Abstract
Global climate changes as well as abnormal climate phenomena have affected the agricultural environment on a great scale. Thus, there is a strong need for countermeasures by making full use of agriculture related information. As agricultural lands in South Korea are mostly operated by private farmers on a small parcel level, it is difficult to gather information for an overview on changing crop condition and to construct database necessary for disease management, production estimation and compensation measures on a regional or governmental level. The objective of this study is to evaluate the multispectral reflectance characteristics of RapidEye image data to classify agricultural land cover as well as crop condition in South Korea. As the RapidEye sensor offers the spectral information in red edge range as a first multispectral satellite system, we focus on the usefulness of red edge reflectance for identifying crop species and for interpreting crop growth or stress condition.
| Original language | English |
|---|---|
| Title of host publication | Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII |
| DOIs | |
| State | Published - 2011 |
| Event | Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII - Prague, Czech Republic Duration: 2011.09.19 → 2011.09.21 |
Publication series
| Name | Proceedings of SPIE - The International Society for Optical Engineering |
|---|---|
| Volume | 8174 |
| ISSN (Print) | 0277-786X |
Conference
| Conference | Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII |
|---|---|
| Country/Territory | Czech Republic |
| City | Prague |
| Period | 11.09.19 → 11.09.21 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
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SDG 13 Climate Action
Keywords
- Agriculture
- Crop condition
- Object-based classification
- RapidEye
- Red edge
- Spectral vegetation index
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