scholarly journals Natural Afforestation on Abandoned Agricultural Lands during Post-Soviet Period: A Comparative Landsat Data Analysis of Bordering Regions in Russia and Belarus

2022 ◽  
Vol 14 (2) ◽  
pp. 322
Author(s):  
Dmitry V. Ershov ◽  
Egor A. Gavrilyuk ◽  
Natalia V. Koroleva ◽  
Elena I. Belova ◽  
Elena V. Tikhonova ◽  
...  

Remote monitoring of natural afforestation processes on abandoned agricultural lands is crucial for assessments and predictions of forest cover dynamics, biodiversity, ecosystem functions and services. In this work, we built on the general approach of combining satellite and field data for forest mapping and developed a simple and robust method for afforestation dynamics assessment. This method is based on Landsat imagery and index-based thresholding and specifically targets suitability for limited field data. We demonstrated method’s details and performance by conducting a case study for two bordering districts of Rudnya (Smolensk region, Russia) and Liozno (Vitebsk region, Belarus). This study area was selected because of the striking differences in the development of the agrarian sectors of these countries during the post-Soviet period (1991-present day). We used Landsat data to generate a consistent time series of five-year cloud-free multispectral composite images for the 1985–2020 period via the Google Earth Engine. Three spectral indices, each specifically designed for either forest, water or bare soil identification, were used for forest cover and arable land mapping. Threshold values for indices classification were both determined and verified based on field data and additional samples obtained by visual interpretation of very high-resolution satellite imagery. The developed approach was applied over the full Landsat time series to quantify 35-year afforestation dynamics over the study area. About 32% of initial arable lands and grasslands in the Russian district were afforested by the end of considered period, while the agricultural lands in Belarus’ district decreased only by around 5%. Obtained results are in the good agreement with the previous studies dedicated to the agricultural lands abandonment in the Eastern Europe region. The proposed method could be further developed into a general universally applicable technique for forest cover mapping in different growing conditions at local and regional spatial levels.

2020 ◽  
Vol 12 (18) ◽  
pp. 2918
Author(s):  
Yang Liu ◽  
Ronggao Liu

Forest cover mapping based on multi-temporal satellite observations usually uses dozens of features as inputs, which requires huge training data and leads to many ill effects. In this paper, a simple but efficient approach was proposed to map forest cover from time series of satellite observations without using classifiers and training data. This method focuses on the key step of forest mapping, i.e., separation of forests from herbaceous vegetation, considering that the non-vegetated area can be easily identified by the annual maximum vegetation index. We found that the greenness of forests is generally stable during the maturity period, but a similar greenness plateau does not exist for herbaceous vegetation. It means that the mean greenness during the vegetation maturity period of forests should be larger than that of herbaceous vegetation, while its standard deviation should be smaller. A combination of these two features could identify forests with several thresholds. The proposed approach was demonstrated for mapping the extents of different forest types with MODIS observations. The results show that the overall accuracy ranges 91.92–95.34% and the Kappa coefficient is 0.84–0.91 when compared with the reference datasets generated from fine-resolution imagery of Google Earth. The proposed approach can greatly simplify the procedures of forest cover mapping.


Author(s):  
Miroslava Pytulyak ◽  
Mykola Pytulyak ◽  
Lesia Zastavetska ◽  
Taras Zastavetskyi ◽  
Natalya Taranova

