Knowing fire incidence through fuel phenology: A remotely sensed approach

S. Bajocco; L. Rosati; C. Ricotta

doi:10.1016/j.ecolmodel.2008.12.024

Knowing fire incidence through fuel phenology: A remotely sensed approach

Ecological Modelling ◽

10.1016/j.ecolmodel.2008.12.024 ◽

2010 ◽

Vol 221 (1) ◽

pp. 59-66 ◽

Cited By ~ 26

Author(s):

S. Bajocco ◽

L. Rosati ◽

C. Ricotta

Keyword(s):

Remotely Sensed ◽

Fire Incidence

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Groundwater recharge estimation in karst aquifers of southern Apennines (Italy) by integration of remotely sensed data

Rendiconti online della Società Geologica Italiana ◽

10.3301/rol.2019.18 ◽

2019 ◽

Vol 47 ◽

pp. 97-101

Author(s):

Giovanni Ruggieri ◽

Vincenzo Allocca ◽

Flavio Borfecchia ◽

Pantaleone De Vita

Keyword(s):

Groundwater Recharge ◽

Remotely Sensed ◽

Karst Aquifers ◽

Southern Apennines ◽

Remotely Sensed Data ◽

Recharge Estimation

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Analysis of remotely sensed ocean data by the optimal spectral decomposition (OSD) method

OCEANS 2009 ◽

10.23919/oceans.2009.5422453 ◽

2009 ◽

Author(s):

Peter Chu

Keyword(s):

Spectral Decomposition ◽

Remotely Sensed

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Remotely sensed imagery revealing the effects of hurricanes Gustav and Ike on coastal Louisiana

Data Series ◽

10.3133/ds566 ◽

2010 ◽

Cited By ~ 1

Author(s):

John A. Barras ◽

John C. Brock ◽

Robert A. Morton ◽

Laurinda J. Travers

Keyword(s):

Remotely Sensed ◽

Remotely Sensed Imagery ◽

Coastal Louisiana

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Use of Remotely Sensed Data to extract geographical information of the area around Ballıhisar (Pessinus) in Central Anatolia. Field campaign, August 1992

Anatolia Antiqua ◽

10.3406/anata.1996.1193 ◽

1996 ◽

Vol 4 (1) ◽

pp. 97-109

Author(s):

Morgan De Dapper ◽

Pascal Brackman

Keyword(s):

Remotely Sensed ◽

Geographical Information ◽

Central Anatolia ◽

Remotely Sensed Data ◽

Field Campaign

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Developing the Assessment and Indicators for Local Institutions in Dealing with Forest Fire Dilemma

11th GLOBAL CONFERENCE ON BUSINESS AND SOCIAL SCIENCES - Global Conference on Business and Social Sciences Proceeding ◽

10.35609/gcbssproceeding.2020.11(163) ◽

2020 ◽

Vol 11 (1) ◽

pp. 163-163

Author(s):

Eko Priyo Purnomo ◽

Agustiyara ◽

Rijal Ramdani ◽

Dina Wahyu Trisnawati

Keyword(s):

Forest Management ◽

Forest Fire ◽

Structural Equation ◽

Equation Modeling ◽

Local Institutions ◽

Microsoft Excel ◽

Organization Capacity ◽

The Government ◽

Depth Interviews ◽

Fire Incidence

This study analyzes the main criteria and indicators in strengthening local institutions in charge of forest management towards dealing with forest fire incidence in Riau Province, Indonesia. Data were collected using in-depth interviews, observation, and questionnaires and analyzed with Microsoft Excel spreadsheets and other Structural Equation Modeling (SEM) techniques such as SPSS and Smart PLS. Moreover, only 87 out of the 120 questionnaires administered to related stakeholders were retrieved. Four variables, including Organization, Capacity, Authority, and Governance, were measured using ten indicators for each. The results showed a significant correlation between local institutions and these variables in solving forest management issues. It means there is a need to strengthen the institutions' structural plans to ensure the effective management of natural resources, and this is achievable through the support and help of the government and communities. Keywords: forest fire, local institutions, forest management.

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