Classification Bamboo Shoot Machine Learning
2023/6/5
The nutrition and quality of bamboo shoots from different species have a large variation, and traditional methods used for the classification of different bamboo shoot species are expensive and time-c...
Comparison of partial least squares-discriminant analysis, support vector machines and deep neural networks for spectrometric classification of seed vigour in a broad range of tree species
least squares-discriminant analysis spectrometric classification seed tree species
2023/6/5
Seed vigour significantly influences the seed production and plant regeneration performance. The capability of NIR spectroscopy to identify seed vigour across multiple tree species rapidly and cost-ef...
Tree Species Classification in a Highly Diverse Subtropical Forest Integrating UAV-Based Photogrammetric Point Cloud and Hyperspectral Data
tree species mapping tropical biodiversity imaging spectroscopy photogrammetry support vector machine
2024/2/4
The use of remote sensing data for tree species classification in tropical forests is still a challenging task, due to their high floristic and spectral diversity. In this sense, novel sensors on boar...
MULTI-TEMPORAL CLASSIFICATION AND CHANGE DETECTION USING UAV IMAGES
Change Detection Random Forest Fully Connected CRF UAV images
2018/6/4
In this paper different methodologies for the classification and change detection of UAV image blocks are explored. UAV is not only the cheapest platform for image acquisition but it is also the easie...
APPLYING RANDOM FOREST CLASSIFICATION TO MAP LAND USE/LAND COVER USING LANDSAT 8 OLI
Classification Landsat 8 OLI Land use Land cover Random Forest Decision Tree
2018/4/18
This study used the Random Forest classifier (RF) running in R environment to map Land use/Land cover (LULC) of Dak Lak province in Vietnam based on the Landsat 8 OLI. The values of two RF parameters ...