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The consistent monitoring of trees both inside and outside of forests is key to sustainable land management. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we use the PlanetScope nanosatellite constellation, which delivers global very high-resolution daily imagery, to map both forest and non-forest tree cover for continental Africa using images from a single year. Our prototype map of 2019 (RMSE = 9.57%, bias = −6.9%). demonstrates that a precise assessment of all tree-based ecosystems is possible at continental scale, and reveals that 29% of tree cover is found outside areas previously classified as tree cover in state-of-the-art maps, such as in croplands and grassland. Such accurate mapping of tree cover down to the level of individual trees and consistent among countries has the potential to redefine land use impacts in non-forest landscapes, move beyond the need for forest definitions, and build the basis for natural climate solutions and tree-related studies. Recent analyses have suggested that tree cover in non-forest ecosystems may be much higher than expected. Here, the authors map tree cover down to the individual tree level for the entire continent of Africa and find that almost 30% is found outside areas classified as forests. [ABSTRACT FROM AUTHOR]

In this study, we assessed the impacts of land use and climate changes on the river flows of 81 watersheds within the Cerrado biome, Brazil, based on a comprehensive analysis of field and secondary data acquired between 1985 and 2018. Complementarily, we projected a future deforestation and climate scenario up to 2050 and predicted their impacts on surface water in the study area. We observed that direct impacts by large-scale deforestation oriented to the production of irrigated agricultural commodities have more significantly impacted river flows than climate changes. We estimated an average decrease of 8.7% and 6.7% in the streamflow due to deforestation and climate changes, respectively. Most of the observed changes (56.7%) were due to land use and land cover changes and occurred in recent decades. Climate and land use and land cover changes combined were responsible for a total surface water reduction of −19,718 m³/s within the Cerrado watersheds. By assuming the current deforestation rates, we predicted a total water reduction of 23,653 m³/s by 2050, equivalent to a decrease of 33.9% of the river flows in the study region. It will cause severe streamflow discontinuity in many rivers and strongly affect agricultural, electric power production, biodiversity, and water supply, especially during dry seasons in that region. [ABSTRACT FROM AUTHOR]

While closed canopy forests have been an important focal point for land cover change monitoring and climate change mitigation, less consideration has been given to methods for large scale measurements of trees outside of forests. Trees outside of forests are an important but often overlooked natural resource throughout sub-Saharan Africa, providing benefits for livelihoods as well as climate change mitigation and adaptation. In this study, the development of an individual tree cover map using very high-resolution remote sensing and a comparison with a new automated machine learning mapping product revealed an important contribution of trees outside of forests to landscape tree cover and carbon stocks in a region where trees outside of forests are important components of livelihood systems. Here, we test and demonstrate the use of allometric scaling from remote sensing crown area to provide estimates of landscape-scale carbon stocks. Prominent biomass and carbon maps from global-scale remote sensing greatly underestimate the “invisible” carbon in these sparse tree-based systems. The measurement of tree cover and carbon in these landscapes has important application in climate change mitigation and adaptation policies. [ABSTRACT FROM AUTHOR]

In the late 1990s, DeFries and her colleagues combined Landsat analysis with global tree cover from Advanced Very High Resolution Radiometer (AVHRR) data to calibrate a carbon emissions product (DeFries and Townshend 1999). The Landsat mission continued its saga with the launch of Landsat 8 in 2013, which introduced next-generation Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) instruments (www.usgs.gov/landsat-missions/landsat-8). Basemap source: Google Earth using NASA Landsat imagery as back coverage. [Extracted from the article]

Regrowth and planted trees in agricultural landscapes are rarely protected from clearing under national Forest Acts. There is, therefore, some question over the long-term security of any value they might provide to biodiversity and the global carbon cycle. Engaging landholders in carbon credits that are conditioned on planted areas being maintained into the future could improve the situation. To begin carbon trading, landholders need precise and accurate estimates of the carbon sequestered by the trees in their fields. Accurate estimates of carbon stocks depend to a greater degree on the availability and adequacy of the allometric equations that are used to estimate tree biomass. The present study has developed an allometric model for estimating the woody biomass of Jatropha trees planted as boundary hedges in agricultural landscapes under smallholder farming systems in Malawi. The predictive performance of the model was assessed and was subsequently compared with the published Jatropha models. The results showed that the statistical fits of our model were generally good, enabling one to use it with confidence for estimating wood biomass in Jatropha stands from which they were derived. The published Jatropha models consistently overestimated the woody biomass by as much as 55%, rendering them unsuitable for application in estimating woody biomass in our study sites. [ABSTRACT FROM AUTHOR]

Selective logging degrades tropical forests. Logging operations vary in timing, location, and intensity. Evidence of this land use is rapidly obscured by forest regeneration and ongoing deforestation. A detailed study of selective logging operations was conducted near Sinop, State of Mato Grosso, Brazil, one of the key Amazonian logging centers. An 11-yr series of annual Lansdat images (1992¿2002) was used to detect and track logged forests across the landscape. A semiautomated method was applied and compared to both visual interpretation and field data. Although visual detection provided precise delineation of some logged areas, it missed many areas. The semiautomated technique provided the best estimates of logging extent that are largely independent of potential user bias. Multitemporal analyses allowed the authors to analyze the annual variations in logging and deforestation, as well as the interaction between them. It is shown that, because of both rapid regrowth and deforestation, evidence of logging activities often disappeared within 1¿3 yr. During the 1992¿2002 interval, a total of 11 449 km2 of forest was selectively logged. Around 17% of these logged forests had been deforested by 2002. An intra-annual analysis was also conducted using four images spread over a single year. Nearly 3% of logged forests were rapidly deforested during the year in which logging occurred, indicating that even annual monitoring will underestimate logging extent. Great care will need to be taken when inferring logging rates from observations greater than a year apart because of the partial detection of previous years of logging activity. [ABSTRACT FROM AUTHOR]

