Adia S.O^a, Rabiu A. B (Phd)^b
aDepartment of Meteorology, Federal University Of Technology, Akure Ondo State
^bSpace Physics Lab, Physics Department Federal University of Technology, Akure Ondo State

Abstract
Remote sensing technology in combination with geographic information system (GIS) can render reliable information on vegetation cover. The analysis of the spatial extent and temporal change of vegetation cover using remotely sensed data is of critical importance to agricultural sciences.

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M. G. S. M. Zaffar Sadiq
Project Associate

M. Ramalingam
Asst. Professor

L Venugopal
Anna University, Chennai

Abstract
Public health management needs information on various aspects like the prevalence of diseases, facilities that are available in order to take decisions on either creating infrastructure facilities or for taking immediate action to handle the situation and so on. These decisions need to be taken based on the observations made and available data.

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This Tutorial is Separated in to Five steps :

1. a. Step 1 Preparing The Dataset
2. b. Step 2 Creating a Multimodal Network Dataset
3. c. Step 3 Finding a Route
4. d. Step 4 Calculating service area and creating a OD Cost Matrix
5. e. Step 5 Creating a Model For route Analysis

Exercise 7: Creating a model for route analysis

In this Exercise you will create a model for fi nding the fastest delivery route connecting 21 stores in Paris.

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This Tutorial is Separated in to Five steps :

1. a. Step 1 Preparing The Dataset
2. b. Step 2 Creating a Multimodal Network Dataset
3. c. Step 3 Finding a Route
4. d. Step 4 Calculating service area and creating a OD Cost Matrix
5. e. Step 5 Creating a Model For route Analysis

Exercise 6: Calculating service area and creating a OD Cost Matrix

In this Exercise you will create a series of polygons representing the distance that can be reached from a facility within a specifi ed amount of time. These polygons are known as service area polygons. You will calculate 3-, 5-, and 10-minute service area polygons for six warehouses in Paris. You will also fi nd out how many stores lie within each of these service areas. You have to identify one warehouse that should be relocated to better service the stores. Additionally, you will create an Origin- Destination Cost Matrix for delivery of goods from the warehouses to all the stores within a 10-minute drive time. Such a matrix is used as an input for logistics, delivery, and routing analyses.

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This Tutorial is Separated in to Five steps :

1. a. Step 1 Preparing The Dataset
2. b. Step 2 Creating a Multimodal Network Dataset
3. c. Step 3 Finding a Route
4. d. Step 4 Calculating service area and creating a OD Cost Matrix
5. e. Step 5 Creating a Model For route Analysis

Exercise 4: Finding the best route using a network dataset

In this Exercise you will fi nd the best route for the given order of stops based on travel time.

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This Tutorial is Separated in to Five steps :

1. a. Step 1 Preparing The Dataset
2. b. Step 2 Creating a Multimodal Network Dataset
3. c. Step 3 Finding a Route
4. d. Step 4 Calculating service area and creating a OD Cost Matrix
5. e. Step 5 Creating a Model For route Analysis

Exercise 3: Creating a multimodal network dataset

In this Exercise you will create a multimodal network dataset from multiple feature classes within a feature dataset in a geodatabase.

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This Tutorial is Separated in to Five steps :

1. a. Step 1 Preparing The Dataset
2. b. Step 2 Creating a Multimodal Network Dataset
3. c. Step 3 Finding a Route
4. d. Step 4 Calculating service area and creating a OD Cost Matrix
5. e. Step 5 Creating a Model For route Analysis

Exercise 1: Creating a shapefile based network dataset

In this Exercise you will create a simple shapefile based network dataset from a single line feature class and a turn feature class.

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J. I. Igbokwe1 , K. U. Orisakwe1, J. O. Akinyede2, B. Dang3 and T. Alaga3

1. Department of Surveying and Geoinformatics
Nnamdi Azikiwe University
Awka, Nigeria.
2. Space Applications Department
National Space Research and Development Agency
Abuja, Nigeria
3. National Centre for Remote Sensing
Jos
Nigeria

Abstract
Landslides occur in different parts of Southeastern Nigeria due to widespread impact of gully erosion resulting from annual rainfall and subsequent flooding. In this area landslide occur mostly as earth movement, rock and debris flows on slopes previously weakened by flood water. Remotely sensed images combined with field observation were used in this study to map potential areas of landslides in south – central parts of Anambra State in Southeastern Nigeria. The study generated landslide zonation map highlighting areas of different degrees of susceptibility and confirmed the possibility of using medium scaled remotely sensed data in landslide susceptibility study. Read more »

Shahab Poursaleh
Head of image processor at SSTEC (Satellite Science & Technology Engineering Co)

Abstract
Concerning the importance of carbonates in mineralization and the necessity of separation of important formations in remote sensing data, we try to separate carbonates into two groups including limestone and dolomite by using PCA on ASTER SWIR bands. As you know this analysis results can be used in compiling geological maps and GIS modeling for finding the favorable potential area.

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G.Venkata Bapalu
ESRI India, 8, Balaji Estate, Kalkaji,
New Delhi – 110019, INDIA

Rajiv Sinha
Department of Civil Engineering, Indian Institute of Technology, Kanpur-208016, India
Email: rsinha@iitk.ac.in

Flood Hazard Mapping is a vital component for appropriate land use planning in flood-prone areas. It creates easily-read, rapidly-accessible charts and maps which facilitates the administrators and planners to identify areas of risk and prioritize their mitigation/ response efforts. This article presents an efficient methodology to accurately delineate the flood-hazard areas in the Kosi River Basin, North Bihar, India in a GIS environment.

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