7 research outputs found
Particular issues of analysis of collisions of the current land legislation
The article analyzes the main legal conflicts that arose as a result of the adoption of changes to the land legislation of Ukraine during 2020-2021.
It was found that the transfer of land for use requires a permit for the development of technical documentation on land management to establish (restore) the boundaries of land in kind (on the ground). At the same time, there is another conflict - the specified technical documentation performs the same function as the land management project for the allocation of land for use.
As a result of the analysis of amendments to the Law of Ukraine "On Land Management", it is established that the wording of the text of the article in terms of the basis of work has two interpretations, the first of which concerns privately owned land, and the second - state and municipal land in use.
In addition, it was found that in the latest versions of regulations, the terms "owner" and "owner (manager)" meet next to each other, which allows us to state that the authors of the regulation aimed to separate the disposal of private land from one on the one hand and state and communal - on the other.
Key words: legislative acts, land plots, land management, division (association) of land plots, privatization of land plots
ΠΠΏΡΠΈΠΌΡΠ·Π°ΡΡΡ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ Ρ Π²ΠΎΠ΄Ρ Π·Π°Π»ΠΈΡΠΊΠΎΠ²ΠΈΡ ΠΊΡΠ»ΡΠΊΠΎΡΡΠ΅ΠΉ ΠΏΠ΅ΡΡΠΈΡΠΈΠ΄ΡΠ² ΡΠΈΡΡΠ΅ΠΌΠΈ Π·Π°Ρ ΠΈΡΡΡ ΠΊΠ°ΡΡΠΎΠΏΠ»Ρ
Introduction. One of the main agricultural crops of Ukraine is the potato β the most favorite and indispensable food product for millions of our compatriots. One of the most important conditions for the integrated protection of crops is the control of the correct pesticide formulations application, the element of which is to determine the content of their active substances in the objects of the environment.The aim of the study β to develop a method for the analytical determination of thiamethoxam, imidacloprid, metrubuzine, dimetomorph, azoxystrobin, oxathiapiproline and famoxadone in water in their co-presence.Research Methods. The method of reverse-phase high-performance liquid chromatography with ultraviolet detection was used. Statistical processing