- The Mission
- Main Ideas
- S&T Objectives
- Technical Approach
The mission of SLOPE is to develop an integrated system that allows optimization of the forest production in mountain areas.
SLOPE aims at filling the current gap between more expensive, less flexible forestry operations in mountain areas and optimized cut-to-length systems commonly found in flatland forests.
For this purpose, spatial information and multi-sensor data from remote sensing, UAVs (Unmanned Aerial Vehicles) and TLS (terrestrial laser scanner) surveying systems will be integrated in a model for Sustainable Forest Management and for optimal planning and logistics management of forest operations.
SLOPE also aims at adding value to the mountain forest production, through reliable stumpage price evaluation and quality control of the harvested material, thanks to the integrated use of novel sensing technologies. A methodological basis will be developed for a semi-automated and real-time grading system for the mountainous forest production, in order to:
- Improve log/biomass segregation
- Update forest inventories
- Refine stand growth and yield models
To do so, the integration of targeted intelligent systems in the cable crane/processor head/truck, to measure a set of different data for the assessment of the assortment variety will be evaluated in the project. Different traceability systems will be used, to trace the material, from the site throughout the whole supply chain.
Integration of information about the forest (topographic and geomorphological, cadastral data, road network, environmental, climatic data, etc.), harvesting data (extraction distance and direction, stand density, silviculture management, utilization amount etc.) and material origin, quality and availability in a unique system, accessible online and available in real time to a series of operators (e.g. logistic operators, brokers, forest owners, sawmills) will be addressed by the project. This will enable a series of services, ranging from stumpage price evaluation, pre-selling, forest harvest planning, logistic management, real-time information stream, timber and biomass purchasing on web platform.
The integration and post-processing of data collected by SLOPE will be available for further optimization of the “mountain forest models” and finally silviculture routines.
Forests play a significant role in the mountain economy by ensuring employment in economic fields such as planting, maintenance, harvesting, wood processing, biomass and paper production, among others. Proper utilization of mountainous forests is critical to ensure sustainability, protect the soil from erosion, conserve water and maintain a rich biodiversity.
Mountain forest management and forest utilization differ from management schemes elsewhere mainly with respect to the temporal sequences of vegetative succession, the remoteness of the forests, their limited accessibility, and the hydro-geological constraints. Forest harvesting in mountain conditions poses a series of organizational and technical problems. Working on steep terrains, and in areas typically served by a relatively poor road network, makes the cost of forest operations higher, and the consequent product (assortments) competitiveness is lower, when compared to similar products from other areas.
Forestry operations in mountain areas are seldom performed by the harvester/forwarder system, being the sector still characterized by manual felling, while extraction of timber (or whole trees) is done, only in the most evolved cases, by cable cranes. Due to the limits posed by steep terrain conditions, typical poor road network of mountain areas, limited storage and operational room (pads, roadside areas, yards, etc.) those harvesting and extracting systems are more expensive and less flexible compared to the cut-to-length (CTL) systems based on wheeled machines, common in flatland forests in European Nordic Countries.
A higher degree of mechanization in steep terrain conditions, coupling cable crane and processor, can lead to significant improvement, particularly when whole-tree extraction techniques are applied. In this case timber production costs can be reduced of about 30%, while improving efficiency and work safety. Furthermore the use of the processor at landing makes available large quantities of residual biomass, which becomes a further assortment. Nevertheless this work system requires expert tree marking and directional felling and is still limited by long setting up operations and limited storage areas, which increase overall costs. This is the gap that SLOPE will try to fill in, by developing an integrated system that allows optimization of the forest production in mountain areas.
A Forest Information Model will be developed, integrating information from remote sensing, UAVs (Unmanned Aerial Vehicles) and TLS (terrestrial laser scanner) surveying systems to support macro and local analysis of forest resources in mountain areas. This will enable to evaluate the accessibility for and efficiency of harvesting technologies in mountain forests, supporting planning and logistics management of forest operations.
An intelligent interaction among all the operators involved in forest harvesting in steep terrain will be created by the integration of targeted intelligent systems in the cable crane/processor head/truck. Along the production chain, quality and quantity data will be measured by a number of sensors for the assessment of the assortment variety. Different traceability systems will be used, to trace the material, from the site throughout the whole supply chain.
Integration of information about material origin, quality and availability in a unique system, accessible online and available in real time to a series of operators (e.g. logistic operators, brokers, forest owners, sawmills) will enable a series of services, ranging from stumpage price evaluation, pre-selling, forest harvest planning, logistic management, real-time information stream, timber and biomass purchasing on web platform.
Finally, data collected by the SLOPE system can be used in the “mountain forest models” to optimize silviculture routines.
The SLOPE framework will be applied, tested and validated in at least two test sites representing two different operative scenarios (whole tree extraction and cut-to-length extraction).
