B. Velázquez-Martí

Analysis of the factors affecting LiDAR DTM accuracy in a steep shrub area

The creation of a quality Digital Terrain Model (DTM) is essential for representing and analyzing the Earth in a digital form. The continuous improvements in the acquisition and the potential of airborne Light Detection and Ranging (LiDAR) data are increasing the range of applications of this technique to the study of the Earth surface. The aim of this study was to determine the optimal parameters for calculating a DTM by using an iterative algorithm to select minimum elevations from LiDAR data in a steep mountain area with shrub vegetation. The parameters were: input data type, analysis window size, and height thresholds. The effects of slope, point density, and vegetation on DTM accuracy were also analyzed. The results showed that the lowest root mean square error (RMSE) was obtained with an analysis window size of 10 m, 5 m, and 2.5 m, rasterized data as input data, and height thresholds equal to or greater than 1.5 m. These parameters showed a RMSE of 0.19 m. When terrain slope varied from 0–10% to 50–60%, the RMSE increased by 0.11 m. The RMSE decreased by 0.06 m when point density was increased from 4 to 8 points/m2, and increased by 0.05 m in dense vegetation areas.

GIS Application to Define Biomass Collection Points as Sources for Linear Programming of Delivery Networks

Much bio-energy can be obtained from wood pruning operations in forests and fruit orchards. Several spatial studies have been carried out for biomass surveys, and many linear programming models have been developed to model the logistics of bio-energy chains. These models can assist in determining the best alternatives for bio-energy chains. Most of these models use network structures built up from nodes with one or more depots, with arcs connecting the depots. Each depot is a source of a certain biomass type. Nodes can also be biomass storage points or production facilities (e.g., power plants) where biomass is used. The arcs in the networks represent transport between depots. In order to combine GIS spatial studies with linear programming models, it is necessary to build a network from a digital map of biomass production centers, such as orchards. Biomass collection points should therefore be defined as sources in the delivery network model. In this work, a mathematical calculation method is developed to select the actual biomass collection points on a map. The database for this model is composed of area surveys of forest and agricultural biomass storage points given in GIS maps (shape files). The limits of the area studied and different types of biomass are defined and located in different layers of the GIS maps. These energy-biomass production maps are overlaid with a 1 km × 1 km grid of the area studied. The result is a grid in which the different types of total available biomass in each quadrant are known. Harvesting and collection costs are also defined. The connections between all n × m quadrants of the area studied are defined by the available road network. Every quadrant is associated with a point on the road network. The selection criteria for sources of biomass (sub-areas) are the following: firstly, a minimum production of available biomass type is required; and secondly, harvesting and collection costs should be minimal. The algorithm provides the location of points where biomass from the associated area can be concentrated. These biomass collection points are then taken as source nodes in the network during the implementation of the logistics models. In the next step, the network is analyzed by linear programming techniques to supply the optimal position of energy plants or factories, given the available biomass sources.

Estimation of wood volume and height of olive tree plantations using airborne discrete-return LiDAR data

The aim of this study is to analyze methodologies based on airborne LiDAR (light detection and ranging) technology of low pulse density points (0.5 m−2) for height and volume quantification of olive trees in Viver (Spain). A total of 29 circular plots, each with a radius of 20 m, were sampled and their volumes and heights were obtained by dendrometric methods. For these estimations, several statistics derived from LiDAR data were calculated in each plot. Regression models were used to predict volume and height. The results showed good performance for estimating volume (R2 = 0.70) and total height (R2 = 0.67).

Mechanized methods for harvesting residual biomass from Mediterranean fruit tree cultivations.

This study evaluates the technology and work systems used in order to harvest residual biomass from pruning in the specific conditions of Mediterranean fruit orchards (narrow distances between crop-rows). Harvesting has been divided into several types of operations - pruning, biomass alignment between crop tracks, biomass concentration in piles, chipping and bundling - which have been analyzed in five Mediterranean cultivations for three years. Altogether, three types of pruning have been analyzed: Manual, previous mechanical followed by manual, and fully mechanical; Two types of alignment: Manual and mechanical; Three concentration systems: Manual, tractor with a rake and a forwarder; Four chipping work organization systems: chipper driven inside orchard and manually fed by operators, mobile chipper driven inside orchard with pick-up header, mobile chipper fed by means of mechanical crane, chipper mounted on a truck fed by means of mechanical crane, which was working in a fixed position in a border of the plot after wood concentration. Also two bundling organization systems were checked: bundler machine working in a fixed position after wood concentration and working inside the plot driven among the crops. Previous concentration of the materials was the best alternative for their chipping or bundling in the studied conditions. Regression models have been calculated to predict the time of work of machinery and labor for each alternative. These equations were used to implement logistic planning as the Borvemar model, which defines a logistics network for supplying bio-energy systems.

Assessment of factors affecting shrub volume estimations using airborne discrete-return LiDAR data in Mediterranean areas

Shrub vegetation is a key element of Mediterranean forest areas and it is necessary to develop tools that allow a precise knowledge of this vegetation. This study aims to predict shrub volume and analyze the factors affecting the accuracy of these estimations in small stands using airborne discrete-return LiDAR data. The study was performed over 83 circular stands with 0.5 m radius located in Chiva (Spain) mainly occupied by Quercus coccifera. The vegetation inside each area was clear cut, and the height and the diameter of each plant was measured to compute the volume of shrub vegetation per stand. Volume values were related with maximum height values derived from LiDAR data reaching a coefficient of determination value R 2 = 0.26 . Afterwards, factors affecting the quality of volume estimations were analyzed, i.e., vegetation type, LiDAR density, and accuracy of the digital terrain model (DTM). Significant accuracy improvements ( R 2 = 0.71 ) were detected for stands with 0.5 m, LiDAR data density greater than 8     points / m 2 , vegetation Q. coccifera, and error associated to the DTM less than 0.20 m. These results show the feasibility of using LiDAR data to predict shrub volume under certain conditions, which can contribute to improved forest management and characterization.