of the results was carried out using the package of statistical programs IBM SPSS Statistics Base v.22 and MS Excel.Results and Discussion. As a result of the conducted laboratory researches, the most optimal chromatographic conditions were selected, including mobile phase (acetonitrile + water in the ratio (50+50) and (70+30)) using gradient elution. The optimal wavelength for the research was 245 nm. The retention time (min) for: thiamethoxamis 3.5Β±0.1; imidacloprid β 4.1Β±0.1; metrubuzin β 6.3Β±0.1; E isomer of dimethomorph β 8.5Β±0.1; Z isomer of dimethomorph β 8.9Β±0.1; azoxystrobin β 9.5Β±0.1; oxathiapiroline β 10.2Β±0.1 and famoxadone β 12.1Β±0.1. We developed the optimal conditions for the chromatographic determination of thiamethoxam, imidacloprid, metribuzin, dimethomorph, azoxystrobin, oxathiapiproline and famoxadone in a joint presence in the water sample: wavelength β 245 nm, gradient elution conditions selected for different gradient profiles of the two components of the mobile phase, acetonitrile and water 50+50; 70+30; 50+50).Conclusion. The optimal conditions of extraction and chromatography of the studied substances at a copresence in the water sample provide control of their content with a limit of quantitative determination of each compound of 0.0002 mg/dm3.ΠΡΡΡΠΏΠ»Π΅Π½ΠΈΠ΅. ΠΠ΄Π½ΠΎΠΉ ΠΈΠ· ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΡΠ΅Π»ΡΡΠΊΠΎΡ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΡΡ
ΠΊΡΠ»ΡΡΡΡ Π£ΠΊΡΠ°ΠΈΠ½Ρ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΊΠ°ΡΡΠΎΡΠ΅Π»Ρ β ΡΠ°ΠΌΡΠΉ Π»ΡΠ±ΠΈΠΌΡΠΉ ΠΈ Π½Π΅Π·Π°ΠΌΠ΅Π½ΠΈΠΌΡΠΉ ΠΏΠΈΡΠ΅Π²ΠΎΠΉ ΠΏΡΠΎΠ΄ΡΠΊΡ Π΄Π»Ρ ΠΌΠΈΠ»Π»ΠΈΠΎΠ½ΠΎΠ² Π½Π°ΡΠΈΡ
ΡΠΎΠΎΡΠ΅ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΈΠΊΠΎΠ². ΠΠ΄Π½Π° ΠΈΠ· Π²Π°ΠΆΠ½Π΅ΠΉΡΠΈΡ
ΡΡΠ»ΠΎΠ²ΠΈΠΉ ΠΈΠ½ΡΠ΅Π³ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π·Π°ΡΠΈΡΡ ΡΠ΅Π»ΡΡΠΊΠΎΡ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΡΡ
ΠΊΡΠ»ΡΡΡΡ β ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ Π·Π° ΠΏΡΠ°Π²ΠΈΠ»ΡΠ½ΡΠΌ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ ΠΏΠ΅ΡΡΠΈΡΠΈΠ΄Π½ΡΡ
ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠΎΠ² Π² ΡΠΈΡΡΠ΅ΠΌΠ΅ Ρ
ΠΈΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π·Π°ΡΠΈΡΡ, ΡΠ»Π΅ΠΌΠ΅Π½ΡΠΎΠΌ ΠΊΠΎΡΠΎΡΠΎΠΉ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΈΡ
