Muhammad Ardiansyah

Spatiotemporal trends of forest cover change in Southeast Asia

The current state of tropical forest cover and its change have been identified as key variables in modelling and measuring the consequences of human action on ecosystems. The conversion of tropical forest cover to any other land cover (deforestation) directly contributes to the two main environmental threats of the recent past: 1) the alteration of the global climate by the emission of carbon to the atmosphere and 2) the decline in tropical biodiversity by land use intensification and habitat conversion. The sub-continent of Southeast Asia exhibits one of the highest rates of forest loss and comprises one of the regions with the highest amount and diversity of flora and fauna species, worldwide.

From global to regional scale: Remote sensing-based concepts and methods for mapping land-cover and land-cover change in tropical regions

A great number of studies have been dealing with land-cover mapping of tropical regions using earth remote sensing technology recently. This is partly due to a growing number of operational sensor systems for both scientific and commercial use and also because of an increasing demand for land-cover information relevant to global environmental issues and international policy instruments (e.g. the Kyoto protocol). Within this context, the present article discusses the state of the art of data processing and analysis for the assessment of broad scale land-cover and land-cover change in tropical regions. Current global scale land-cover maps are compared with regional satellite mapping products (Landsat/ETM+) for a test region in the humid tropics of Central Sulawesi, Indonesia.

Forest and Land Fires Hazard Level Modeling: Case study of Kapuas, Central Kalimantan

Forest and land fires occur almost every year in Indonesia and their impacts are detrimental to human life and the environment. The major causes of forest and land fires thus need to be determined and spatial pattern of the fire activity needs to be developed. The assessment of hazard levels can help policy makers to develop strategy and actions for managing fire risks and to develop spatial plans that can decrease the fire risk or evaluate the impacts of land use change on fire risk.

DETEKSI KONDISI KETAHANAN PANGAN BERAS MENGGUNAKAN PEMODELAN SPASIAL KERENTANAN PANGAN

In 2005 and 2009, BKP and WFP has provided food security conditions in Indonesia on Food Insecurity Map which were developed using food availability, food accessibility, food absorption and food vulnerability. There are 100 out of 265 districts in Indonesia or about 37,7%, which fall into the vulnerable to very vulnerable categories, where 11 districts were found in Java. The main objective of this research is to develope a spatial model of the rice production vulnerability (KPB) based on Remote Sensing and GIS technologies for estimating the food insecurity condition. Several criteria used to obtain food vulnerability information are percentage level of green vegetation (PV), rainfall anomaly (ACH), land degradation due to erosion (Deg), and paddy harvest failure due to drought and flood in paddy field (BK). Dynamic spatial information on the greenness level of land cover can be obtained from multitemporal EVI (Enhanced vegetation Index) of MODIS (Moderate Resolution Imaging Spectroradiometer) data. Spatial information of paddy harvest failure caused by drought and flood was estimated by using vegetation index, land surface temperature, rainfall and moisture parameters with advance image processing of multitemporal EVI MODIS data. The GIS technology were used to perform spatial modelling based on weighted overlay index (multicriteria analysis). The method for computing weight of factors in the vulnerability model was AHP (Analytical Hierarchy Process). The spatial model of production vulnerability (KPB) developed in this study is as follows: KPB = 0,102 PV + 0,179 Deg + 0,276 ACH + 0,443 BK. In this study, level of production vulnerability can be categorized into six classes, i.e.: (1) invulnerable; (2) very low vulnerability; (3) low vulnerability; (4) moderately vulnerable; (5) highly vulnerable; and (6) extremely vulnerable. The result of spatial modelling then was used to evaluate progress production vulnerability condition at several sub-districts in Indramayu Regency. According to the investigation results of WFP in 2005, this area fall into moderately vulnerable category. Only few sub-districts that fall into highly and extremely vulnerable during the period of May ~ August 2008, namely: Kandanghaur, Losarang, part of Lohbener, and Arahan.