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1.
Rajdeep Roy K. H. Rao T. Preethi Latha Vinay Kumar Dadhwal V. V. S. S. Sarma P. V. Nagamani S. B. Choudhury Seetharam Pondala 《Journal of the Indian Society of Remote Sensing》2017,45(3):513-524
A phytoplankton bloom was monitored in coastal waters of Bay of Bengal and its influence in water column properties was investigated. Significant draw down of CO2 was noted within the vicinity of the bloom associated with high chlorophyll biomass. Microscopic analysis revealed diatoms as the dominant population. Skeletonema costatum a diatom, reached cell density of 36,898 cells l?1 within the bloom. The lowest surface pCO2 observed was 287 µatm at the southern end of the transect covarying with surface chlorophyll of 1.090 µg l?1. At the northern end the surface pCO2 went as low as 313 µatm. The pCO2 levels below the mixed layer increased twice of that of surface value (~600 µatm). The chlorophyll values observed by Ocean Colour Monitor-2 were modestly related with the in situ measurements. The primary productivity derived from growth rate, assimilation number and maximum surface chlorophyll was 160.6 mg C m?2 day?1 leading to a modest sequestration ~of 0.08 Gg of carbon per day by the surface waters. Our observations reflects the potential role of diatom blooms on coastal carbon dynamics therefore should be carefully monitored in realm of anthropogenic changes. 相似文献
2.
Satellite-based atmospheric CO2 observations have provided a great opportunity to improve our understanding of the global carbon cycle. However, thermal infrared (TIR)-based satellite observations, which are useful for the investigation of vertical distribution and the transport of CO2, have not yet been studied as much as the column amount products derived from shortwave infrared data. In this study, TIR-based satellite CO2 products – from Atmospheric Infrared Sounder, Tropospheric Emission Spectrometer (TES), and Thermal And Near infrared Sensor for carbon Observation – and carbon tracker mole fraction data were compared with in situ Comprehensive Observation Network for Trace gases by AIrLiner (CONTRAIL) data for different locations. The TES CO2 product showed the best agreement with CONTRAIL CO2 data resulting in R2 ~ 0.87 and root-mean-square error ~0.9. The vertical distribution of CO2 derived by TES strongly depends on the geophysical characteristics of an area. Two different climate regions (i.e., southeastern Japan and southeastern Australia) were examined in terms of the vertical distribution and transport of CO2. Results show that while vertical distribution of CO2 around southeastern Japan was mainly controlled by horizontal and vertical winds, horizontal wind might be a major factor to control the CO2 transport around southeastern Australia. In addition, the vertical transport of CO2 also varies by region, which is mainly controlled by anthropogenic CO2, and horizontal and omega winds. This study improves our understanding of vertical distribution and the transport of CO2, both of which vary by region, using TIR-based satellite CO2 observations and meteorological variables. 相似文献
3.
