GIS-Assisted Prediction and Risk Zonation of Wildlife Attacks
in the Chitwan National Park in Nepal

J 2018

GIS-Assisted Prediction and Risk Zonation of Wildlife Attacks in the Chitwan National Park in Nepal

RUDA, Aleš, Jaromír KOLEJKA and Thakur SILWAL

Basic information

Original name

GIS-Assisted Prediction and Risk Zonation of Wildlife Attacks in the Chitwan National Park in Nepal

Name in Czech

Využití GIS k předpovědi rizika napadení člověka zvířetem a k zonaci rizika v NP Chitwan v Nepálu

Authors

RUDA, Aleš, Jaromír KOLEJKA and Thakur SILWAL

Edition

ISPRS International Journal of Geo-Information, Basel, MDPI AG, 2018, 2220-9964

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10508 Physical geography

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 1.840

Organization unit

Faculty of Education

DOI

http://dx.doi.org/10.3390/ijgi7090369

UT WoS

000445767900037

Keywords (in Czech)

zonace rizika; Kernelovská hustota; bezpečnostní analýza; řízení chráněných území

Keywords in English

risk zonation; kernel density; safety analysis; protected area management

Abstract

ORIG CZ

V originále

Population growth forces the human community to expand into the natural habitats of wild animals. Their efforts to use natural sources often collide with wildlife attacks. These animals do not only protect their natural environment, but in the face of losing the potential food sources, they also penetrate in human settlements. The research was situated in the Chitwan National Park (CNP) in Nepal, and the aim of this study was to investigate possible geospatial connections between attacks of all kinds of animals on humans in the CNP and its surroundings between 2003 and 2013. The patterns of attacks were significantly uneven across the months, and 89% of attacks occurred outside the park. In total, 74% attacks occurred in the buffer zone forests and croplands within 1 km from the park. There was a strong positive correlation among the number of victims for all attacking animals with a maximum of one victim per 4 km2, except elephant and wild boar. The density of bear victims was higher where the tiger and rhino victims were lower, e.g., in the Madi valley. The data collected during this period did not show any signs of spatial autocorrelation. The calculated magnitude per unit area using the kernel density, together with purpose-defined land use groups, were used to determine five risk zones of wildlife attacks. In conclusion, it was found that the riskiest areas were locations near the forest that were covered by agricultural land and inhabited by humans. Our research results can support any local spatial decision-making processes for improving the co-existence of natural protection in the park and the safety of human communities living in its vicinity

In Czech

Population growth forces the human community to expand into the natural habitats of wild animals. Their efforts to use natural sources often collide with wildlife attacks. These animals do not only protect their natural environment, but in the face of losing the potential food sources, they also penetrate in human settlements. The research was situated in the Chitwan National Park (CNP) in Nepal, and the aim of this study was to investigate possible geospatial connections between attacks of all kinds of animals on humans in the CNP and its surroundings between 2003 and 2013. The patterns of attacks were significantly uneven across the months, and 89% of attacks occurred outside the park. In total, 74% attacks occurred in the buffer zone forests and croplands within 1 km from the park. There was a strong positive correlation among the number of victims for all attacking animals with a maximum of one victim per 4 km2, except elephant and wild boar. The density of bear victims was higher where the tiger and rhino victims were lower, e.g., in the Madi valley. The data collected during this period did not show any signs of spatial autocorrelation. The calculated magnitude per unit area using the kernel density, together with purpose-defined land use groups, were used to determine five risk zones of wildlife attacks. In conclusion, it was found that the riskiest areas were locations near the forest that were covered by agricultural land and inhabited by humans. Our research results can support any local spatial decision-making processes for improving the co-existence of natural protection in the park and the safety of human communities living in its vicinity

Detailed Information on Publication Record