Improving the Accuracy of Vegetation Index Retrieval for Biomass by Combining Ground-UAV Hyperspectral Data-A New Method for Inner Mongolia Typical Grasslands

Grassland biomass is an important parameter of grassland ecosystems.The complexity of the grassland canopy vegetation spectrum makes the long-term assessment of grassland growth a challenge.Few studies have explored the original spectral information of typical grasslands in Inner Mongolia and examined the influence of spectral information on aboveground biomass(AGB)estimation.In order to improve the accuracy of vegetation index inversion of grassland AGB,this study combined ground and Unmanned Aerial Vehicle(UAV)remote sensing technology and screened sensitive bands through ground hyperspectral data transformation and correlation analysis.The narrow band vegetation indices were calculated,and ground and airborne hyperspectral inversion models were established.Finally,the accuracy of the model was verified.The results showed that:(1)The vegetation indices constructed based on the ASD FieldSpec 4 and the UAV were significantly correlated with the dry and fresh weight of AGB.(2)The comparison between measured R^(2) with the prediction R^(2) indicated that the accuracy of the model was the best when using the Soil-Adjusted Vegetation Index(SAVI)as the independent variable in the analysis of AGB(fresh weight/dry weight)and four narrow-band vegetation indices.The SAVI vegetation index showed better applicability for biomass monitoring in typical grassland areas of Inner Mongolia.(3)The obtained ground and airborne hyperspectral data with the optimal vegetation index suggested that the dry weight of AGB has the best fitting effect with airborne hyperspectral data,where y=17.962e^(4.672x),the fitting R^(2) was 0.542,the prediction R^(2)was 0.424,and RMSE and REE were 57.03 and 0.65,respectively.Therefore,established vegetation indices by screening sensitive bands through hyperspectral feature analysis can significantly improve the inversion accuracy of typical grassland biomass in Inner Mongolia.Compared with ground monitoring,airborne hyperspectral monitoring better reflects the inversion of actual surface biomass.It provides a reliable modeling framework for grassland AGB monitoring and scientific and technological support for grazing management.

Estimating aboveground biomass in Mu Us Sandy Land using Landsat spectral derived vegetation indices over the past 30 years

Remote sensing is a valuable and effective tool for monitoring and estimating aboveground biomass （AGB） in large areas.The current international research on biomass estimation by remote sensing technique mainly focused on forests,grasslands and crops,with relatively few applications for desert ecosystems.In this paper,Landsat Thematic Mapper （TM）/Enhanced Thematic Mapper Plus （ETM＋） images from 1988 to 2007 and the data of 283 AGB samples in August 2007 were used to estimate the AGB for Mu Us Sandy Land over the past 30 years.Moreover,temporal and spatial distribution characteristics of AGB and influencing factors of climate and underlying surface were also studied.Results show that：（1） Differences of correlations exist in the fitted equations between AGB and different vegetation indices in desert areas.The modified soil adjusted vegetation index （MSAVI） and soil adjusted vegetation index （SAVI） show relatively higher correlations with AGB,while the correlation between normalized difference vegetation index （NDVI） and AGB is relatively lower.Error testing shows that the AGB-MSAVI model established can be used to accurately estimate AGB of Mu Us Sandy Land in August.（2） AGB in Mu Us Sandy Land shows the fluctuant characteristics over the past 30 years,which decreased from the 1980s to the 1990s,and increased from the 1990s to 2007.AGB in 2007 had the highest value,with a total AGB of 3.352×106 t.Moreover,in the 1990s,AGB had the lowest value with a total AGB of 2.328×106 t.（3） AGB with relatively higher values was mainly located in the middle and southern parts of Mu Us Sandy Land in the 1980s.AGB was low in the whole area in the1990s,and relatively higher AGB values were mainly located in the southern parts of Uxin.In 2007,AGB in the whole area was relatively higher than those of the last twenty years,and higher AGB values were mainly located in the northern,western and middle parts of Mu Us Sandy Land.

