Mapping and assessing crop diversity in the irrigated Fergana Valley, Uzbekistan

Abstract Crop diversity (e.g. the number of agricultural crop types and the level of evenness in area distribution) in the agricultural systems of arid Central Asia has recently been increased mainly to achieve food security of the rural population, however, not throughout the irrigation system. Site-specific factors that promote or hamper crop diversification after the dissolvent of the Soviet Union have hardly been assessed yet. While tapping the potential of remote sensing, the objective was to map and explain spatial patterns of current crop diversity by the example of the irrigated agricultural landscapes of the Fergana Valley, Uzbekistan. Multi-temporal Landsat and RapidEye satellite data formed the basis for creating annual and multi-annual crop maps for 2010–2012 while using supervised classifications. Applying the Simpson index of diversity (SID) to circular buffers with radii of 1.5 and 5 km elucidated the spatial distribution of crop diversity at both the local and landscape spatial scales. A variable importance analysis, rooted in the conditional forest algorithm, investigated potential environmental and socio-economic drivers of the spatial patterns of crop diversity. Overall accuracy of the annual crop maps ranged from 0.84 to 0.86 whilst the SID varied between 0.1 and 0.85. The findings confirmed the existence of areas under monocultures as well as of crop diverse patches. Higher crop diversity occurred in the more distal parts of the irrigation system and sparsely settled areas, especially due to orchards. In contrast, in water-secure and densely settled areas, cotton-wheat rotations dominated due to the state interventions in crop cultivation. Distances to irrigation infrastructure, settlements and the road network influenced crop diversity the most. Spatial explicit information on crop diversity per se has the potential to support policymaking and spatial planning towards crop diversification. Driver analysis as exemplified at the study region in Uzbekistan can help reaching the declared policy to increase crop diversity throughout the country and even beyond.

[1]  R. Dick.  A review: long-term effects of agricultural systems on soil biochemical and microbial parameters , 1992 .

[2]  Olena Dubovyk,et al.  Spatio-temporal analyses of cropland degradation in the irrigated lowlands of Uzbekistan using remote-sensing and logistic regression modeling , 2012, Environmental Monitoring & Assessment.

[3]  E. H. Simpson.  Measurement of Diversity , 1949, Nature.

[4]  K. Hornik,et al.  Unbiased Recursive Partitioning: A Conditional Inference Framework , 2006 .

[5]  J. Lamers,et al.  FINANCIAL ANALYSIS OF SMALL-SCALE FORESTS IN THE AMU DARYA LOWLANDS OF RURAL UZBEKISTAN , 2008 .

[6]  Achim Zeileis,et al.  BMC Bioinformatics BioMed Central Methodology article Conditional variable importance for random forests , 2008 .

[7]  C. Kouveliotou,et al.  Gamma Ray Bursts , 1997, Science.

[8]  S. Hurlbert.  The Nonconcept of Species Diversity: A Critique and Alternative Parameters. , 1971, Ecology.

[9]  B. Lin.  Resilience in Agriculture through Crop Diversification: Adaptive Management for Environmental Change , 2011 .

[10]  Mark Giordano,et al.  Agricultural Water Use and Trade in Uzbekistan: Situation and Potential Impacts of Market Liberalization , 2009 .

[11]  Christopher Conrad,et al.  Remote sensing and hydrological measurement based irrigation performance assessments in the upper Amu Darya Delta, Central Asia , 2013 .

[12]  J. Mohan Reddy,et al.  Evaluation of furrow irrigation practices in Fergana Valley of Uzbekistan , 2013 .

[13]  Christopher Conrad,et al.  Satellite based calculation of spatially distributed crop water requirements for cotton and wheat cultivation in Fergana Valley, Uzbekistan , 2013 .

[14]  Cuizhen Wang,et al.  MODIS-Based Fractional Crop Mapping in the U.S. Midwest with Spatially Constrained Phenological Mixture Analysis , 2015, Remote. Sens..

[15]  C. Martius,et al.  Options and Constraints for Crop Diversification: A Case Study in Sustainable Agriculture in Uzbekistan , 2013 .

[16]  M. Glantz,et al.  Irrigation and Land Degradation in the Aral Sea Basin , 2001 .

[17]  J. Mohan Reddy,et al.  Analysis of cotton water productivity in Fergana Valley of Central Asia. , 2012 .

