SAR and optical data in land degradation processes estimation: a case study from Southeast Bulgaria

Soil is a dominant factor of the terrestrial geosystems in semi-arid and dry sub-humid zones, particularly through its effect on biomass production. Due to the climate changes and industrial development, soil resources in these zones are prone to degradation. On the other hand, degradation processes cause changes in land cover. Remote sensing optical data are widely used in the process of determining land cover change whereas SAR data is suitable for determination of soil moisture dynamics. In the present study, Tasseled Cap Transform (TCT) and modified Change Vector Analysis (mCVA) techniques are applied to Landsat and Sentinel 2 data in order to be determined magnitude and direction of land cover changes in the semi-natural areas of Haskovo Region, Southeast Bulgaria. The study of the vector direction presents some distinct changes in the soil characteristics for the whole territory and significant changes in vegetation characteristics and moisture content in part of the semi-mountainous territories of the examined region. It has been found that the magnitude of those changes increases up to 50% in some of the territories under investigation. SAR data has been used to evaluate the relative soil moisture content in various soil differences and to trace its dynamics during growing season. In order to achieve this aim, Relative Soil Moisture Index (RSMI) is used. The index estimates the relative variation of volumetric soil moisture content in a given time period and enables determination of its change in relative values. On the basis of integrated application of aforementioned techniques, a model providing key information about the impact of soil moisture change and dynamics upon processes related to land cover change. The suggested model is appropriate for estimation of ecosystem services and functions delivered by landscapes in semi-arid and dry sub-humid zones.

[1]  Mehrez Zribi,et al.  Soil moisture estimation using multi‐incidence and multi‐polarization ASAR data , 2006 .

[2]  Daniela Avetisyan,et al.  Determining the magnitude and direction of land cover changes in the semi-natural areas of Haskovo Region, Southeast Bulgaria , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[3]  Mehrez Zribi,et al.  Potential of ASAR/ENVISAT for the characterization of soil surface parameters over bare agricultural fields , 2005 .

[4]  Richard K. Moore,et al.  Microwave Remote Sensing, Active and Passive , 1982 .

[5]  Brian W. Barrett,et al.  Soil Moisture Retrieval from Active Spaceborne Microwave Observations: An Evaluation of Current Techniques , 2009, Remote. Sens..

[6]  Ayad Mohammed Fadhil,et al.  Drought mapping using Geoinformation technology for some sites in the Iraqi Kurdistan region , 2011, Int. J. Digit. Earth.

[7]  E. Engman.  Progress in microwave remote sensing of soil moisture , 1990 .

[8]  F. Ulaby,et al.  Microwave Dielectric Behavior of Wet Soil-Part 1: Empirical Models and Experimental Observations , 1985, IEEE Transactions on Geoscience and Remote Sensing.

[9]  F. Bonn,et al.  Assessment of land‐cover changes related to shrimp aquaculture using remote sensing data: a case study in the Giao Thuy District, Vietnam , 2006 .

[10]  R. J. Kauth,et al.  The Tasseled Cap de-mystified , 1986 .

[11]  F. Ulaby,et al.  Microwave Dielectric Behavior of Wet Soil-Part II: Dielectric Mixing Models , 1985, IEEE Transactions on Geoscience and Remote Sensing.

[12]  Munmun Baisantry,et al.  Change vector Analysis using Enhanced PCA and Inverse Triangular Function-based Thresholding , 2012 .

[13]  Pol Coppin,et al.  Comparative performance of a modified change vector analysis in forest change detection , 2005 .

[14]  T. Schmugge,et al.  Remote sensing in hydrology , 2002 .

[15]  Martha C. Anderson,et al.  Remote sensing of drought : innovative monitoring approaches , 2012 .

[16]  V. SPACE TECHNOLOGY AND ENVIRONMENT FOREST VEGETATION STATE AND DYNAMICS IN THE HASKOVO REGION (BULGARIA) - A RESEARCH BASED ON VEGETATION INDICES, CLIMATE AND SOLAR ACTIVITY DATA , 2015 .