Distribution patterns of vegetation biomass and nutrients bio-cycle in alpine tundra ecosystem on Changbai Mountains,Northeast China

A study was conducted to test the correlation between biomass and elevation and the differences in concentration and storks of nutrients among five vegetation types （Felsenmeer alpine tundra vegetation-FA, Lithic alpine tundra vegetation-LA, Typical alpine tundra vegetation-TA, Meadow alpine tundra vegetation-MA, and Swamp alpine tundra vegetation-SA） on alpine tundra of Changbai Mountains, Jilin Province, China in growing seasons of 2003, 2004 and 2005. The biomass of 43 mono-species and soil nutrients in alpine tundra ecosystem were also investigated. Dominant species from Ericaceae （such as Rhododendron chrysanthum and Vaccinium jliginosum var. alpinum） were taken to analyze organ biomass distribution. Result showed that the biomass and elevation had a significant correlation （Biomass-237.3 in（Elevation） ＋494.36; R^2=0.8092; P〈0.05）. No significant differences were found in phosphorus and sulphur concentrations of roots, stems and leaves among the five vegetation types. There were significant differences in nitrogen and phosphorus stocks of roots, stems and leaves and in sulphur stock of stems and leaves among TA, MA, and SA vegetation types （p〈0.05）. The nutrient stock of five vegetations was averagely 72.46 kg.hm^-2, of which N, P, S were 48.55, 10.33 and 13.61 kg·hm^-2, respectively. Soil N and S concentrations in meadow alpine tundra soil type was significantly higher than those in other four soil types （Cold desert alpine tundra soil, Lithic alpine tundra soil, Peat alpine tundra soil, and Gray alpine tundra soil）. Phosphorous concentration in SA type was higher （p〈0.05） than in other types. Soil nutrient stock （0-20cm） was averagely 39.59 t.hm^-2, of which N, P, S were 23.74, 5.86, 9.99 t·hm^-2, respectively.

Study on the Surface Soil Micro-biomass Carbon of Kinds of Vegetation Types in Dagu Estuary Wetland

A field experiment was carried out to explore surface soil mircro-biomass carbon （MBC）. The results showed that the difference of soil MBC was significant among three vegetation types in five sample spots in July. The order of surface soil MBC was： Aquaculture pond reed （sample 2）〉 reed of river bank （sample 5）〉 sea- plant（sample 5）〉 river flat（sample 4）〉 The alkaline（sample 1）. There is a very sig- nificant correlation among the soil MBC, the water content of soil and the content of organic matter. Among wetland plants, reed is kind of plant content of high ground biomass and below-ground biomass,especially the MBC planted in wetland is high- er, which shows that compared with common plants, reed is more conducive to the accumulation of soil MBC and has an important effect to wetland protecting and re- covery of function of ecosystem.

Deep neural network algorithm for estimating maize biomass based on simulated Sentinel 2A vegetation indices and leaf area index

Accurate estimation of biomass is necessary for evaluating crop growth and predicting crop yield.Biomass is also a key trait in increasing grain yield by crop breeding.The aims of this study were(i)to identify the best vegetation indices for estimating maize biomass,(ii)to investigate the relationship between biomass and leaf area index(LAI)at several growth stages,and(iii)to evaluate a biomass model using measured vegetation indices or simulated vegetation indices of Sentinel 2A and LAI using a deep neural network(DNN)algorithm.The results showed that biomass was associated with all vegetation indices.The three-band water index(TBWI)was the best vegetation index for estimating biomass and the corresponding R2,RMSE,and RRMSE were 0.76,2.84 t ha−1,and 38.22%respectively.LAI was highly correlated with biomass(R2=0.89,RMSE=2.27 t ha−1,and RRMSE=30.55%).Estimated biomass based on 15 hyperspectral vegetation indices was in a high agreement with measured biomass using the DNN algorithm(R2=0.83,RMSE=1.96 t ha−1,and RRMSE=26.43%).Biomass estimation accuracy was further increased when LAI was combined with the 15 vegetation indices(R2=0.91,RMSE=1.49 t ha−1,and RRMSE=20.05%).Relationships between the hyperspectral vegetation indices and biomass differed from relationships between simulated Sentinel 2A vegetation indices and biomass.Biomass estimation from the hyperspectral vegetation indices was more accurate than that from the simulated Sentinel 2A vegetation indices(R2=0.87,RMSE=1.84 t ha−1,and RRMSE=24.76%).The DNN algorithm was effective in improving the estimation accuracy of biomass.It provides a guideline for estimating biomass of maize using remote sensing technology and the DNN algorithm in this region.

