Current Issue

10 February 2018, Volume 10 Issue 1 Previous Issue    Next Issue
For Selected: View Abstracts Toggle Thumbnails
Orginal Article
Determinants and rates of land degradation: Application of stationary time-series model to data from a semi-arid environment in Kenya
Z MGANGA Kevin, M NYARIKI Dickson, K R MUSIMBA Nashon, A AMWATA Dorothy
Journal of Arid Land. 2018, 10 (1): 1-11.   DOI: 10.1007/s40333-017-0036-0
Abstract ( 559 )   HTML ( 30 )     PDF (293KB) ( 1322 )  

The causes of land degradation in the African drylands have been shown to vary. Some researchers consider climate to be the major contributor to degradation, with anthropogenic factors playing a minor role. Others reverse the significance of these two factors. A third group attributes land degradation to climate and anthropogenic factors equally. This study was undertaken to establish the factors influencing land degradation in a semi-arid environment in southeastern Kenya and the rate of change in vegetation types for a period of 35 years (1973-2007). The reduction in grassland cover was used as an indicator of land degradation. Causes of land degradation were determined by a multiple regression analysis. A log-linear regression analysis was used to establish the rate of vegetation change. The multiple and log-linear regression analyses showed: (1) woody vegetation, livestock population and cultivated area to be the main contributors of reduction in grassland cover in the area, and (2) an increase in undesirable woody species, livestock population and cultivated area had a significant (P<0.05) negative effect on grassland vegetation. Increased human population, low amounts of rainfall and drought showed no significant negative effect on grassland vegetation cover. In conclusion, human and livestock population growth and increased agricultural land have contributed to intensive crop cultivation and overgrazing in the semi-arid lands. This overuse of the semi-arid rangelands has worsened the deterioration of the natural grassland vegetation.

Monitoring desertification processes in Mongolian Plateau using MODIS tasseled cap transformation and TGSI time series
Qingsheng LIU, Gaohuan LIU, Chong HUANG
Journal of Arid Land. 2018, 10 (1): 12-26.   DOI: 10.1007/s40333-017-0109-0
Abstract ( 701 )   HTML ( 21 )     PDF (987KB) ( 1630 )  

Most remote sensing studies assess the desertification using vegetation monitoring method. But it has the insufficient precision of vegetation monitoring for the limited vegetation cover of the desertification region. Therefore, it offers an alternative approach for the desertification research to assess sand dune and sandy land change using remote sensing in the desertification region. In this study, the indices derived from the well-known tasseled cap transformation (TCT), tasseled cap angle (TCA), disturbance index (DI), process indicator (PI), and topsoil grain size index (TGSI) were integrated to monitor and assess the desertification at the thirteen study sites including sand dunes and sandy lands distributed in the Mongolian Plateau (MP) from 2000 to 2015. A decision tree was used to classify the desertification on a regional scale. The average overall accuracy of 2000, 2005, 2010 and 2015 desertification classification was higher than 90%. Results from this study indicated that integration of the advantages of TCA, DI and TGSI could better assess the desertification. During the last 16 years, Badain Jaran Desert, Tengger Desert, and Ulan Buh Desert showed a relative stabilization. Otindag Sandy Land and the deserts of Khar Nuur, Ereen Nuur, Tsagan Nuur, Khongoryn Els, Hobq, and Mu Us showed a slow increasing of desertification, whereas Bayan Gobi, Horqin and Hulun Buir sandy lands showed a slow decreasing of desertification. Compared with the other 11 sites, the fine sand dunes occupied the majority of the Tengger Desert, and the coarse sandy land occupied the majority of the Horqin Sandy Land. Our findings on a three or four years’ periodical fluctuated changes in the desertification may possibly reflect changing precipitation and soil moisture in the MP. Further work to link the TCA, DI, TGSI, and PI values with the desertification characteristics is recommended to set the thresholds and improve the assessment accuracy with field investigation.