Using LANDSAT time series for assessing reforestation on clear cuts in Bryansk region

© 2019

full text

E.I. Belova^*, D.V. Ershov

Center for Forest Ecology and Productivity of RAS

Profsoyuznaya st. 84/32 bldg. 14, Moscow, 117997, Russia

^*E-mail: belova@ifi.rssi.ru

Reseived 23 September 2019

This paper submitted the method of remote sensed estimate the forest artificial regeneration (tree planting). The objective was to designate the moment of transition from clear cuts to forested lands. The studies took place in Suzemskoe forestry in Bryansk region. We used a forest taxation data and annual cloud-free Landsat composite images (2002 – 2015 years). Vegetation indexes (NDVI and SWVI) were calculated by the time series of cloud-free composite images. The database of the ages of transition of clear cuts to artificial regeneration was compiled based on taxation data from forest inventory of the forestries (2003 y.). Cumulative values of vegetation indexes for the whole study period were calculated from the time series for the whole period. Examining the NDVI-SWVI indexes of the artificial regeneration sites allowed finding the linear relationship, the incline of the linear regression and thresholds of clear cuts transitioning to forested lands. The method was tested for Steklyanskoe, Krasnoslobodskoe and Kokorevskoe forestries. The correct classification of the clear cuts transitioned to the regrowth category reached 80.1%.

Key words: reforestation, artificial regeneration, forest regrowth, time series, vegetation indexes, NDVI, SWVI.

REFERENCES

Belova E.I., Ershov D.V., Opyt ocenki estestvennogo lesovosstanovlenija na sploshnyh vyrubkah po vremennym rjadam LANDSAT (Assessing reforestation on clear cuts based on Landsat time series), Lesovedenie, 2015, Vol. 5, pp. 339-345.

Belova E.I., Ershov D.V., Predvaritel’naja obrabotka vremennyh serij izobrazhenij Landsat-TM/ETM+ pri sozdanii bezoblachnyh kompozitnyh izobrazhenij mestnosti (Preprocessing Landsat TM/ETM+ data sets for creating cloud-free composite imagery), Sovremennye problemy distancionnogo zondirovanija Zemli iz kosmosa, 2011, Vol. 8, No. 1, pp. 73-82.

http://www.consultant.ru/document/cons_doc_LAW_296757/77e0bc4c1b732cffc4ef23c2113effb964769f33/ (2019, 28 August)

http://www.consultant.ru/document/cons_doc_LAW_64299/710f2a2a776bb8cff9e204556177d7cb26f79dee/ (2019, 28 August)

http://www.consultant.ru/document/cons_doc_LAW_207285/4f0faeaf51f7cf71d1e928c355da9b3db3d3545d/ (2019, 28 August)

http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/environment/# (2019, 28 August)

Hansen M.C., Potapov P.V., Moore R., Turubanova S.A., Tyukavina A., Thau D., Stehman S.V., Goetz S.J., Loveland T R., Kommareddy A., Egorov A., Chini L., Justice C.O., Townshend J.R.G., High Resolution Global Maps of 21st Century Forest Cover Change, Science, 2013, Vol. 342, pp. 850-853.

Potapov P.V., Turubanova S.A., Tyukavina A., Krylov A.M., McCarty J L., Radeloff V. C., Hansen M.C, Eastern Europe’s forest cover dynamics from 1985 to 2012 quantified from the full Landsat archive, Remote Sensing of Environment, 2015, Vol. 159, pp. 28-43.