Wetland vegetation biomass estimation and mapping from Landsat ETM data: a case study of Poyang Lake

Poyang Lake is the largest freshwater lake in China. This paper conducted a digital and rapid investigation of the lake’s wetland vegetation biomass using Landsat ETM data acquired on April 16, 2000. First, utilizing the false color composite derived from the ETM data as one of the main references, the authors designed a reasonable sampling route for field measurement of the biomass, and carried it out on April 18–28, 2000. Then after both the sampling data and the ETM data were geometrically corrected to an equal-area projection of Albers, linear relationships among the sampling data and some transformed data derived from the ETM data and the ETM 4 were calculated. The results show that the sampling data is best relative to the band 4 data with a high correlation coefficient of 0.86, followed by the DVI and NDVI data with 0.83 and 0.80 respectively. Therefore, a linear regression model, which was based on the field data and band 4 data, was used to estimate the total biomass of entire Poyang Lake, and then the map of the biomass distribution was compiled.

The Response of Vegetation Biomass to Soil Properties along Degradation Gradients of Alpine Meadow at Zoige Plateau

Alpine grassland of the Tibetan Plateau has undergone severe degradation, even desertification. However, several questions remain to be answered, especially the response mechanisms of vegetation biomass to soil properties. In this study, an experiment on degradation gradients was conducted in an alpine meadow at the Zoige Plateau in 2017. Both vegetation characteristics and soil properties were observed during the peak season of plant growth. The classification and regression tree model(CART) and structural equation modelling(SEM) were applied to screen the main factors that govern the vegetation dynamics and explore the interaction of these screened factors. Both aboveground biomass(AGB) and belowground biomass(BGB) experienced a remarkable decrease along the degradation gradients. All soil properties experienced significant variations along the degradation gradients at the 0.05 significance level. Soil physical and chemical properties explained 54.78% of the variation in vegetation biomass along the degradation gradients. AGB was mainly influenced by soil water content(SWC), soil bulk density(SBD), soil organic carbon(SOC), soil total nitrogen(STN), and pH. Soil available nitrogen(SAN), SOC and p H, had significant influence on BGB. Most soil properties had positive effects on AGB and BGB, while SBD and p H had a slightly negative effect on AGB and BGB. The correlations of SWC with AGB and BGB were relatively less significant than those of other soil properties. Our results highlighted that the soil properties played important roles in regulating vegetation dynamics along the degradation gradients and that SWC is not the main factor limiting plant growth in the humid Zoige region. Our results can provide guidance for the restoration and improvement of degraded alpine grasslands on the Tibetan Plateau.

Different Responses of Vegetation to Frozen Ground Degradation in the Source Region of the Yellow River from 1980 to 2018

Frozen ground degradation under a warming climate profoundly influences the growth of alpine vegetation in the source region of the Qinghai-Tibet Plateau.This study investigated spatiotemporal variations in the frozen ground distribution,the active layer thickness(ALT)of permafrost(PF)soil and the soil freeze depth(SFD)in seasonally frozen soil from 1980 to 2018 using the temperature at the top of permafrost(TTOP)model and Stefan equation.We compared the effects of these variations on vegetation growth among different frozen ground types and vegetation types in the source region of the Yellow River(SRYR).The results showed that approximately half of the PF area(20.37%of the SRYR)was projected to degrade into seasonally frozen ground(SFG)during the past four decades;furthermore,the areal average ALT increased by 3.47 cm/yr,and the areal average SFD decreased by 0.93 cm/yr from 1980 to 2018.Accordingly,the growing season Normalized Difference Vegetation Index(NDVI)presented an increasing trend of 0.002/10 yr,and the increase rate and proportion of areas with NDVI increase were largest in the transition zone where PF degraded to SFG(the PF to SFG zone).A correlation analysis indicated that variations in ALT and SFD in the SRYR were significantly correlated with increases of NDVI in the growing season.However,a rapid decrease in SFD(<-1.4 cm/10 yr)could have reduced the soil moisture and,thus,decreased the NDVI.The NDVI for most vegetation types exhibited a significant positive correlation with ALT and a negative correlation with SFD.However,the steppe NDVI exhibited a significant negative correlation with the SFD in the PF to SFG zone but a positive correlation in the SFG zone,which was mainly limited by water condition because of different change rates of the SFD.

