Biomass and vegetation index by remote sensing in different caatinga forest areas

ABSTRACT: Continued unsustainable exploitation of natural resources promotes environmental degradation and threatens the preservation of dry forests around the world. This situation exposes the fragility and the necessity to study landscape transformations. In addition, it is necessary to consider the biomass quantity and to establish strategies to monitor natural and anthropic disturbances. Thus, this research analyzed the relationship between vegetation index and the estimated biomass using allometric equations in different Brazilian caatinga forest areas from satellite images. This procedure is performed by estimating the biomass from 9 dry tropical forest fragments using allometric equations. Area delimitations were obtained from the Embrapa collection of dendrometric data collected in the period between 2011 and 2012. Spectral variables were obtained from the orthorectified images of the RapidEye satellite. The aboveground biomass ranged from 6.88 to 123.82 Mg.ha-1. SAVI values were L = 1 and L = 0.5, while NDVI and EVI ranged from 0.1835 to 0.4294, 0.2197 to 0.5019, 0.3622 to 0.7584, and 0.0987 to 0.3169, respectively. Relationships among the estimated biomass and the vegetation indexes were moderate, with correlation coefficients (Rs) varying between 0.64 and 0.58. The best adjusted equation was the SAVI equation, for which the coefficient of determination was R² = 0.50, R2aj = 0.49, RMSE = 17.18 Mg.ha-1 and mean absolute error of prediction (MAE) = 14.07 Mg.ha-1, confirming the importance of the Savi index in estimating the caatinga aboveground biomass.

Tree Biomass Estimation in Karst Forest of West Papua, Indonesia

Indonesia is estimated to have 14,5 million hectares of karst areas. The characteristic of karst vegetation is specific, one of which is the dominance of small trees. With all of the potency, their vegetation acts as a significant carbon sequester and store it in biomass. This study aims to estimate and discuss biomass estimation in the karst forest within the Nature Recreational Park of Beriat, a protected area in South Sorong, West Papua. A total of 28 plots were made in the forest using the purposive random sampling method. Tree biomass (DBH ≥10 cm) was estimated using five different allometric equations. The results showed that the biomass was estimated at ca. 264 Mg ha-1 (95 % CI: 135-454 Mg ha-1). While small trees (DBH 10 – 30 cm) only contribute 30 % of the total biomass, about 38 % of the biomass is the contribution of large trees (DBH >50 cm), where Pometia pinnata contributes ca. 39 % of the biomass at plot-level. The use of various allometric equations results in different biomass estimates and biases with deviations ranged from -14.78 % to +17.02 % compared to the reference equation. Therefore, the selection of allometric equations used must be considered carefully to reduce uncertainties in biomass estimation.

An Allometric Model Based Approach For Estimating Biomass In Seven Indian Bamboo Species In Western Himalayan Foothills, India

The rapid growth rate, high biomass production, and annual harvesting, makes bamboo as suitable species for commercial production. Allometric equations for many broadleaf and conifer tree species are available. However, knowledge on biomass production and allometric equations of bamboos are limited. This study aims at developing species specific allometric models for predicting biomass and synthetic height values as a proxy variable for seven bamboo species in Himalayan foothills. Two power form based allometric models were used to predict above ground and culm biomass using Diameter at breast height (D) alone and D in combination with culm height (H) as independent variable. This study also extended to establishing H-D allometric model that can be used to generate synthetic H values as proxy to missing H. In the seven bamboo species studied, among three major biomass component (culm, branch and foliage), culm is the most important component with highest share (69.56 to 78.71%).Distribution of percentage (%) share of culm, branch and foliage to above ground fresh weight varies significantly between different bamboo species. D. hamiltonii has highest productivity for above ground biomass components. Ratio of dry to fresh weight of seven bamboo species was estimated for culm, branch, foliage and above ground biomass to convert fresh weight to dry weight.

Allometric equations for estimating on-farm fuel production of Gliricidia sepium (Gliricidia) shrubs and Cajanus cajan (pigeon pea) plants in semi-arid Tanzania

