Journal Article•
Biomass and productivity estimation using aerospace data and Geographic Information System
01 Jan 2002-Tropical Ecology (International Society for Tropical Ecology)-Vol. 43, Iss: 1, pp 123-136
TL;DR: Process based models were developed to make use of the remotely sensed data available on monthly basis for estimation of Net Primary Productivity (NPP).
Abstract: Traditionally biomass estimation involved harvesting of the trees. As the forest cover decreased, there became the need for non-destructive methods for volume/biomass estimation. Methods were developed to relate the biomass with girth, height etc. Component-wise biomass equations were developed, which were used to estimate biomass at the plot level. In last couple of years satellite remote sensing has been successfully used for biomass and productivity estimation. The unique characteristic of plants is displayed by its reflectance in red and infrared region of electro-magnetic radiation. These have relationship with the biophysical parameters of plants. Therefore, process based models were developed to make use of the remotely sensed data available on monthly basis for estimation of Net Primary Productivity (NPP). Production efficiency model was used to estimate the NPP at the patch level, which takes Intercepted Photosynthetically Active Radiation (IPAR) and photosynthetic efficiency as input parameters to estimate NPP.
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TL;DR: In this paper, the potential of the standwise tree outside forest inventory data and finer spatial resolution of IRS-P6 LISS-IV satellite data to classify TOF, to estimate above-ground TOF phytomass and the carbon content of TOF in a semi-arid region of the southern Haryana, India.
Abstract: Trees outside forest (TOF) play an important role in global carbon cycling, since they are large pools of carbon as well as potential carbon sinks and sources to the atmosphere. In view of the importance of biomass estimates in the global carbon (C) cycle, the present study demonstrates the potential of the standwise tree outside forest inventory data and finer spatial resolution of IRS-P6 LISS-IV satellite data to classify TOF, to estimate above-ground TOF phytomass and the carbon content of TOF in a semiarid region of the southern Haryana, India. The study reports that above-ground TOF phytomass varied from 1.26 tons/ha in the scattered trees in the rural/urban area to 91.5 tons/ha in the dense linear TOF along the canal. The total above-ground TOF phytomass and carbon content was calculated as 367.04 and 174.34 tons/ha, respectively in the study area. The study results conclude that the classification of TOF and estimation of phytomass and carbon content in TOF can be successfully achieved through the combined approach of Remote Sensing and GIS based spatial technique with the supplement of field data. The present approach will help to find out the potential carbon sequestration zone in the semi-arid region of southern Haryana, India.
34 citations
TL;DR: In this paper, a spectral modeling of above ground biomass (AGB) with field data collected in 48 field sites representing moist deciduous forest in Surat district is reported.
Abstract: Spectral modeling of above ground biomass (AGB) with field data collected in 48 field sites representing moist deciduous forest in Surat district is reported. Models were generated using LISS-III and MODIS data. The plot-wise field data was aggregated to MODIS pixel (250 m) using area weightages of forest/vegetation. The study reports that above ground phytomass varied from 6.13 t/ha to 389.166 t/ha while AGB phytomass estimated using area-weights for sites of 250×250 m, ranged from 5.534 t/ha to 134.082 t/ha. The contribution of bamboo in AGB has been found very high. The analysis indicated that the highest correlation between AGB phytomass and red band (R) of MODIS satellite data of October was (R2=0.7823) and R2=0.6998 with both NDVI of October data as well as NDVImax. High correlation (R2=0.402) with IR band of February month was also found. The phytomass range obtained by using MODIS data varies from 0.147 t/ha to 182.16 t/ha. The mean biomass is 40.50 t/ha. Total biomass is 31.44 Mt. The mean Carbon density is 19.44 tC/ha in forest areas. The study is validation of region-wise spectral modeling approach that will be adopted for mapping vegetation carbon pool of the India under National Carbon Project of ISRO-Geosphere Biosphere Programme.
18 citations
Cites background or methods from "Biomass and productivity estimation..."
...At patch level several methods have been proposed to estimate forest biomass (Whittaker 1966; Ovington 1968; Brown et al. 1991; Kale et al. 2002)....
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...and Singh 1987; Rawat and Singh 1988; Haripriya 2002) and still our understanding on these forests is poor (Kale et al. 2002)....
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...Remote sensing data has been widely used for phytomass estimation (Sader et al. 1989; Tiwari 1994; Kale et al. 2002; Foody et al. 2003; Lu 2005)....
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...…(*) Indian Institute of Remote Sensing (IIRS), Dehradun 248 001, India e-mail: sarnam.singh@gmail.com V. K. Dadhwal National Remote Sensing Centre, Hyderabad 500 625, India and Singh 1987; Rawat and Singh 1988; Haripriya 2002) and still our understanding on these forests is poor (Kale et al. 2002)....
