A high-resolution canopy height model of the Earth.

The worldwide variation in vegetation height is fundamental to the global carbon cycle and central to the functioning of ecosystems and their biodiversity. Geospatially explicit and, ideally, highly resolved information is required to manage terrestrial ecosystems, mitigate climate change and prevent biodiversity loss. Here we present a comprehensive global canopy height map at 10 m ground sampling distance for the year 2020. We have developed a probabilistic deep learning model that fuses sparse height data from the Global Ecosystem Dynamics Investigation (GEDI) space-borne LiDAR mission with dense optical satellite images from Sentinel-2. This model retrieves canopy-top height from Sentinel-2 images anywhere on Earth and quantifies the uncertainty in these estimates. Our approach improves the retrieval of tall canopies with typically high carbon stocks. According to our map, only 5% of the global landmass is covered by trees taller than 30 m. Further, we find that only 34% of these tall canopies are located within protected areas. Thus, the approach can serve ongoing efforts in forest conservation and has the potential to foster advances in climate, carbon and biodiversity modelling.

Cocoa plantations are associated with deforestation in Côte d'Ivoire and Ghana.

Côte d'Ivoire and Ghana, the world's largest producers of cocoa, account for two thirds of the global cocoa production. In both countries, cocoa is the primary perennial crop, providing income to almost two million farmers. Yet precise maps of the area planted with cocoa are missing, hindering accurate quantification of expansion in protected areas, production and yields and limiting information available for improved sustainability governance. Here we combine cocoa plantation data with publicly available satellite imagery in a deep learning framework and create high-resolution maps of cocoa plantations for both countries, validated in situ. Our results suggest that cocoa cultivation is an underlying driver of over 37% of forest loss in protected areas in Côte d'Ivoire and over 13% in Ghana, and that official reports substantially underestimate the planted area (up to 40% in Ghana). These maps serve as a crucial building block to advance our understanding of conservation and economic development in cocoa-producing regions.

The overlooked contribution of trees outside forests to tree cover and woody biomass across Europe.

Trees are an integral part in European landscapes, but only forest resources are systematically assessed by national inventories. The contribution of urban and agricultural trees to national-level carbon stocks remains largely unknown. Here we produced canopy cover, height and above-ground biomass maps from 3-meter resolution nanosatellite imagery across Europe. Our biomass estimates have a systematic bias of 7.6% (overestimation; R = 0.98) compared to national inventories of 30 countries, and our dataset is sufficiently highly resolved spatially to support the inclusion of tree biomass outside forests, which we quantify to 0.8 petagrams. Although this represents only 2% of the total tree biomass, large variations between countries are found (10% for UK) and trees in urban areas contribute substantially to national carbon stocks (8% for the Netherlands). The agreement with national inventory data, the scalability, and spatial details across landscapes, including trees outside forests, make our approach attractive for operational implementation to support national carbon stock inventory schemes.

Irradiation-dependent effects on tumor perfusion and endogenous and exogenous hypoxia markers in an A549 xenograft model.

PURPOSE: Hypoxia is a major determinant of tumor radiosensitivity, and microenvironmental changes in response to ionizing radiation (IR) are often heterogenous. We analyzed IR-dependent changes in hypoxia and perfusion in A549 human lung adenocarcinoma xenografts. MATERIALS AND METHODS: Immunohistological analysis of two exogenously added chemical hypoxic markers, pimonidazole and CCI-103F, and of the endogenous marker Glut-1 was performed time dependently after IR. Tumor vessels and apoptosis were analyzed using CD31 and caspase-3 antibodies. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and fluorescent beads (Hoechst 33342) were used to monitor vascular perfusion. RESULTS: CCI-103F signals measuring the fraction of hypoxic areas after IR were significantly decreased by approximately 50% when compared with pimonidazole signals, representing the fraction of hypoxic areas from the same tumors before IR. Interestingly, Glut-1 signals were significantly decreased at early time point (6.5 h) after IR returning to the initial levels at 30.5 h. Vascular density showed no difference between irradiated and control groups, whereas apoptosis was significantly induced at 10.5 h post-IR. DCE-MRI indicated increased perfusion 1 h post-IR. CONCLUSIONS: The discrepancy between the hypoxic fractions of CCI-103F and Glut-1 forces us to consider the possibility that both markers reflect different metabolic alterations of tumor microenvironment. The reliability of endogenous markers such as Glut-1 to measure reoxygenation in irradiated tumors needs further consideration. Monitoring tumor microvascular response to IR by DCE-MRI and measuring tumor volume alterations should be encouraged.