Remote sensing and GIS tools to support vegetation fire management in developing countries

Flasse, S.; Ceccato, Pietro; Downey, Ian; Raimadoya, M.; Navarro, Pedro

doi:10.1109/igarss.1997.608950

Cited by 7 publications

(3 citation statements)

References 5 publications

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“…At this time winds appear to be transporting the smoke towards mainland Malaysia and Singapore, which explains the poor breathing conditions reported in these non-burning regions. For several years now a network of local receiving stations, supported by development projects ( Flasse et al 1997), has enabled full resolution AVHRR HRPT data to be received directly in departments of the Indonesian Ministry of Forestry in Palembang (Sumatra), Jakarta ( Java) and Palangka Raya ( Kalimantan). Figure 2 displays a part of a full spatial resolution HRPT image captured in Palembang during the summer 1997 burning season.…”

Section: Satellite Observations Of the Activitymentioning

confidence: 99%

Cover - Indonesian fires observed using AVHRR

Wooster¹,

Ceccato²,

Flasse³

1998

International Journal of Remote Sensing

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Section: Satellite Observations Of the Activitymentioning

confidence: 99%

Cover - Indonesian fires observed using AVHRR

Wooster¹,

Ceccato²,

Flasse³

1998

International Journal of Remote Sensing

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“…They may also plan the allocation of suppression forces to improve the probability that initial attack will control fires occurring in areas ofhigh concern [9]. By using GIS, managers can establish priorities across the area for prevention activities to reduce the risk of wildfire ignition and spread.…”

Section: Third Stage: Decision-makingmentioning

confidence: 99%

Multispectral image analysis of forest (grassland) fire based on agent

Guan

2001

SPIE Proceedings

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Now the developing research of "Agent" can help operators to do the routine assignments, by which we can economize the precious resources and improve the real-time image analysis of the computers. This paper firstly makes a brief introduction of the Agent conception. Then we make some discussions about the multispectral images of a certain area, which is based on the concept of "Agent". The main objects of this paper are inspections of forest (grassland) fire. The purpose of this paper is to propose three stages with which Agent could monitor the wildly areas and make decision automatically, without operators' intervention. First stage, if the value of pixels are more than a given threshold, Agent will give the operators an alarm and notify the operators that there are something happened; Second stage, analyze data and self-learning; Third stage, according to the database and knowledge database, Agents make decisions. As the decisions will be influenced by many factors, so some models, such as heat sources model, weather model, fire model, vegetation model are needed.

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“…Unfortunately, however, the POES data holding capacity limits storage of the full spatial resolution AVHRR local area coverage (LAC) data to only 10% of each Earth orbit, making AVHRR LAC observations of any particular Earth location generally patchy in both space and time. Since all LAC data are transmitted from the POES satellite as a real‐time direct broadcast, one solution to this problem is to rely on a locally installed AVHRR receiving station to obtain data from each relevant satellite overpass [ Flasse et al , 1997; Legg and Laumonier , 1999]. Such stations have been shown to be very effective, but they do not provide data prior to the receiving station installation date and so cannot assist in providing long‐term historical data coverage.…”

Section: Introductionmentioning

confidence: 99%

Study of the 1997 Borneo fires: Quantitative analysis using global area coverage (GAC) satellite data

Wooster

Strub

2002

Global Biogeochemical Cycles

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In 1997 a drought commenced in Southeast Asia, this being directly related to the then ongoing El Niño‐Southern Oscillation (ENSO) event. Interaction between land clearance activities and this drought led to massive, uncontrolled vegetation fires that burned large areas of forest and agricultural land, most severely on the Indonesian island of Borneo. A similar situation in 1982–1983 led to the largest uncontrolled forest fire ever documented, damaging around 50,000 km2 of Borneo's forest. This paper investigates the extent to which nighttime advanced very high resolution radiometer (AVHRR) global area coverage (GAC) data can be used to detail the spatial and temporal evolution of these large‐scale Indonesian fire events, and particularly the 1997 activity. GAC data are a spatial subsample of the full resolution local area coverage (LAC) AVHRR data, but unlike LAC, they have been archived globally on a daily basis for almost 20 years. Despite the extreme subsampling involved in GAC data production, simulation modeling and analysis of real data indicates that surprisingly reliable fire statistics can be obtained for the 1997 Borneo fire event from GAC imagery. For three dates in October 1997 where coincident LAC and GAC data are available, once numerical adjustment for the GAC subsampling procedure is included, fire counts extracted from LAC and GAC data consistently agree to within 0.15–13%. Time series analysis of the 1997 GAC data indicates that fires began in July in south Kalimantan, principally at the interface between cleared, cultivated land and lowland rain forest. Fire activity moved generally southward and peaked in September 1997. GAC data show the equivalent of 9733 LAC pixels as containing one or more active fires on 2 September. Fire activity declined significantly in November owing to the onset of the monsoon rains, with all fires ceasing by December 1997. Analysis of the cumulative fire map distinguishes peat swamp forest as the most severely affected ecosystem on Borneo, with >20% of this land cover category being identified as directly impacted by active fires. If the performance of GAC data can be shown to extend to other El Niño years and also to less intense periods of burning, then the GAC archive offers a tool for analyzing long‐term changes in the spatiotemporal pattern of fire activity in the region. Any trend can then be investigated for its relation to variations in agriculture, El Niño‐related climate, and other phenomena relevant to regional change in Southeast Asia.

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Remote sensing and GIS tools to support vegetation fire management in developing countries

Cited by 7 publications

References 5 publications

Cover - Indonesian fires observed using AVHRR

Cover - Indonesian fires observed using AVHRR

Multispectral image analysis of forest (grassland) fire based on agent

Study of the 1997 Borneo fires: Quantitative analysis using global area coverage (GAC) satellite data

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