The article presents an ecological and geographical analysis of the current state of land resources. The structure of land resources in UTC (United Territorial Community) is dominated by lands of agricultural and forestry use. They occupy the largest areas - 67072.3 hectares, 40004.8 hectares and their share in the structure of the land fund is 57.8%, 34.4%, respectively. The structure of agricultural lands of the district is dominated by agricultural lands, namely arable land. Its area is 67072.3 hectares (97.3%) The largest area of agricultural land is concentrated within the central part of the district. The largest area in the structure of agricultural land is occupied by arable land - 2500 - 3570.8 hectares. In the eastern and south-eastern parts of the district the share of arable land in the structure of agricultural lands is the highest (more than 70%). The share of pastures and hayfields in the structure of agricultural lands is 18.2% and 16.8%, respectively. The smallest share in the structure of lands of perennial plantations (1.6%). The largest areas of hayfields and pastures in the northern and northeastern part of the district, which is due to the natural features of the territory. Peculiarities of forestry use of land resources on UTC area are analyzed. Lands covered with forest vegetation there are unevenly distributed and are mainly subordinated to Brody Forestry. The largest areas of forestry land in the northern and southern parts of the district. Forests in the northern part are located within Male Polissya. Here in the area there is the highest forest cover (45 - 67%). Forest cover in the southern part of the district is 45 - 67%. The structure of lands occupied by forest vegetation is dominated by forest areas (96.0%), including covered with forest crops (71.0%) On the basis of the defined indicators the analysis of ecological stability of lands in UTC is carried out, also the anthropogenic loading on agricultural lands of the area is defined. This figure depends on the area of land of different species. Using the method of Shyshchenko P. H. (1982) we have determined the anthropogenic load on the agricultural lands of the district. This figure depends on the area of the land of different species. Within the district there are spatial differences in this indicator. The greatest anthropogenic load on agricultural land is in the central part of the district. Here the anthropogenic load is more than 6.6 (strongly converted). In the north-western part of the district this indicator is the lowest: 5.2-5.3. On the territory of other village councils agricultural lands are moderately transformed (6.1 - 6.5) The results of the study of the ecological condition of the land resources of the district are presented. The level of plowing, agricultural development of the district is analyzed. The central and southern part of the district is characterized by an unbalanced structure of land use, as there is a fairly high rate of plowing of agricultural land. The share of arable land here is more than 70% of the total area of agricultural land. The average value of this indicator is around 57.7%. The highest agricultural development is in the central part of the district (except for Brody town territorial community), and in the southern part (more than 60%). The maximum indicators of agricultural development are - 86.8-91%. The ecological condition of the land resources of the district was assessed and five groups with different levels of this indicator were identified. The ecological condition of land resources varies from optimal to catastrophic, depending on the ratio of arable land (R) and the share of ecological and stabilizing lands (ESL). Optimal and satisfactory ecological condition of land resources in the region on the area of 40.6%, critical - 25.7%, crisis - 20.4%, catastrophic - 13.3% Land resources are one of the most important resources of the district. In modern conditions, productive agricultural lands should be involved in intensive agricultural cultivation, and the rest should remain in a natural state, which will ensure ecological sustainability and balanced nature management. Key words: land resources, agricultural lands, agricultural development, ecological condition, ecological stability.


2021 ◽  
Author(s):  
Xiaofang Ling ◽  
Ruyin Cao

<p>The Normalized Difference Vegetation Index (NDVI) data provided by the satellite Landsat have rich historical archive data with a spatial resolution of 30 m. However, the Landsat NDVI time-series data are quite discontinuous due to its 16-day revisit cycle, cloud contamination and some other factors. The spatiotemporal data fusion technology has been proposed to reconstruct continuous Landsat NDVI time-series data by blending the MODIS data with the Landsat data. Although a number of spatiotemporal fusion algorithms have been developed during the past decade, most of the existing algorithms usually ignore the effective use of partially cloud-contaminated images. In this study, we presented a new spatiotemporal fusion method, which employed the cloud-free pixels in the partially cloud-contaminated images to improve the performance of MODIS-Landsat data fusion by <strong>C</strong>orrecting the inconsistency between MODIS and Landsat data in <strong>S</strong>patiotemporal <strong>DA</strong>ta <strong>F</strong>usion (called CSDAF). We tested the new method at three sites covered by different vegetation types, including deciduous forests in the Shennongjia Forestry District of China (SNJ), evergreen forests in Southeast Asia (SEA), and the irrigated farmland in the Coleambally irrigated area of Australia (CIA). Two experiments were designed. In experiment I, we first simulated different cloud coverages in cloud-free Landsat images and then used both CSDAF and the recently developed IFSDAF method to restore these “missing” pixels for quantitative assessments. Results showed that CSDAF performed better than IFSDAF by achieving the smaller average Root Mean Square Error (RMSE) values (0.0767 vs. 0.1116) and the larger average Structural SIMilarity index (SSIM) values (0.8169 vs. 0.7180). In experiment II, we simulated the scenario of “inconsistence” between MODIS and Landsat by simulating different levels of noise on MODIS and Landsat data. Results showed that CSDAF was able to reduce the influence of the inconsistence between MODIS and Landsat data on MODIS-Landsat data fusion to some extent. Moreover, CSDAF is simple and can be implemented on the Google Earth Engine. We expect that CSDAF is potentially to be used to reconstruct Landsat NDVI time-series data at the regional and continental scales.</p>


