Zobacz książki o podobnej tematyce

Więcej informacji o Remote Sensing, Nonlinear Model, Supercomputing

• Dane szczegółowe
• Opis
• Ulubione w innej kategorii

Za ten zakup dostaniesz 61 punkty

Opis

The novelty of this algorithm is to apply multiple sources of remote sensing data combined with data of unmanned weather stations, topography, ground cover,DEM, and astronomy and calendar rules. The results indicated that the model has high accuracy, reliability, and generalization ability. Factors such as cloudiness, ground vegetation, and water vapor show little interference, so the model seems suitable for large area retrieving under natural conditions. The required high-performance computation was achieved by a CPU + GPU isomery and synergy parallel computation system that improved computing speed by more than 1000-fold, with easily extendable computing capability. We found that the current algorithm is superior to seven major split-window algorithms and their best combined algorithms based on prediction errors, root-meansquare errors, and the percentage of data points with 3 C absolute error. Our SVM approach overcomes shortcomings of classical temperature remote sensing technologies, and is the first report of such application.

Szczegóły książki

• Pełny tytuł: Remote Sensing, Nonlinear Model, Supercomputing
• Autor: Jiang Lin Qin
• Język: Angielski
• Oprawa: Miękka
• Liczba stron: 84
• EAN: 9783659978203
• ID: 15555900
• Wydawca: LAP Lambert Academic Publishing
• Waga: 143 g
• Wymiary: 220 × 150 × 5 mm
• Rok wydania: 2016

Ulubione w innej kategorii

---

---

---