Background Fuelwood is considered to be the primary source of cooking energy in Tanzania and, due to ongoing deforestation, access to fuelwood is becoming more cumbersome. On-farm agroforestry systems can reduce dependency on off-farm fuel; however, the output of on-farm produced fuel is typically uncertain as production potentials are often not known. In this paper, we have developed allometric equations to model the above-ground woody biomass (AGWB) production from intercropped Gliricidia sepium (Jacq.) Kunth ex Walp (Gliricidia) shrubs and Cajanus cajan (L.) Millsp. (pigeon pea) plants. Methods We used a destructive sampling approach, for measuring the dendrometric characteristics, such as the root collar diameter at a 20 cm stem height (RCD20) and the stem height to estimate the AGWB production. The models are based on 112 Gliricidia and 80 pigeon pea observations from annually pruned plants. Seven allometric equations were fitted to derive the best-fit models for the AGWB production. Results We found that using a natural log-transformed linear model with RCD20 as a single predictor variable provides the highest explanatory value to estimate the AGWB production (Gliricidia: R2 = 95.7%, pigeon pea: R2 = 91.4%) while meeting Ordinary Least Square (OLS) estimator requirements. Adding stem height as an additional variable to predict the AGWB production does not improve model accuracy enough to justify the extra work for including it. Conclusions While on-farm pigeon pea plants produced a stable amount of woody biomass per annum, annual fuelwood production from Gliricidia shrubs increased over the years. Compared to the annual fuelwood consumption data from the literature, our results show that on-farm produced fuelwood can substantially offset the demand for off-farm fuel, potentially resulting in household fuelwood autarky.

Allometric equations for selected Acacia species (Vachellia and Senegalia genera) of Ethiopia

Background Allometric equations are used to estimate biomass and carbon stock of forests. In Ethiopia, despite the presence of large floral diversity, only a few site-specific allometric equations have been developed so far. This study was conducted in the Omo-Gibe woodland of south-western Ethiopia to develop an allometric equation to estimate the Above-ground Biomass (AGB) of the four Acacia species (Senegalia polyacantha, Vachellia seyal, Vachellia etbaica and Vachellia tortilis). Fifty-four (54) Acacia trees were sampled and measured within 35 temporarily established square plots. In each plot, dendrometric variables were measured to derive the models based on combinations of Diameter at Breast Height (DBH), height, and wood density as predictor variables. Model performance was evaluated using goodness-of-fit statistics. The biomass was compared using four allometric biomass models that have been widely used in the tropics. Results The model containing DBH alone was more accurate to estimate AGB compared to the use of multiple predictor variables. This study, therefore, substantiated the importance of site-specific allometric equations in estimating the AGB of Acacia woodlands. This is because a site-specific allometric equation recognizes the environmental factors, vegetation types and management practices. Conclusions The results of this study contribute to a better understanding of allometric equations and an accurate estimate of AGB of Acacia woodlands in Ethiopia and similar ecosystems elsewhere.

The patterns of agroforestry: the implementation and its impact on local community income and carbon stock in Sesaot Forest, Lombok, Indonesia

This article aims to explore the implementation of agroforestry patterns in the Sesaot forest area and the impacts on the local community income and the carbon stocks. It is written based on descriptive research, data are collected through observation, interviews, and FGDs to 42 respondents, and measuring carbon stocks in 18 locations. The analysis in this study is divided into three: 1) clustering based on plant dominance to identify existing agroforestry patterns, 2) allometric equations to measure the amount of carbon stock, and 3) using scoring to analyze the identified agroforestry patterns to find out the most optimal. This study finds that there are four agroforestry patterns in this area: candlenut dominant, mahogany dominant, mixed agroforestry, and simple agroforestry. From these patterns, mixed agroforestry seems to be the best practice in this area since it has complied with the principles of sustainable forest management both from the perspective of economic and the environment.

Local Allometric Equations for Estimating Above-Ground Biomass (AGB) of Mangroves (Rhizophora spp. and Avicennia germinans) from the Komo, Mondah and Rio Mouni Estuaries in Gabon

The aboveground biomass (AGB) of Gabonese mangroves is commonly estimated from equations calibrated in other countries, and is generally adapted poorly to the local context. This paper focuses on developing local allometric equations for the AGB estimation and to evaluate their accuracy compared to other general equations. The local equations for Rhizophora spp and Avicennia germinans were performed with tree volume, bark and wood densities, and are used with the diameter as an independent variable. The heights and diameters of 408 trees (314 Rhizophora spp and 94 Avicennia germinans) were measured at 13 sites in Estuaire Province. Sixty-four aliquots were taken from the trunks of both species at the Mondah site. This site has tree diameters ranging from 2 to 127 cm for Avicennia and from 1.4 to 75.8 cm for Rhizophora. The tree height ranges from 0.9 to 24 m for Avicennia, and from 1.1 to 53 m for Rhizophora. Avicennia has an overall trunk density of 0.88 g/cm3 and Rhizophora has 1.17 g/cm3. The coefficient of determination (R2) of the equations are 0.98 for Rhizophora spp, 0.97 for Avicennia germinans, and 0.99 for the general equation. The seven equation display biases that are less than 1% and the root mean square errors vary between 0.073 and 1.68. Compared to other equations generally used, these local equations improve the accuracy of aboveground biomass estimations of Gabonese mangroves.