DYNAMICAL LAND/FOREST FIRE HAZARD MAPPING OF KALIMANTAN BASED ON SPATIAL AND SATELLITE DATA (PEMETAAN KEBAKARAN LAHAN/HUTAN DINAMIS PULAU KALIMANTAN BERDASARKAN DATA SPASIAL DAN SATELIT)

Early warning system is an important component in land/forest fire management. Since Kalimantan is one of prone areas to fires in Indonesia, land/forest fire hazard mapping for the area is essential to provide early warning information. Methods on static fire hazard mapping have been established using geographic information system. Land/forest fire hazard mapping could be established based on spatial biophysical parameters such as rainfall, vegetation condition, land cover, and land type. Since most parameters can be derived from satellite data and some of them are predictable, a dynamical land/forest fire hazard maps can be generated. The objective of this research was to construct a model of forest fire hazard mapping for Kalimantan. Spatial data used consisted of spatial rainfall maps, Normalized Difference Vegetation Index (NDVI) maps derived from NOAA-AVHRR data, land cover maps from Landsat TM data, and land type map. The results show that contributions of rainfall and NDVI to fire hazards should be higher than land cover and land type. The weights of NDVI, rainfall, land cover, and land type are 0.35, 0.30, 0.20, and 0.15 respectively. For the case study of 1997 – 2002 periods, it has been shown that most hotspots are located in areas with forest fire hazard of high level

Dynamical Land/forest Fire Hazard Mapping Of Kalimantan Based On Spatial And Satellite Data (Pemetaan Kebakaran Lahan/hutan Dinamis Pulau Kalimantan Berdasarkan Data Spasial dan Satelit)

Early warning system is an important component in land/forest fire management. Since Kalimantan is one of prone areas to fires in Indonesia, land/forest fire hazard mapping for the area is essential to provide early warning information. Methods on static fire hazard mapping have been established using geographic information system. Land/forest fire hazard mapping could be established based on spatial biophysical parameters such as rainfall, vegetation condition, land cover, and land type. Since most parameters can be derived from satellite data and some of them are predictable, a dynamical land/forest fire hazard maps can be generated. The objective of this research was to construct a model of forest fire hazard mapping for Kalimantan. Spatial data used consisted of spatial rainfall maps, Normalized Difference Vegetation Index (NDVI) maps derived from NOAA-AVHRR data, land cover maps from Landsat TM data, and land type map. The results show that contributions of rainfall and NDVI to fire hazards should be higher than land cover and land type. The weights of NDVI, rainfall, land cover, and land type are 0.35, 0.30, 0.20, and 0.15 respectively. For the case study of 1997 – 2002 periods, it has been shown that most hotspots are located in areas with forest fire hazard of high level

People exposure and land use damage estimation caused by tsunami using numerical modelling and GIS approaches (Case study: South Coast of Java - Indonesia)

For tsunami risk analysis information about thenumber of exposed people and about the land-use inthe endangered areas are important inputparameters. Data on people distribution could helpto manage the evacuation planning and mitigate thepeople loss by tsunami. Land-use and potentialdamages are relevant for rehabilitation managementThe aim of the paper is to presentmethodologies and tools to generate the abovementioned missing information before a disasterhappens. Based on this, governmental authoritiescan prepare and calculate how many people areliving in the affected area, how many people couldbe evacuated, and how to perform adequate landuse planning to mitigate the disaster impact. For thedisaster response phase, the local government willbe supported to plan and manage the evacuationprocess more efficiently. For the recovery phase,government will be provided by estimates on theamount and type of potential damages.This research analyzes the estimation of peopleat risk and potential land-use damage estimation bytsunamis in the South Coast of Java, Indonesia.Combinations of numerical modelling andGeographic Information System (GIS) approacheshave been applied in this research. There are threescenarios for tsunami simulations generated byearthquake magnitude Mw 8.5 with differentlocations of the epicentres.TUNAMI-N1 model has been applied todetermine the tsunami wave height in the coastalarea. Validation of tsunami modelling has beenperformed using Aceh Tsunami 2004 data.Inundation modelling was applied to the studyarea and the results were combined with the peopledistribution map and land-use data to estimatepeople at risk and land-use damage by tsunami.People distribution maps during day time andnight time were derived.The results of this research will be integrated inan information system, which in future can beapplied on the level of the local government tobetter mitigate the impact of tsunami disaster andprovide tools for an improved tsunami riskassessment for decision makers at the local level

Complex hazard cascade culminating in the Anak Krakatau sector collapse

Flank instability and sector collapses, which pose major threats, are common on volcanic islands. On 22 Dec 2018, a sector collapse event occurred at Anak Krakatau volcano in the Sunda Strait, triggering a deadly tsunami. Here we use multiparametric ground-based and space-borne data to show that prior to its collapse, the volcano exhibited an elevated state of activity, including precursory thermal anomalies, an increase in the island's surface area, and a gradual seaward motion of its southwestern flank on a dipping decollement. Two minutes after a small earthquake, seismic signals characterize the collapse of the volcano's flank at 13:55 UTC. This sector collapse decapitated the cone-shaped edifice and triggered a tsunami that caused 430 fatalities. We discuss the nature of the precursor processes underpinning the collapse that culminated in a complex hazard cascade with important implications for the early detection of potential flank instability at other volcanoes

Analysis of the dynamics of land use change and its prediction based on the integration of remotely sensed data and CA-Markov model, in the upstream Citarum Watershed, West Java, Indonesia

In this research, the integration of remotely sensed data and Cellular Automata-Markov model (CA-Markov) have been used to analyze the dynamics of land use change and its prediction for the next year. Training phase for the CA-Markov model has been created based on the input pair of land use, which is the result of land use mapping using Maximum Likelihood (ML) algorithm. Three-map comparison has been used to evaluate process accuracy assessment of the training phase for the CA-Markov model. Furthermore, the simulation phase for the CA-Markov model can be used to predict land use map for the next year. The analyze of the dynamics of land use change and its prediction during the period 1990 to 2050 can be obtained that the land serves as a water absorbent surfaces such as primary forest, secondary forest and the mixed garden area continued to decline. Meanwhile, on build land area that can lead to reduced surface water absorbing tends to increase from year to year. The results of this research can be used as input for the next research, which aims to determine the impact of land use changes in hydrological conditions against flooding in the research area