NDVI and Related Remote Sensing -- Complete Table of Contents

 

           

 

TABLE OF CONTENTS

1 INTRODUCTION

2 SATELLITES and IMAGES

2.1 Satellites and Images: A non-technical overview

2.2 How satellites work

2.2.1 Radiation in the atmosphere
2.2.2 Radiometers

2.3 Geostationary satellites

2.3.1 General features
2.3.2 METEOSAT satellites
2.3.3 GOES satellites
2.3.4 GMS satellites

2.4 Polar orbiting satellites

2.4.1 General features
2.4.2 NOAA satellites

2.5 Other satellites

2.5.1 Introduction
2.5.2 Tropical Rainfall Measuring Mission (TRMM)
2.5.3 LANDSAT
2.5.4 SPOT
2.5.5 ERS

2.6 Types of image

2.6.1 Introduction
2.6.2 Visible
2.6.3 Near Infrared
2.6.4 Thermal Infrared

3 DERIVED PRODUCTS

3.1 Cold Cloud Duration (CCD)

3.1.1 CCD: A non-technical overview
3.1.2 How CCD images are produced.
3.1.3 CCD products from ARTEMIS

3.2 Rainfall estimates

3.2.1 Estimating rainfall: A non-technical overview
3.2.2 Estimated rainfall: TAMSAT technique
3.2.3 Estimated rainfall: CPC technique
3.2.4 Limitations of CCD imagery and rainfall estimates

3.3 Normalised Difference Vegetation Index (NDVI)

3.3.1 NDVI: A non-technical overview
3.3.2 NDVI: How it is produced.
3.3.3 NDVI: ARTEMIS products
3.3.4 NDVI: The limitations
3.3.5 Other vegetation indices

3.4 Sea Surface Temperature (SST).

3.4.1 SST: A non-technical overview.
3.4.2 Calculating SST
3.4.3 Limitations of SST data

4 TOOLS

4.1 Non-technical overview

4.2 IDA

4.2.1 IDA: A non-technical overview
4.2.2 Technical details
4.2.3 Viewing Images with IDA
4.2.4 Visual analysis with IDA
4.2.5 Image manipulation with IDA
4.2.6 Statistics with IDA

4.3 WINDISP

4.3.1 WINDISP:A non-technical overview
4.3.2 The GIEWS workstation
4.3.3 Satellite Enhanced Data Interpolation

4.4 ADDAPIX

4.4.1 A non-technical overview
4.4.2 Clustering Procedure
4.4.3 Example
4.4.4 Limitations

4.5 Vegetation Analysis in Space and Time (VAST)

4.6 MADAM

4.7 AICON

5 APPLICATIONS

5.1 Using satellite data in Zambia

5.1.1 AgroMeteorological Information System (AMIS)
5.1.2 River flow forecasting

5.2 Locust prevention

5.2.1 Introduction
5.2.2 Emergency Centre for Locust Operations (ECLO)

5.3 Using satellite data to identify farming systems

5.3.1 Introduction
5.3.2 Ecozones
5.3.3 Combining ecozones with ground-based data
5.3.4 Predicting farming systems
5.3.5 Tsetse distributions

6 FUTURE DEVELOPMENTS

7 REFERENCES

 

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