Biomass accumulation and organic carbon stocks of Kandelia obovata mangrove vegetation under different simulated sea levels

Mangrove forests are vulnerably threatened by sea level rise(SLR).Vegetation organic carbon(OC)stocks are important for mangrove ecosystem carbon cycle.It is critical to understand how SLR affects vegetation OC stocks for evaluating mangrove blue carbon budget and global climate change.In this study,biomass accumulation and OC stocks of mangrove vegetation were compared among three 10 year-old Kandelia obovata(a common species in China)mangrove forests under three intertidal elevations through species-specific allometric equations.This study simulated mangrove forests with SLR values of 0 cm,40 cm and 80 cm,respectively,representing for the current,future~100 a and future~200 a SLR of mangrove forests along the Jiulong River Estuary,China.SLR directly decreased mangrove individual density and inhibited the growth of mangrove vegetation.The total vegetation biomasses were(12.86±0.95)kg/m^2,(7.97±0.90)kg/m^2 and(3.89±0.63)kg/m^2 at Sites SLR 0 cm,SLR40 cm and SLR 80 cm,respectively.The total vegetation OC stock decreased by approximately 3.85 kg/m^2(in terms of C)from Site SLR 0 cm to Site SLR 80 cm.Significantly lower vegetation biomass and OC stock of various components(stem,branch,leaf and root)were found at Site SLR 80 cm.Annual increments of vegetation biomass and OC stock also decreased with SLR increase.Moreover,significant lower sedimentation rate was found at Site SLR 80 cm.These indicated that SLR will decrease mangrove vegetation biomass and OC stock,which may reduce global blue carbon sink by mangroves,exacerbate global warming and give positive feedback to SLR.

Seasonal variation in soil microbial biomass carbon and nitrogen in an artificial sand-binding vegetation area in Shapotou, northern China

In this study, seasonal variation characteristics of surface soil microbial biomass carbon （MBC） and soil microbial biomass nitrogen （MBN） of an artificial vegetation area located in Shapotou for different time periods were studied using the chloroform fumigation method, and the results were compared with those of near-natural vegetation areas and mobile dunes. Results showed that the MBC and MBN levels in the 0-5 cm soil layer were higher in autumn than in summer and spring. As the prolongation of vegetation restoration raised the MBC and MBN levels in summer and autumn, no clear variation was found in spring. However, the MBC and MBN in 5-20 cm had no obvious seasonal variation. During summer and autumn, the variation trend of MBC and MBN in the vertical direction was shown to be 0-5 〉 5-10 〉 10-20 cm in the vegetation area, while for mobile dunes, the MBC and MBN levels increased as the depth increased. The natural vegetation area was shown to possess the highest MBC and MBN levels, and yet mobile dunes have the lowest MBC and MBN levels. MBC and MBN levels in artificial sand-binding vegetation increased with the prolongation of vegetation restoration, indicating that the succession of sand-binding vegetation will result in the ac- cumulation of soil carbon and nitrogen, as well as the restoration of soil fertility.

Quantification of Above-Ground Biomass and Carbon Sequestration Potential of Roadside Trees in the Plateau Department of Benin Republic

Roadside trees are effective natural solutions for mitigating climate change. Despite the usefulness of trees to carbon sequestration, there is a dearth of information on the estimation of biomass and carbon stock for roadside trees in the study area. This study aimed to estimate the carbon stock and carbon dioxide equivalent of roadside trees. A complete enumeration of trees was carried out in Kétou, Pobè and Sakété within the communes of the Plateau Department, Bénin Republic. Total height and diameter at breast height were measured from trees along the roads while individual wood density value was obtained from wood density database. The allometric method of biomass estimation was adopted for the research. The results showed that the total estimations for above-ground biomass, carbon stock and carbon equivalent from all the enumerated roadside trees were 154.53 mt, 72.63 mt and 266.55 mt, respectively. The results imply that the roadside trees contain a substantial amount of carbon stock that can contribute to climate change mitigation through carbon sequestration.

