Soil and vegetation cover spatial-temporal dynamics of the river basin landscapes according to the remote sensing data

2020 ◽  
Author(s):  
Tatiana Trifonova ◽  
Natalia Mishchenko ◽  
Pavel Shutov
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
River Basin ◽  
Carbon Balance ◽  
Carbon Deposition ◽  
Remote Sensing Data ◽  
Biological Indicators ◽  
Forest Vegetation ◽  
Land Use Structure ◽  
Productivity Indicators

<p>The Klyazma river catchment basin is located in the center of the East European plain. It is characterized by a diverse landscape structure but at the same time represents a single ecosystem possessing common functioning features and similar features of dynamic processes.</p><p>The biological indicators dynamics of the Klyazma river basin landscape functioning has been analyzed. These indicators included: phytoproductivity, photosynthetic activity, soil cover carbon accumulation, as well as the analysis of land use structure changes over the past 20 years.  The assessment was carried out for the entire basin, as well as for individual landscapes within the basin differing in structure and composition of the soil and vegetation cover.</p><p>The research was performed using geoinformation analysis of remote sensing data and cartographic information applying basin approach. The river network vectorization and the watershed boundaries definition were carried out basing on digital terrain model (DEM). The input data comprised radar topographic survey of the Earth-SRTM 90. The productivity indicators calculation in carbon units, LAI (Leaf area index) and FPAR (Fraction of Absorbed Photosynthetically Active Radiation) indices are based on Modis data. Organic carbon stocks in soil are determined using the "Trends. Earth " GIS package QGIS 2.18.</p><p>The land use structure analysis shows that the trend for forest vegetation increase and arable land and pastures reduction is common to all landscapes, but different in changes speed and scale. The most stable is the land structure in Meshchera province, where almost 90% is occupied by forests and their area has not changed significantly.</p><p>Over the period of 2000 - 2019, the Klyazma river basin ecosystem was characterized by the annual value fluctuations of gross primary GPP production, net primary NPP production, and MP respiration costs up and down in comparison with the average values. There is no stable tendency in productivity growth or decline.</p><p>The maximum annual changes in productivity indicators are observed for the landscape of the Klin-Dmitrov ridge. The analysis showed that various landscapes differ in their biological parameters varying within different limits.</p><p>The agricultural land overgrowing with forest vegetation is accompanied by the increase in carbon deposition in the soil. Landscapes of the stable land use structure are characterized with zero carbon balance, while landscapes with forest vegetation with slightly negative carbon balance in the soil. However, the average biological indicators of the entire river basin ecosystem remain relatively stable. It testifies of the compensating biological mechanisms maintaining the ecosystem stability within a large ecosystem. That is, changes in some landscapes are compensated by changes in others according to the feedback principle.</p><p>The analysis of productivity features, land use structure, and carbon deposition in the soil in the Klyazma basin and certain key sites associated with different landscapes allowed us to determine a representative key site, located within Klin-Dmitrov ridge for the environmental monitoring of the entire basin.</p><p>The research allowed determining a representative area within the basin for environmental monitoring of the entire basin ecosystem.</p><p>The research has been carried out under RFBR financial support (№ 19-05-00363)</p>

ANALYSIS OF DYNAMICS OF LAND USE STRUCTURE AND SOIL FERTILITY INDICATORS OVER THE KLYAZMA RIVER BASIN

2021 ◽  
pp. 88-98
Author(s):  
I.N. Kurochkin ◽  
◽  
E.Yu. Kulagina ◽  
N.V. Chugay ◽  
◽  
...  
Keyword(s):  
Land Use ◽  
Soil Fertility ◽  
River Basin ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Livestock Grazing ◽  
Land Use Structure ◽  
Vladimir Region ◽  
Fallow Lands ◽  
Analysis Of Dynamics

