Using mixed integer programming and airborne laser scanning to generate forest management units

Author(s):  
Adrián Pascual ◽  
Sándor F. Tóth
Silva Fennica ◽  
2021 ◽  
Vol 55 (4) ◽  
Author(s):  
Hans Ørka ◽  
Endre Hansen ◽  
Michele Dalponte ◽  
Terje Gobakken ◽  
Erik Næsset

Tree species composition is an essential attribute in stand-level forest management inventories and remotely sensed data might be useful for its estimation. Previous studies on this topic have had several operational drawbacks, e.g., performance studied at a small scale and at a single tree-level with large fieldwork costs. The current study presents the results from a large-area inventory providing species composition following an operational area-based approach. The study utilizes a combination of airborne laser scanning and hyperspectral data and 97 field sample plots of 250 m collected over 350 km of productive forest in Norway. The results show that, with the availability of hyperspectral data, species-specific volume proportions can be provided in operational forest management inventories with acceptable results in 90% of the cases at the plot level. Dominant species were classified with an overall accuracy of 91% and a kappa-value of 0.73. Species-specific volumes were estimated with relative root mean square differences of 34%, 87%, and 102% for Norway spruce ( (L.) Karst.), Scots pine ( L.), and deciduous species, respectively. A novel tree-based approach for selecting pixels improved the results compared to a traditional approach based on the normalized difference vegetation index.22Picea abiesPinus sylvestris


2020 ◽  
Vol 82 (4) ◽  
pp. 352-358
Author(s):  
Vitor Antunes Martins da Costa ◽  
Adeliton da Fonseca de Oliveira ◽  
Jhonathan Gomes dos Santos ◽  
Alex Augusto Abreu Bovo ◽  
Danilo Roberti Alves de Almeida ◽  
...  

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1724
Author(s):  
Cristiano Rodrigues Reis ◽  
Eric Bastos Gorgens ◽  
Danilo Roberti Alves de Almeida ◽  
Carlos Henrique Souza Celes ◽  
Jacqueline Rosette ◽  
...  

(1) Background: Forests throughout the world are managed to fulfil a range of commercial and ecosystem services. The same applies to managed areas of the Amazon forest. We explore a method of sustainable forest management (SFM) which anticipates the result of processes of natural mortality of large, mature trees that could fall and damage their neighbors. Collecting all the information required for planning logging in the Brazilian Amazon is, currently, a hard, time-consuming and expensive task. (2) Methods: This information can be obtained more quickly, accurately and objectively by including airborne laser scanning (ALS) products in the operational plan. We used ALS point clouds to isolate emergent crowns from the canopy height model. Then, we performed field work to validate the existence of these trees, and to understand how many commercial trees (tree diameter ≥ 50 cm) we identified by orienting the trees search through the emergent canopy model. (3) Results: We were able to detect 184 (54.4%) trees from 338 field-recorded individuals in 20 plots (totaling 8 ha). Of the detected trees, 66 individuals were classified as having potential for commerce. Furthermore, 58 individuals presented the best stem quality for logging, which represents more than seven high quality commercial trees per hectare. The logistic regression showed that the effects that positively influence the emergent crown formation are strongly presented in the commercial species. (4) Conclusions: Using airborne laser scanning can improve the SFM planning in a structurally complex, dense and mixed composition tropical forest by reducing field work in the initial stages of management. Therefore, we propose that ALS operational planning can be used to more efficiently direct field surveys without the need for a full census.


2017 ◽  
Vol 0 (0) ◽  
Author(s):  
Anamaria Roman ◽  
Tudor-Mihai Ursu ◽  
Sorina Fărcaş ◽  
Vlad-Andrei Lăzărescu ◽  
Coriolan Horaţiu Opreanu

Author(s):  
V.F. Kovyazin ◽  
◽  
K.P. Vinogradov ◽  
A.A. Kitcenko ◽  
Е.А. Vasilyeva

Nowadays the latest non-contact methods and technologies for studying the forest fund are being developed for forest monitoring improvement, forest lands assessment and their cadastral registration. It is the use of airborne laser scanning (ALS) in forest inventory that is designed to solve the challenges forest management facing. Laser scanning is the only method of collecting data on the real surface covered with forest vegetation, which allows to obtain data on the shape, location and reflectivity of the studied forest objects. The result of ALS is a 3D array of laser reflections with a density of up to several dozens of points per 1 m2 and accuracy of determining their coordinates of less than 10 cm in plan and height. Various imported scanning systems are used for surveying. The ALS of the Earth’s vegetation cover is superior to all existing technologies for assessing the quantitative and qualitative parameters of forest stands in a set of characteristics. This method of assessment and inventory of forests has no competitors in the field of monitoring and valuation of forest stands. It also has sufficient accuracy in mapping woody vegetation, up to the tree survey of forested lands. The article proposes a method for determining valuation indicators: species composition, density, stock, height and diameter of forest stands according to the results of ALS in the forest area of the Vsevolozhsk district (Leningrad region). The species composition and density were determined by horizontal projections of tree crowns. The heights of the trees were determined using the Global Mapper software, and their average diameter was found using the diameter and height relationship equations known in forest valuation. The planting stock was calculated using the equations of Dementiev, Dentsin and G. Cuvier. It was found that the results of determining the valuation indicators by means of ALS can be used in forest monitoring along with the data of visual valuation, since the obtained information on the forest stand stays within the limits of permissible errors specified in the forest management instruction.


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