scholarly journals Quantification of CH<sub>4</sub> coal mining emissions in Upper Silesia by passive airborne remote sensing observations with the Methane Airborne MAPper (MAMAP) instrument during the CO<sub>2</sub> and Methane (CoMet) campaign

2021 ◽  
Vol 21 (23) ◽  
pp. 17345-17371
Author(s):  
Sven Krautwurst ◽  
Konstantin Gerilowski ◽  
Jakob Borchardt ◽  
Norman Wildmann ◽  
Michał Gałkowski ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Weighting Function ◽  
Source Region ◽  
Mitigation Strategies ◽  
Spectral Radiance ◽  
Optical Absorption Spectroscopy ◽  
Climate Mitigation ◽  
Target Area ◽  
Atmospheric Concentration ◽  
Small Clusters

Abstract. Methane (CH4) is the second most important anthropogenic greenhouse gas, whose atmospheric concentration is modulated by human-induced activities, and it has a larger global warming potential than carbon dioxide (CO2). Because of its short atmospheric lifetime relative to that of CO2, the reduction of the atmospheric abundance of CH4 is an attractive target for short-term climate mitigation strategies. However, reducing the atmospheric CH4 concentration requires a reduction of its emissions and, therefore, knowledge of its sources. For this reason, the CO2 and Methane (CoMet) campaign in May and June 2018 assessed emissions of one of the largest CH4 emission hot spots in Europe, the Upper Silesian Coal Basin (USCB) in southern Poland, using top-down approaches and inventory data. In this study, we will focus on CH4 column anomalies retrieved from spectral radiance observations, which were acquired by the 1D nadir-looking passive remote sensing Methane Airborne MAPper (MAMAP) instrument, using the weighting-function-modified differential optical absorption spectroscopy (WFM-DOAS) method. The column anomalies, combined with wind lidar measurements, are inverted to cross-sectional fluxes using a mass balance approach. With the help of these fluxes, reported emissions of small clusters of coal mine ventilation shafts are then assessed. The MAMAP CH4 column observations enable an accurate assignment of observed fluxes to small clusters of ventilation shafts. CH4 fluxes are estimated for four clusters with a total of 23 ventilation shafts, which are responsible for about 40 % of the total CH4 mining emissions in the target area. The observations were made during several overflights on different days. The final average CH4 fluxes for the single clusters (or sub-clusters) range from about 1 to 9 t CH4 h−1 at the time of the campaign. The fluxes observed at one cluster during different overflights vary by as much as 50 % of the average value. Associated errors (1σ) are usually between 15 % and 59 % of the average flux, depending mainly on the prevailing wind conditions, the number of flight tracks, and the magnitude of the flux itself. Comparison to known hourly emissions, where available, shows good agreement within the uncertainties. If only emissions reported annually are available for comparison with the observations, caution is advised due to possible fluctuations in emissions during a year or even within hours. To measure emissions even more precisely and to break them down further for allocation to individual shafts in a complex source region such as the USCB, imaging remote sensing instruments are recommended.

scholarly journals Quantification of CH<sub>4</sub> coal mining emissions in Upper Silesia by passive airborne remote sensing observations with the MAMAP instrument during CoMet

2021 ◽  
Author(s):  
Sven Krautwurst ◽  
Konstantin Gerilowski ◽  
Jakob Borchardt ◽  
Norman Wildmann ◽  
Michal Galkowski ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Weighting Function ◽  
Source Region ◽  
Mitigation Strategies ◽  
Spectral Radiance ◽  
Optical Absorption Spectroscopy ◽  
Climate Mitigation ◽  
Target Area ◽  
Ch4 Emissions ◽  
Small Clusters