The main trends in changing the land use structure in the territory of the Klyazma River basin were de-scribed in the article. Using GIS technologies and remote sensing data the areas of land with different land use regimes in the studied territory were determined in the period from 2001 to 2019. The indices of LAI and FPAR phytoproductivity for the territory of the Klyazma basin as a whole, and for each basin included in it were determined. The analysis of the dynamics of changes occurring in the structure of land use is carried out. For the territory of Vladimir region, which is a part of the Klyazma River basin, an assessment of soil types distribution over occupied area was carried out. An integral indicator of soil fertility was calcu-lated on the basis of statistical data of agrochemical indicators. The fraction of fallow lands decreased by 2019 and it amounts 33.76% of the total area of the studied territory. The fraction of mixed forests increased from 38.48% in 2001 to 44.50% in 2019 due to the formation of fast-growing tree species shoots on fallow lands. The area of meadow vegetation for the period from 2015 to 2019 decreased by 3.5%, from 4 276 to 3 121 km2, due to agriculture degradation and a significant decrease in livestock grazing. The indicator of soil fertility for the Klyazma basin was 0.74, which is a high indicator. It is established that the most active decrease in the agricultural land area occurs in the central, north-western and western parts of the river basin.

scholarly journals Spatiotemporal Differentiation and the Factors of Ecological Vulnerability in the Toutun River Basin Based on Remote Sensing Data

2019 ◽  
Vol 11 (15) ◽  
pp. 4160 ◽  
Author(s):  
Qin Liu ◽  
Tiange Shi
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
River Basin ◽  
Hot Spot ◽  
Remote Sensing Data ◽  
Cold Spot ◽  
Strengthening Effect ◽  
Land Use Type ◽  
Sensing Data ◽  
Ecological Vulnerability

Ecological vulnerability assessment increases the knowledge of ecological status and contributes to formulating local plans of sustainable development. A methodology based on remote sensing data and spatial principal component analysis was introduced to discuss ecological vulnerability in the Toutun River Basin (TRB). Exploratory spatial data analysis and a geo-detector were employed to evaluate the spatial and temporal distribution characteristics of ecological vulnerability and detect the driving factors. Four results were presented: (1) During 2003 and 2017, the average values of humidity, greenness, and heat in TRB increased by 49.71%, 11.63%, and 6.51% respectively, and the average values of dryness decreased by 165.24%. However, the extreme differences in greenness, dryness, and heat tended to be obvious. (2) The study area was mainly dominated by a high and extreme vulnerability grade, and the ecological vulnerability grades showed the distribution pattern that the northern desert area was more vulnerable than the central artificial oasis, and the central artificial oasis was more vulnerable than the southern mountainous area. (3) Ecological vulnerability in TRB showed significant spatial autocorrelation characteristics, and the trend was enhanced. The spatial distribution of hot/cold spots presented the characteristics of “hot spot—cold spot—secondary hot spot—cold spot” from north to south. (4) The explanatory power of each factor of ecological vulnerability was temperature (0.5955) > land use (0.5701) > precipitation (0.5289) > elevation (0.4879) > slope (0.3660) > administrative division (0.1541). The interactions of any two factors showed a non-linear strengthening effect, among which, land use type ∩ elevation (0.7899), land use type ∩ precipitation (0.7867), and land use type ∩ temperature (0.7791) were the significant interaction for ecological vulnerability. Overall, remote sensing data contribute to realizing a quick and objective evaluation of ecological vulnerability and provide valuable information for decision making concerning ecology management and region development.

scholarly journals Land use analysis of Lake Khanka basin using remote sensing data

2021 ◽  
Vol 895 (1) ◽  
pp. 012007
Author(s):  
K Yu Bazarov ◽  
E G Egidarev ◽  
N V Mishina
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Paddy Field ◽  
Arable Land ◽  
Remote Sensing Data ◽  
Open Pit ◽  
Geoinformation Systems ◽  
Sensing Data ◽  
Land Use Structure ◽  
Lake Khanka