K. L. Webster J. S. Bhatti D. K. Thompson S. A. Nelson C. H. Shaw K. A. Bona S. L. Hayne W. A. Kurz 《Carbon balance and management》2018,13(1):16
Background
Peatlands are an important component of Canada’s landscape, however there is little information on their national-scale net emissions of carbon dioxide [Net Ecosystem Exchange (NEE)] and methane (CH4). This study compiled results for peatland NEE and CH4 emissions from chamber and eddy covariance studies across Canada. The data were summarized by bog, poor fen and rich-intermediate fen categories for the seven major peatland containing terrestrial ecozones (Atlantic Maritime, Mixedwood Plains, Boreal Shield, Boreal Plains, Hudson Plains, Taiga Shield, Taiga Plains) that comprise >?96% of all peatlands nationally. Reports of multiple years of data from a single site were averaged and different microforms (e.g., hummock or hollow) within these peatland types were kept separate. A new peatlands map was created from forest composition and structure information that distinguishes bog from rich and poor fen. National Forest Inventory k-NN forest structure maps, bioclimatic variables (mean diurnal range and seasonality of temperatures) and ground surface slope were used to construct the new map. The Earth Observation for Sustainable Development map of wetlands was used to identify open peatlands with minor tree cover.Results
The new map was combined with averages of observed NEE and CH4 emissions to estimate a growing season integrated NEE (±?SE) at ??108.8 (±?41.3) Mt CO2 season?1 and CH4 emission at 4.1 (±?1.5) Mt CH4 season?1 for the seven ecozones. Converting CH4 to CO2 equivalent (CO2e; Global Warming Potential of 25 over 100 years) resulted in a total net sink of ??7.0 (±?77.6) Mt CO2e season?1 for Canada. Boreal Plains peatlands contributed most to the NEE sink due to high CO2 uptake rates and large peatland areas, while Boreal Shield peatlands contributed most to CH4 emissions due to moderate emission rates and large peatland areas. Assuming a winter CO2 emission of 0.9 g CO2 m?2 day?1 creates an annual CO2 source (24.2 Mt CO2 year?1) and assuming a winter CH4 emission of 7 mg CH4 m?2 day?1 inflates the total net source to 151.8 Mt CO2e year?1.Conclusions
This analysis improves upon previous basic, aspatial estimates and discusses the potential sources of the high uncertainty in spatially integrated fluxes, indicating a need for continued monitoring and refined maps of peatland distribution for national carbon and greenhouse gas flux estimation.4.
Prasun K. Gangopadhyay Freek van der Meer Paul van Dijk 《International Journal of Applied Earth Observation and Geoinformation》2009
Over the time-scale, earth's atmospheric CO2 concentration has varied and that is mostly determined by balance among the geochemical processes including burial of organic carbon in sediments, silicate rock weathering and volcanic activity. The best recorded atmospheric CO2 variability is derived from Vostok ice core that records last four glacial/interglacial cycles. The present CO2 concentration of earth's atmosphere has exceeded far that it was predicted from the ice core data. Other than rapid industrialization and urbanization since last century, geo-natural hazards such as volcanic activity, leakage from hydrocarbon reservoirs and spontaneous combustion of coal contribute a considerable amount of CO2 to the atmosphere. Spontaneous combustion of coal is common occurrence in most coal producing countries and sometimes it could be in an enormous scale. Remote sensing has already proved to be a significant tool in coalfire identification and monitoring studies. However, coalfire related CO2 quantification from remote sensing data has not endeavoured yet by scientific communities because of low spectral resolution of commercially available remote sensing data and relatively sparse CO2 plume than other geological hazards like volcanic activity. The present research has attempted two methods to identify the CO2 flux emitted from coalfires in a coalmining region in north China. Firstly, a band rationing method was used for column atmospheric retrieval of CO2 and secondly atmospheric models were simulated in fast atmospheric signature code (FASCOD) to understand the local radiation transport and then the model was implemented with the inputs from hyperspectral remote sensing data. It was observed that retrieval of columnar abundance of CO2 with the band rationing method is faster as less simulation required in FASCOD. Alternatively, the inversion model could retrieve CO2 concentration from a (certain) source because it excludes the uncertainties in the higher altitude. 相似文献
5.
