Remote sensing analysis of forest disturbances

The present invention provides systems and methods to automatically analyze Landsat satellite data of forests. The present invention can easily be used to monitor any type of forest disturbance such as from selective logging, agriculture, cattle ranching, natural hazards (fire, wind events, storms), etc. The present invention provides a large-scale, high-resolution, automated remote sensing analysis of such disturbances

Accelerated losses of protected forests from gold mining in the Peruvian Amazon

Gold mining in Amazonia involves forest removal, soil excavation, and the use of liquid mercury, which together pose a major threat to biodiversity, water quality, forest carbon stocks, and human health. Within the global biodiversity hotspot of Madre de Dios, Peru, gold mining has continued despite numerous 2012 government decrees and enforcement actions against it. Mining is now also thought to have entered federally protected areas, but the rates of miner encroachment are unknown. Here, we utilize high-resolution remote sensing to assess annual changes in gold mining extent from 1999 to 2016 throughout the Madre de Dios region, including the high-diversity Tambopata National Reserve and buffer zone. Regionally, gold mining-related losses of forest averaged 4437 ha yr−1. A temporary downward inflection in the annual growth rate of mining-related forest loss following 2012 government action was followed by a near doubling of the deforestation rate from mining in 2013–2014. The total estimated area of gold mining throughout the region increased about 40% between 2012 and 2016, including in the Tambopata National Reserve. Our results reveal an urgent need for more socio-environmental effort and law enforcement action to combat illegal gold mining in the Peruvian Amazon

Hyperion Studies Of Crop Stress In Mexico

Satellite-based measurements of crop stress could provide much needed information for cropland management, especially in developing countries where other precision agriculture technologies are too expensive (Pierce and Nowak 1999; Robert 2002). For example, detection of areas that are nitrogen deficient or water stressed could guide fertilizer and water management decisions for all farmers within the swath of the satellite. Several approaches have been proposed to quantify canopy nutrient or water content based on spectral reflectance, most of which involve combinations of reflectance in the form of vegetation indices. While these indices are designed to maximize sensitivity to leaf chemistry, variations in other aspects of plant canopies may significantly impact remotely sensed reflectance. These confounding factors include variations in canopy structural properties (e.g., leaf area index, leaf angle distribution) as well as the extent of canopy cover, which determines the amount of exposed bare soil within a single pixel. In order to assess the utility of spectral indices for monitoring crop stress, it is therefore not only necessary to establish relationships at the leaf level, but also to test the relative importance of variations in other canopy attributes at the spatial scale of the remote sensing measurement. In this context, the relative importance of a given attribute will depend on (1) the sensitivity of the reflectance index to variation in the attribute and (2) the degree to which the attribute varies spatially and temporally

Liana canopy cover mapped throughout a tropical forest with high-fidelity imaging spectroscopy

Increasing size and abundance of lianas relative to trees are pervasive changes in Neotropical forests that may lead to reduced forest carbon stocks. Yet the liana growth form is chronically understudied in large-scale tropical forest censuses, resulting in few data on the scale, cause, and impact of increasing lianas. Satellite and airborne remote sensing provide potential tools to map and monitor lianas at much larger spatial and rapid temporal scales than are possible with plot-based forest censuses. We combined high-resolution airborne imaging spectroscopy and a ground-based tree canopy census to investigate whether tree canopies supporting lianas could be discriminated from tree canopies with no liana coverage. Using support vector machine algorithms, we achieved accuracies of nearly 90% in discriminating the presence–absence of lianas, and low error (15.7% RMSE) when predicting liana percent canopy cover. When applied to the full image of the study site, our model had a 4.1% false-positive error rate as validated against an independent plot-level dataset of liana canopy cover. Using the derived liana cover classification map, we show that 6.1%–10.2% of the 1823 ha study site has high-to-severe (50–100%) liana canopy cover. Given that levels of liana infestation are increasing in Neotropical forests and can result in high tree mortality, the extent of high-to-severe liana canopy cover across the landscape may have broad implications for ecosystem function and forest carbon storage. The ability to accurately map landscape-scale liana infestation is crucial to quantifying their effects on forest function and uncovering the mechanisms underlying their increase

Accelerated soil carbon loss does not explain warming related increases in soil CO2 efflux

The universally observed exponential increase in soil-surface CO2 efflux (‘soil respiration’; FS) with increasing temperature has led to speculation that global warming will accelerate soil-organic-carbon (SOC) decomposition, reduce SOC storage, and drive a positive feedback to future warming. However, interpreting temperature–FS relationships, and so modelling terrestrial carbon balance in a warmer world, is complicated by the many sources of respired carbon that contribute to FS (ref. 3) and a poor understanding of how temperature influences SOC decomposition rates. Here we quantified FS, litterfall, bulk SOC and SOC fraction size and turnover, and total below-ground carbon flux (TBCF) across a highly constrained 5.2 °C mean annual temperature (MAT) gradient in tropical montane wet forest. From these, we determined that: increases in TBCF and litterfall explain >90% of the increase in FS with MAT; bulk SOC and SOC fraction size and turnover rate do not vary with MAT; and increases in TBCF and litterfall do not influence SOC storage or turnover on century to millennial timescales. This gradient study shows that for tropical montane wet forest, long-term and whole-ecosystem warming accelerates below-ground carbon processes with no apparent impact on SOC storage

Scaling Up Coral Reef Restoration Using Remote Sensing Technology

Coral reefs face an uncertain future and may not recover naturally from anthropogenic climate change. Coral restoration is needed to rehabilitate degraded reefs and to sustain biodiversity. There is a need for baseline data on global reef distribution, composition, and condition to provide targets for conservation and restoration. Remote sensing can address this issue and is currently underutilized in reef research and restoration. This synthesis integrates current capabilities of remote sensing with key reef restoration criteria, to facilitate coral restoration success. Research into the development of a spectral database for corals, linking habitat type and extent with predator abundance, and identification of species-specific acoustic signatures are needed to advance the use of remote sensing in reef restoration design and monitoring. Reciprocally, reef restoration efforts should innovate at ecosystem, regional, and global levels using remote sensing, to preserve as much of the coral reef biome as possible with continued ocean-climate change

Synergy of VSWIR and LiDAR for Ecosystem Structure, Biomass, and Canopy Diversity

This slide presentation reviews the use of Visible ShortWave InfraRed (VSWIR) Imaging Spectrometer and LiDAR to study ecosystem structure, biomass and canopy diversity. It is shown that the biophysical data from LiDAR and biochemical information from hyperspectral remote sensing provides complementary data for: (1) describing spatial patterns of vegetation and biodiversity, (2) characterizing relationships between ecosystem form and function, and (3) detecting natural and human induced change that affects the biogeochemical cycles