Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1002/ldr.2850 |
Desertification vulnerability indexan effective approach to assess desertification processes: A case study in Anantapur District, Andhra Pradesh, India | |
Dharumarajan, Subramanian1; Bishop, Thomas F. A.3; Hegde, Rajendra1; Singh, Surendra Kumar2 | |
通讯作者 | Dharumarajan, Subramanian |
来源期刊 | LAND DEGRADATION & DEVELOPMENT
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ISSN | 1085-3278 |
EISSN | 1099-145X |
出版年 | 2018 |
卷号 | 29期号:1页码:150-161 |
英文摘要 | There is a need for the up-to-date assessment of desertification/land degradation maps that are dynamic in nature at different scales for comprehensive planning and preparation of action plans. This paper aims to develop the desertification vulnerability index (DVI) and predict the different desertification processes operating in Anantapur District, India, based on machine language techniques. Climate, land use, soil, and socioeconomic parameters were used to prepare DVI by a multivariate index model. The computed DVI along with climate, terrain, and soil properties was used as explanatory variable to predict the desertification processes by using a random forest model. About 14.2% of the area was created as a training dataset in 9 places for modeling and remaining area was tested for prediction of desertification processes. We used desertification status map (DSM) of Anantapur District prepared under Desertification status mapping of India-2nd cycle as a reference dataset for calculation of accuracy indices. Kappa and classification accuracy index were calculated for training and validation datasets. We recorded overall accuracy rate and kappa index of 85.5% and 75.8% for training datasets and 71.0% and 51.8% for testing datasets. The results of variable importance analysis of random forest model showed that DVI was the most important predictor followed by potential evapotranspiration and Normalized Difference Vegetation Index for prediction of desertification processes. The results from this work given new insight into using the existing knowledge on prediction of desertification in unvisited areas and also quick update of DSM maps. |
英文关键词 | desertification desertification vulnerability indices prediction random forest model variable importance |
类型 | Article |
语种 | 英语 |
国家 | India ; Australia |
收录类别 | SCI-E |
WOS记录号 | WOS:000423123700014 |
WOS关键词 | LAND DEGRADATION ; SOIL PROPERTIES ; FOREST ; CLASSIFICATION ; SENSITIVITY ; SCALE ; RISK ; MAP |
WOS类目 | Environmental Sciences ; Soil Science |
WOS研究方向 | Environmental Sciences & Ecology ; Agriculture |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/211466 |
作者单位 | 1.ICAR Res Complex, Natl Bur Soil Survey & Land Use Planning, Hebbal 560024, Bangaluru, India; 2.ICAR Res Complex, Natl Bur Soil Survey & Land Use Planning, Amaravati Rd, Nagpur 560024, Maharashtra, India; 3.Univ Sydney, Sydney Inst Agr, Sch Life & Environm Sci, Sydney, NSW 2006, Australia |
推荐引用方式 GB/T 7714 | Dharumarajan, Subramanian,Bishop, Thomas F. A.,Hegde, Rajendra,et al. Desertification vulnerability indexan effective approach to assess desertification processes: A case study in Anantapur District, Andhra Pradesh, India[J],2018,29(1):150-161. |
APA | Dharumarajan, Subramanian,Bishop, Thomas F. A.,Hegde, Rajendra,&Singh, Surendra Kumar.(2018).Desertification vulnerability indexan effective approach to assess desertification processes: A case study in Anantapur District, Andhra Pradesh, India.LAND DEGRADATION & DEVELOPMENT,29(1),150-161. |
MLA | Dharumarajan, Subramanian,et al."Desertification vulnerability indexan effective approach to assess desertification processes: A case study in Anantapur District, Andhra Pradesh, India".LAND DEGRADATION & DEVELOPMENT 29.1(2018):150-161. |
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