Abstract. Methane (CH4) is the second most important anthropogenic greenhouse gas, whose atmospheric concentration is modulated by human-induced activities, and it has a larger global warming potential than carbon dioxide (CO2). Because of its short atmospheric lifetime relative to that of CO2, the reduction of the atmospheric abundance of CH4 is an attractive target for short term climate mitigation strategies. However, reducing the atmospheric CH4 concentration requires a reduction of its emissions and, therefore, knowledge of its sources is essential. For this reason, the CO2 and Methane (CoMet) campaign in early summer of 2018 was initiated with the primary goal of assessing emissions of one of the largest CH4 emission hot spots in Europe, the Upper Silesian Coal Basin (USCB) in southern Poland, using top-down approaches and inventory data. In this campaign, a variety of instruments (both in situ and remote sensing) and platforms (e.g., ground-based and airborne) were deployed, which were supplemented by modeling activities supporting the flight planning and the interpretation of the observations. Consequently, CH4 emissions originating from ~54 coal mine ventilation shafts distributed over an area of around 60 × 40 km2 could be investigated on different scales, ranging from single shafts over smaller clusters up to the entire basin. In this study, we will focus on CH4 column anomalies retrieved from spectral radiance observations, which were acquired by the 1D nadir-looking passive remote sensing Methane Airborne MAPper (MAMAP) instrument, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) method. The column anomalies are combined with wind lidar measurements and inverted to cross-sectional fluxes for different flight tracks making use of a mass balance approach. These fluxes are subsequently used to assess the reported emissions of small clusters of ventilation shafts. The MAMAP CH4 column observations allow for accurate assignment of observed fluxes to small clusters of ventilation shafts. CH4 fluxes are estimated for 4 clusters comprising 23 ventilation shafts in total, which are responsible for about 40 % of the total CH4 emissions from mining in the target area. The observations used were made during multiple overflights on different days between 28 May and 7 June 2018. The final averaged CH4 fluxes for the single clusters (or sub-clusters) range from about 1 to 9 t CH4 hr−1 at the time of the campaign. The range of fluxes observed at one cluster during different overflights can vary by as much as 50 % of the respective averaged value. Associated errors (1-σ) are usually between 15 % and 59 % of the averaged flux, mainly depending on the prevailing wind conditions, the number of flight tracks, and the magnitude of the flux itself. Comparison to known hourly emissions, where available, shows good agreement with the computed fluxes within the uncertainties. In the case that only annually reported emissions are available for comparison with the observations, caution is required due to potential fluctuations of the emissions during one year or even within hours. To measure emissions even more precisely and to further unravel them for allocation to individual shafts in a complex source region as encountered in the USCB, imaging remote sensing instruments are recommended.

scholarly journals Global Sustainability Crossroads: A Participatory Simulation Game to Educate in the Energy and Sustainability Challenges of the 21st Century

2019 ◽  
Vol 11 (13) ◽  
pp. 3672 ◽  
Author(s):  
Iñigo Capellán-Pérez ◽  
David Álvarez-Antelo ◽  
Luis J. Miguel
Keyword(s):  
Mitigation Strategies ◽  
Simulation Game ◽  
Climate Mitigation ◽  
Global Sustainability ◽  
Environmental Consequences ◽  
Environment Model ◽  
Participatory Simulation ◽  
Simulation Group ◽  
Energy Economy ◽  
Sustainability Challenges

There is a general need to facilitate citizens’ understanding of the global sustainability problem with the dual purpose of raising their awareness of the seriousness of the problem and helping them get closer to understanding the complexity of the solutions. Here, the design and application of the participatory simulation game Global Sustainability Crossroads is described, based on a global state-of-the-art energy–economy–environment model, which creates a virtual scenario where the participants are confronted with the design of climate mitigation strategies as well as the social, economic, and environmental consequences of decisions. The novelty of the game rests on the global scope and the representation of the drivers of anthropogenic emissions within the MEDEAS-World model, combined with a participatory simulation group dynamic flexible enough to be adapted to a diversity of contexts and participants. The performance of 13 game workshops with ~420 players has shown it has a significant pedagogical potential: the game is able to generate discussions on crucial topics which are usually outside the public realm such as the relationship between economic growth and sustainability, the role of technology, how human desires are limited by biophysical constraints or the possibility of climate tipping points.

scholarly journals Towards Understanding Variability in Droughts in Response to Extreme Climate Conditions over the Different Agro-Ecological Zones of Pakistan

2021 ◽  
Vol 13 (12) ◽  
pp. 6910
Author(s):  
Adil Dilawar ◽  
Baozhang Chen ◽  
Arfan Arshad ◽  
Lifeng Guo ◽  
Muhammad Irfan Ehsan ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Principal Component ◽  
Mitigation Strategies ◽  
Precipitation Extremes ◽  
Climate Mitigation ◽  
Mean Annual Temperature ◽  
Climate Extreme ◽  
Ecological Zones ◽  
The Mean ◽  
Agro Ecological Zones

