Abdolreza Ansari Amoli. Remote Sensing Department Iranian Space Agency

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Transcription:

Risk Assessment and Mapping Using Earth Observation Data In Iran Abdolreza Ansari Amoli Remote Sensing & GIS Expert Remote Sensing Department Iranian Space Agency

Different Types of Disasters in Iran Epidemic Floods Drought Mudflow Earthquake Sand Storm Volcanic Eruption Tornado Hailstorm Landslide Wildfire More than 90 percent of damages among all disasters in Iran

Outline: Part (A) - Iran A)Location B)Climate C)Drought History Part (B) -The Important Activities involved in Major Aspects of Disaster Risk Management Part (C) - Drought Risk Assessment Activities and Projects in Iranian Space Agency A) Drought Monitoring B) Drought Prediction C) Drought Risk Mapping

Part (A) Iran Location:

Iran Climate: Desert Belt of the World

Iran Climate: Annual precipitation rate =240 mm (about one third of world average precipitation)

Drought in Iran: History 1956-1958 The most severe drought periods in Iran during last 60 years 1970-1973 1983-1984 1989-1991 1998-2001 One Severe Drought in every 10 years Total Damages=$7.5 Billion Losing 800,000 head of livestock 80 percent damages in annual cereal crops. 2008-2011

Part (B) The Important Activities involved in Major Aspects of disaster risk management Diagram of Disaster Management Phases

Mitigation: Aim: To minimize or mitigate the consequences of impacts Preparedness: Aim: Activities that reduce the degree of risk to human life and property.

The Examples of Activities in Mitigation Phase Legislation Insurance Strategies Tax incentives and disincentives Land-use Management Risk mapping The development of technological solutions The Examples of Activities in Preparedness Phase Long-term activity: Disaster Prediction Short-term activity: Disaster warnings

Part (C) Projects & Activities in Drought Risk Assessment in Iranian Space Agency A) Drought Monitoring B) Drought Risk Mapping C) Drought Prediction

A)Drought Monitoring Phase: Inter-sensor Relationship Between MODIS and AVHRR Data for Monitoring Drought in Iran Target: Simulating MODIS Data for the period of 1995-2001 Method: Regression Modeling Inputs: Vegetation Indices of NOAA/AVHRR (1.1Km) & Terra/MODIS (250m) Outputs: Simulated NDVI of MODIS for the period of 1995-2001

Source of Data NOAA AVHRR Terra MODIS

Monthly NDVI Map of August in Iran by Terra/MODIS (2001-2011)

Periods of Data & Regression Relationship M O AVHRR DNDVI MODIS NDVI A H R R I S NDVIMODIS=1.0213NDVINOAA+0.0081

B)Drought Prediction Natural Drought Management System by Using Space Technologies Target: Drought Monitoring & Prediction by Using Terra/MODIS Satellite Data. Method: Exploring Relationship between Satellite and Meteorological Indices by Using Artificial Neural Network Models. Inputs: MODIS Vegetation Indices for 20 Years (1995-2015) Meteorological Data Series for 30 Years Iran Climate Map Iran Basin Map Output Standardized Precipitation Index MODIS Acquired by Ground Receiver of Iranian Space Agency Satellite Data Sources MODIS Simulated Data 2001-2015 1995-2000 A Schematic Diagram of the Model

Models Satellite Indices: NDVI,NDVI-Dev, VCI, TCI Neural Network Models : ADALINE,MLP(Multi-layer Perceptron),RBF(Radial Basis Function) Data Classification Based on Climate and Basin NDVI Dev VCI TCI ADALINE MLP RBF Climate Basin 24 Models

Last Conclusions: The best Index (among satellite indices assessed in this research) for drought prediction is TCI. MLP is the best ANN Model for Drought Prediction by Using TCI

Other Satellite Based Drought Index Will be Used in This Research in the Next Steps Enhanced Vegetation Index

Software Designed for Running ANN for Drought Prediction Training Box of Software Designed for Modeling Test Box of Software Designed for Modeling

Drought Prediction Map Extreme Drought Severe Drought Moderate Drought Mild Drought Normal Today Toward Future The prediction time range until now = 3 month

C)Drought Risk Mapping Remote Sensing Applications in Preparing Drought Risk Map of Iran Step (1) Preparing Drought Hazard Map Meteorological Data Layer Map Remote Sensing Data Layer Step (2) Preparing Drought Vulnerability Map Drought Hazard Map Population Density Map of Iran Annual Landuse Map of Iran by Using MODIS Data Drought Vulnerability Map Step (3) Preparing Drought Exposure Map Irrigated Lands Area based on statistics Step (4) Preparing Drought Risk Map Hazard X Vulnerability X Exposure= Risk

Step (1) Preparing Drought Hazard Map The Probability of Disaster Occurrences in a period with a certain Severity

Hazard Assessment by Using Meteorological Data

Hazard Assessment by Using Remote Sensing Data Drought Severity Index by using Terra/MODIS Satellite Data Drought Severity Index= NDVIi-NDVImean

+ = Output Hazard Map by Using Meteorological Data Output Hazard Map by Using Remote Sensing Data Final Hazard Map

Step (2) Preparing Drought Vulnerability Map Degree of resilience to the impact of natural hazards

Vulnerability Indicators & Factors Socio-economic indicators: Population density: Female to male ratio: Poverty level: Agricultural occupation: Physical/infrastructural factors: Land Use Map

Population Density Map of Iran

Annual Landuse Map of Iran by Using MODIS Data

+ = Output Landuse Map by Using Remote Sensing Data Population Density Map Final Vulnerability Map

Step (3) Preparing Drought Exposure Map The interaction between element at the risk and natural hazard

Data Source: Iranian Ministry of Agriculture

X X Iran Drought Hazard Map Iran Drought Vulnerability Map Iran Drought Exposure Map Hazard X Vulnerability X Exposure= Risk Iran Drought Risk Map

Thank you!