RePlant Alfa: Integrating Google Earth Engine and R Coding to Support the Identification of Priority Areas for Ecological Restoration

Abstract

Land degradation and climate change are among the main threats to the sustainability of ecosystems worldwide. As a result, the restoration of degraded landscapes is essential to maintaining the functionality of ecosystems, especially those with greater social, economic, and environmental vulnerability. Nevertheless, policymakers are frequently challenged by deciding where to prioritize restoration actions, which usually includes dealing with multiple and complex needs under an always limited budget. If these decisions are not taken based on proper data and processes, restoration implementation can easily fail. In order to help decision-makers take informed decisions on where to implement restoration activities, we have developed a semiautomatic geospatial platform to prioritize areas for restoration activities based on ecological, social, and economic variables. This platform takes advantage of the potential to integrate R coding, Google Earth Engine cloud computing, and GIS visualization services to generate an interactive geospatial decision-maker tool for restoration. Here, we present a prototype version called “RePlant alpha”, which was tested with data from the Central Zone of Chile. This exercise proved that integrating R and GEE was feasible, and that the analysis with at least six indicators for a specific region was also feasible to implement even from a personal computer. Therefore, the use of a virtual machine in the cloud with a large number of indicators over large areas is both possible and practical.

Multi-Criteria Prioritization of Watersheds for Post-Fire Restoration Using GIS Tools and Google Earth Engine: A Case Study from the Department of Santa Cruz, Bolivia

“…Furthermore, the Earth Engine platform imposes a quota per project on the number of simultaneous interactive requests [52]. But overall, in remote working conditions, online applications and web-based solutions allow for interactivity and flexibility [73]. The future of such cloud-based approaches for GIS-based MCA and their incorporation as an element of participatory GIS is promising, especially when local knowledge is included [40].…”

Zoning and Management of Ecological Restoration from the Perspective of Ecosystem Service Supply and Demand: A Case Study of Yuzhong County in Longzhong Loess Hilly Region, China

“…The quality of a forest, shrub, or grassland area is characterized by the quality of the ecosystem [15][16][17]. Some scholars have focused on a single function, such as biodiversity and ecological sensitivity [18][19][20], and carried out restoration of the natural reserve system, habitat degradation, soil erosion, and land desertification [21,22]. However, the existing literature does not take into account the systematization and completeness of the ecological restoration of a land space, which leads to an insignificant improvement in the quality and services of the overall ecosystem in a region.…”