## 3 Conclusions  
In this review paper, we emphasized the impact of wildfires on human life and global ecosystems, and the current climate research indicates worsening fire seasons in the future. Advanced technologies like satellites, drones, ground-based sensor nodes and camera systems have been proposed to supplement traditional firefighting techniques. We discussed the stages and current state of research in these four main methodologies, specifically focusing on detecting wildfires at early stages, predicting hot spots at high risk and monitoring the spread. The paper highlights the technical aspects of the front end of the device, along with the algorithms used in the back end for processing the data and identifying an actual fire. Each category has its own shortcomings and limitations, but also excels at its own niche applications, and under different circumstances one technology will outperform the other. For example, satellites have the capability of scanning a considerable area in a short period of time, which is either impossible or time-consuming using the other methods. However, satellites have very low resolving power and typically sweep the same area once in several hours, making them unsuitable for real-time fire detection. Stationary camera networks address these issues but are immobile and need to be tethered to a power source. UAVs are characterized by flexible flight paths that can be used to adapt to the changes in fire patterns and survey different areas as required. However, they are also power hungry, and are inadequate for long-term continuous monitoring. In comparison to the above, sensor nodes are the most low-power units that can be placed to monitor very remote locations continuously, are relatively inexpensive to produce on a large scale and do not need intensive data processing like those for analyzing images from UAVs, satellites or cameras. On the other hand, nodes face the highest risk of damage due to their proximity to fires on the ground. Ultimately, none of these methods can fully substitute the usefulness of the others, but all four can be unified for a robust firewatch system that together can exhaustively detect wildfires around the clock. The shortcomings and gaps in research in each area were underlined, which we hope will be addressed in the future through rigorous research. \begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt} p{142.3 pt}} \hline \hline
**Instrument** & & **Notes** & **Launch Date** \\ \hline Visible Infrared Imaging Radiometer Suite (VIIRS) [108] & \(\bullet\) & Spans visible and infrared wavelengths, covers 22 channels between 0.41 \(\upmu\)m–12.01 \(\upmu\)m \\ Visible Infrared Imaging Radiometer Suite (VIIRS) [108] & \(\bullet\) & Similar to MODIS but gathers data at higher resolution. Also measures aerosol, among other parameters & 28 October 2011 \\ \(\bullet\) & Carried by Suomi National Polar-Orbiting Partnership (NPP) satellite & \(\bullet\) & Covers 256 spectral channels between 7.5 \(\upmu\)m–12 \(\upmu\)m \\ Hyperspectual Thermal Emission Spectrometer (HyTES) [109] & \(\bullet\) & Determines fire temperature, tracks gas plumes of methane, hydrogen sulfide, ammonia, sulphur dioxide, nitrogen dioxide natural disasters & July 2012 \\ \(\bullet\) & The first Landsat was launched in 1978 & \(\bullet\) & The Landsat-8 has an Operational Land Imager (OLI) and thermal infrared sensors & 2013 \\ Landsat 8 [110] & \(\bullet\) & Provides data in visible, near-IR, SW-IR and thermal IR & 2013 \\ \(\bullet\) & Measures six spectral bands data in 8.29 \(\upmu\)m–12.09 \(\upmu\)m range Helps estimate drought levels by measuring transpiration and water stress in critical areas & 29 June 2018 \\ Station (ECOSTRESS) [111] & \(\bullet\) & A potential fire identification product is currently being tested & 29 June 2018 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._  
**Author Contributions:** [PERSON]--conceptualization and layout of the paper, literature survey, analysis of various methods and deriving their comparative performance and usability.