נגישות
menu      
חיפוש מתקדם
תחביר
חפש...
הספר "אוצר וולקני"
אודות
תנאי שימוש
ניהול
קהילה:
אסיף מאגר המחקר החקלאי
פותח על ידי קלירמאש פתרונות בע"מ -
Inference of the activity timeline of cattle foraging on a mediterranean woodland using GPS and pedometry
Year:
2011
Source of publication :
sensors (source)
Authors :
אונגר, יוג'ין דוד
;
.
ברוש, אריה
;
.
הנקין, זלמן
;
.
Volume :
11
Co-Authors:
Ungar, E.D., Department of Agronomy and Natural Resources, Institute of Plant Sciences, Agricultural Research Organization-the Volcani Center, P.O. Box 6, Bet Dagan 50250, Israel
Schoenbaum, I., The Robert H. Smith Institute for Plant Sciences and Genetics in Agriculture, Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot 76100, Israel
Henkin, Z., Beef Cattle Section, Newe Yaar Regional Research Center, Agricultural Research Organization, P.O. Box 1021, Ramat Yishay 30095, Israel
Dolev, A., Migal-Galilee Technology Center, P.O. Box 831, Kiryat Shmona 11016, Israel
Yehuda, Y., Migal-Galilee Technology Center, P.O. Box 831, Kiryat Shmona 11016, Israel
Brosh, A., Beef Cattle Section, Newe Yaar Regional Research Center, Agricultural Research Organization, P.O. Box 1021, Ramat Yishay 30095, Israel
Facilitators :
From page:
362
To page:
383
(
Total pages:
22
)
Abstract:
The advent of the Global Positioning System (GPS) has transformed our ability to track livestock on rangelands. However, GPS data use would be greatly enhanced if we could also infer the activity timeline of an animal. We tested how well animal activity could be inferred from data provided by Lotek GPS collars, alone or in conjunction with IceRobotics IceTag pedometers. The collars provide motion and head position data, as well as location. The pedometers count steps, measure activity levels, and differentiate between standing and lying positions. We gathered synchronized data at 5-min resolution, from GPS collars, pedometers, and human observers, for free-grazing cattle (n = 9) at the Hatal Research Station in northern Israel. Equations for inferring activity during 5-min intervals (n = 1,475), classified as Graze, Rest (or Lie and Stand separately), and Travel were derived by discriminant and partition (classification tree) analysis of data from each device separately and from both together. When activity was classified as Graze, Rest and Travel, the lowest overall misclassification rate (10%) was obtained when data from both devices together were subjected to partition analysis; separate misclassification rates were 8, 12, and 3% for Graze, Rest and Travel, respectively. When Rest was subdivided into Lie and Stand, the lowest overall misclassification rate (10%) was again obtained when data from both devices together were subjected to partition analysis; misclassification rates were 6, 1, 26, and 17% for Graze, Lie, Stand, and Travel, respectively. The primary problem was confusion between Rest (or Stand) and Graze. Overall, the combination of Lotek GPS collars with IceRobotics IceTag pedometers was found superior to either device alone in inferring animal activity. © 2011 by the authors.
Note:
Related Files :
Animal
Animals
cattle
geographic information systems
Grazing behavior
Mediterranean Region
Motion sensors
pedometer
עוד תגיות
תוכן קשור
More details
DOI :
10.3390/s110100362
Article number:
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
24589
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:08
Scientific Publication
Inference of the activity timeline of cattle foraging on a mediterranean woodland using GPS and pedometry
11
Ungar, E.D., Department of Agronomy and Natural Resources, Institute of Plant Sciences, Agricultural Research Organization-the Volcani Center, P.O. Box 6, Bet Dagan 50250, Israel
Schoenbaum, I., The Robert H. Smith Institute for Plant Sciences and Genetics in Agriculture, Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot 76100, Israel
Henkin, Z., Beef Cattle Section, Newe Yaar Regional Research Center, Agricultural Research Organization, P.O. Box 1021, Ramat Yishay 30095, Israel
Dolev, A., Migal-Galilee Technology Center, P.O. Box 831, Kiryat Shmona 11016, Israel
Yehuda, Y., Migal-Galilee Technology Center, P.O. Box 831, Kiryat Shmona 11016, Israel
Brosh, A., Beef Cattle Section, Newe Yaar Regional Research Center, Agricultural Research Organization, P.O. Box 1021, Ramat Yishay 30095, Israel
Inference of the activity timeline of cattle foraging on a mediterranean woodland using GPS and pedometry
The advent of the Global Positioning System (GPS) has transformed our ability to track livestock on rangelands. However, GPS data use would be greatly enhanced if we could also infer the activity timeline of an animal. We tested how well animal activity could be inferred from data provided by Lotek GPS collars, alone or in conjunction with IceRobotics IceTag pedometers. The collars provide motion and head position data, as well as location. The pedometers count steps, measure activity levels, and differentiate between standing and lying positions. We gathered synchronized data at 5-min resolution, from GPS collars, pedometers, and human observers, for free-grazing cattle (n = 9) at the Hatal Research Station in northern Israel. Equations for inferring activity during 5-min intervals (n = 1,475), classified as Graze, Rest (or Lie and Stand separately), and Travel were derived by discriminant and partition (classification tree) analysis of data from each device separately and from both together. When activity was classified as Graze, Rest and Travel, the lowest overall misclassification rate (10%) was obtained when data from both devices together were subjected to partition analysis; separate misclassification rates were 8, 12, and 3% for Graze, Rest and Travel, respectively. When Rest was subdivided into Lie and Stand, the lowest overall misclassification rate (10%) was again obtained when data from both devices together were subjected to partition analysis; misclassification rates were 6, 1, 26, and 17% for Graze, Lie, Stand, and Travel, respectively. The primary problem was confusion between Rest (or Stand) and Graze. Overall, the combination of Lotek GPS collars with IceRobotics IceTag pedometers was found superior to either device alone in inferring animal activity. © 2011 by the authors.
Scientific Publication
You may also be interested in