Π΄Π΅ΠΉΡΡΠ²ΡΡΡΠΈΡ
Π²Π΅ΡΠ΅ΡΡΠ² Π² ΠΎΠ±ΡΠ΅ΠΊΡΠ°Ρ
ΠΎΠΊΡΡΠΆΠ°ΡΡΠ΅ΠΉ ΡΡΠ΅Π΄Ρ.Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ β ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°ΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΡ Π°Π½Π°Π»ΠΈΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΡΠΈΠ°ΠΌΠ΅ΡΠΎΠΊΡΠ°ΠΌΠ°, ΠΈΠΌΠΈΠ΄Π°ΠΊΠ»ΠΎΠΏΡΠΈΠ΄Π°, ΠΌΠ΅ΡΡΠΈΠ±ΡΠ·ΠΈΠ½Π°, Π΄ΠΈΠΌΠ΅ΡΠΎΠΌΠΎΡΡΠ°, Π°Π·ΠΎΠΊΡΠΈΡΡΡΠΎΠ±ΠΈΠ½Π°, ΠΎΠΊΡΠ°ΡΠΈΠ°ΠΏΠΈΠΏΡΠΎΠ»ΠΈΠ½Π° ΠΈ ΡΠ°ΠΌΠΎΠΊΡΠ°Π΄ΠΎΠ½Π° Π² Π²ΠΎΠ΄Π΅ ΠΏΡΠΈ ΠΈΡ
ΡΠΎΠ²ΠΌΠ΅ΡΡΠ½ΠΎΠΌ ΠΏΡΠΈΡΡΡΡΡΠ²ΠΈΠΈ.ΠΠ΅ΡΠΎΠ΄Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ. ΠΡΠΈΠΌΠ΅Π½Π΅Π½ ΠΌΠ΅ΡΠΎΠ΄ ΠΎΠ±ΡΠ°ΡΠ½ΠΎ-ΡΠ°Π·ΠΎΠ²ΠΎΠΉΒ Π²ΡΡΠΎΠΊΠΎΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠΉ ΠΆΠΈΠ΄ΠΊΠΎΡΡΠ½ΠΎΠΉ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΠΈ Ρ ΡΠ»ΡΡΡΠ°ΡΠΈΠΎΠ»Π΅ΡΠΎΠ²ΡΠΌ Π΄Π΅ΡΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ. Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΡΡ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΏΠ°ΠΊΠ΅ΡΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌ IBM SPSS Statistics Base v.22 ΠΈ MS ExΡel.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈ ΠΎΠ±ΡΡΠΆΠ΄Π΅Π½ΠΈΠ΅. Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΡ
Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠ½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΠΏΠΎΠ΄ΠΎΠ±ΡΠ°Π½Ρ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠ΅ ΡΡΠ»ΠΎΠ²ΠΈΡΒ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ ΠΏΠΎΠ΄Π²ΠΈΠΆΠ½Π°Ρ ΡΠ°Π·Π° (Π°ΡΠ΅ΡΠΎΠ½ΠΈΡΡΠΈΠ»+Π²ΠΎΠ΄Π° Π² ΡΠΎΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ (50+50) ΠΈ (70+30)) Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π³ΡΠ°Π΄ΠΈΠ΅Π½ΡΠ½ΠΎΠ³ΠΎ ΡΠ»ΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ. ΠΠΏΡΠΈΠΌΠ°Π»ΡΠ½Π°Ρ Π΄Π»ΠΈΠ½Π° Π²ΠΎΠ»Π½Ρ ΠΏΡΠΈ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΡΠΎΡΡΠ°Π²Π»ΡΠ»Π° 245 Π½ΠΌ. ΠΡΠ΅ΠΌΡ ΡΠ΄Π΅ΡΠΆΠΈΠ²Π°Π½ΠΈΡ (ΠΌΠΈΠ½) ΡΠΎΡΡΠ°Π²Π»ΡΠ»ΠΎ: ΡΠΈΠ°ΠΌΠ΅ΡΠΎΠΊΡΠ°ΠΌΠ° β 3,5Β±0,1; ΠΈΠΌΠΈΠ΄Π°ΠΊΠ»ΠΎΠΏΡΠΈΠ΄Π° β 4,1Β±0,1; ΠΌΠ΅ΡΡΠΈΠ±ΡΠ·ΠΈΠ½Π° β 6,3Β±0,1; Z ΠΈΠ·ΠΎΠΌΠ΅ΡΠ° Π΄ΠΈΠΌΠ΅ΡΠΎΠΌΠΎΡΡΠ° β 8,5Β±0,1; Z ΠΈΠ·ΠΎΠΌΠ΅ΡΠ° Π΄ΠΈΠΌΠ΅ΡΠΎΠΌΠΎΡΡΠ° β 8,9Β±0,1; Π°Π·ΠΎΠΊΡΠΈΡΡΡΠΎΠ±ΠΈΠ½Π° β 9,5Β±0,1; ΠΎΠΊΡΠ°ΡΠΈΠ°ΠΏΠΈΠΏΡΠΎΠ»ΠΈΠ½Π° β 10,2Β±0,1; ΡΠ°ΠΌΠΎΠΊΡΠ°Π΄ΠΎΠ½Π° β 12,1Β±0,1. Π Π°Π·ΡΠ°Π±ΠΎΡΠ°Π½Ρ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠ΅ ΡΡΠ»ΠΎΠ²ΠΈΡ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΡΠΈΠ°ΠΌΠ΅ΡΠΎΠΊΡΠ°ΠΌΠ°, ΠΈΠΌΠΈΠ΄Π°ΠΊΠ»ΠΎΠΏΡΠΈΠ΄Π°, ΠΌΠ΅ΡΡΠΈΠ±ΡΠ·ΠΈΠ½Π°, Π΄ΠΈΠΌΠ΅ΡΠΎΠΌΠΎΡΡΠ°, Π°Π·ΠΎΠΊΡΠΈΡΡΡΠΎΠ±ΠΈΠ½Π°, ΠΎΠΊΡΠ°ΡΠΈΠ°ΠΏΠΈΠΏΡΠΎΠ»ΠΈΠ½Π° ΠΈ ΡΠ°ΠΌΠΎΠΊΡΠ°Π΄ΠΎΠ½Π° ΠΏΡΠΈ ΡΠΎΠ²ΠΌΠ΅ΡΡΠ½ΠΎΠΌ ΠΏΡΠΈΡΡΡΡΡΠ²ΠΈΠΈ Π² ΠΏΡΠΎΠ±Π΅ Π²ΠΎΠ΄Ρ (Π΄Π»ΠΈΠ½Π° Π²ΠΎΠ»Π½Ρ β 245 Π½ΠΌ), ΠΏΠΎΠ΄ΠΎΠ±ΡΠ°Π½Ρ ΡΡΠ»ΠΎΠ²ΠΈΡ Π³ΡΠ°Π΄ΠΈΠ΅Π½ΡΠ½ΠΎΠ³ΠΎ ΡΠ»ΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΈ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΠΏΡΠΎΡΠΈΠ»ΡΡ
Π³ΡΠ°Π΄ΠΈΠ΅Π½ΡΠ° ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΉ Π΄Π²ΡΡ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠΎΠ² ΠΏΠΎΠ΄Π²ΠΈΠΆΠ½ΠΎΠΉ ΡΠ°Π·Ρ β Π°ΡΠ΅ΡΠΎΠ½ΠΈΡΡΠΈΠ»Π° ΠΈ Π²ΠΎΠ΄Ρ (50+50; 70+30; 50+50).ΠΡΠ²ΠΎΠ΄. Π Π°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΡΠ΅ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠ΅ ΡΡΠ»ΠΎΠ²ΠΈΡ ΡΠΊΡΡΡΠ°ΠΊΡΠΈΠΈ ΠΈ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΡΡ
Π²Π΅ΡΠ΅ΡΡΠ² ΠΏΡΠΈ ΡΠΎΠ²ΠΌΠ΅ΡΡΠ½ΠΎΠΌ ΠΏΡΠΈΡΡΡΡΡΠ²ΠΈΠΈ Π² ΠΏΡΠΎΠ±Π΅ Π²ΠΎΠ΄Ρ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°ΡΡ ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ ΠΈΡ
ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ Ρ ΠΏΡΠ΅Π΄Π΅Π»ΠΎΠΌ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΊΠ°ΠΆΠ΄ΠΎΠ³ΠΎ ΡΠΎΠ΅Π΄ΠΈΠ½Π΅Π½ΠΈΡ 0,0002 ΠΌΠ³/Π΄ΠΌ3.ΠΡΡΡΠΏ. ΠΠ΄Π½ΡΡΡ Π· ΠΎΡΠ½ΠΎΠ²Π½ΠΈΡ
ΡΡΠ»ΡΡΡΠΊΠΎΠ³ΠΎΡΠΏΠΎΠ΄Π°ΡΡΡΠΊΠΈΡ
ΠΊΡΠ»ΡΡΡΡ Π£ΠΊΡΠ°ΡΠ½ΠΈ Ρ ΠΊΠ°ΡΡΠΎΠΏΠ»Ρ β Π½Π°ΠΉΡΠ»ΡΠ±Π»Π΅Π½ΡΡΠΈΠΉ ΡΠ° Π½Π΅Π·Π°ΠΌΡΠ½Π½ΠΈΠΉ Ρ
Π°ΡΡΠΎΠ²ΠΈΠΉ ΠΏΡΠΎΠ΄ΡΠΊΡ Π΄Π»Ρ ΠΌΡΠ»ΡΠΉΠΎΠ½ΡΠ² Π½Π°ΡΠΈΡ
ΡΠΏΡΠ²Π²ΡΡΡΠΈΠ·Π½ΠΈΠΊΡΠ². ΠΠ΄Π½Π° Π· Π½Π°ΠΉΠ²Π°ΠΆΠ»ΠΈΠ²ΡΡΠΈΡ
ΡΠΌΠΎΠ² ΡΠ½ΡΠ΅Π³ΡΠΎΠ²Π°Π½ΠΎΠ³ΠΎ Π·Π°Ρ
ΠΈΡΡΡ ΡΡΠ»ΡΡΡΠΊΠΎΠ³ΠΎΡΠΏΠΎΠ΄Π°ΡΡΡΠΊΠΈΡ
ΠΊΡΠ»ΡΡΡΡ β ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ Π·Π° ΠΏΡΠ°Π²ΠΈΠ»ΡΠ½ΠΈΠΌ Π·Π°ΡΡΠΎΡΡΠ²Π°Π½Π½ΡΠΌ ΠΏΠ΅ΡΡΠΈΡΠΈΠ΄Π½ΠΈΡ
ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΡΠ² Ρ ΡΠΈΡΡΠ΅ΠΌΡ Ρ
ΡΠΌΡΡΠ½ΠΎΠ³ΠΎ Π·Π°Ρ
ΠΈΡΡΡ, Π΅Π»Π΅ΠΌΠ΅Π½ΡΠΎΠΌ ΡΠΊΠΎΡ Ρ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½Π½Ρ Π²ΠΌΡΡΡΡ ΡΡ
Π΄ΡΡΡΠΈΡ
ΡΠ΅ΡΠΎΠ²ΠΈΠ½ Π² ΠΎΠ±βΡΠΊΡΠ°Ρ
Π΄ΠΎΠ²ΠΊΡΠ»Π»Ρ.ΠΠ΅ΡΠ° Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ β ΡΠΎΠ·ΡΠΎΠ±ΠΈΡΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΡ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΎΠ³ΠΎ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½Π½Ρ ΡΡΠ°ΠΌΠ΅ΡΠΎΠΊΡΠ°ΠΌΡ, ΡΠΌΡΠ΄Π°ΠΊΠ»ΠΎΠΏΡΠΈΠ΄Ρ, ΠΌΠ΅ΡΡΠΈΠ±ΡΠ·ΠΈΠ½Ρ, Π΄ΠΈΠΌΠ΅ΡΠΎΠΌΠΎΡΡΡ, Π°Π·ΠΎΠΊΡΠΈΡΡΡΠΎΠ±ΡΠ½Ρ, ΠΎΠΊΡΠ°ΡΡΠ°ΠΏΡΠΏΡΠΎΠ»ΡΠ½Ρ ΡΠ° ΡΠ°ΠΌΠΎΠΊΡΠ°Π΄ΠΎΠ½Ρ Ρ Π²ΠΎΠ΄Ρ ΠΏΡΠΈ ΡΡ