Here, we provided a comprehensive analysis of long-term drought and climate extreme patterns in the agro ecological zones (AEZs) of Pakistan during 1980–2019. Drought trends were investigated using the standardized precipitation evapotranspiration index (SPEI) at various timescales (SPEI-1, SPEI-3, SPEI-6, and SPEI-12). The results showed that droughts (seasonal and annual) were more persistent and severe in the southern, southwestern, southeastern, and central parts of the region. Drought exacerbated with slopes of −0.02, −0.07, −0.08, −0.01, and −0.02 per year. Drought prevailed in all AEZs in the spring season. The majority of AEZs in Pakistan’s southern, middle, and southwestern regions had experienced substantial warming. The mean annual temperature minimum (Tmin) increased faster than the mean annual temperature maximum (Tmax) in all zones. Precipitation decreased in the southern, northern, central, and southwestern parts of the region. Principal component analysis (PCA) revealed a robust increase in temperature extremes with a variance of 76% and a decrease in precipitation extremes with a variance of 91% in the region. Temperature and precipitation extremes indices had a strong Pearson correlation with drought events. Higher temperatures resulted in extreme drought (dry conditions), while higher precipitation levels resulted in wetting conditions (no drought) in different AEZs. In most AEZs, drought occurrences were more responsive to precipitation. The current findings are helpful for climate mitigation strategies and specific zonal efforts are needed to alleviate the environmental and societal impacts of drought.

scholarly journals Twentieth-Century Climate Change over Africa: Seasonal Hydroclimate Trends and Sahara Desert Expansion

2018 ◽  
Vol 31 (9) ◽  
pp. 3349-3370 ◽  
Author(s):  
Natalie Thomas ◽  
Sumant Nigam
Keyword(s):  
Twentieth Century ◽  
Source Region ◽  
Surface Air Temperature ◽  
Rain Gauge ◽  
Mitigation Strategies ◽  
Annual Rainfall ◽  
Sahara Desert ◽  
Seasonal Temperature ◽  
African Continent ◽  
Climate Simulations

Twentieth-century trends in seasonal temperature and precipitation over the African continent are analyzed from observational datasets and historical climate simulations. Given the agricultural economy of the continent, a seasonal perspective is adopted as it is more pertinent than an annual-average one, which can mask offsetting but agriculturally sensitive seasonal hydroclimate variations. Examination of linear trends in seasonal surface air temperature (SAT) shows that heat stress has increased in several regions, including Sudan and northern Africa where the largest SAT trends occur in the warm season. Broadly speaking, the northern continent has warmed more than the southern one in all seasons. Precipitation trends are varied but notable declining trends are found in the countries along the Gulf of Guinea, especially in the source region of the Niger River in West Africa, and in the Congo River basin. Rainfall over the African Great Lakes—one of the largest freshwater repositories—has, however, increased. It is shown that the Sahara Desert has expanded significantly over the twentieth century, by 11%–18% depending on the season, and by 10% when defined using annual rainfall. The expansion rate is sensitively dependent on the analysis period in view of the multidecadal periods of desert expansion (including from the drying of the Sahel in the 1950s–80s) and contraction in the 1902–2013 record, and the stability of the rain gauge network. The desert expanded southward in summer, reflecting retreat of the northern edge of the Sahel rainfall belt, and to the north in winter, indicating potential impact of the widening of the tropics. Specific mechanisms for the expansion are investigated. Finally, this observational analysis is used to evaluate the state-of-the-art climate simulations from a comparison of the twentieth-century hydroclimate trends. The evaluation shows that modeling regional hydroclimate change over the African continent remains challenging, warranting caution in the development of adaptation and mitigation strategies.

