Munzer Jahjah

Remote Sensing and GIS Techniques for Natural Disaster Monitoring

On 26 Dec 2004, a magnitude 9.0 earthquake occurred off the west coast of northern Sumatra, Indonesia. Over 300,000 people lost their lives in this disaster. Areas near to the epicentre in Indonesia, especially Aceh, were devastated by the earthquake and tsunamis.

Spatial change analysis using temporal remote sensing and ancillary data for desertification change detection

Desertification is reported to be intensifying and spreading in Kenya dry lands, threatening millions of inhabitants and severely reducing productivity of the land. Concern over desertification acceleration status in the country has been raised and measures to address the problem called upon. Among these measures is assessment of desertification using available data and technological tools. Vegetation cover was used as a land degradation indicator to determine land degradation and rate of change using spectral change detection technique based on pixel-wise operation. In combination with ancillary data, vegetation degradation occurrence and areas at risk of desertification were assessed. The study area is located in Northwestern Kenya, one of the dry land areas. Multi-spectral and multi-temporal analysis was applied to NOAA/AVHRR 1km and Landsat TM/ETM 30 meter resolution for periods covering wet and dry season of 1986 to 2001. Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) were used to detect change. The results show desertification is apparent and increased vegetation degradation. Arid areas were found to be increasingly degraded and at high risk of further degradation at a rate of 1.8% per year.

A space-time analysis technique for monitoring terrain displacements from SAR differential interferometric measurements

Synthetic aperture radar (SAR) differential interferometry is a powerful technique that allows to measure very small movements of the terrain that occurred between two data acquisitions. In previous works we demonstrated how to overcome the main limitations of the technique (i.e. decorrelation noise and atmospheric artifacts) by means of a method for unwrapping sparse phase data and by performing a temporal analysis of successive acquisitions. In this work we explore the possibility of considering together the space and time properties of the studied signal. The two steps mentioned above (i.e., sparse phase unwrapping and temporal analysis) act in the space and in the time domains separately. A significant advance can be obtained by considering the data as samples of a function in a three-dimensional (3D) space-time, and by exploiting this structure in the processing. The 3D structure of the data makes the processing more complex but can help both phase unwrapping and atmospheric (and other) artifact filtering.

Crop species classification: A phenology based approach

We investigated the use of phenological information extracted from satellite imagery and supported by agro-ecological zoning (AEZ) in accurate crop classification and monitoring. Vegetation indices extracted from Landsat 8 imagery are capable to track the vegetation development through the year and from them the phenological profile can be extrapolated and implemented into a multi-temporal automatic classification process to detect agricultural vegetated areas and to discriminate among different crop species. Our case study is the Nakuru district located within the Great Rift Valley of Kenya.

SIGRI project: Results of the products validation process

The SIGRI (Sistema Integrato per la Gestione del Rischio Incendi) pilot project, funded by ASI (the Italian Space Agency), aims at developing an integrated system for the management of the wild fire events. The system provides satellite based products capable of assisting all the phases of the fire contrasting activities: prevision, detection, and damage assessment/recovering. The SIGRI project aims at implementing consolidated methodologies and/or developing innovative tools and methods for the analysis of remote sensing data and the extraction of information useful to the application. This paper concerns the final phase of the SIGRI project: test and validation of algorithms developed. The validation of the generated products is a very important phase through which the products potentiality is assessed and the algorithms can be calibrated. In this paper we will discuss the results of a preliminary validation process.

The development of a fire vulnerability index for the mediterranean region

The SIGRI (Sistema Integrato per la Gestione del Rischio Incendi) pilot project, funded by ASI (the Italian Space Agency), aims at developing an Integrated System for the Management of the Wild Fire Events. The system should provide satellite based products capable to help fire contrasting activities during all the phases: prevision, detection, and damage assessment/recovering. In particular, the paper concerns the development of a Fire Risk Index to be produced daily with the objective of showing the total level of risk for the area of interest and the zones of major concern within such area. In the European Community the member countries interested by forest fires are at least six: Portugal, Spain, France, Germany, Italy, and Greece. The higher number of wild fires occurs in the western part of Spain and Portugal, in southern Italy and in the Mediterranean islands The idea to develop maps able to show the fire risk is based on the observation that there is a tight relationship between the fire and the characteristics of the fuel (vegetation type, density, humidity content), of the topography (slope, altitude, solar aspect angle) and the meteorological conditions (rainfall, wind direction and speed, air humidity, surface and air temperature). These parameters directly impact the proneness of a given area to the fire ignition and propagation. Since these quantities can be measured, notwithstanding the cause of the fire ignition, mainly due, in Italy, to human actions (more than 90% of the ignitions is intentional or accidental), could be unpredictable the behaviour of the fire can be considered strictly dependent from those and then it can be foreseen when such parameters are known.

GIS and RS integration: application of geostatistical techniques and environmental changes in the coastal zone in Kenya

Understanding the dynamics of land cover change has increasingly been recognized as one of the key research imperatives in global environmental change research. Scientists have developed and applied various methods in order to find and propose solutions for many environmental world problems. From 1986-1995 changes in Kenya coastal zone landcover, derived from the post-classification TM images, were significant with arid areas growing from 3% to 10%, woody areas decreased from 4% to 2%, herbaceous areas decreased from 25% to 20%, developed land increased from 2% to 3%. In order to generate the change probability map as a continuous surface using geostatistical method-ArcGIS, we used as an input the Generalized Linear Model (GLM) probability result. The results reveal the efficiency of the Probability-of-Change map (POC), especially if reference data are lacking, in indicating the possibility of having a change and its type in a determined area, taking advantage of the layer transparency of the GIS systems. Thus, the derived information supplies a good tool for the interpretation of the magnitude of the land cover changes and guides the final user directly to the areas of changes to understand and derive the possible interactions of human or natural processes.