Increasing human population, economical development, and industrialization of our society lead to disturbance of natural ecosystems. To prevent long-term damage of the environment, the affected ecosystems need to be rehabilitated to a sustainable form after industrial operations cease. Environment rehabilitation is a long-term process that is complex and costly as it includes restoration of soil, water bodies, and reintroduction of plant, insect, and animal species. We present a wireless sensor network for evidence-based rehabilitation of disturbed natural ecosystems. Drawing on our case study of an open-cut surface mine in rural Australia, we show that microclimate data can provide insights into the efficiency of specific rehabilitation processes, disentangle the impact of microclimate on the rehabilitation success, and provide early indicators into potential rehabilitation problems. We worked with ecologists to provide domain-based advice on addressing a range of rehabilitation problems and developed a system that periodically generates reports on the rehabilitation status of areas of interest. The report incorporates data from expert surveys from the field and microclimate data from sensors, and provides recommendations to improve rehabilitation in under-performing areas. Such evidence-based assessment of rehabilitation is an important step towards ensuring compliance with set rehabilitation objectives, potentially leading to both more successful and less costly environment rehabilitation.
['Branislav Kusy', 'Christian Richter', 'Siddartha Bhandari', 'Raja Jurdak', 'Victor J. Neldner', 'Michael R. Ngugi']
Evidence-based landscape rehabilitation through microclimate sensing