The Paradox of Climate Change Mitigation and Adaptation in Danish Housing

2012 ◽  
Vol 37 (4) ◽  
pp. 19-28
Author(s):  
Rob Marsh
Keyword(s):  
Climate Change ◽  
Energy Consumption ◽  
Solar Energy ◽  
Theoretical Study ◽  
Climate Adaptation ◽  
Mitigation Strategy ◽  
Mitigation Strategies ◽  
Space Heating ◽  
Climate Mitigation ◽  
Passive Solar

Climate change means that buildings must greatly reduce their energy consumption. It is however paradoxical that climate mitigation in Denmark has created negative energy and indoor climate problems in housing that may be made worse by climate change. A literature review has been carried out of housing schemes where climate mitigation was sought through reduced space heating demand, and it is shown that extensive problems with overheating exist. A theoretical study of regulative and design strategies for climate mitigation in new build housing has therefore been carried out, and it is shown that reducing space heating with high levels of thermal insulation and passive solar energy results in overheating and a growing demand for cooling. Climate change is expected to reduce space heating and increase cooling demand in housing. An analysis of new build housing using passive solar energy as a climate mitigation strategy has therefore been carried out in relation to future climate change scenarios. It is shown that severe indoor comfort problems can occur, questioning the relevance of passive solar energy as a climate mitigation strategy. In conclusion, a theoretical study of the interplay between climate adaptation and mitigation strategies is carried out, with a cross-disciplinary focus on users, passive design and active technologies. It is shown that the cumulative use of these strategies can create an adaptation buffer, thus eliminating problems with overheating and reducing energy consumption. New build housing should therefore be designed in relation to both current and future climate scenarios to show that the climate mitigation strategies ensure climate adaptation.

An assessment of the Dead Sea level change using remotely sensed data

2021 ◽  
Author(s):  
Musab Mbideen ◽  
Balázs Székely
Keyword(s):  
Remote Sensing ◽  
Water Level ◽  
Surface Area ◽  
Dead Sea ◽  
Spectral Radiance ◽  
Water Volume ◽  
Surface Model ◽  
Atmospheric Effects ◽  
Level 1 ◽  
The Dead

&lt;p&gt;Remote Sensing (RS) and Geographic Information System (GIS) instruments have spread rapidly in recent years to manage natural resources and monitor environmental changes. Remote sensing has a vast range of applications; one of them is lakes monitoring. The Dead Sea (DS) is subjected to very strong evaporation processes, leading to a remarkable shrinkage of its water level. The DS is being dried out due to a negative balance in its hydrological cycle during the last five decades. This research aims to study the spatial changes in the DS throughout the previous 48 years. Change detection technique has been performed to detect this change over the research period (1972-2020). 73 Landsat imageries have been used from four digital sensors; Landsat&amp;#160;1-5 MSS C1 Level-1, Landsat&amp;#160;4-5 TM C1 Level-1, Land&amp;#160;sat&amp;#160;7&amp;#160;ETM+ C1 &amp;#160;Level-1, and Landsat&amp;#160;8 OLI-TIRS C1 Level. After following certain selection criteria , the number of studied images decreased. Furthermore, the Digital Surface Model of the Space Shuttle Radar Topography Mission and a bathymetric map of the Dead Sea were used. The collected satellite imageries were pre-processed and normalized using ENVI 5.3 software by converting the Digital Number (DN) to spectral radiance, the spectral radiance was converted to apparent reflectance, atmospheric effects were removed, and finally, the black gaps were removed. It was important to distinguish between the DS lake and the surrounding area in order to have accurate results, this was done by performing classification techniques. The digital terrain model of the DS was used in ArcGIS (3D) to reconstruct the elevation of the shore lines. This model generated equations to detect the water level, surface area, and water volume of the DS. The results were compared to the bathymetric data as well. The research shows that the DS water level declined 65&amp;#160;m (1.35&amp;#160;m/a) in the studied period. The surface area and the water volume declined by 363.56&amp;#160;km&lt;sup&gt;2 &lt;/sup&gt;(7.57&amp;#160;km&lt;sup&gt;2&lt;/sup&gt;/a) and 53.56&amp;#160;km&lt;sup&gt;3&lt;/sup&gt; (1.11&amp;#160;km&lt;sup&gt;3&lt;/sup&gt;/a), respectively. The research also concluded that due to the bathymetry of the DS, the direction of this shrinkage is from the south to the north. We hypothesize that anthropogenic effects have contributed in the shrinkage of the DS more than the climate. The use of the DS water by both Israel and Jordan for industrial purposes is the main factor impacting the DS, another factor is the diversion of the Jordan and Yarmouk rivers. Our results also allow to give a prediction for the near future of the DS: the water level is expected to reach &amp;#8211;445&amp;#160;m in 2050, while the surface area and the water volume is expected to be 455&amp;#160;km&lt;sup&gt;2&lt;/sup&gt; and 142&amp;#160;km&lt;sup&gt;3&lt;/sup&gt;, respectively.&amp;#160;&lt;/p&gt;

scholarly journals Sensitivity of black carbon concentrations and climate impact to aging and scavenging