2020 ◽  
Vol 12 (1) ◽  
pp. 187 ◽  
Author(s):  
Viktor Myroniuk ◽  
Mykola Kutia ◽  
Arbi J. Sarkissian ◽  
Andrii Bilous ◽  
Shuguang Liu

Satellite imagery of 25–30 m spatial resolution has been recognized as an effective tool for monitoring the spatial and temporal dynamics of forest cover at different scales. However, the precise mapping of forest cover over fragmented landscapes is complicated and requires special consideration. We have evaluated the performance of four global forest products of 25–30 m spatial resolution within three flatland subregions of Ukraine that have different forest cover patterns. We have explored the relationship between tree cover extracted from the global forest change (GFC) and relative stocking density of forest stands and justified the use of a 40% tree cover threshold for mapping forest in flatland Ukraine. In contrast, the canopy cover threshold for the analogous product Landsat tree cover continuous fields (LTCCF) is found to be 25%. Analysis of the global forest products, including discrete forest masks Global PALSAR-2/PALSAR Forest/Non-Forest Map (JAXA FNF) and GlobeLand30, has revealed a major misclassification of forested areas under severe fragmentation patterns of landscapes. The study also examined the effectiveness of forest mapping over fragmented landscapes using dense time series of Landsat images. We collected 1548 scenes of Landsat 8 Operational Land Imager (OLI) for the period 2014–2016 and composited them into cloudless mosaics for the following four seasons: yearly, summer, autumn, and April–October. The classification of images was performed in Google Earth Engine (GEE) Application Programming Interface (API) using random forest (RF) classifier. As a result, 30 m spatial resolution forest mask for flatland of Ukraine was created. The user’s and producer’s accuracy were estimated to be 0.910 ± 0.015 and 0.880 ± 0.018, respectively. The total forest area for the flatland Ukraine is 9440.5 ± 239.4 thousand hectares, which is 3% higher than official data. In general, we conclude that the Landsat-derived forest mask performs well over fragmented landscapes if forest cover of the territory is higher than 10–15%.


Author(s):  
Eric A. Lehmann ◽  
Jeremy F. Wallace ◽  
Peter A. Caccetta ◽  
Suzanne L. Furby ◽  
Katherine Zdunic

2016 ◽  
Vol 46 (1) ◽  
pp. 13-24 ◽  
Author(s):  
Everton Hafemann FRAGAL ◽  
Thiago Sanna Freire SILVA ◽  
Evlyn Márcia Leão de Moraes NOVO

ABSTRACTThe Amazon várzeas are an important component of the Amazon biome, but anthropic and climatic impacts have been leading to forest loss and interruption of essential ecosystem functions and services. The objectives of this study were to evaluate the capability of the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) algorithm to characterize changes in várzeaforest cover in the Lower Amazon, and to analyze the potential of spectral and temporal attributes to classify forest loss as either natural or anthropogenic. We used a time series of 37 Landsat TM and ETM+ images acquired between 1984 and 2009. We used the LandTrendr algorithm to detect forest cover change and the attributes of "start year", "magnitude", and "duration" of the changes, as well as "NDVI at the end of series". Detection was restricted to areas identified as having forest cover at the start and/or end of the time series. We used the Support Vector Machine (SVM) algorithm to classify the extracted attributes, differentiating between anthropogenic and natural forest loss. Detection reliability was consistently high for change events along the Amazon River channel, but variable for changes within the floodplain. Spectral-temporal trajectories faithfully represented the nature of changes in floodplain forest cover, corroborating field observations. We estimated anthropogenic forest losses to be larger (1.071 ha) than natural losses (884 ha), with a global classification accuracy of 94%. We conclude that the LandTrendr algorithm is a reliable tool for studies of forest dynamics throughout the floodplain.


2022 ◽  
Vol 14 (2) ◽  
pp. 343
Author(s):  
Fujue Huang ◽  
Xingsheng Xia ◽  
Yongsheng Huang ◽  
Shenghui Lv ◽  
Qiong Chen ◽  
...  

