Environmental Remote Sensing
Course Code
GD4119
Number of Credits
3
Semester
Course Type
Study Material
| Study Material | Depth |
|---|---|
| Elements of Remote Sensing | Expert |
| Vegetation Remote Sensing: - spectral characteristics, phenology, vegetation indices, applications to vegetation | Expert |
| Water Remote Sensing: - spectral characteristics, Inorganic material mapping, Organic material mapping | Expert |
| Urban Remote Sensing : - Spectral/temporal characteristics/data resolution, Cover class/land use | Expert |
| Remote Sensing Soil/mineral/geomorphology : - Soil spectral characteristics, mineral characteristics and mapping, Geomorphology mapping | Expert |
| Atmospheric Remote Sensing: - Aerosol particle characterization, Aerosol mapping, Cloud mapping | Expert |
| Earth observation satellites (remote sensing data collection / Big Data Remote Sensing): - Various kinds of remote sensing sensors for the environment, open access data | Expert |
| Environmental Remote Sensing for Disaster (PjBL) | |
| Environmental Remote Sensing for Precission Farming (PjBL) |
Graduate Learning Outcomes (GLO) carried by the course
| CPMK Code | Course Learning Outcomes Elements (CLO) |
|---|---|
| CPMK 1 | Able to explain and utilize remote sensing in specific fields of geodesy and geomatics engineering. |
| CPMK 2 | Able to explain the concepts and applications of remote sensing data for the extraction of information related to vegetation. |
| CPMK 3 | Able to explain the concepts and applications of remote sensing data for the extraction of water-related information. |
| CPMK 4 | Able to explain the concepts and applications of remote sensing data for urban information extraction. |
| CPMK 5 | Able to explain the concepts and applications of remote sensing data for information extraction related to soil / cereals / geomorphology. |
| CPMK 6 | Able to explain the concepts and applications of remote sensing data for information extraction related to the atmosphere. |
| CPMK 7 | Able to explain various kinds of remote sensing data and their derivative products that are openly available (open access). |
| CPMK 8 | Able to apply and utilize remote sensing data and methods for disasters. |
| CPMK 9 | Able to apply and utilize remote sensing data and methods for precision farming. |
Learning Method
- SCL: PBL, CBL, PjBL
Learning Modality
- Offline, Synchronous, Asynchronous
Assessment Methods
- Written: Optional, Description, Essay Oral: Presentation Assignment: Report, Demonstration, Practice