2016 ◽  
Author(s):  
Marianne T. Lund ◽  
Terje K. Berntsen ◽  
Bjørn H. Samset
Keyword(s):  
Nitric Acid ◽  
Black Carbon ◽  
Radiative Forcing ◽  
Mitigation Strategies ◽  
The Arctic ◽  
Climate Mitigation ◽  
Vertical Profiles ◽  
The Impact ◽  
Model Measurement ◽  
Global Mean

Abstract. Despite recent improvements, significant uncertainties in global modeling of black carbon (BC) aerosols persist, posing important challenges for the design and evaluation of effective climate mitigation strategies targeted at BC emission reductions. Here we investigate the sensitivity of BC concentrations in the chemistry-transport model OsloCTM2 with the microphysical aerosol parameterization M7 (OsloCTM2-M7) to parameters controlling aerosol aging and scavenging. We focus on Arctic surface concentrations and remote region BC vertical profiles, and introduce a novel treatment of condensation of nitric acid on BC. The OsloCTM2-M7 underestimates annual averaged BC surface concentrations, with a mean normalized bias of −0.55. The seasonal cycle and magnitude of Arctic BC surface concentrations is improved compared to previous OsloCTM2 studies, but model-measurement discrepancies during spring remain. High-altitude BC over the Pacific is overestimated compared with measurements from the HIPPO campaigns. We find that a shorter global BC lifetime improves the agreement with HIPPO, in line with other recent studies. Several processes can achieve this, including allowing for convective scavenging of hydrophobic BC and reducing the amount of soluble material required for aging. Simultaneously, the concentrations in the Arctic are reduced, resulting in poorer agreement with measurements in part of the region. A first step towards inclusion of aging by nitrate in OsloCTM2-M7 is made by allowing for condensation of nitric acid on BC. This results in a faster aging and reduced lifetime, and in turn to a better agreement with the HIPPO measurements. On the other hand, model-measurement discrepancies in the Arctic are exacerbated. Work to further improve this parameterization is needed. The impact on global mean radiative forcing (RF) and surface temperature response (TS) in our experiments is estimated. Compared to the baseline, decreases in global mean direct RF on the order of 10–30 % of the total pre-industrial to present BC direct RF is estimated for the experiments that result in the largest changes in BC concentrations. We show that globally tuning parameters related to BC aging and scavenging can improve the representation of BC vertical profiles in the OsloCTM2-M7 compared with observations. Our results also show that such improvements can result from changes in several processes and often depend on assumptions about uncertain parameters such as the BC ice nucleating efficiency and the change in hygroscopicity with aging. It is also important to be aware of potential tradeoffs in model performance between different regions. Other important sources of uncertainty, particularly for Arctic BC, such as model resolution has not been investigated here. Our results underline the importance of more observations and experimental data to improve process understanding and thus further constrain models.

scholarly journals Estimation and Validation of Land Surface Temperature by using Remote Sensing & GIS for Chittoor District, Andhra Pradesh

2021 ◽  
Vol 12 (5) ◽  
pp. 607-617
Author(s):  
A. Rajani, Dr. S.Varadarajan
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Andhra Pradesh ◽  
Temperature Data ◽  
Sensor Data ◽  
Spectral Radiance ◽  
Landsat 8 ◽  
Thermal Band

Land Surface Temperature (LST) quantification is needed in various applications like temporal analysis, identification of global warming, land use or land cover, water management, soil moisture estimation and natural disasters. The objective of this study is estimation as well as validation of temperature data at 14 Automatic Weather Stations (AWS) in Chittoor District of Andhra Pradesh with LST extracted by using remote sensing as well as Geographic Information System (GIS). Satellite data considered for estimation purpose is LANDSAT 8. Sensor data used for assessment of LST are OLI (Operational Land Imager) and TIR (Thermal Infrared). Thermal band  contains spectral bands of 10 and 11 were considered for evaluating LST independently by using algorithm called Mono Window Algorithm (MWA). Land Surface Emissivity (LSE) is the vital parameter for calculating LST. The LSE estimation requires NDVI (Normalized Difference Vegetation Index) which is computed by using Band 4 (visible Red band) and band 5 (Near-Infra Red band) spectral radiance bands. Thermal band images having wavelength 11.2 µm and 12.5 µm of 30th May, 2015 and 21st October, 2015 were processed for the analysis of LST. Later on validation of estimated LST through in-suite temperature data obtained from 14 AWS stations in Chittoor district was carried out. The end results showed that, the LST retrieved by using proposed method achieved 5 per cent greater correlation coefficient (r) compared to LST retrieved by using existing method which is based on band 10.