This article examines forest change in the Brazilian Amazon in light of forest transition theory. We draw on satellite-based land cover data matched in a geographic information system (GIS) to census-based social and agricultural data for Brazilian municipalities at multiple time points. Subregions with distinct settlement histories serve as proxies for different stages along the forest transition, theorized to exhibit depletion of forest cover, eventually followed by a recovery. Satellite images allow for distinctions between primary (old-growth) and secondary (successional) forests, but the data indicate more successional forests than expected. We argue that biophysical impediments (e.g., poor soils) and social obstacles (e.g., capital scarcity) led to limited land settlement, low incomes, urbanization, and a shift from crops to pasture, resulting in the rapid expansion of secondary forests without primary forest depletion. These findings call for refinements in forest transition theory that can better account for land cover changes in tropical regions of non-OECD countries. [ABSTRACT FROM AUTHOR]

Carbon fluxes from tropical deforestation and regrowth are highly uncertain components of the contemporary carbon budget, due in part to the lack of spatially explicit and consistent information on changes in forest area. We estimate fluxes for the 1980s and 1990s using subpixel estimates of percent tree cover derived from coarse (National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer) satellite data in combination with a terrestrial carbon model. The satellite-derived estimates of change in forest area are lower than national reports and remotesensing surveys from the United Nations Food and Agriculture Organization Forest Resource Assessment (FRA) in all tropical regions, especially for the 1980s. However, our results indicate that the net rate of tropical forest clearing increased ≈10% from the 1980s to 1990s, most notably in southeast Asia, in contrast to an 11% reduction reported by the FRA. We estimate net mean annual carbon fluxes from tropical deforestation and regrowth to average 0.6 (0.3-0.8) and 0.9 (0.5-1.4) petagrams (Pg)·yr[sup -1] for the 1980s and 1990s, respectively. Compared with previous estimates of 1.9 (0.6-2.5) Pg·yr[sup -1] based on FRA national statistics of changes in forest area, this alternative estimate suggests less "missing" carbon from the global carbon budget but increasing emissions from tropical land-use change. [ABSTRACT FROM AUTHOR]

Spatial time-series measurements of forest degradation rates are important for estimating national greenhouse gas emissions but have been challenging for open forests and woodlands. This lack of quantitative data on forest degradation rates, location and biomass is an important constraint to developing national REDD+ policy. In Malawi, and in most countries in Africa, most assessments of forest cover change for carbon emissions monitoring tend to report only deforestation in the public forest estate managed by the government, even when important forest degradation also occurs in agricultural areas, such as customary forests and other tree-based systems. This study has resulted in: (a) a new robust forest map for Malawi, (b) spatial and quantitative measurements of both forest degradation and deforestation, and (c) a demonstration of the approach through the introduction of a tool that maps across the broad landscape of forests and trees outside of forests. The results can be used to support REDD+ National Forest Monitoring Systems. This analysis produces new estimates of landscape-wide deforestation rates between 2000–2009 (22,410 ha yr−1) and 2009–2015 (38,937 ha yr−1). We further produce new estimates of the rate of forest degradation between 2000–2009 (42,961 ha yr−1) and 2009–2015 (71,878 ha yr−1). The contribution of these new tools and estimates to capacities for calculating carbon emissions are important, increasing prospects for full REDD+ readiness across semi-arid Africa. [ABSTRACT FROM AUTHOR]

Comments on the progress in the Landsat Program in the U.S. Revision of the Landsat Data Continuity Mission specification; Concern on the pricing and distribution policy for Landsat data.

One of the concerns regarding transformation of land cover in tropical areas has been the large degree of uncertainty associated with both rates of deforestation over time and total deforestation. Special monitoring mechanisms must be taken into consideration if a program toward deforestation control is going to be implemented at the nationalor regional scale. The premise of this paper is that any attempt to quantify tropical deforestation and deforestation rates - at regionallevel, by randomly selecting sites within a population of satellite scenes - would require an overwhelming number of samples. This paper suggests a methodological approach for sampling remote sensing databases to be used as part of land use/cover change or joint implementation projects. This paper uses the concept of stratification and persistence as main tools. [ABSTRACT FROM AUTHOR]

An international system for monitoring land cover change is needed to support a range of scientific and policy objectives. Although much of the technology and methods are readily available, such a program has yet to be implemented. This paper outlines the rationale, requirements, and strategy for implementing a land cover-monitoring program using satellite remote sensing, field and ground measurements, and models and assessments. The proposed program builds on existing activities throughout the world and is designed to simultaneously meet the needs of the international policy, global change research, and nationalresource management. Outputs from this program would provide supportto the Framework Convention on Climate Change, lead to the development of consistent country-level emission inventories, and address important scientific problems in global change research such as closing the global carbon budget. [ABSTRACT FROM AUTHOR]