ΡΡΠΌΡΡΠ½ΡΠΉ ΠΏΡΠΈΡΡΡΠ½ΠΎΡΡΡ.ΠΠ΅ΡΠΎΠ΄ΠΈ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ. ΠΠ°ΡΡΠΎΡΠΎΠ²Π°Π½ΠΎ ΠΌΠ΅ΡΠΎΠ΄ ΠΎΠ±Π΅ΡΠ½Π΅Π½ΠΎ-ΡΠ°Π·ΠΎΠ²ΠΎΡΒ Π²ΠΈΡΠΎΠΊΠΎΠ΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡ ΡΡΠ΄ΠΈΠ½Π½ΠΎΡ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΡΡ Π· ΡΠ»ΡΡΡΠ°ΡΡΠΎΠ»Π΅ΡΠΎΠ²ΠΈΠΌ Π΄Π΅ΡΠ΅ΠΊΡΡΠ²Π°Π½Π½ΡΠΌ. Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ½Ρ ΠΎΠ±ΡΠΎΠ±ΠΊΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡΠ² ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Π· Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½ΡΠΌ ΠΏΠ°ΠΊΠ΅ΡΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ½ΠΈΡ
ΠΏΡΠΎΠ³ΡΠ°ΠΌ IBM SPSS Statistics Base v.22 ΡΠ° MS ExΡel.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΠΈ ΠΉ ΠΎΠ±Π³ΠΎΠ²ΠΎΡΠ΅Π½Π½Ρ. Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ
Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠ½ΠΈΡ
Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Ρ ΠΏΡΠ΄ΡΠ±ΡΠ°Π½ΠΎ Π½Π°ΠΉΠ±ΡΠ»ΡΡ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½Ρ ΡΠΌΠΎΠ²ΠΈ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΡΠ²Π°Π½Π½Ρ, Π² ΡΠΎΠΌΡ ΡΠΈΡΠ»Ρ ΡΡΡ
ΠΎΠΌΡ ΡΠ°Π·Ρ (Π°ΡΠ΅ΡΠΎΠ½ΡΡΡΠΈΠ»+Π²ΠΎΠ΄Π° Ρ ΡΠΏΡΠ²Π²ΡΠ΄Π½ΠΎΡΠ΅Π½Π½Ρ (50+50) ΡΠ° (70+30)) Π· Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½ΡΠΌ Π³ΡΠ°Π΄ΡΡΠ½ΡΠ½ΠΎΠ³ΠΎ Π΅Π»ΡΡΠ²Π°Π½Π½Ρ. ΠΠΏΡΠΈΠΌΠ°Π»ΡΠ½Π° Π΄ΠΎΠ²ΠΆΠΈΠ½Π° Ρ
Π²ΠΈΠ»Ρ ΠΏΡΠΈ Π²ΠΈΠΊΠΎΠ½Π°Π½Π½Ρ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Ρ ΡΠΊΠ»Π°Π΄Π°Π»Π° 245 Π½ΠΌ. Π§Π°Ρ ΡΡΡΠΈΠΌΡΠ²Π°Π½Π½Ρ (Ρ
Π²) ΡΡΠ°Π½ΠΎΠ²ΠΈΠ²: ΡΡΠ°ΠΌΠ΅ΡΠΎΠΊΡΠ°ΠΌΡ β 3,5Β±0,1; ΡΠΌΡΠ΄Π°ΠΊΠ»ΠΎΠΏΡΠΈΠ΄Ρ β 4,1Β±0,1; ΠΌΠ΅ΡΡΠΈΠ±ΡΠ·ΠΈΠ½Ρ β 6,3Β±0,1; Π ΡΠ·ΠΎΠΌΠ΅ΡΡ Π΄ΠΈΠΌΠ΅ΡΠΎΠΌΠΎΡΡΡ β 8,5Β±0,1; Z ΡΠ·ΠΎΠΌΠ΅ΡΡ Π΄ΠΈΠΌΠ΅ΡΠΎΠΌΠΎΡΡΡ β 8,9Β±0,1; Π°Π·ΠΎΠΊΡΠΈΡΡΡΠΎΠ±ΡΠ½Ρ β 9,5Β±0,1; ΠΎΠΊΡΠ°ΡΡΠ°ΠΏΡΠΏΡΠΎΠ»ΡΠ½Ρ β 10,2Β±0,1; ΡΠ°ΠΌΠΎΠΊΡΠ°Π΄ΠΎΠ½Ρ β 12,1Β±0,1. Π ΠΎΠ·ΡΠΎΠ±Π»Π΅Π½ΠΎ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½Ρ ΡΠΌΠΎΠ²ΠΈ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΡΡΠ½ΠΎΠ³ΠΎ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½Π½Ρ ΡΡΠ°ΠΌΠ΅ΡΠΎΠΊΡΠ°ΠΌΡ, ΡΠΌΡΠ΄Π°ΠΊΠ»ΠΎΠΏΡΠΈΠ΄Ρ, ΠΌΠ΅ΡΡΠΈΠ±ΡΠ·ΠΈΠ½Ρ, Π΄ΠΈΠΌΠ΅ΡΠΎΠΌΠΎΡΡΡ, Π°Π·ΠΎΠΊΡΠΈΡΡΡΠΎΠ±ΡΠ½Ρ, ΠΎΠΊΡΠ°ΡΡΠ°ΠΏΡΠΏΡΠΎΠ»ΡΠ½Ρ ΡΠ° ΡΠ°ΠΌΠΎΠΊΡΠ°Π΄ΠΎΠ½Ρ ΠΏΡΠΈ ΡΡΠΌΡΡΠ½ΡΠΉ ΠΏΡΠΈΡΡΡΠ½ΠΎΡΡΡ Π² ΠΏΡΠΎΠ±Ρ Π²ΠΎΠ΄ΠΈ (Π΄ΠΎΠ²ΠΆΠΈΠ½Π° Ρ