Collins O. Oduor Nancy Karanja Richard Onwong’a Stephen Mureithi David Pelster Gert Nyberg 《Carbon balance and management》2018,13(1):24
Background
Pasture enclosures play an important role in rehabilitating the degraded soils and vegetation, and may also influence the emission of key greenhouse gasses (GHGs) from the soil. However, no study in East Africa and in Kenya has conducted direct measurements of GHG fluxes following the restoration of degraded communal grazing lands through the establishment of pasture enclosures. A field experiment was conducted in northwestern Kenya to measure the emission of CO2, CH4 and N2O from soil under two pasture restoration systems; grazing dominated enclosure (GDE) and contractual grazing enclosure (CGE), and in the adjacent open grazing rangeland (OGR) as control. Herbaceous vegetation cover, biomass production, and surface (0–10 cm) soil organic carbon (SOC) were also assessed to determine their relationship with the GHG flux rate.Results
Vegetation cover was higher enclosure systems and ranged from 20.7% in OGR to 40.2% in GDE while aboveground biomass increased from 72.0 kg DM ha?1 in OGR to 483.1 and 560.4 kg DM ha?1 in CGE and GDE respectively. The SOC concentration in GDE and CGE increased by an average of 27% relative to OGR and ranged between 4.4 g kg?1 and 6.6 g kg?1. The mean emission rates across the grazing systems were 18.6 μg N m?2 h?1, 50.1 μg C m?2 h?1 and 199.7 mg C m?2 h?1 for N2O, CH4, and CO2, respectively. Soil CO2 emission was considerably higher in GDE and CGE systems than in OGR (P?<?0.001). However, non-significantly higher CH4 and N2O emissions were observed in GDE and CGE compared to OGR (P?=?0.33 and 0.53 for CH4 and N2O, respectively). Soil moisture exhibited a significant positive relationship with CO2, CH4, and N2O, implying that it is the key factor influencing the flux rate of GHGs in the area.Conclusions
The results demonstrated that the establishment of enclosures in tropical rangelands is a valuable intervention for improving pasture production and restoration of surface soil properties. However, a long-term study is required to evaluate the patterns in annual CO2, N2O, CH4 fluxes from soils and determine the ecosystem carbon balance across the pastoral landscape.6.
7.
Zhe Yang Shuli Song Wenhai Jiao Guangming Chen Junchen Xue Weili Zhou Wenyao Zhu 《GPS Solutions》2017,21(2):363-375
This study carries out a quantitative analysis of the performance of ionospheric tomography in the topside ionosphere, utilizing data of October 2011 collected from 260 Global Navigation Satellite System (GNSS) stations in the Crustal Movement Observation Network of China. This tomographic reconstruction with a resolution of 2° in latitude, 2° in longitude and 20 km in altitude has more than 70 % of voxels traversed by GPS raypaths and is able to provide reliable bottom parts of ionospheric profiles. Compared with the observations measured by the Defense Meteorological Satellite Program (DMSP) satellites (F16, F17 and F18) at an altitude of 830–880 km, the results show that there is an overestimation in the reconstructed plasma density at the DMSP altitude, and the reconstruction is better during daytime than nighttime. In addition, the reconstruction at nighttime also indicates a solar activity and latitudinal dependence. In summary, with respect to DMSP measurements, the daytime bias is on average from ?0.32 × 105/cm3 to ?0.28 × 105/cm3, while the nighttime bias is between ?0.37 × 105/cm3 and ?0.24 × 105/cm3, and the standard deviation at daytime and at nighttime is, respectively, 0.082 × 105/cm3 to 0.244 × 105/cm3 and 0.086 × 105/cm3 to 0.428 × 105/cm3. This study suggests that vertical ionospheric profiles from other sources, such as ionosondes or GNSS occultation satellites, should be incorporated into ground-based GNSS topside tomographic studies. 相似文献
8.
