Αποτελέσματα Αναζήτησης
23 Φεβ 2023 · Mapping the distribution of coniferous forests is of great importance to the sustainable management of forests and government decision-making. The development of remote sensing, cloud computing and deep learning has provided the support of data, computing power and algorithms for obtaining large-scale forest parameters.
2 Φεβ 2024 · To improve the accuracy and efficiency of the forest inventory, a methodological framework is needed to identify coniferous forests in the semi-arid area of northwestern Liaoning, which can provide a baseline for forest management policy development and forest ecosystem conservation.
13 Ιαν 2021 · A forest mapping system using UAVs and digital images would be a particularly cost-effective and useful tool for forest management applications.
23 Φεβ 2023 · This study indicates that the proposed approach combining GEE and U2-Net can extract coniferous forests quickly and accurately, which helps obtain dynamic information and assists scientists...
11 Νοε 2020 · This study aimed at mapping and classifying coniferous and broad-leaved forest using Sentinel-2 imagery integrated in GEE, using machine learning algorithms such as SVM. This study aimed at high-accuracy classification using minimal knowledge of the study area and thus minimal sample collection.
1 Νοε 2023 · Specifically, we aimed to (1) examine the suitability of bi-temporal ALS data and other remotely sensed data for SIS prediction, (2) compare the performance of parametric and non-parametric models for SIS prediction, and (3) produce national-level maps of SIS and associated prediction errors.
11 Νοε 2020 · The results in this study showed that with the use of Google Earth Engine, Sentinel-2 data alone can be effectively used to obtain rapid and accurate mapping of main forest types...
