Can rich-habitat or cultural landscape management be ensured by private agents?

In brief, one can state that it is a rare situation that a farmer can ensure agri-environmental goods at a social optimum in a free market at a maximum welfare, unless the farmer himself has high nonmonetary values. 

One set of agricultural and forestry practices and standards including sparing an extra area for biodiversity or scenery are not optimal for an entire country. The key tradeoffs should be quantified locally. 

The situation may be solved with the help of collaboration between private agents, society, and local governments, i.e., environmental community-based public-private partnerships.

At the same time, the key area of interaction is not the private agents, but rural areas as a complex of relations and core place for the agricultural and forestry activities, at participants´ and habitats´ level. The engagement and support of municipalities is an extremely important factor for the successful projects.

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Combination of camera relascope-based field data and medium-resolution satellite imagery gives accurate enough results for forest resources assessment

MDPI (Remote Sens., Volume 10, Issue 11 (November 2018) – the scientific journal based in Basel, Switzerland, published an article jointly prepared by RusFor Consult Oy Ab, LUT University and Arbonaut Ltd. The study considers a forest inventory for the mean volume, basal area, and coniferous/deciduous mapping of a large territory in central Siberia (Russia), employing a camera relascope at arbitrary sized sample plots and medium resolution satellite imagery Landsat 8.

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New article in Siberian Journal of Forest Science by RusFor Consult

RusFor has made a study on remote sensing technique for mean volume estimation obtained using a small-sized unmanned aerial vehicle (sUAV) and a high-resolution photogrammetric digital surface model (DSM). An innovative technology for field measurements (Trestima) was also applied in the research.

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We came to a conclusion that the UAV and Trestima are reliable and potentially cost-effective means of forest data acquisition with good prospects for operational forest inventory.

Research on preharvest efficiency of different forest inventory tools

The study conducted by RusFor specialists compares the accuracy of forest attribute estimates, delivered by airborne laser scanning data, conventional stand-wise forest inventory in the form of Forest Management Plan and Trestima forest inventory app. The measurements are validated by actual results of commercial harvesting, measured and registered by a harvester’s measurement system during logging.

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Trestima turned out to be the most accurate and effective in predicting preharvest stand characteristics, stand-level-wise.