Abiogenic hydrocarbons are fundamentally important for understanding the deep microbial communities and the origin of life. The generation of abiogenic hydrocarbons was proposed to be limited to ultramafic-hosted hydrothermal systems, fueled by the serpentinization product H₂. Here, we present the discharge of short-chain alkanes from an andesitic rock-hosted Lutao geothermal field in the north Luzon arc, carrying abiotic chemical and isotopic signals. These abiogenic hydrocarbons were generated from CO₂-H₂O-rich fluid inclusions, where the long-term storage since Lutao volcanism (~ 1.3 Ma) allowed overcoming the sluggish kinetics of CO₂ to CH₄ reduction at temperatures of 174 - 206 ^oC. Natural abiogenic production of hydrocarbons, therefore, can be more ubiquitous than previously thought. The hypothesis regarding the origin of methane in Earth’s early atmosphere and its implication to the origin of life may require reconsideration.

Estimating evapotranspiration (ET) has been one of the most important research in agriculture recently because of water scarcity, growing population, and climate change. ET is the sum of evaporation from the soil and transpiration from the crops to the atmosphere. The accurate estimation and mapping of ET are necessary for crop water management. Traditionally, people use weighing lysimeters, Bowen ratio, eddy covariance and many other methods to estimate ET. However, these ET methods are points or location-specific measurements and cannot be extended to a large scale of ET estimation. With the advent of satellites technology, remote sensing images can provide spatially distributed measurements. The satellites multispectral images spatial resolution, however, is in the range of meters, which is often not enough for crops with clumped canopy structure such as trees and vines. And, the timing or frequency of satellites overpass is not always enough to meet the research or water management needs. The Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, can help solve these spatial and temporal challenges. Lightweight cameras and sensors can be mounted on drones and take high-resolution images on a large scale of field. Compared with satellites images, the spatial resolution of UAVs’ images can be as high as 1 cm per pixel. And, people can fly a drone at any time if the weather condition is good. Cloud cover is less of a concern than satellite remote sensing. Both temporal and spatial resolution is highly improved by drones. In this paper, a review of different UAVs based approaches of ET estimations are presented. Different modified models used by UAVs, such as Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC), Two-source energy balance (TSEB) model, etc, are also discussed.