- The first scenario, located on a fertile stand, focuses on extraction of whole trees considering that the removal of branches, tops, needles/leaves will have no significant impact on the nutrient and organic matter balance. Within this pilot the whole-tree system is tested with the cable crane and processor combination, thus allowing maximum degree of automation and operational safety and efficiency.
- The second scenario, located on a less fertile stand or in a sensitive area, doesn’t focus on the whole tree system. Instead, the pilot will use a cut-to-length system with manual felling and partial processing in the forest. This system is less efficient and it exposes the operators to higher working risks; however it ensures the highest level of soil protection and nutrient balance by leaving tops, branches, needles/leaves and defective wood in the forest. When possible, stems is left entire, or divided in multiples of the final timber assortments, reducing at a minimum the work in forest and increasing the average size of the single piece handled (and thus work productivity). Log quality indicators will be provided to the cloud database by the same processor unit, acting as a loader, sensor carrier and log marking unit.
The testing sites are selected in two Alpine countries, namely Austria, Italy and Norway as non-Alpine mountain country in order to test the reliability of the developed system in different environments (work organization, infrastructures, topography, etc.) linked by the same dominant tree species (Norway spruce).
This section presents an outline of the SLOPE system in a typical case scenario. This helps to better appreciate the issues addressed as well as the technological development and benefits that will result from the project.
In a mountain region a forest area is planned to be harvested during the next season. The historical series and up-to-date remote sensing data, and other relevant information related to the area (i.e. local land-use plans, cadastral maps, other thematic maps) will be loaded into the system. Remote sensing analysis of multi-spectral images will be performed in order to extract macro information of the forest (biomass volume, spectral vegetation indices –SVIs-, growth rate). Furthermore a combination of UAV or Vehicle Mounted LIDAR (Light Detection and Ranging) and TLS surveys will be planned and carried out some weeks before the scheduled harvesting operations.
The processing of the acquired data generates the Digital Forest Model (DFM), where each tree is a single object in a Geodatabase providing Greater Product Knowledge. The DFM will support the forest planners for multiple criteria decision analysis (MCDA), to plan and simulate the harvesting operation, taking into account all possible constraints (e.g. infrastructural, geomorphological, etc.) and optimization procedures (e.g. joint forest management and coordination of harvesting of adjacent parcels owned by different landowners). The DFM will also support specific logistical decisions, such as the selection of the optimal cable crane positioning and set-up. As an added application, the DFM could be used as a tool for pre-selling procedures, where one or more customers commit to buy the whole lot upon an estimation of the volume and the timber assortments potentially available.
The DFM is also used as a pre-marking tool for the selection of trees to be felled. During field inspection, the forester validates or corrects the decisions, and marks the selected trees with RFID tags and high-visibility paint. The forester can add further information into the DFM database (virtual marking) and transfer data into each RFID tag. Marked trees are felled by a chainsaw operator. If the tree is to be extracted as whole plant, no further operations are required. If it has to be processed on the spot (debranched and crosscut), each resulting log or tree section must be identified with an additional tag, relating it to the original plant. Trees or logs are extracted by cable crane, whose carriage will read the RFID tag and measure the load weight while lifting and moving it to the landing area. Here the processor will finally reduce the trees into logs, defining the quality class of each piece with built-in sensors (also in the case of log extraction). The set of operators and machines provides real time data about quantity (volume and weight) and quality of each assortment including residues to the centralized Forest Inventory System (FIS). Information about the work rate and the volume of material in the storage areas will enable an efficient logistic, stocking and delivery of all wood products, while minimizing the operational delay time. The tracking system ensures the traceability of forest products along the whole supply chain. As such, customers could purchase on the FIS timber lots (as a whole or as discrete units of truck loads) while they are made available at the landing or at roadside. This would result in a virtual elimination of timber stocking at sawmill yards, responding to a tendency already on-going, and allowing a significant reduction of overall costs (yard, handling and transport costs).