Abstract The paper presents results of the analysis of the land use map compiled for transboundary Lake Khanka Basin using remote sensing data and geoinformation systems. The map reflects the distribution of 12 land categories in Lake Khanka basin in 2017 (arable land, abandoned arable land, paddy field, abandoned paddy field, shrubs and sparse growth, forest land, open pit, settlements, meadows and pastures, wet meadows and marshes, water bodies, forest cuttings and fire sites). The data of land use structure in the whole Lake’s watershed, in its Russian and Chinese parts are given. Data on the distribution of different land categories in the administrative territories of the rank of districts (Russia) and counties (China) are also presented. The analysis of land use structure showed that about 50 % of the Chinese part of the basin is covered by anthropogenically transformed natural complexes. The share of such lands in the territory of Russia amounts to 28 %. Agriculture is the most important factor in the change of natural complexes in Lake Khanka basin. Before early 1990s, the area of farmland had increased in the basin on both sides of the border, after that there was a significant reduction in cultivated lands, which had lasted for 10 years in the territory of China and for 20 years in Russia. Over the past decade, the area of cultivated areas in the basin and adjacent territories has extended again, which indicates an increase of anthropogenic impact and requires serious attention to monitoring of the ecological state of lands in the basin.

scholarly journals Organic matter temporal dynamics in the river ecosystem basin using remote sensing

One Ecosystem ◽  
2021 ◽  
Vol 6 ◽  
Author(s):  
Tatiana Trifonova ◽  
Natalia Mishchenko ◽  
Pavel Shutov
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Organic Matter ◽  
River Basin ◽  
Landscape Structure ◽  
Catchment Area ◽  
Carbon Accumulation ◽  
Biological Processes ◽  
Land Use Structure ◽  
Key Sites

Environmental research addresses ecosystems of various hierarchical levels. One of the ecosystem types is the river basin. The basin approach has been applied in the research. We consider the river basin as a single ecosystem of complex landscape structure. The research objective was to assess the biological processes in various landscapes within a holistic natural geosystem – a catchment area. The Klyazma River Basin (a part of the Volga River of 40 thousand km2 area) was the research object. It is a complex combination of different landscapes, each marked by a diverse composition of geomorphological and soil-vegetation structures. According to the geomorphological structure and soil and vegetation cover, four landscape provinces and eight key sites have been identified in the studied catchment area where the ecosystem parameter have been measured. The study is based on remote sensing data and the Trends. Earth Land Degradation Monitoring. The calculation of productivity indicators (GPP, NPP) in carbon units and the land use structure analysis are based on Modis data. The soil organic carbon pool was determined by the UN FAO’s data, based on Trends. Earth and QGIS 2.18. The two-factor variance analysis ANOVA has been used for the data statistic processing. The cartographic analysis of the land use structure dynamics of the entire Klyazma Basin resulted in revealing the areas where various land transitions from one category to another have been identified. They are basically associated with the agricultural land overgrowth. The forest area increased by 9% during the period from 2001 to 2017. Considerable increase in the waterlogged, wetlands areas was observed in the eastern part of the Basin, in the Volga-Klyazma Province. The landscapes react differently to changes in climatic parameters and land use. Thus, the active revegetation of farmland by forests gives the increased rate of carbon accumulation in the soil. Landscapes covered with grasses and shrubs are more productive those covered with forest. On the other hand, woody biotopes are more stable in their development over time. Statistical analysis using the two-factor variation analysis ANOVA method resulted in demonstrating that phytoproductivity dynamics of the key sites does not depend on their productivity parameters nor on the site landscape structure, but is mainly determined by a time factor. In different landscapes the biological processes, characterising the organic matter dynamics in the form of plant production, organic matter accumulation and others are shown to differ both in rate and intensity and ambiguously respond to changes in climate parameters and land use. The river basin, as a single ecosystem, showed sufficient stability of the dynamic processes. This suggests that holistic natural ecosystems, such as catchment areas, have internal compensatory mechanisms that maintain the development stability for a long time, while unplanned land use remains the main damaging factor.

Monitoring land use change in the Lake Taupo catchment between 1975, 1990 and 2002 using satellite remote sensing data

2007 ◽  
pp. 17-22
Author(s):  
H. Lilienthal ◽  
A. Brauer ◽  
K. Betteridge ◽  
E. Schnug
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Land Use ◽  
Land Use Change ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Native Vegetation ◽  
Lake Water Quality ◽  
Livestock Farming ◽  
Slow Decline

Conversion of native vegetation into farmed grassland in the Lake Taupo catchment commenced in the late 1950s. The lake's iconic value is being threatened by the slow decline in lake water quality that has become apparent since the 1970s. Keywords: satellite remote sensing, nitrate leaching, land use change, livestock farming, land management

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