ABSTRACTWidespread forest fire events occurred in the foothills of North Western Himalaya during 24 April to 2 May 2016 (Event-1) and 20–30 May 2018 (Event-2). Their impacts were investigated on the distribution of pollutant gases ozone (O3), carbon monoxide (CO), and oxides of nitrogen (NOx) over Uttarakhand using simulations of Weather Research and Forecasting model coupled with chemistry (WRF-Chem) and in-situ observations of these gases over Dehradun, the capital of Uttarakhand. During Event-1, the observed CO mixing ratio over Dehradun increased from 25 April 2016 onwards, attained maximum (705.8 ± 258 ppbv) on 2 May 2016 and subsequently decreased. The rate of increase of daily baseline CO was 29 ppbv/day during HFAP (High Fire Activity Period). During Event-2, daily average concentrations of CO, O3, and NOx showed systematic increase over Dehradun during HFAP period. The rate of increase of CO was 9 ppbv/day, while it was very small for NOx and O3. To quantitatively estimate the influence of forest fire emissions, two WRF-Chem simulations were made: one with biomass burning (BB) emissions and other without BB emissions. These simulations showed 52% (34%) enhancement in CO, 52% (32%) enhancement in NOx, and 11% (9%) enhancement in O3 during HFAP for Event-1 (Event-2). A clear positive correlation (r = 0.89 for Event-1, r = 0.69 for Event-2) was found between ?O3 (O3with BB minus O3without BB) and ?CO (COwith BB minus COwithout BB), indicating rapid production of ozone in the fire plumes. For both the events, the vertical distribution of ?O3, ?CO, and ?NOx showed that forest fire emissions influenced the air quality upto 6.5 km altitude. Peaks in ?O3, ?CO, and ?NOx during different days suggested the role of varying dispersion and horizontal mixing of fire plumes. 相似文献
9.
High-data dimensionality is a common problem in hyperspectral data processing. Consequently, remote sensing techniques that reduce the number of bands are considered essential tools for most hyperspectral applications. The aim of this study was to examine the utility of the random forest ensemble to select the optimal subset of hyperspectral bands to predict the age of Pinus patula stands. Airborne AISA Eagle hyperspectral image data were collected over the study area. The random forest ensemble was used to test whether the forward or backward variable selection methods could identify the optimal subset of bands. Results indicate that both the selection methods produced high-predictive accuracies (root mean square error = 3.097 years). However, the backward variable selection method utilized 206 bands for the final model, while the forward variable selection utilized only a small subset of non-redundant bands (n = 9) while preserving the highest model accuracy (R 2 = 0.6). 相似文献
10.
P. C. Padhy R. K. Nayak V. K. Dadhwal M. Salim D. Mitra S. B. Chaudhury P. R. Rao K. H. Rao C.B. S. Dutt 《Journal of the Indian Society of Remote Sensing》2016,44(1):135-143
An empirical model is developed and used with remotely sensed predictors: sea surface temperature (SST) and chlorophyll-a concentration (Chl-a), to compute surface water partial pressure of carbon dioxide (pCO2w) and air-sea fluxes of CO2 in the Hooghly estuary and its adjacent coastal oceans. In situ observations used here were based on measurements carried out in this region during winter and summer periods in 2008. The estimated pCO2w compares well with the in situ observations at root mean square error ±18 μatm. In winter, estimated pCO2w ranges between 320 and 500 μatm with large values (>400 μatm) on the south-western and south-eastern flanks of the coastal domain and lower values (340–375 μatm) on the main-channel. In summer, it remained spatially uniform at 450 μatm. Extrapolation of the results over the study region based on the Moderate Imaging Specroradiometer (MODIS) measured SST and Chl-a suggests that the region is a strong source of atmospheric CO2 during the summer with net release of 0.095 Tg C year?1 (equivalent to mean flux of 90 molC m?2 year?1) and is a weak source during the winter with net release of 0.006 Tg C yr?1 (0.5 molC m?2 year?1) from the geographical extent of 6000 Km2 area. 相似文献
11.
This study integrates the RUSLE, remote sensing and GIS to assess soil loss and identify sensitive areas to soil erosion in the Nilufer creek watershed in Bursa province, Turkey. The annual average soil loss was generated separately for years 1984 and 2011, in order to expose possible soil loss differences occurred in 27 years. In addition, sediment accumulation and sediment yield of the studied watershed was also predicted and discussed. The results indicated that very severe erosion risk areas in 1984 was 13.4% of the area, but it was increased to 15.3% by the year 2011, which needs immediate attention from soil conservation point of view. Furthermore, the estimated annual sediment yield of the Nilufer creek watershed was increased from 903 to 979 Mg km?2 y?1 in 27 years period. The study also provides useful information for decision-makers and planners to take appropriate land management practices in the area. 相似文献
12.