Π²ΠΈΠ»Ρ β 245 Π½ΠΌ), ΠΏΡΠ΄ΡΠ±ΡΠ°Π½ΠΎ ΡΠΌΠΎΠ²ΠΈ Π³ΡΠ°Π΄ΡΡΠ½ΡΠ½ΠΎΠ³ΠΎ Π΅Π»ΡΡΠ²Π°Π½Π½Ρ ΠΏΡΠΈ ΡΡΠ·Π½ΠΈΡ
ΠΏΡΠΎΡΡΠ»ΡΡ
Π³ΡΠ°Π΄ΡΡΠ½ΡΠ° ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΡΠΉ Π΄Π²ΠΎΡ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΡΠ² ΡΡΡ
ΠΎΠΌΠΎΡ ΡΠ°Π·ΠΈ β Π°ΡΠ΅ΡΠΎΠ½ΡΡΡΠΈΠ»Ρ Ρ Π²ΠΎΠ΄ΠΈ (50+50; 70+30; 50+50).ΠΠΈΡΠ½ΠΎΠ²ΠΎΠΊ. Π ΠΎΠ·ΡΠΎΠ±Π»Π΅Π½Ρ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½Ρ ΡΠΌΠΎΠ²ΠΈ Π΅ΠΊΡΡΡΠ°ΠΊΡΡΡ ΡΠ° Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΡΠ²Π°Π½Π½Ρ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΡΠ²Π°Π½ΠΈΡ
ΡΠ΅ΡΠΎΠ²ΠΈΠ½ ΠΏΡΠΈ ΡΡΠΌΡΡΠ½ΡΠΉ ΠΏΡΠΈΡΡΡΠ½ΠΎΡΡΡ Π² ΠΏΡΠΎΠ±Ρ Π²ΠΎΠ΄ΠΈ Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΡΡΡΡ ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ ΡΡ
Π²ΠΌΡΡΡΡ Π· ΠΌΠ΅ΠΆΠ΅Ρ ΠΊΡΠ»ΡΠΊΡΡΠ½ΠΎΠ³ΠΎ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½Π½Ρ ΠΊΠΎΠΆΠ½ΠΎΡ ΡΠΏΠΎΠ»ΡΠΊΠΈ 0,0002 ΠΌΠ³/Π΄ΠΌ3
ΠΠ΄Π΅Π½ΡΠΈΡΡΠΊΠ°ΡΡΡ ΡΠ° ΠΎΡΡΠ½ΡΠ²Π°Π½Π½Ρ Π²ΠΈΡΠΎΡ Π΄Π΅ΡΠ΅Π² ΡΠΎΡΠ½ΠΈ Π·Π²ΠΈΡΠ°ΠΉΠ½ΠΎΡ Ρ Π½Π°ΡΠ°Π΄ΠΆΠ΅Π½Π½ΡΡ Π§ΠΎΡΠ½ΠΎΠ±ΠΈΠ»ΡΡΡΠΊΠΎΡ Π·ΠΎΠ½ΠΈ Π²ΡΠ΄ΡΡΠΆΠ΅Π½Π½Ρ ΡΡΠ΅ΡΠ΅ΠΎΡΠΎΡΠΎΠ³ΡΠ°ΠΌΠΌΠ΅ΡΡΠΈΡΠ½ΠΈΠΌ ΡΠΏΠΎΡΠΎΠ±ΠΎΠΌ
The paper discusses the possibilities of identification of the tops of Scots pine (Pinus sylvestris L.) trees and the subsequent assessment of their heights in forest stands using aerial photographs made from an unmanned aerial vehicle and stereo photogrammetric processing. The research was carried out in a young forest stand composed of the trees of different ages (up to 30 year old) and growing within a circular plot with a radius of 12.6 m. Within the studied area we determined coordinates of all live pine trees and measured their heights using a laser-optical rangefinder. This field data was used for estimation of the inaccuracies of determination of the tree heights using the drone. The study confirmed applicability of the drone survey method for identification of the tops of the highest trees using the GIS filter tools for search local maxima in the output raster images of the canopy height model. Research results have confirmed the impossibility of detecting the stem tops of trees if they do not occupy the dominant position in the forest stands. We