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Remote sensing for vegetation monitoring in carbon capture storage regions: A review

Chen, Yun, Guerschman, Juan P, Cheng, Zhibo, Guo, Longzhu
Applied energy 2019 v.240 pp. 312-326
Landsat, carbon, carbon dioxide, carbon sequestration, climate change, energy policy, environmental monitoring, greenhouse gas emissions, hyperspectral imagery, pastures, plant tissues, pollution, rangelands, remediation, remote sensing, renewable energy sources, social impact, surveys, unmanned aerial vehicles, vegetation
Carbon Capture and Storage (CCS) is an emerging climate change mitigation technology which prevents carbon dioxide (CO2) from entering the atmosphere, so as to reduce greenhouse gas emissions. Environmental monitoring in CCS sites is critical for ensuring that any CO2 leakage and its effect on biota, especially vegetation, is detectable. It also plays an important role in creating a social license to operate and assuring the general public that the mechanisms for leak detection and remediation are in place. This review overviews current remote sensing technologies for vegetation monitoring of CCS sites/regions (with a focus on rangelands and pastures), including medium-to-high resolution satellite, aerial (both manned and unmanned aircrafts) and in situ sensors and methods. Our literature survey has pointed out that remote sensing, particularly hyperspectral sensors, can accurately detect CO2 leakage derived effects on vegetation. It can compensate the two main drawbacks of operational systems for detecting these effects over large areas. One is the areas affected tend to be relatively small (1–15 m); and the other is symptoms in vegetation tissues tend to be similar to other stresses, such as nutrient or water deficiency. With this in mind, we have recommend that a comprehensive system should be put in place. It integrates continuous monitoring with ad-hoc detection to assess vegetation conditions in a planned CCS site. Site-based pheonocams and area-based medium-resolution satellite remote sensing sources can be used to compare any given point in time (e.g. the injection point) with the condition at the same location in the past. Before an injection commences, a baseline assessment should be conducted using the combination of high-resolution aerial hyperspectral imaging and medium-resolution long-term data from Landsat sensors. Further acquisition of high-resolution aerial imagery (ideally hyperspectral) is particularly useful following specific detected CO2 leaking events. Aiming at bridging the gaps between research, development and implementation of CCS, this review will contribute to environmental and social impacts of sustainable energy policies, including climate change mitigation and environmental pollution reduction.