Christopher Potter Steven Klooster Robert Crabtree Shengli Huang Peggy Gross Vanessa Genovese 《Carbon balance and management》2011,6(1):1-16
Background
A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades.Results
Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr-1 (1 Tg = 1012 g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO2 on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO2 to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr-1 for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas.Conclusions
Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape. 相似文献13.
Evapotranspiration (ET) is a vital process in land surface atmosphere research. In this study, Surface Energy Balance Algorithm for Land (SEBAL) for the assessment of ET (for 23 December 2010, 8 January 2011, 24 January 2011, 9 February 2011, 25 February 2011, 29 March 2011 and 14 April 2011) from LANDSAT7-ETM+ and validation with Lysimeter data set is illustrated. It is based on the evaporative fraction concept, and it has been applied to LANDSAT7-ETM + (30 m resolution) data acquired over the Indian Agricultural Research Institute’s agricultural farm land. The ET from SEBAL was compared with Lysimeter ET using four statistical tests (root-mean-square error (RMSE), relative root-mean-square error (R-RMSE), mean absolute error (MAE), and normalized root-mean square error (NRMSE)), and each test showed a good correlation between the predicted and observed ET values. Results from this study revealed that the RMSE of crop-growing period was 0.51 mm d?1 for ETSEBAL, i.e. ETSEBAL having good accuracy with respect to observed ETLysimeter. Results were also validated using R-RMSE test, which also proved that ETSEBAL data are having good accuracy with respect to observed ETLysimeter as R-RMSE of crop-growing period is 0.19 mm d?1. MAE (0.19), NRMSE (0.21) and r2 (0.91) tests indicated that model prediction is significant, and model can be effectively used for the estimation of ET from SEBAL as input of remote sensing data sets. Finally, the SEBAL has been useful for remote agricultural land where ground-based data (Lysimeter data) are not available for daily ET (ET24 h) estimation. The temporal study of the ET24 h values analysed has revealed that the highest ET24 h values are owing to the higher development (high greenness) of crops, whereas the lower values are related to the lower development (low greenness) or null crop. 相似文献
14.
Background
To address how natural disturbance, forest harvest, and deforestation from reservoir creation affect landscape-level carbon (C) budgets, a retrospective C budget for the 8500 ha Sooke Lake Watershed (SLW) from 1911 to 2012 was developed using historical spatial inventory and disturbance data. To simulate forest C dynamics, data was input into a spatially-explicit version of the Carbon Budget Model-Canadian Forest Sector (CBM-CFS3). Transfers of terrestrial C to inland aquatic environments need to be considered to better capture the watershed scale C balance. Using dissolved organic C (DOC) and stream flow measurements from three SLW catchments, DOC load into the reservoir was derived for a 17-year period. C stocks and stock changes between a baseline and two alternative management scenarios were compared to understand the relative impact of successive reservoir expansions and sustained harvest activity over the 100-year period.Results
Dissolved organic C flux for the three catchments ranged from 0.017 to 0.057 Mg C ha?1 year?1. Constraining CBM-CFS3 to observed DOC loads required parameterization of humified soil C losses of 2.5, 5.5, and 6.5%. Scaled to the watershed and assuming none of the exported terrestrial DOC was respired to CO2, we hypothesize that over 100 years up to 30,657 Mg C may have been available for sequestration in sediment. By 2012, deforestation due to reservoir creation/expansion resulted in the watershed forest lands sequestering 14 Mg C ha?1 less than without reservoir expansion. Sustained harvest activity had a substantially greater impact, reducing forest C stores by 93 Mg C ha?1 by 2012. However approximately half of the C exported as merchantable wood during logging (~176,000 Mg C) may remain in harvested wood products, reducing the cumulative impact of forestry activity from 93 to 71 Mg C ha?1.Conclusions
Dissolved organic C flux from temperate forest ecosystems is a small but persistent C flux which may have long term implications for C storage in inland aquatic systems. This is a first step integrating fluvial transport of C into a forest carbon model by parameterizing DOC flux from soil C pools. While deforestation related to successive reservoir expansions did impact the watershed-scale C budget, over multi-decadal time periods, sustained harvest activity was more influential.15.
Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models 总被引：1，自引：0，他引：1
This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detections indicated that three major changes were predicted from 2004 to 2016 (a period of 12 years): (1) forest cover and open area significantly decreased at rates of almost 30 and 8 km2, respectively; (2) cultivated land and oil palm have shown an increment in sizes at rates of 25.02 and 5.77 km2, respectively; and, (3) settlement and Urbanization has intensified also by almost 5 km2. Soil erosion risk analysis results also showed that the Semenyih basin exhibited an average annual soil erosion between 143.35 ton ha?1 year?1 in 2004 and 151 in 2010, followed by the expected 162.24 ton ha?1 year?1. These results indicated that Semenyih is prone to water erosion by 2016. The wide range of erosion classes were estimated at a very low level (0–1 t/ha/year) and mainly located on steep lands and forest areas. This study has shown that using both LTM and USLE in combination with remote sensing and GIS is a suitable method for forecasting LC and accurately measuring the amount of soil losses in the future. 相似文献
16.
17.
Land surface temperature (LST) is an important aspect in global to regional change studies, for control of climate change and balancing of high temperature. Urbanization is one of the influencing factors increasing land surface and atmospheric temperature, by the emission of greenhouse gases (e.g. CO2, NO and methane). In the present study, LST was derived from Landsat-8 of multitemporal data sets to analyse the spatial structure of the urban thermal environment in relation to the urban surface characteristics and land use–land cover (LULC). LST is influenced by the greenhouse gases i.e. CO2 plays an important role in increasing the earth’s surface temperature. In order to provide the evidence of influence of CO2 on LST, the relationship between LST, air temperature and CO2 was analysed. Landsat-8 satellite has two thermal bands, 10 and 11. These bands were used to accurately to calculate the temperature over the study area. Results showed that the strength of correlation between ground monitoring data and satellite data was high. Based on correlation values of each month April (R2 = 0.994), May (R2 = 0.297) and June (R2 = 0.934), observed results show that band 10 was significantly correlating with air temperature. Relationship between LST and CO2 levels were obtained from linear regression analysis. band 11 was correlating significantly with CO2 values in each of the months April (R2 = 0.217), May (R2 = 0.914) and June, (R2 = 0.934), because band 11 is closer to the 15-micron band of CO2. From the results, it was observed that band 10 can be used for calculating air temperature and band 11 can be used for estimation of greenhouse gases. 相似文献
18.