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TL;DR: In this paper, a spectral modeling approach was used to assess the relation of Normalized Difference Vegetation Index (NDVI) with biomass carbon, crown density, tree density, slope, altitude, aspect, species, and forest division in temperate conifer region of Himalaya.
Abstract: Assessing biophysical variables are essential for evaluation of carbon dynamics due to anthropogenic activities. Biomass carbon is an important biophysical parameter of forest ecosystems that indicates carbon mitigation and human–forest interactions. Spectral modeling approach was used to assess the relation of Normalized Difference Vegetation Index (NDVI) with biomass carbon, crown density, tree density, slope, altitude, aspect, species, and forest division in temperate conifer region of Himalaya. Field inventory was recorded from 188 biomass plots of 0.1 ha each across the study area. NDVI was observed to have a positive relation with aboveground biomass carbon, crown density, tree density, and altitude. The NDVI and ABC values ranged from (0.11 to 0.43) and (1.54 to 276.82 t ha−1), respectively. Among the aspects, highest and lowest average NDVI was observed for south east (0.289) and north (0.258), respectively. Similarly highest and lowest average aboveground biomass carbon was observed for north east (72.63 t ha−1) and east (44.30 t ha−1), respectively. NDVI expressed a fairly good relation with biophysical parameters including altitude, aspect, crown density, tree density, species, and location (forest division). NDVI using principal tree species composition (forest type) revealed a relation with aboveground biomass carbon for Cedrus deodara (R2 = 0.63), Mixed I (R2 = 0.61), Pinus wallichiana (R2 = 0.57), and Mixed-II (R2 = 0.48). NDVI demonstrates potential to understand biomass carbon variability through establishment of relations with forest biophysical parameters using spectral modeling approach. Varying NDVI can be ascribed to vegetation canopy density, number of stems, species, and altitude. The database and established relations would help indicate biomass carbon dynamics and enable to adopt site-specific management. The study further helps draw inferences on mitigation and adaptation perspectives in view of varying biophysical conditions that occur in a forest.
13 citations
TL;DR: In this article, the authors present an overview of the methodologies adopted in India fro m local to country level estimates to assess C sequestration potential in different forest co-partonents, and discuss remote sensing and Geographical Informat ion System (GIS) in itiat ives taken in this field and the possibility of adopting an integrated approach for reliable, accurate and cost effective estimates.
Abstract: Under the United Nat ions Framewo rk Convention on Climate Change (UNFCC), part icipating countries are required to report national inventory of greenhouse gas (GHG) emissions or uptake. The current challenge is to reduce the uncertainties in producing accurate and reliable act ivity data of Carbon (C) stock changes and emission factors essential for reporting national inventories. Improvements in above ground biomass estimation can also help account for changes in C stock in forest areas that may potentially participate in the Clean Develop ment Mechanism (CDM), REDD plus and other initiat ives. The methods adopted for such estimations vary with respect to geography, objective of the study, available expertise, data and scientific excellence adopted. However the current objectives for such estimates need a unified approach which can be measurable, reportable, and verifiable. Th is might result to a geographically referenced bio mass density database for tropical forests that would reduce uncertainties in estimat ing annual bio mass increment and forest aboveground biomass. In the light of above requirements, this paper intends to present an overview of the methodologies adopted in India fro m local to country level estimates to assess C sequestration potential in d ifferent forest co mponents. The paper also discusses remote sensing and Geographical Informat ion System (GIS) in itiat ives taken in this field and the possibility of adopting an integrated approach for reliable, accurate and cost effective estimates.
10 citations
Cites background from "Biomass and productivity estimation..."
...Phenology plays an important role in using satellite data for estimat ing qualitative and quantitative characters especially in deciduous vegetation as similarly reported[58] that SAR (Synthetic Aperture Radar) being sensitive to moisture, temperature, branch architecture, b iomass, age classes, girth, canopy density etc....
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TL;DR: In this article, the authors performed geospatial modeling of plot-level field data on forest above ground biomass (AGB) by correlating it with textural, spectral and linearly transformed variables retrieved from Landsat 8 OLI data using of random forest (RF) machine learning algorithm.
