GIS in Lithuanian Forest Inventory – 20 Years' Experience

Bikuvienė, Ina; Tiškutė-Memgaudienė, Daiva

doi:10.15308/sinteza-2016-208-212

Cited by 3 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Remote sensing and forest management has long been associated in Lithuania only in the context of forest inventory related application (Bikuvienė & Tiškutė-Memgaudienė, 2016;Mozgeris, 2008;Mozgeris et al, 2008). Stand-wise forest inventories were completely based on application of orthophotos, Figure 2.…”

Section: Resultsmentioning

confidence: 99%

Open geo-spatial data for sustainable forest management: Lithuanian case

Tiškutė-Memgaudienė¹,

Mozgeris²,

Gaižutis³

2020

Research for Rural Development

View full text Add to dashboard Cite

In Lithuania, forests are managed by Lithuanian State Forest Enterprise, municipalities, ministries, etc. and private forest owners. About 50% of all forest land is State importance, privately owned forests cover 40% of forest land, and about 10% of forest land belongs to forests reserved for restitution. Forest management of private ownership force many challenges, because private forest owners are people, who have purchased or received the property after restitution, and often lacks knowledge about forest resources, its dynamics and sustainable forest management. As remote sensing is a valuable source for forest monitoring, because it provides periodic data on forest resource and condition status, these methods are gaining increased attention worldwide. In this context, more scientific efforts are made at developing remote sensing derived geo-spatial data services for sustainable forest management through a web service platform, which would integrate geo-information into daily decision making processes and operation for private forest owners. This article presents a review of privately owned forests’ statistics, questionnaire-based survey about GIS usage and demand for forest owners in Lithuania and links available sources of open geo-spatial data useful for sustainable forest management.

show abstract

Section: Resultsmentioning

confidence: 99%

Open geo-spatial data for sustainable forest management: Lithuanian case

Tiškutė-Memgaudienė¹,

Mozgeris²,

Gaižutis³

2020

Research for Rural Development

View full text Add to dashboard Cite

show abstract

“…Following the requirements for SFC database, the accuracy of clearly identifiable features, such as intersection points of roads, drainage canals, etc. may not exceed 5 m [6]. Even though there were formal requirements to update the FSC database permanently registering all changes due to silvicultural activities, in fact the solution used was to replace all information in the areas, where the stand-wise forest inventories took place, usually every 10 years [6].…”

Section: Environmental Data Science Sessionmentioning

confidence: 99%

“…may not exceed 5 m [6]. Even though there were formal requirements to update the FSC database permanently registering all changes due to silvicultural activities, in fact the solution used was to replace all information in the areas, where the stand-wise forest inventories took place, usually every 10 years [6]. Thus, it was soon realized, that the position of by-definition stable object in the forest, like the block lines, road infrastructures or hydrographic network changes with the stand-wise forest inventories [4].…”

Section: Environmental Data Science Sessionmentioning

confidence: 99%

Mapping Forest Infrastructure – Comparing Different Data Acquisition Techniques

Mozgeris¹

2020

Proceedings of the International Scientific Conference - Sinteza 2020

Self Cite

View full text Add to dashboard Cite

Forest resource information usually change over time, what is monitored by forest inventories using different methods. Forest infrastructures, such like roads, hydrographic network, other linear facilities are relatively stable in time. Nevertheless, conventional forest inventories in Lithuania map forest infrastructures every time the survey of forest resources takes place. Assuming, that different and rapidly developing forest stand inventory techniques are applied each time, there are significant changes in location of forest infrastructures observed. Repeated inventories of such objects usually assume increased inventory costs and introduce significant disorder when aiming for permanent forest management. This study investigates the opportunities of different data acquisition techniques for mapping relatively stable over time forest infrastructure objects. We compare classification and geometric accuracies of forest infrastructures achieved using (i) ground geodetic survey, (ii) available from state maintained geo-referenced background database, which has been created using interpretation of aerial images, (iii) extracted from 3D airborne laser scanning point clouds and (iv) very high-resolution World-View-1 satellite images. The key finding is that costly and time-consuming ground data collection approaches may be successfully substituted by remote sensing based data collection, which delivers compatible data contents for significantly lower costs.

show abstract