Background
Forest landscape restoration (FLR) has been adopted by governments and practitioners across the globe to mitigate and adapt to climate change and restore ecological functions across degraded landscapes. However, the extent to which these activities capture CO2 with associated climate mitigation impacts are poorly known, especially in geographies where data on biomass growth of restored forests are limited or do not exist. To fill this gap, we developed biomass accumulation rates for a set of FLR activities (natural regeneration, planted forests and woodlots, agroforestry, and mangrove restoration) across the globe and global CO2 removal rates with corresponding confidence intervals, grouped by FLR activity and region/climate.Results
Planted forests and woodlots were found to have the highest CO2 removal rates, ranging from 4.5 to 40.7 t CO2 ha?1 year?1 during the first 20 years of growth. Mangrove tree restoration was the second most efficient FLR at removing CO2, with growth rates up to 23.1 t CO2 ha?1 year?1 the first 20 years post restoration. Natural regeneration removal rates were 9.1–18.8 t CO2 ha?1 year?1 during the first 20 years of forest regeneration, followed by agroforestry, the FLR category with the lowest and regionally broad removal rates (10.8–15.6 t CO2 ha?1 year?1). Biomass growth data was most abundant and widely distributed across the world for planted forests and natural regeneration, representing 45% and 32% of all the data points assessed, respectively. Agroforestry studies, were only found in Africa, Asia, and the Latin America and Caribbean regions.Conclusion
This study represents the most comprehensive review of published literature on tree growth and CO2 removals to date, which we operationalized by constructing removal rates for specific FLR activities across the globe. These rates can easily be applied by practitioners and decision-makers seeking to better understand the positive climate mitigation impacts of existing or planned FLR actions, or by countries making restoration pledges under the Bonn Challenge Commitments or fulfilling Nationally Determined Contributions to the UNFCCC, thereby helping boost FLR efforts world-wide.19.
Winter wheat biomass estimation using high temporal and spatial resolution satellite data combined with a light use efficiency model 总被引：1，自引：0，他引：1
Winter wheat biomass was estimated using HJ CCD and MODIS data, combined with a radiation use efficiency model. Results were validated with ground measurement data. Winter wheat biomass estimated with HJ CCD data correlated well with observed biomass in different experiments (coefficients of determination R2 of 0.507, 0.556 and 0.499; n?=?48). In addition, R2 values between MODIS estimated and observed biomass are 0.420, 0.502 and 0.633. Even if we downscaled biomass estimated using HJ CCD data to MODIS pixel size (9?×?9 HJ CCD pixels to approximate that MODIS pixel), R2 values between estimated and observed biomass were still higher than those from MODIS. We conclude that estimation with remote sensing data, such as the HJ CCD data with high spatial resolution and shorter revisit cycle, can show more detail in spatial pattern and improve the application of remote sensing on a local scale. There is also potential for applying the approach to many other studies, including agricultural production estimation, crop growth monitoring and agricultural ecosystem carbon cycle studies. 相似文献
20.
Digital elevation model (DEM) data of Shuttle Radar Topography Mission (SRTM) are distributed at a horizontal resolution of 90 m (30 m only for US) for the world, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM data provide 30 m horizontal resolution, while CARTOSAT-1 (IRS-P5) gives 2.6 m horizontal resolution for global coverage. SRTM and ASTER data are available freely but 2.6 m CARTOSAT-1 data are costly. Hence, through this study, we found out a horizontal accuracy for selected ground control points (GCPs) from SRTM and ASTER with respect to CARTOSAT-1 DEM to implement this result (observed from horizontal accuracy) for those areas where the 2.6-m horizontal resolution data are not available. In addition to this, the present study helps in providing a benchmark against which the future DEM products (with horizontal resolution less than CARTOSAT-1) with respect to CARTOSAT-1 DEM can be evaluated. The original SRTM image contained voids that were represented digitally as ?140; such voids were initially filled using the measured values of elevation for obtaining accurate DEM. Horizontal accuracy analysis between SRTM- and ASTER-derived DEMs with respect to CARTOSAT-1 (IRS-P5) DEM allowed a qualitative assessment of the horizontal component of the error, and the appropriable statistical measures were used to estimate their horizontal accuracies. The horizontal accuracy for ASTER and SRTM DEM with respect to CARTOSAT-1 were evaluated using the root mean square error (RMSE) and relative root mean square error (R-RMSE). The results from this study revealed that the average RMSE of 20 selected GCPs was 2.17 for SRTM and 2.817 for ASTER, which are also validated using R-RMSE test which proves that SRTM data have good horizontal accuracy than ASTER with respect to CARTOSAT-1 because the average R-RMSE of 20 GCPs was 3.7 × 10?4 and 5.3 × 10?4 for SRTM and ASTER, respectively. 相似文献