Technological advances to improve the quantification of volcanic emissions

2021 ◽  
Author(s):  
Christopher Fuchs ◽  
Jonas Kuhn ◽  
Nicole Bobrowski ◽  
Ulrich Platt
Keyword(s):  
Remote Sensing ◽  
Temporal Resolution ◽  
Volcanic Activity ◽  
Imaging Techniques ◽  
Correlation Spectroscopy ◽  
Trace Gas ◽  
Optical Absorption Spectroscopy ◽  
Integration Time ◽  
Volcanic Plume ◽  
Flux Measurements

&lt;p&gt;Variations in volcanic trace gas composition and fluxes are a valuable indicator for changes in magmatic systems and therefore allow monitoring of the volcanic activity. An established method to measure trace gas emissions is to use remote sensing techniques like, for example, Differential Optical Absorption Spectroscopy (DOAS) and more recently SO&lt;sub&gt;2&lt;/sub&gt;-cameras, that can quantify volcanic sulphur dioxide (SO&lt;sub&gt;2&lt;/sub&gt;) emissions during quiescent degassing and eruptive phases, making it possible to correlate fluxes with volcanic activity.&amp;#160;&lt;/p&gt;&lt;p&gt;We present flux measurements of volcanic SO&lt;sub&gt;2&lt;/sub&gt; emissions based on the novel remote sensing technique of Imaging Fabry-P&amp;#233;rot Interferometer Correlation Spectroscopy (IFPICS) in the UV spectral range. The basic principle of IFPICS lies in the application of an Fabry-P&amp;#233;rot Interferometer (FPI) as wavelength selective element. The FPIs periodic transmission profile is matched to the periodic spectral absorption features of SO&lt;sub&gt;2&lt;/sub&gt;, resulting in high spectral information for its detection. This technique yields a higher trace gas selectivity and sensitivity than imaging approaches based on interference filters, e.g. SO&lt;sub&gt;2&lt;/sub&gt;-cameras and an increased spatio-temporal resolution over spectroscopic imaging techniques, e.g. imaging DOAS. Hence, IFPICS shows reduced cross sensitivities to broadband absorption (e.g. to ozone, aerosols), which allows the application to weaker volcanic SO&lt;sub&gt;2&lt;/sub&gt; emitters and increases the range of possible atmospheric conditions. It further raises the possibility to apply IFPICS to other trace gas species like, for example, bromine monoxide, that still can be characterized with a high spatial and temporal resolution (&lt; 1 HZ).&lt;/p&gt;&lt;p&gt;In October 2020, we acquired SO&lt;sub&gt;2&lt;/sub&gt; column density distribution images of Mt Etna volcanic plume with a detection limit of 2x10&lt;sup&gt;17&lt;/sup&gt; molec cm&lt;sup&gt;-2&lt;/sup&gt;, 1 s integration time, 400x400 pixel spatial, and 0.3 Hz temporal resolution.&amp;#160; We compare the SO&lt;sub&gt;2&lt;/sub&gt; fluxes retrieved by IFPICS with simultaneous flux measurements using the mutli-axis DOAS technique.&lt;/p&gt;

scholarly journals Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

2014 ◽  
Vol 11 (23) ◽  
pp. 6827-6840 ◽  
Author(s):  
M. Réjou-Méchain ◽  
H. C. Muller-Landau ◽  
M. Detto ◽  
S. C. Thomas ◽  
T. Le Toan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Variability ◽  
Spatial Scales ◽  
Forest Biomass ◽  
Remote Sensing Data ◽  
Field Measurements ◽  
Forest Degradation ◽  
Forest Carbon ◽  
Mitigation Strategies ◽  
Large Plot

Abstract. Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8–50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mg ha–1) at spatial scales ranging from 5 to 250 m (0.025–6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20–400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial "dilution" bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

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