Prediction models based on higher heating value from the elemental analysis of neem, mango, avocado, banana, and carob trees in Guayas (Ecuador)

The energy use of biomass in rural areas is starting to interest the farmers in Ecuador. Its use is recognized as environmentally friendly, but knowledge about the raw materials to be used as bioenergy remains meager. The objective of this research was to characterize five species located in the province of Guayas: avocado (Persea americana L.), carob (Prosopis spp.), mango (Mangifera indica L.), neem (Azadirachta indica L.), and bananas (Musa acuminata L.). The elemental composition and higher heating value were analyzed following harmonized standards. These species did not significantly differ in CHN composition, being about 33.012% C, 6.232% H, 0.610% N, and their higher heating value 14.322 MJ kg−1. However, significant differences were found with respect to Cl and S: banana wood had the highest Cl and S content 1.162% and 0.134%, respectively, while avocado had the lowest Cl and S content, 0.032% and 0.063%, respectively. Fifteen mathematical models were formulated to predict the higher heating value...

STRUCTURE ANALYSIS AND BIOMASS MODELS FOR PLUM TREE (PRUNUS DOMESTICA L.) IN ECUADOR

The development of dendrometric methodologies could allow accurate estimation of variables associated with the crown, such as primary production (fruit and timber) and tree vigor. The aim of this work was to develop a suitable method to estimate woody biomass in plum trees ( Prunus domestica L.) in Imbabura, Ecuador by using an adapted dendrometry. Form factors and regression models were defined for branch volume calculation. From this, the distribution of woody biomass in the crown tree was characterized in every stratum. Occupation Factor and regression models were obtained in order to calculate the biomass in the crown tree, which can be used to estimate the CO 2 captured in its structure during its development. Regression models for calculation of whole volume of the tree and pruned biomass were directly obtained from crown diameter and crown height with R ajustated 2 of 0.74 and 0.81. The average moisture content of green material was 51%, and the average density of dry material was 0.66 ± 0.07 g cm −3 . Proximate analysis of plum wood showed at 79.8 ± 9.2% volatiles and 2.1 ± 0.3% ash. Elemental analysis of the wood pointed to 46.5 ± 1.2% C, 6.1 ± 0.5% H, 46.3 ± 1.2% O, 0.6 ± 0.3% N, 0.06 ± 0.02% S and 0.02 ± 0.01% Cl. Cl, S and N contents are lower than the limits established by the standard EN 14691-part 4. With 46% of C, considering the relation 3.67 (44/12) between CO 2 and C content, the CO 2 sequestrated in the materials is 1.11 Mg m −3 wood material. Such method represents a tool to manage orchard resources and for assessing other parameters, such as raw materials for cultivation, fruit production, CO 2 sink and waste materials (residual wood) used for energy or industry.

A SOLID CARBON DIOXIDE (DRY ICE) COOLING SYSTEM FOR THE MECHANIZED AERIAL RELEASE OF STERILE MALE CERATITIS CAPITATA

One alternative to chemical treatment in the fight against Ceratitis capitata is the liberation of sterilized male insects to compete with wild flies in mating. This method decreases the number of fertilized females in each generation, maintaining a reduced population so as to prevent crop damage. A system for insect storage and a method for the mechanized aerial release of insects are proposed in this article. The system cools the mass of stored insects by convection, using an external flow of air passing through a bed of solid carbon dioxide, sublimated at -79°C. To control the system, three parameters have been determined: the airflow necessary to maintain latency for a specific volume of insects, the relationship between the volumes of sublimated CO2 and external air necessary to obtain air at a specific temperature, and the volume of solid carbon dioxide (dry ice) necessary to cool a specific volume of insects for the duration of the treatment. A prototype has been built to validate the system, in which insects are released with worm screws located on the bottom of the storage module. The prototype allows for the release of 1000 to 4000 flies per second with no injury to the insects, which maintain their ability to fly and mate. With this prototype, between 2000 and 8000 insects per week per hectare can feasibly be released by airplane, covering an area between 200 and 250 m in width with each pass at speeds of 160 to 180 km/h.

Logistic Models to Ensure Residual Agroforestry Biomass as a Sustainable Resource

Sustainable development strategy promotes activities related to clean energy and energy saving. In this context, actions in forest and agricultural areas which add value to immediate productions and positive externalities are prioritized. The use of agricultural waste is often not viable due to high costs of harvesting and transport operations. In order to consider biomass as an agro forestry sustainable resource to produce biofuels, a high-level system based on the operational concept of the Biofuels Supply Chain sets the basis for a strategic framework which helps to overcome such sustainability. This chapter presents advanced techniques applied by the authors for the detection and quantification of biomass (LiDAR and multispectral images). From these results, logistic models are developed for determining the optimal collection points, managing the best transportation routes and deciding on the desirable location of the processing industries.

Systems of Pruning on Jigacho (Vasconcellea stipulata Badillo) under Greenhouse Conditions

The participation of Borja Velazquez Marti in this work was possible by the funding from the Ecuadorian Government through PROMETEO program, leaded by the Secretaria Nacional de Educacion Superior, Ciencia y Tecnologia (SENESCYT).