The objectives of SLOPE are manifold, interrelated and consequential:
to deliver an integrated forest surveying system for mountain areas
- for a multi-scale description of the spatial and physical characteristics of the forest
- to provide data for a Digital Forest Model to support operation and resource planning
to formalize a model-based forest operational planning system for mountain areas
- to plan harvesting operations in steep terrain
- for optimization of the logistics at the short and mid/long term
to integrate novel intelligent systems in harvesting machines operating in mountain areas
- to guarantee easy and safe use of machines and monitor machine performance
- to measure characteristics (quality indicators) and guarantee traceability of the harvested material
to deliver a multi-sensor model-based quality control system for mountain forest production
- to improve and automatize segregation (commercial grading) of forest production
- to provide data for refinement of forest management plans and silvicultural routines
to customize an enterprise resource planning (ERP) system for mountain forest
- to provide a multi-stakeholder platform for coordinated management of the forest and a lean supply chain
- to support mid/long term forest management
to integrate and validate the developed systems in real-life scenarios
- to ensure robustness and reliability of the developed systems
- to ensure rapid introduction of developed solutions and the highest impact on stakeholder community
Development of an integrated forest surveying system for mountain areas:
SLOPE aims at delivering an integrated system for a multi-level survey of forests in mountain areas (WP2). The system will allow collection, classification and integration of geospatial and geo-spectral data from remote sensing satellite sensors, UAV and Vehicle Mounted LIDAR. Collected data will be geo- referenced, combined and harmonized and eventually used to monitor the health of the forest, growth rate, brush cutting, weather damage, harvest planning and planting. Off the shelf Terrestrial Laser Scanning (TLS) will be used then for on-field digital surveying, in order to provide foresters with detailed information, about the vegetation, before and after harvesting.
The sensing data are used to stratify the forest into optimal ground sampling locations. The combined data are processed to provide an accurate estimation as to the potential log products in the proposed harvest area. The resultant forest model will be integrated to a constraint modelling platform that includes typical mountainous constraints such as terrain, harvesting option and available markets.
An important component of the SLOPE integrated surveying system is the data fusion formal framework that will be able to align data originated from different sources.
Development of a model-based forest operations planning system for mountain areas:
A Forest Information Model will integrate spatial information, such as Digital Terrain Models (DTM), Digital Surface Models (DSM) and Canopy Models (DCM), together with multi- sensor data and resources from existing databases and forest management plans.
The model intends to improve planning of timber and biomass harvesting in steep terrain. For this scope, SLOPE will develop a planning tool that analyses and improves supply networks for wood supply chain. Within this network potential sources (harvesting sites), storage places, infrastructure (cable lanes, forest roads) and sinks (saw and paper mills, biomass plant) will be identified. The model developed in SLOPE optimizes the material flow between sources and sinks and suggests adequate machines and equipment as well as forest infrastructure to be used. As additional result, the system will also generate information useful for forest road development and maintenance. 3D visualization of forest landscapes will be used to visualize stand succession, landscape transformation, and regional planning, and to improve decision-making processes and understanding of forest management in general. Combining 3D visualization of trees and ecosystem information with management practices, SLOPE can create realistic visual scenarios of forest management.
Integration of novel intelligent harvesting systems operating in mountain areas:
For a further improvement of harvesting operations in mountainous forests, the planning tools will be matched with an innovative human-machine technology delivering a more optimized control of harvesting tools and machines used in mountain areas (WP3). Dedicated Human Machine Interfaces (HMI) will ensure easier and safer use of harvesting machines, particularly by providing an increased control of machine interactions. Intelligent systems will be included in the cable crane and in the processor head equipment, in order to support automatic/continuous acquisition of all available resource characteristics. For this purpose, an original NDT methodology will be developed (WP4), including dedicated sensors, signal processing algorithms and data mining software.
Special care will be taken in processing steps to assure full traceability of wood and at the same time maximize the wood usage. The tracking systems will be adaptable to the different harvesting scenarios in mountainous areas (i.e whole tree extraction vs. pre-processing of the tree on the spot).
Information system for transport management with new portable communication techniques (fleet management equipment including GPS in form of mobile terminals) will be integrated for optimization of material flows, stock accounting and controlling transportation distances for invoicing.
Development of a multi-sensor model-based quality control system for mountain forest production:
Models incorporating material parameters extracted from multi-source data acquired during surveying and harvesting operations will be implemented, following an incremental approach (from the standing tree to the felled tree and the log).
Calibration values will be incorporated into the models from measurements taken along different stages of the supply chain.
Threshold values and variability models of different properties will be then defined for the different end-uses (i.e. wood processing industries, bioenergy production). This will contribute to the development of automated pre-sort and grading systems and the improvement of existing classification standards.
The quality parameters acquired during harvesting, together with site parameters from the DFMs will provide fundamental information for the development and refinement of precision forestry models.
Customization of an enterprise resource planning (ERP) system for mountain forest:
SLOPE will develop a unique system integrating information about material origin, quality and availability that will be accessible online and in real-time to a series of users (including logistic operators, brokers, end-users, and forest owners) enabling online stock exchange (WP5).
Sharing information before, during and after harvesting will enable real-time computing of economically crucial parameters, such as quantity and quality indices of the different assortments (including biomass) present in a stand (stumpage values) or accumulated in a buffer and ready to be transported. All the information will be useful for:
- Forest owners and wood buyers, who can collaborate, to simulate and optimize the potential flow of log products from the forest.
- Planning and monitoring of size, location and moving schedule for storages and buffers.
- Optimization of the storage and transportation procedures.
- Simplifying online purchasing/invoicing of industrial timber (and biomass).