✦ LIBER ✦

The quality of animal habitats estimated from track activity and remote sensing data

✍ Scribed by A. S. Zheltukhin; Yu. G. Puzachenko; R. B. Sandlerskii

Book ID: 111474089
Publisher: SP MAIK Nauka/Interperiodica
Year: 2009
Tongue: English
Weight: 690 KB
Volume: 2
Category: Article
ISSN: 1995-4255
DOI: 10.1134/s1995425509030035

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Estimation of phenological stages and ph

Estimation of phenological stages and physiological states of grasslands from remote sensing data

✍ C. M. Girard 📂 Article 📅 1982 🏛 Springer Netherlands 🌐 English ⚖ 495 KB

How well can animals navigate? Estimatin

How well can animals navigate? Estimating the circle of confusion from tracking data

✍ J. E. Mills Flemming; C. A. Field; M. C. James; I. D. Jonsen; R. A. Myers 📂 Article 📅 2006 🏛 John Wiley and Sons 🌐 English ⚖ 160 KB

Robust multiple estimator systems for th

Robust multiple estimator systems for the analysis of biophysical parameters from remotely sensed data

✍ Bruzzone, L.; Melgani, F. 📂 Article 📅 2005 🏛 IEEE 🌐 English ⚖ 699 KB

Estimating and accommodating uncertainty

Estimating and accommodating uncertainty through the soft classification of remote sensing data

✍ Ibrahim, M. A.; Arora, M. K.; Ghosh, S. K. 📂 Article 📅 2005 🏛 Taylor and Francis Group 🌐 English ⚖ 415 KB

Mapping specific habitats from remotely

Mapping specific habitats from remotely sensed imagery: Support vector machine and support vector data description based classification of coastal saltmarsh habitats

✍ Carolina Sanchez-Hernandez; Doreen S. Boyd; Giles M. Foody 📂 Article 📅 2007 🏛 Elsevier Science 🌐 English ⚖ 262 KB

Estimation of the material budget from t

Estimation of the material budget from tracker data to improve the quality of the track fit

✍ Moritz Nadler; Rudolf Frühwirth 📂 Article 📅 2011 🏛 Elsevier Science 🌐 English ⚖ 257 KB

We present two methods to improve the reconstruction of particle tracks by explicit estimates of the amount of material passed by the tracks. The first one is based on a linearized least-squares estimator, the second one on the combination of a forward and a backward Kalman filter. Our simulation st