used three different search radiuses for detection of local maximum values for identifying the following tree tops: 0.5 m, 0.75 m and 1.0 m. Reduction of the search radius in order to identify the trees in the lower tier resulted in the false detection of a numerous local maxima (branch tops) as the separate trees. The best result was obtained with the largest search radius, since all the found maxima corresponded to the actual individual trees, and their heights were estimated with the smallest deviations from the values measured in field using a laser-optical rangefinder (the standard deviation was 0.44 m for 27 trees detected in the upper tier), although the number of detected trees was smaller comparing to those obtained with the shorter search radiuses. We have concluded that the above-mentioned remote detection approach has good prospects for application both in scientific researches and in forest inventory considering that the upper height of the forest stands is closely correlated with other forest parameters, especially since stereo photogrammetry methods are rapidly evolving and modified for solution increasingly complex problems.Π ΠΎΠ·Π³Π»ΡΠ½ΡΡΠΎ ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ Π°Π΅ΡΠΎΡΠΎΡΠΎΠ·ΠΉΠΎΠΌΠΊΠΈ Π·Π° Π΄ΠΎΠΏΠΎΠΌΠΎΠ³ΠΎΡ Π±Π΅Π·ΠΏΡΠ»ΠΎΡΠ½ΠΎΠ³ΠΎ Π»ΡΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Π°ΠΏΠ°ΡΠ°ΡΡ ΡΠ° ΠΏΠΎΠ΄Π°Π»ΡΡΠΎΠ³ΠΎ ΠΎΠ±ΡΠΎΠ±Π»Π΅Π½Π½Ρ ΠΎΡΡΠΈΠΌΠ°Π½ΠΈΡ
Π·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½Ρ ΡΡΠ΅ΡΠ΅ΠΎΡΠΎΡΠΎΠ³ΡΠ°ΠΌΠΌΠ΅ΡΡΠΈΡΠ½ΠΈΠΌΠΈ ΠΏΡΠ΄Ρ
ΠΎΠ΄Π°ΠΌΠΈ Π΄Π»Ρ ΡΠ΄Π΅Π½ΡΠΈΡΡΠΊΠ°ΡΡΡ Π΄Π΅ΡΠ΅Π² ΡΠΎΡΠ½ΠΈ Π·Π²ΠΈΡΠ°ΠΉΠ½ΠΎΡ ΡΠ° ΠΎΡΡΠ½ΠΊΠΈ ΡΡ
Π²ΠΈΡΠΎΡΠΈ Ρ Π·ΡΠΌΠΊΠ½ΡΡΠΈΡ
Π΄Π΅ΡΠ΅Π²ΠΎΡΡΠ°Π½Π°Ρ
ΡΠΏΠΎΡΠΎΠ±ΠΎΠΌ ΠΏΠΎΡΡΠ²Π½ΡΠ½Π½Ρ Π΄Π°Π½ΠΈΡ
, ΠΎΡΡΠΈΠΌΠ°Π½ΠΈΡ
Π΄Π»Ρ ΠΊΡΡΠ³ΠΎΠ²ΠΎΡ ΠΏΡΠΎΠ±Π½ΠΎΡ ΠΏΠ»ΠΎΡΡ Π²Π½Π°ΡΠ»ΡΠ΄ΠΎΠΊ Π°Π΅ΡΠΎΡΠΎΡΠΎΠ·ΠΉΠΎΠΌΠΊΠΈ ΡΠ° Π² ΠΏΠΎΠ»ΡΠΎΠ²ΠΈΡ
ΡΠΌΠΎΠ²Π°Ρ
Π»Π°Π·Π΅ΡΠ½ΠΎ-ΠΎΠΏΡΠΈΡΠ½ΠΈΠΌΠΈ Π΄Π°Π»Π΅ΠΊΠΎΠΌΡΡΠ°ΠΌΠΈ, ΡΠΎ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Ρ ΡΠΊ ΠΊΠΎΠ½ΡΡΠΎΠ»ΡΠ½Ρ Π·Π½Π°ΡΠ΅Π½Π½Ρ. ΠΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΡΠ΄Π΅Π½ΡΠΈΡΡΠΊΠ°ΡΡΡ Π²Π΅ΡΡ
ΡΠ²ΠΎΠΊ ΡΡΠΎΠ²Π±ΡΡΡΠ² Π΄Π΅ΡΠ΅Π² ΡΠΎΡΠ½ΠΈ Π·Π²ΠΈΡΠ°ΠΉΠ½ΠΎΡ Π·Π° Π΄ΠΎΠΏΠΎΠΌΠΎΠ³ΠΎΡ Π°Π»Π³ΠΎΡΠΈΡΠΌΡΠ² ΠΏΠΎΡΡΠΊΡ ΠΌΠ°ΠΊΡΠΈΠΌΡΠΌΡΠ² ΡΠ°ΡΡΡΡΠ² Ρ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠ½ΠΈΡ
ΠΏΡΠΎΠ΄ΡΠΊΡΠ°Ρ