Advanced land observing satellite data to identify ground vegetation in a juniper forest,northeast Iran

Juniperus excelsa subsp.polycarpos,(Persian juniper),is found in northeast Iran.In this study,the relationship between ground cover and vegetation indices have been investigated using remote sensing data for a Persian juniper forest.Multispectral data were analyzed based on the Advanced Visible and Near Infrared Radiometer type 2 and panchromatic data obtained by the Panchromatic Remote-sensing Instrument for Stereo Mapping sensors,both on board the advanced land observing satellite(ALOS).The ground cover was calculated using field survey data from 25 sub-sample plots and the vegetation indices were derived with 595 maximum filtering algorithm from ALOS data.R2 values were calculated for the normalized difference vegetation index(NDVI)and various soil-adjusted vegetation indices(SAVI)with soilbrightness-dependent correction factors equal to 1 and 0.5,a modified SAVI(MSAVI)and an optimized SAVI(OSAVI).R2 values for the NDVI,MSAVI,OSAVI,SAVI(1),and SAVI(0.5)were 0.566,0.545,0.619,0.603,and 0.607,respectively.Total ratio vegetation index for arid and semi-arid regions based on spectral wavelengths of ALOS data with an R2 value 0.633 was considered.Results of the current study will be useful for forest inventories in arid and semi-arid regions in addition to assisting decisionmaking for natural resource managers.

Effect of Different Vegetation Systems on Soil Erosion and Soil Nutrients in Red Soil Region of Southeastern China

The effect of different vegetation systems including bamboo plantation (BP), forest ecosystem (CF),citrus orchard (Ctr) and farmland (FL) on erosion and nutrients of red soil were investigated in hilly region of southeastern China to find effective control measures for soil erosion. The results showed that all the vegetation systems could significantly reduce soil erosion and nutrient losses compared to bare land (Br).The ability of different vegetation systems to conserve soil and water was in the order of Ctr ＞ BP ＞ CF ＞ FL ＞ Br. Vegetation could also improve soil fertility. The soil organic matter, total N and total P contents were much higher in all the vegetation systems than in bare land, especially for the top soils. Vegetation systems improved soil physical properties remarkably. Compared to the bare land, soil organic matter, TP,TK and available K, especially soil microbial biomass C, N and P, increased under all the vegetation covers.However, they were still much lower than expected, thus these biological measurements are still needed to be carried out continuously.

Effect of Different Vegetation Types on the Rhizosphere Soil Microbial Community Structure in the Loess Plateau of China

The Loess Plateau in China is one of the most eroded areas in the world. Accordingly, vegetation restoration has been implemented in this area over the past two decades to remedy the soil degradation problem. Understanding the microbial community structure is essential for the sustainability of ecosystems and for the reclamation of degraded arable land. This study aimed to determine the effect of different vegetation types on microbial processes and community structure in rhizosphere soils in the Loess Plateau. The six vegetation types were as follows：two natural grassland （Artemisia capillaries and Heteropappus altaicus）, two artificial grassland （Astragalus adsurgens and Panicum virgatum）, and two artificial shrubland （Caragana korshinskii and Hippophae rhamnoides） species. The microbial community structure and functional diversity were examined by analyzing the phospholipid fatty acids （PLFAs） and community-level physiological profiles. The results showed that rhizosphere soil sampled from the H. altaicus and A. capillaries plots had the highest values of microbial biomass C, average well color development of carbon resources, Gram-negative （G-） bacterial PLFA, bacterial PLFA, total PLFA, Shannon richness, and Shannon evenness, as well as the lowest metabolic quotient. Soil sampled from the H. rhamnoides plots had the highest metabolic quotient and Gram-positive （G＋） bacterial PLFA, and soil sampled from the A. adsurgens and A. capillaries plots had the highest fungal PLFA and fungal：bacterial PLFA ratio. Correlation analysis indicated a signiifcant positive relationship among the microbial biomass C, G- bacterial PLFA, bacterial PLFA, and total PLFA. In conclusion, plant species under arid climatic conditions signiifcantly affected the microbial community structure in rhizosphere soil. Among the studied plants, natural grassland species generated the most favorable microbial conditions.

Estimation of above-ground biomass and carbon stock of an invasive woody shrub in the subtropical deciduous forests of Doon Valley,western Himalaya,India