Abstract: Forest operates as sink–source of the atmospheric CO2; hence, they form the integral part of terrestrial global carbon cycle. Biomass and primary productivity are the crucial dynamic biophysical parameters for understanding the ecosystem functioning in any forested landscape. The present study was performed in Aglar watershed situated in outer Indian Himalayan range. We performed geospatial modeling of plot-level field data on forest above ground biomass (AGB) by correlating it with textural, spectral and linearly transformed variables retrieved from Landsat 8 OLI data using of random forest (RF) machine learning algorithm. We also applied recursive feature elimination function (RFE) to obtain the variables contributing most in AGB prediction. A combination of 24 among 96 variables was identified as the most effective variables. Ground-based AGB varied from 62.54 to 470.98 Mg ha−1, whereas RF-modeled AGB ranged from 48.5 to 407.73 Mg ha−1. Results indicated that RFE selected variables were able to predict AGB with R2 of 0.84, RMSE of 42.03 Mg ha−1, MAE of 34.68 and %RMSE of 19.49 Mg ha−1 which was accepted considering the terrain complexity. Light use efficiency approach was used to model monthly NPP using Landsat 8 OLI data. The results indicated that Quercus mixed forest had highest carbon assimilation (95,148,073.9 gC) followed by Pinus roxburghii (1,863,187.7 gC), Cedrus deodara (5,752,954.1 gC) and mixed forest (2,634,737.1 gC). The seasonal pattern of NPP indicated that its strike peaked in October, whereas December and January were the lean months, suggesting that NPP is governed by climatic factors, viz. PAR, precipitation and temperature. Such watershed-level study in complex Himalayan terrain would help to understand complex biogeochemical processes in basins and ecosystem services provided by the forests.
9 citations
References
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TL;DR: In this paper, the authors present a modeling approach aimed at seasonal resolution of global climatic and edaphic controls on patterns of terrestrial ecosystem production and soil microbial respiration using satellite imagery (Advanced Very High Resolution Radiometer and International Satellite Cloud Climatology Project solar radiation), along with historical climate (monthly temperature and precipitation) and soil attributes (texture, C and N contents) from global (1°) data sets as model inputs.
Abstract: This paper presents a modeling approach aimed at seasonal resolution of global climatic and edaphic controls on patterns of terrestrial ecosystem production and soil microbial respiration. We use satellite imagery (Advanced Very High Resolution Radiometer and International Satellite Cloud Climatology Project solar radiation), along with historical climate (monthly temperature and precipitation) and soil attributes (texture, C and N contents) from global (1°) data sets as model inputs. The Carnegie-Ames-Stanford approach (CASA) Biosphere model runs on a monthly time interval to simulate seasonal patterns in net plant carbon fixation, biomass and nutrient allocation, litterfall, soil nitrogen mineralization, and microbial CO2 production. The model estimate of global terrestrial net primary production is 48 Pg C yr−1 with a maximum light use efficiency of 0.39 g C MJ−1PAR. Over 70% of terrestrial net production takes place between 30°N and 30°S latitude. Steady state pools of standing litter represent global storage of around 174 Pg C (94 and 80 Pg C in nonwoody and woody pools, respectively), whereas the pool of soil C in the top 0.3 m that is turning over on decadal time scales comprises 300 Pg C. Seasonal variations in atmospheric CO2 concentrations from three stations in the Geophysical Monitoring for Climate Change Flask Sampling Network correlate significantly with estimated net ecosystem production values averaged over 50°–80° N, 10°–30° N, and 0°–10° N.
2,398 citations
"Biomass and productivity estimation..." refers methods in this paper
...Some models in this category like CASA, (Potter et al. 1993) CENTURY, (Patron et al....
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...Some models in this category like CASA, (Potter et al. 1993) CENTURY, (Patron et al. 1993) and HRBM (Field et al. 1995) take into the consideration vegetation characteristics and environmental variables or indicators such as temperature, precipitation, available soil nitrogen and other fertility…...
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...Some models in this category like CASA, (Potter et al. 1993) CENTURY, (Patron et al. 1993) and HRBM (Field et al. 1995) take into the consideration vegetation characteristics and environmental variables or indicators such as temperature, precipitation, available soil nitrogen and other fertility factors to estimate NPP as the difference between two processes viz., (a) GPP i.e. the total uptake of carbon from the atmosphere by plants, and (b) autotrophic respiration (RA: the release of carbon to the atmosphere by plant respiration)....
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TL;DR: Conventional estimates of efficiency in terms of the amount of solar radiation incident at the earth's surface provide ecologists and agronomists with a method for comparing plant productivity under different systems of land use and management and in different * Opening paper read at IBP/UNESCO Meeting on Productivity of Tropical Ecosystems.
