Here is an extensive English summary of the document *"Raster data & remotely sensed images"* (University of Natural Resources and Life Sciences Vienna – Thomas Bauer & Franz Suppan).

This is Part 2.3 of the Geodata Management Course.

---

### **1. Introduction to Remote Sensing**

Remote Sensing (RS) is the science and art of obtaining information about objects, areas, or phenomena without direct contact. It uses sensors to capture electromagnetic radiation reflected or emitted from Earth's surface. Definitions from Lillesand et al. and Campbell/Wynne highlight the focus on overhead perspectives and data derived from electromagnetic spectra.

---

### **2. Energy Sources and Interactions**

There are both natural and artificial sources of energy in remote sensing:

* **Passive systems** rely on natural energy (e.g., sunlight reflected or emitted from Earth).
* **Active systems** emit their own energy (e.g., radar).

Main interactions of energy with the Earth's surface:

* **Absorption**: energy is absorbed
* **Reflection**: energy is redirected
* **Transmission**: energy passes through a target

---

### **3. Electromagnetic Spectrum**

Remote sensing utilizes different parts of the electromagnetic spectrum:

* **Visible**, **near-infrared**, **mid-infrared**, **thermal infrared** for passive systems
* **Microwave/radar** for active systems

An electromagnetic wave consists of perpendicular electric and magnetic fields. Key parameters: wavelength (λ), frequency (v), and velocity of light (c).

---

### **4. Spectral Reflectance**

Reflectance defines how much of the incoming energy is reflected by a surface. Spectral reflectance curves are specific to surface types (e.g., vegetation) and are measured using spectrometers or satellite sensors. Atmospheric effects influence reflectance and must be accounted for.

---

### **5. Applications of Remote Sensing**

Applications span multiple sectors:

* **Agriculture**: crop identification, health monitoring, yield estimation
* **Forestry**: tree species mapping, health/vitality analysis
* **Water resources**: irrigation management
* **Disaster monitoring**: droughts, landslides, forest fires
* **Weather and climate**: forecasting, monitoring
* **Change detection**: land cover/use changes, time series analysis

---

### **6. Sensor Characteristics – Concept of Resolution**

Four main resolution types describe sensor capabilities:

* **Spatial resolution**: size of the ground area each pixel covers (e.g., <1 m to >250 m)
* **Spectral resolution**: number and width of spectral bands a sensor captures (e.g., RGB, multispectral, hyperspectral)
* **Radiometric resolution**: sensitivity of a sensor to detect small differences in energy (e.g., 8-bit = 256 levels, 16-bit = 65,536 levels)
* **Temporal resolution**: frequency of data acquisition over the same area (e.g., Sentinel every 5 days, Landsat every 16 days)

Trade-offs exist between resolution types due to physical and cost constraints.

---

### **7. Airborne Remote Sensing**

Airborne platforms include:

* **Aerial photographs**: very high spatial resolution, require orthorectification for GIS use
* **Orthophotos**: geometrically corrected images for accurate distance measurement
* **Digital airborne cameras**: e.g., Vexcel Ultracam, colour infrared images
* **Hyperspectral sensors**: e.g., HySPEX with 416 bands
* **Airborne Laser Scanners (ALS)**: LiDAR systems for terrain and surface models (e.g., DSM, DTM)

---

### **8. Satellite Sensors and Orbits**

Satellites operate in different orbits:

* **Low Earth Orbit (LEO)**: 600–1,000 km, used for most Earth observation
* **Geostationary Orbit**: 36,000 km, used for weather satellites
* **Sun-synchronous polar orbits**: constant solar time coverage

Scanner systems can be:

* **Whiskbroom (mechanical)**: scan one point at a time
* **Pushbroom (electronic)**: scan line-by-line

---

### **9. Examples of Satellite Systems**

#### **WorldView Series (Digital Globe)**

* WorldView-3: 0.30 m panchromatic, 1.24 m multispectral, 16 spectral bands

#### **PLÉIADES**

* 0.5 m panchromatic, 2 m multispectral, high flexibility in acquisition modes

#### **Landsat (USGS)**

* Landsat 8: 30 m resolution for most bands, 15 m panchromatic, free access

#### **Sentinel-2 (ESA/Copernicus)**

* Spatial resolutions: 10, 20, 60 m across 13 bands, 5-day revisit with twin satellites

#### **MODIS (NASA)**

* On Terra and Aqua satellites, large swath width (2,330 km), daily revisit, 36 bands, low spatial resolution (250 m to 1 km)

---

### **10. Summary**

Remote sensing provides critical data for environmental monitoring and spatial analysis. The choice of sensor depends on required resolution types, area of interest, and costs. There is no single sensor optimal for all use cases due to inherent trade-offs.

---

Would you like this summary formatted into a Word document or PowerPoint presentation?