This study describes the different parameters used to derive the allometric equation for calculating the biomass of an invasive woody shrub Lantana camara L.from the subtropical conditions of western Himalaya.It identifies the most accurate and convenient method for biomass calculation by comparing destructive with nondestructive methodology.Different parameters were measured on a wide range of Lantana from different community levels for the non-destructive calculation of total aboveground biomass.Different explanatory variables were identified and measured such as basal diameter either as a single independent variable or in combination with plant height.The other suitable combinations of available independent variables include crown length,crown width,crown area,crown volume and coverage of the plant.Amongst the wide range of allometric equations used with different variables,the equation with D2 H as a variable was found to be the most suitable estimator of biomass calculation for Lantana.Sahastradhara,being the most disturbed area due to its high tourist activity round the year,showed maximum coverage（58.57 % ha-1）,highest biomass（13,559.60 kg ha-1） and carbon density（6,373.01 kg ha-1）of Lantana.The degree of Lantana’s invasiveness in subtropical conditions was also calculated on the basis of importance value index（IVI）.The maximum IVI（22.77）and mean coverage（26.8 % ha-1） was obtained from the areas near Jolly Grant airport,indicating that physically disturbed areas are more suitable for the growth of Lantana,which may significantly increase shrub biomass.The importance of incorporating allometric equations in calculation of shrub biomass,and its role in atmospheric carbon assimilation has thus been highlighted through the findings of this study.

Spatio-temporal variation of vegetation in an arid and vulnerable coal mining region

Environmental assessment in an arid coal mining area requires an understanding of the influences of coal mining,the arid climate and ecological remediation.To that end,we selected vegetation as the key environmental factor to observe.Remote sensing approaches to monitoring the spatio-temporal variation of vegetation caused by mining activities,the arid climate and ecological remediation in the Shengdong coal mining area are described.Over a large regional scale it was found that the vegetation was improved as a result of ecological remediation activities.At the local scale,however,the vegetation coverage and soil moisture in the mined areas were slightly lower than those in un-mined areas due to mining subsidence.These differences are partly attributed to ground fissures that injure root systems and increase the depletion of soil moisture.It is recommended that fissures be reduced and filled to lessen their adverse effects on the environment.

Soil Organic Matter Fractions under Different Vegetation Types in Permafrost Regions along the Qinghai-Tibet Highway, North of Kunlun Mountains, China

As a key attribute of soil quality, soil organic matter(SOM) and its different fractions play an important role in regulating soil nutrient cycling and soil properties.This study evaluated the soil carbon(C) and nitrogen(N) concentrations in different SOM fractions(light– and heavy fractions,microbial biomass) under different vegetation types and analyzed their influencing factors in continuous permafrost regions along the Qinghai-Tibet Highway in the North of Kunlun Mountains, China.Soil samples were collected in pits under four vegetation types — Alpine swamp meadow(ASM), Alpine meadow(AM), Alpine steppe(AS) and Alpine desert(AD) — at the depth of 0-50 cm.The vegetation coverage was the highest at ASM and AM, followed byAS and AD.The results indicated that the concentrations of light fraction carbon(LFC) and nitrogen(LFN), and microbial biomass carbon(MBC)and nitrogen(MBN) decreased as follows: ASM > AM >AS > AD, with the relatively stronger decrease of LFC,whereas the heavy fraction carbon(HFC) and nitrogen(HFN) concentrations were lower in AS soils than in the AD soils.The relatively higher proportions of LFC/SOC and MBC/SOC in the 0-10 cm depth under the ASM soils are mainly resulted from its higher substrate input and soil moisture content.Correlation analysis demonstrated that aboveground biomass, soil moisture content, soil organic carbon(SOC) and total nitrogen(TN) positively correlated to LFC, LFN, HFC, HFN, MBC and MBN, while p H negatively correlated to LFC, LFN, HFC, HFN, MBC and MBN.There was no relationship between active layer thickness and SOM fractions, except for the LFC.Results suggested that vegetation cover, soil moisture content, and SOC and TN concentrations were significantly correlated with the amount and availability of SOM fractions, while permafrost had less impact on SOM fractions in permafrost regions of the central Qinghai–Tibet Plateau.

Estimation of the carbon storage of forest vegetation and carbon emission from forest fires in Heilongjiang Province,China

