Monitoring Vegetation Coverage and Biomass Using Landsat Thematic Mapper 5 Images in a Foothill Artemisia-Ephemeral Rangeland of Uzbekistan

Abstract

This paper describes the capability of remote sensing in the monitoring of rangeland vegetation productivities and dynamics in the foothill areas of Uzbekistan, in order to enhance the sustainable utilization of natural resources. Seasonal productivity, including above-ground biomass, density, coverage, foliar chlorophyll, and carotene content, was measured for the Artemisia diffusa, the dominant species of the study area. The Normalized Difference Vegetation Index (NDVI), extracted from time-series Landsat TM5 satellite images, was used to obtain pertinent data regarding vegetation coverage and potential productivities. Seasonal precipitation was found to be a key factor in governing soil moisture in the semi-arid foothill rangelands, which directly influence the dynamics of plants and productivities. Precipitation and soil moisture determine the length of the plant growing season and further influence NDVI values. We found that time-series NDVI was significantly correlated with the seasonal green and total aboveground biomass of vegetation and coverage of Artemisia diffusa, soil moisture, and changeable nitrogen. We also found that the foliar chlorophylls of Artemisia diffusa was significantly correlated with the green above-ground biomass (r = 0.44, P < 0.05). The results can contribute to further monitoring of ecosystem health and habitat conditions using remote sensing (RS) as an accurate tool in large rangeland areas.

Assessment of the ecological state of pastures and methods of their improvement, adapted to the conditions of global climate change

“…On this type of pasture, plants such as Carex, Poa bulbosa, and other ephemeroids grow. [4,[15][16] The average annual yield of pastures is low -0.25-0.3 t/ha. Weeds, poorly eaten plants grow in large numbers on pastures.…”

Vegetation monitoring in the South Aral Sea region by remote sensing and GIS

“…The growth and development of plants depends on the influence of environmental factors. Because of, the growth of plants is affected by seasonal climate changes [8]. Remote Sensing-based Normalized Difference Vegetation Index (NDVI) is widely used in vegetation condition assessment, focusing mainly on determining long-term environmental conditions [9].…”