Giulio Marchi

Bio: Giulio Marchi is an academic researcher from Food and Agriculture Organization. The author has contributed to research in topics: Land cover & Land use. The author has an hindex of 2, co-authored 3 publications receiving 357 citations.

The extent of forest in dryland biomes

Abstract: Dryland biomes cover two-fifths of Earth’s land surface, but their forest area is poorly known. Here, we report an estimate of global forest extent in dryland biomes, based on analyzing more than 210,000 0.5-hectare sample plots through a photo-interpretation approach using large databases of satellite imagery at (i) very high spatial resolution and (ii) very high temporal resolution, which are available through the Google Earth platform. We show that in 2015, 1327 million hectares of drylands had more than 10% tree-cover, and 1079 million hectares comprised forest. Our estimate is 40 to 47% higher than previous estimates, corresponding to 467 million hectares of forest that have never been reported before. This increases current estimates of global forest cover by at least 9%.

Collect Earth: Land Use and Land Cover Assessment through Augmented Visual Interpretation

Abstract: Collect Earth is a free and open source software for land monitoring developed by the Food and Agriculture Organization of the United Nations (FAO). Built on Google desktop and cloud computing technologies, Collect Earth facilitates access to multiple freely available archives of satellite imagery, including archives with very high spatial resolution imagery (Google Earth, Bing Maps) and those with very high temporal resolution imagery (e.g., Google Earth Engine, Google Earth Engine Code Editor). Collectively, these archives offer free access to an unparalleled amount of information on current and past land dynamics for any location in the world. Collect Earth draws upon these archives and the synergies of imagery of multiple resolutions to enable an innovative method for land monitoring that we present here: augmented visual interpretation. In this study, we provide a full overview of Collect Earth’s structure and functionality, and we present the methodology used to undertake land monitoring through augmented visual interpretation. To illustrate the application of the tool and its customization potential, an example of land monitoring in Papua New Guinea (PNG) is presented. The PNG example demonstrates that Collect Earth is a comprehensive and user-friendly tool for land monitoring and that it has the potential to be used to assess land use, land use change, natural disasters, sustainable management of scarce resources and ecosystem functioning. By enabling non-remote sensing experts to assess more than 100 sites per day, we believe that Collect Earth can be used to rapidly and sustainably build capacity for land monitoring and to substantively improve our collective understanding of the world’s land use and land cover.

Toward a More Representative Monitoring of Land-Use and Land-Cover Dynamics: The Use of a Sample-Based Assessment through Augmented Visual Interpretation Using Open Foris Collect Earth

Abstract: High-quality data for REDD+ monitoring, measurement, and reporting are critical for the continued success of REDD+ implementation and Results-Based Payments. Collect Earth is a free, user-friendly, and open-source software for land monitoring developed by the Food and Agriculture Organization of the United Nations (FAO). The tool allows countries to undertake land monitoring easily and rapidly through a sample-based approach and generate Activity Data (data on the magnitude of human activity resulting in emissions or removals during a given period of time) through augmented visual interpretation with low costs. Under the Paris Agreement, countries will have to update the greenhouse gas inventories that they report to the United Nations Framework Convention on Climate Change every two years through the Biennial Update Reports. One of the important benefits of using sample-based approaches such as the one proposed by Collect Earth is the possibility to achieve a detailed classification of the land-use sub-categories with high accuracy of the estimates for land-use changes occurring since 2000. However, most guidance documents developed for capacity building in developing countries for REDD+ reporting only advocate developing land-cover and land-cover change maps using remote sensing. As several countries already use Collect Earth and the sample-based methodology to report on REDD+, this commentary advocates for a more representative approach and a methodological debate on the potential of sample-based approaches using remote sensing, and when possible combined with ground truthing, to estimate Activity Data for REDD+ and countries’ greenhouse gas inventories for the Agriculture, Forestry and Other Land Use sector in general.

Earth Map: A Novel Tool for Fast Performance of Advanced Land Monitoring and Climate Assessment

Abstract: Earth Map ( https://earthmap.org/ ) is an innovative and free application developed by the Food and Agriculture Organization of the United Nations that was designed in the framework of the Food and Agriculture Organization of the United Nations–Google partnership and facilitates the visualization, processing, and analysis of land and climate data. Earth Map makes petabytes of multitemporal, multiscale, multiparametric, and quasi-real-time satellite imagery and geospatial datasets available to any user thanks to the power of Google Earth Engine ( https://earthengine.google.com/ ) and a point-and-click graphical user interface. These are further complemented with more planetary-scale analytical capabilities so that global and local changes and trends on Earth’s surface can be easily detected, quantified, and visualized. It does not require users to master coding techniques, thereby avoiding bottlenecks in terms of technical capacities of nonexpert users. It ultimately paves the way for countries, research institutes, farmers, and members of the general public to access critical knowledge to develop science-based policy interventions, leverage investments, and sustain livelihoods. We provide a full overview of Earth Map’s software architecture, design, features, and datasets. To illustrate the possible applications of the tool, different examples are presented including a few case studies that show how quick historical analysis of environmental and climate parameters can be performed and research questions answered. The examples demonstrate that Earth Map is a comprehensive and user-friendly tool for land monitoring and climate assessment and that it has the potential to be used to assess land use, land use change, climate change impacts, and natural disasters.

The global tree restoration potential.

Abstract: The restoration of trees remains among the most effective strategies for climate change mitigation. We mapped the global potential tree coverage to show that 4.4 billion hectares of canopy cover could exist under the current climate. Excluding existing trees and agricultural and urban areas, we found that there is room for an extra 0.9 billion hectares of canopy cover, which could store 205 gigatonnes of carbon in areas that would naturally support woodlands and forests. This highlights global tree restoration as our most effective climate change solution to date. However, climate change will alter this potential tree coverage. We estimate that if we cannot deviate from the current trajectory, the global potential canopy cover may shrink by ~223 million hectares by 2050, with the vast majority of losses occurring in the tropics. Our results highlight the opportunity of climate change mitigation through global tree restoration but also the urgent need for action.

The extent of forest in dryland biomes

Abstract: Dryland biomes cover two-fifths of Earth’s land surface, but their forest area is poorly known. Here, we report an estimate of global forest extent in dryland biomes, based on analyzing more than 210,000 0.5-hectare sample plots through a photo-interpretation approach using large databases of satellite imagery at (i) very high spatial resolution and (ii) very high temporal resolution, which are available through the Google Earth platform. We show that in 2015, 1327 million hectares of drylands had more than 10% tree-cover, and 1079 million hectares comprised forest. Our estimate is 40 to 47% higher than previous estimates, corresponding to 467 million hectares of forest that have never been reported before. This increases current estimates of global forest cover by at least 9%.