The northeastern margin of the Qinghai–Tibet Plateau (QTP) is an agricultural protection area in China’s new development plan, and the primary region of winter wheat growth within QTP. Winter wheat monitoring is critical for understanding grain self-sufficiency, climate change, and sustainable socioeconomic and ecological development in the region. However, due to the complex terrain and high altitude of the region, with discontinuous arable land and the relatively low level of agricultural development, there are no effective localization methodologies for extracting and monitoring the detailed planting distribution information of winter wheat. In this study, Sentinel-2A/B data from 2019 to 2020, obtained through the Google Earth Engine platform, were used to build time series reference curves of vegetation indices in Minhe. Planting distribution information of winter wheat was extracted based on the phenology time-weighted dynamic time warping (PT-DTW) method, and the effects of different vegetation indices’ time series and their corresponding threshold parameters were compared. The results showed that: (1) the three vegetation indices—normalized difference vegetation index (NDVI), normalized differential phenology index (NDPI), and normalized difference greenness index (NDGI)—maintained high mapping potential; (2) under the optimal threshold, >88% accuracy of index identification for winter wheat extraction was achieved; (3) due to improved extraction accuracy and resulting boundary range, NDPI and its corresponding optimal parameter (T = 0.05) performed the best. The process and results of this study have certain reference value for the study of winter wheat planting information change and the formulation of dynamic monitoring schemes in agricultural areas of QTP.


2018 ◽  
Vol 42 ◽  
pp. 245-255
Author(s):  
Rostislav F. Turovsky

The article is devoted to the study of the party model of Russian parliamentarism in post-soviet period. The focus is on the issues of party representation and its correlation with the distribution of the managerial positions and introduction of collective legislation at State Duma. These issues are examined from the point of view of reaching cross-party consensus and implementation of fair parliament party representation principle. According to the author Russian parliamentarism model aims at reaching full-fledged party consensus that corresponds better to the principles of popular representation than strict parliament polarization along the line of “authority-opposition”. Understanding of those issues by the majority of the players was noted from the very start of the State Duma activities, in spite of the acute conflicts in the 1990-ies.The author draws the conclusion that the equation of party representation continues to grow at the level of managerial positions in the parliament that allows to improve cooperation of the parties and to reduce authority and opposition conflicts. Thereby the Russian parliamentarism model makes an important contribution to the stabilization of socio-political situation of the country.


Author(s):  
Elena A. Kosovan ◽  

The author of the publication reviews the photobook “Palimpsests”, published in 2018 in the publishing house “Ad Marginem Press” with the support of the Heinrich Böll Foundation. The book presents photos of post-Soviet cities taken by M. Sher. Preface, the author of which is the coordinator of the “Democracy” program of the Heinrich Böll Foundation in Russia N. Fatykhova, as well as articles by M. Trudolyubov and K. Bush, which accompany these photos, contain explanation of the peculiarities of urban space formation and patterns of its habitation in the Soviet Union times and in the post-Soviet period. The author of the publication highly appreciates the publication under review. Analyzing the photographic works of M. Sher and their interpretation undertaken in the articles, the author of the publication agrees with the main conclusions of N. Fatykhova, M. Trudolyubov and K. Bush with regards to the importance of the role of the state in the processes of urban development and urbanization in the Soviet and post-Soviet space, but points out that the second factor that has a key influence on these processes is ownership relations. The paper positively assesses the approach proposed by the authors of the photobook to the study of the post-Soviet city as an architectural and landscape palimpsest consisting mainly of two layers, “socialist” and “capitalist”. The author of the publication specifically emphasizes the importance of analyzing the archetypal component of this palimpsest, pointing out that the articles published in the reviewed book do not pay sufficient attention to this issue. Particular importance is attributed by the author to the issue of metageography of post-Soviet cities and meta-geographical approach to their exploration. Emphasizing that the urban palimpsest is a system of realities, each in turn including a multitude of ideas, meanings, symbols, and interpretations, the author points out that the photobook “Palimpsests” is actually an invitation to a scientific game with space, which should start a new direction in the study of post-Soviet urban space.


2020 ◽  
Vol 2020 (10-4) ◽  
pp. 49-52
Author(s):  
Yusup Guseynov

The article is based on archival materials, field ethnographic material and examines the problem of youth radicalism in the post-Soviet period. In the XXI century the second regular process of recruiting young people into the ranks of terrorists began. However, thanks to the official clergy (the Muftiate of the Republic of Dagestan), state authorities, public associations of the Republic, the process of radicalization of young people has stopped.


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