[18]  Christopher Conrad,et al.  Integration of Optical and Synthetic Aperture Radar Imagery for Improving Crop Mapping in Northwestern Benin, West Africa , 2014, Remote. Sens..

[19]  L. Mapemba,et al.  The Determinants and Extent of Crop Diversification Among Smallholder Farmers: A Case Study of Southern Province Zambia , 2014 .

[20]  Luis S. Pereira,et al.  Field assessment of the water saving potential with furrow irrigation in Fergana, Aral Sea basin , 2005 .

[21]  C. Woodcock,et al.  Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation , 2013 .

[22]  Christopher Conrad,et al.  Impact of feature selection on the accuracy and spatial uncertainty of per-field crop classification using Support Vector Machines , 2013 .

[23]  Christopher Conrad,et al.  Analysing irrigated crop rotation patterns in arid Uzbekistan by the means of remote sensing: A case study on post-Soviet agricultural land use , 2016 .

[24]  Björn Waske,et al.  Classifying Multilevel Imagery From SAR and Optical Sensors by Decision Fusion , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[25]  A. Haubold,et al.  Water Patterns in the Landscape of Khorezm, Uzbekistan: A GIS Approach to Socio-Physical Research , 2012 .

[26]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[27]  J. Lawton,et al.  Declining biodiversity can alter the performance of ecosystems , 1994, Nature.

[28]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[29]  D. King,et al.  Optimizing landscape selection for estimating relative effects of landscape variables on ecological responses , 2013, Landscape Ecology.

[30]  D. Zilberman,et al.  Economic Factors Affecting Diversified Farming Systems , 2013 .

[31]  A. J. W. De Wit,et al.  Efficiency and accuracy of per-field classification for operational crop mapping , 2004 .

[32]  Gilles Louppe,et al.  Understanding variable importances in forests of randomized trees , 2013, NIPS.

[33]  Thomas Blaschke,et al.  Object based image analysis for remote sensing , 2010 .

[34]  John P. A. Lamers,et al.  The dynamics of groundwater table and salinity over 17 years in Khorezm , 2011 .

[35]  Björn Waske,et al.  Mapping Land Management Regimes in Western Ukraine Using Optical and SAR Data , 2014, Remote. Sens..

[36]  A. Russell.  Relationships between crop-species diversity and soil characteristics in southwest Indian agroecosystems , 2002 .

[37]  W. Parton,et al.  Agricultural intensification and ecosystem properties. , 1997, Science.

[38]  Henrik G. Smith,et al.  Landscape-scale crop diversity interacts with local management to determine ground beetle diversity , 2014 .

[39]  A. Magurran,et al.  Measuring Biological Diversity , 2004 .

[40]  P. Atkinson,et al.  Random Forest classification of Mediterranean land cover using multi-seasonal imagery and multi-seasonal texture , 2012 .

[41]  R. Singh,et al.  Diversification of Indian Agriculture: Composition, Determinants and Trade Implications , 2006 .

[42]  B. Wardlow,et al.  Analysis of time-series MODIS 250 m vegetation index data for crop classification in the U.S. Central Great Plains , 2007 .

[43]  Dennis C. Duro,et al.  Predicting species diversity in agricultural environments using Landsat TM imagery , 2014 .

[44]  L. Thrupp,et al.  Linking agricultural biodiversity and food security: the valuable role of agrobiodiversity for sustainable agriculture. , 2000, International affairs.

[45]  C. Conrad,et al.  Remote Sensing and Hydrological Measurements for Irrigation Performance Assessments in a Water User Association in the Lower Amu Darya River Basin , 2011 .

[46]  Peter Bauer-Gottwein,et al.  Will climate change exacerbate water stress in Central Asia? , 2012, Climatic Change.

[47]  Lenore Fahrig,et al.  Functional landscape heterogeneity and animal biodiversity in agricultural landscapes. , 2011, Ecology letters.

[48]  Olena Dubovyk,et al.  Derivation of temporal windows for accurate crop discrimination in heterogeneous croplands of Uzbekistan using multitemporal RapidEye images , 2014 .

[49]  Christopher Conrad,et al.  Adapting to water scarcity: constraints and opportunities for improving irrigation management in Khorezm, Uzbekistan , 2013 .

[50]  S. Polasky,et al.  Agricultural sustainability and intensive production practices , 2002, Nature.

[51]  Christopher Conrad,et al.  Impact of Categorical and Spatial Scale on Supervised Crop Classification using Remote Sensing , 2015 .