Sustainable Agriculture Systems and Technologies

15Investigation of the Relationship Between NDVI Index, Soil Moisture, and Precipitation Data Using Satellite Images

Shilan Felegari¹, Alireza Sharifi², Kamran Moravej¹, Ahmad Golchin¹, and Aqil Tariq³

¹ Department of Soil Science, Faculty of Agriculture, University of Zanjan, Zanjan, Iran

² Department of Surveying Engineering, Faculty of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran

³ State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China

CONTENTS

1. 15.1 Introduction
2. 15.2 Methodology
   1. 15.2.1 Study Area
   2. 15.2.2 Precipitation, Soil Moisture, and NDVI Data
   3. 15.2.3 Introducing the Google Earth Engine System
   4. 15.2.4 Dataset
      1. 15.2.4.1 Landsat‐8 Sensor
      2. 15.2.4.2 SMAP Sensor
      3. 15.2.4.3 TRMM Sensor
3. 15.3 Results and Discussion
4. 15.4 Conclusion
5. References

15.1 Introduction

Some phenomena and effects of the land surface, such as vegetation, have changed over time due to natural or human factors that affect the condition and function of the ecosystem, so the need for detection, forecasting. And monitoring such changes in an ecosystem is of great importance (Mohajane et al. 2017). Remote sensing can estimate various parameters of earth sciences at the level of extensive coverage and an acceptable cost. One of these variables is soil moisture, which many remote sensing experts consider the combination of reflective and thermal data to be useful for obtaining information on vegetation ...