The forest resource of Heilongjiang province has important position in china. On the basis of the six times of national forest inventory data （1973-1976, 1977-1981, 1985-1988, 1989-1993, 1994-1998, 1999-2003） surveyed by the Forestry Ministry of P. R. China from 1973 to 2003, the carbon storage of forests in Heilongjiang Province are estimated by using the method of linear relationship of each tree species between biomass and volume. The results show that the carbon storage of Heilongjiang forests in the six periods （1973-1976, 1977-1981, 1985-1988, 1989-1993, 1994-1998, 1999-2003） are 7.164×10^8 t, 4.871×10^8 t, 5.094×10^8 t, 5.292×10^8 t, 5.594×10^8 t and 5.410×10^8 t, respectively., which showed a trend of decreasing in early time and then increasing. It indicated that Heilongjiang forests play an important role as a sink of atmospheric carbon dioxide during past 30 years. Based on the data of forest fires from 1980 to 1999 and ground biomass estimation for some forest types in Heilongjiang Province, it is estimated that the amount of mean annual consumed biomass of forests is 391758.65t-522344.95t, accounting for 6.4%-8.4% of total national consummation from forest fires, and the amount of carbon emission is 176 291.39t-235 055.23t, about 8% of total national emission from forest fires. The emission of CO2, CO, CH4 and NMHC from forest fires in Heilongjiang Province are estimated at 581761.6-775682.25 t, 34892.275-46523.04 t, 14091.11-18788.15 t and 6500-9000 t, respectively, every year.

Estimating aboveground biomass using Pléiades satellite image in a karst watershed of Guizhou Province,Southwestern China

Biomass in karst terrain has rarely been measured because the steep mountainous limestone terrain has limited the ability to sample woody plants.Satellite observation, especially at high spatial resolution, is an important surrogate for the quantification of the biomass of karst forests and shrublands. In this study, an artificial neural network(ANN) model was built using Pléiades satellite imagery and field biomass measurements to estimate the aboveground biomass(AGB) in the Houzhai River Watershed, which is a typical plateau karst basin in Central Guizhou Province, Southwestern China. A back-propagation ANN model was also developed.Seven vegetation indices, two spectral bands of Pléiades imagery, one geomorphological parameter,and land use/land cover were selected as model inputs. AGB was chosen as an output. The AGB estimated by the allometric functions in 78 quadrats was utilized as training data(54 quadrats, 70%),validation data(12 quadrats, 15%), and testing data(12 quadrats, 15%). Data-model comparison showed that the ANN model performed well with an absolute root mean square error of 11.85 t/ha, which was 9.88%of the average AGB. Based on the newly developed ANN model, an AGB map of the Houzhai River Watershed was produced. The average predicted AGB of the secondary evergreen and deciduous broadleaved mixed forest, which is the dominant forest type in the watershed, was 120.57 t/ha. The average AGBs of the large distributed shrubland,tussock, and farmland were 38.27, 9.76, and 11.69 t/ha, respectively. The spatial distribution pattern ofthe AGB estimated by the new ANN model in the karst basin was consistent with that of the field investigation. The model can be used to estimate the regional AGB of karst landscapes that are distributed widely over the Yun-Gui Plateau.

IMPACT OF ROAD CONSTRUCTION ON VEGETATION ALONGSIDE QINGHAI-XIZANG HIGHWAY AND RAILWAY

Based on the field investigation in August 2001 and August 2002, digitalChina Vegetation Map in 2001 and Qinghai-Xizang (Tibet) Plateau Vegetation Regionalization Map in1996, vegetation characteristics along two sides of Qinghai-Xizang highway and railway are studiedin this paper. Meanwhile, the impact of Qinghai-Xizang highway and railway constructions on thevegetation types are analyzed using ARCVIEW, ARC/INFO and PATCH ANALYSIS. It was found that: 1)Qinghai-Xizang highway and railway span 9 latitudes, 12 longitudes and 6 physical geographic regions(East Qinghai and Qilian mountain steppe region, Qaidam mountain desert region, SouthQinghai-Xizang alpine meadow steppe region, Qiangtang alpine steppe region, Golog-Nagqu alpine shrubmeadow region and South Xizang mountain shrub steppe region); 2) the construction of Qinghai-Xizanghighway and railway destroyed natural vegetation and landscape, especially in 50m-wide bufferregions along both sides of the roads, it was estimated that the net primary productivity deceasedby about 30 504.62t/a and the gross biomass deceased by 432 919.25-1 436 104.3t. The losing primaryproductivity accounted for 5.70% of the annual primary productivity within Ikm-wide buffer regions(535 005.07-535 740.11t/a), and only 0.80%-0.89% of that within 10km-wide buffer regions (3 408950.45-3 810 480.92t/a). The losing gross biomass was about 9.47%-17.06% of the gross biomass within1km-wide buffer regions (7 502 971.85-25 488 342.71t), and only 1.47%-2.94% of that within10km-wide buffer regions (43 615 065.35-164 150 665.37t).