ΠΠΠ‘. ΠΡΠ΄ΡΠ²Π΅ΡΠ΄ΠΆΠ΅Π½ΠΎ Π½Π΅ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π΄Π΅ΡΠ΅ΠΊΡΡΠ²Π°Π½Π½Ρ Π΄Π΅ΡΠ΅Π² Π½ΠΈΠΆΠ½ΡΡ
Π΅Π»Π΅ΠΌΠ΅Π½ΡΡΠ² ΡΡΡΡΡ ΡΠ»ΡΡ
ΠΎΠΌ Π·Π°ΡΡΠΎΡΡΠ²Π°Π½Π½Ρ ΡΠ°Π΄ΡΡΡΡΠ² ΠΏΠΎΡΡΠΊΡ ΠΌΠ°ΠΊΡΠΈΠΌΡΠΌΡΠ² ΠΌΠ°Π»ΠΈΡ
ΡΠΎΠ·ΠΌΡΡΡΠ² (0,5 ΠΌ), ΡΠΎ ΡΠΏΡΠΈΡΠΈΠ½ΡΡ ΠΏΠΎΠΌΠΈΠ»ΠΊΠΎΠ²Ρ ΡΠ΄Π΅Π½ΡΠΈΡΡΠΊΠ°ΡΡΡ Π·Π½Π°ΡΠ½ΠΎΡ ΠΊΡΠ»ΡΠΊΠΎΡΡΡ Π»ΠΎΠΊΠ°Π»ΡΠ½ΠΈΡ
ΠΌΠ°ΠΊΡΠΈΠΌΡΠΌΡΠ² (Π±ΠΎΠΊΠΎΠ²ΠΈΡ
Π³ΡΠ»ΠΎΠΊ) ΡΠΊ ΠΎΠΊΡΠ΅ΠΌΠΈΡ
Π΄Π΅ΡΠ΅Π². ΠΠ±ΡΠ»ΡΡΠ΅Π½Π½Ρ ΡΠΎΠ·ΠΌΡΡΡΠ² ΡΠ°Π΄ΡΡΡΡ ΡΡΠ»ΡΡΡΠ°ΡΡΡ Π²ΠΈΡΠ²Π»Π΅Π½Π½Ρ ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΠΈΡ
Π·Π½Π°ΡΠ΅Π½Ρ ΡΠ°ΡΡΡΠ° ΡΠΈΡΡΠΎΠ²ΠΎΡ ΠΌΠΎΠ΄Π΅Π»Ρ Π²ΠΈΡΠΎΡΠΈ ΠΊΡΠΎΠ½ΠΈ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΡΠ²Π°Π½ΠΎΠ³ΠΎ Π΄Π΅ΡΠ΅Π²ΠΎΡΡΠ°Π½Ρ Π΄ΠΎ 1 ΠΌ Π΄Π°Π»ΠΎ Π·ΠΌΠΎΠ³Ρ Π· Π΄ΠΎΡΡΠ°ΡΠ½ΡΠΎΡ ΡΠΎΡΠ½ΡΡΡΡ ΠΎΡΡΠ½ΠΈΡΠΈ Π²ΠΈΡΠΎΡΡ (ΡΡΠ°Π½Π΄Π°ΡΡΠ½Π΅ Π²ΡΠ΄Ρ
ΠΈΠ»Π΅Π½Π½Ρ 0,44 ΠΌ) 27 Π΄Π΅ΡΠ΅Π² Ρ Π²Π΅ΡΡ
Π½ΡΠΉ ΡΠ°ΡΡΠΈΠ½Ρ Π»ΡΡΠΎΠ²ΠΎΠ³ΠΎ ΠΏΠΎΠ»ΠΎΠ³Ρ. Π¦Π΅ ΡΠ²ΡΠ΄ΡΠΈΡΡ ΠΏΡΠΎ ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΡΡΡΡ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ ΠΏΠ΅ΡΠ΅Π»ΡΡΠ΅Π½ΠΈΡ
ΠΏΡΠ΄Ρ
ΠΎΠ΄ΡΠ² Π΄Π»Ρ Π²ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½Π½Ρ Π»ΡΡΠΎΡΠ°ΠΊΡΠ°ΡΡΠΉΠ½ΠΈΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΡΠ² Π½Π°ΡΠ°Π΄ΠΆΠ΅Π½Ρ Π½Π΅ Π»ΠΈΡΠ΅ Π· Π½Π°ΡΠΊΠΎΠ²ΠΎΡ ΠΌΠ΅ΡΠΎΡ, Π° ΠΉ ΠΏΡΠ΄ ΡΠ°Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½Ρ Π»ΡΡΠΎΠ²ΠΏΠΎΡΡΠ΄ΠΊΡΠ²Π°Π½Π½Ρ Ρ Π»ΡΡΠΎΡΠ½Π²Π΅Π½ΡΠ°ΡΠΈΠ·Π°ΡΡΡ, ΠΎΡΠΊΡΠ»ΡΠΊΠΈ Π²Π΅ΡΡ
Π½Ρ Π²ΠΈΡΠΎΡΠ° Π΄Π΅ΡΠ΅Π²ΠΎΡΡΠ°Π½Ρ ΠΌΠ°Ρ ΡΡΡΠ½Ρ ΡΡΠ½ΠΊΡΡΠΎΠ½Π°Π»ΡΠ½Ρ Π·Π²'ΡΠ·ΠΊΠΈ Π· ΡΠ½ΡΠΈΠΌΠΈ ΡΠ°ΠΊΡΠ°ΡΡΠΉΠ½ΠΈΠΌΠΈ ΠΎΠ·Π½Π°ΠΊΠ°ΠΌΠΈ
The leak location package for assessment of the time-frequency correlation method for leak location
Voltammetric study of the antioxidant activity of propionic acid bacteria in liquid cultures
On Determining the Vertical Structure of the Aerosol Component in the Atmosphere of Saturn
Optical Polarimetry of Small Solar System Bodies: From Asteroids to Debris Disks
Astrophysics and Space Science Library, vol 460International audienceWe present a review on polarimetric properties of small Solar system bodies. The main results of polarimetric investigations of asteroids, comets, transneptunian objects and Centaurs are discussed focusing on recent findings. We also discuss the polarimetric observations of dust clouds in our Solar system