Abstract: In thermodynamic terms, ecosystems are machines supplied with energy from an external source, usually the sun. When the input of energy to an ecosystem is exactly equal to its total output of energy, the state of equilibrium which exists is a special case of the First Law of Thermodynamics. The Second Law is relevant too. It implies that in every spontaneous process, physical or chemical, the production of 'useful' energy, which could be harnessed in a form such as mechanical work, must be accompanied by a simultaneous 'waste' of heat. No biological system can break or evade this law. The heat produced by a respiring cell is an inescapable component of cellular metabolism, the cost which Nature has to pay for creating biological order out of physical chaos in the environment of plants and animals. Dividing the useful energy of a thermodynamic process by the total energy involved gives a figure for the efficiency of the process, and this procedure has been widely used to analyse the flow of energy in ecosystems. For example, the efficiency with which a stand of plants produces dry matter by photosynthesis can be defined as the ratio of chemical energy stored in the assimilates to radiant energy absorbed by foliage during the period of assimilation. The choice of absorbed energy as a base for calculating efficiency is convenient but arbitrary. To derive an efficiency depending on the environment of a particular site as well as oil the nature of the vegetation, dry matter production can be related to the receipt of solar energy at the top of the earth's atmosphere. This exercise was attempted by Professor William Thomson, later Lord Kelvin, in 1852. 'The author estimates the mechanical value of the solar heat which, were none of it absorbed by the atmosphere, would fall annually on each square foot of land, at 530 000 000 foot pounds; and infers that probably a good deal more, 1/1000 of the solar heat, which actually falls on growing plants, is converted into mechanical effect.' Outside the earth's atmosphere, a surface kept at right angles to the sun's rays receives energy at a mean rate of 1360 W m-2 or 1f36 kJ m-2 s-1, a figure known as the solar constant. As the energy stored by plants is about 17 kJ per gram of dry matter, the solar constant is equivalent to the production of dry matter at a rate of about 1 g m-2 every 12 s, 7 kg m-2 per day, or 2 6 t m-2 year-'. The annual yield of agricultural crops ranges from a maximum of 30-60 t ha-' in field experiments to less than I t ha-' in some forms of subsistence farming. When these rates are expressed as a fraction of the integrated solar constant, the efficiencies of agricultural systems lie between 0-2 and 0 004%, a range including Kelvin's estimate of 0-1%. Conventional estimates of efficiency in terms of the amount of solar radiation incident at the earth's surface provide ecologists and agronomists with a method for comparing plant productivity under different systems of land use and management and in different * Opening paper read at IBP/UNESCO Meeting on Productivity of Tropical Ecosystems, Makerere University, Uganda, September 1970.
2,278 citations
"Biomass and productivity estimation..." refers methods in this paper
...The concept of calculating NPP as a product of IPAR and conversion efficiency (ε) was pioneered by Monteith (1972)....
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TL;DR: In this paper, a two-stream approximation model of radiative transfer was used to calculate values of hemispheric canopy reflectance in the visible and near-infrared wavelength intervals.
Abstract: A two-stream approximation model of radiative transfer is used to calculate values of hemispheric canopy reflectance in the visible and near-infrared wavelength intervals. Simple leaf models of photosynthesis and stomatal resistance are integrated over leaf orientation and canopy depth to obtain estimates of canopy photosynthesis and bulk stomatal or canopy resistance. The ratio of near-infrared and visible reflectances is predicted to be a near linear indicator of minimum canopy resistance and photosynthetic capacity but a poor predictor of leaf area index or biomass.
2,198 citations
"Biomass and productivity estimation..." refers background in this paper
...Sellers (1985) presented a critical analysis of canopy reflectance and its role in studying photosynthesis and transpiration....
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TL;DR: In this paper, an ecosystem process model is described that calculates the carbon, water and nitrogen cycles through a forest ecosystem, which uses leaf area index (lai) to quantify the forest structure important for energy and mass exchange, and represents a key simplification for regional scale applications.
1,465 citations
TL;DR: The spectral properties of plant leaves and stems have been obtained for ultraviolet, visible, and infrared frequencies as discussed by the authors, including reflectance, transmittance, and absorptance for certain plants.
Abstract: The spectral properties of plant leaves and stems have been obtained for ultraviolet, visible, and infrared frequencies. The spectral reflectance, transmittance, and absorptance for certain plants is given. The mechanism by which radiant energy interacts with a leaf is discussed, including the presence of plant pigments. Examples are given concerning the amount of absorbed solar radiation for clear sky and overcast conditions. The spectral properties of desert plants are compared with those of more mesic plants. The evolution of the spectral properties of plant leaves during the early growing season is given as well as the colorimetric behavior during the autumn.
1,300 citations
"Biomass and productivity estimation..." refers background in this paper
...Gates et al. (1965) studied the spectral characteristics of leaf reflection, transmission and absorption....
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