Mapping irrigated agriculture in complex landscapes using SPOT6 imagery and object-based image analysis - A case study in the Central Rift Valley, Ethiopia -
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Marjolein F. A. Vogels | Steven M. De Jong | Geert Sterk | Elisabeth A. Addink | S. M. Jong | E. Addink | G. Sterk
[1] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[2] Geert Sterk,et al. The effectiveness of soil conservation measures at a landscape scale in the West Usambara highlands, Tanzania , 2015 .
[3] Vimal Mishra,et al. Descriptor : Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015 , 2017 .
[4] L. You,et al. Estimating the potential for expanding smallholder irrigation in Sub-Saharan Africa , 2014 .
[5] Thomas Blaschke,et al. Geographic Object-Based Image Analysis – Towards a new paradigm , 2014, ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing.
[6] Andy Liaw,et al. Classification and Regression by randomForest , 2007 .
[7] Tilahun Amede,et al. IRRIGATION WATER PRODUCTIVITY AS AFFECTED BY WATER MANAGEMENT IN A SMALL-SCALE IRRIGATION SCHEME IN THE BLUE NILE BASIN, ETHIOPIA , 2011, Experimental Agriculture.
[8] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[9] Rui Sun,et al. Mapping Irrigated and Rainfed Wheat Areas Using Multi-Temporal Satellite Data , 2016, Remote. Sens..
[10] Jessica L. McCarty,et al. Extracting smallholder cropped area in Tigray, Ethiopia with wall-to-wall sub-meter WorldView and moderate resolution Landsat 8 imagery , 2017 .
[11] A. Huis,et al. Pest management strategies in traditional agriculture: an African perspective. , 2000, Annual review of entomology.
[12] Alireza Soffianian,et al. Crop type mapping in a highly fragmented and heterogeneous agricultural landscape: A case of central Iran using multi-temporal Landsat 8 imagery , 2016, Comput. Electron. Agric..
[13] Mario Chica-Olmo,et al. An assessment of the effectiveness of a random forest classifier for land-cover classification , 2012 .
[14] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[15] J. Bruinsma. BY HOW MUCH DO LAND, WATER AND CROP YIELDS NEED TO INCREASE BY 2050 ? , 2009 .
[16] Peter Droogers,et al. Estimating actual irrigation application by remotely sensed evapotranspiration observations , 2010 .
[17] Justus Wesseler,et al. Performance assessment of smallholder irrigation in the Central Rift Valley of Ethiopia , 2011 .
[18] Martin Volk,et al. The comparison index: A tool for assessing the accuracy of image segmentation , 2007, Int. J. Appl. Earth Obs. Geoinformation.
[19] Alex Bolding,et al. Identifying the potential for irrigation development in Mozambique: Capitalizing on the drivers behind farmer-led irrigation expansion , 2014 .
[20] J. Burney,et al. Smallholder Irrigation as a Poverty Alleviation Tool in Sub-Saharan Africa , 2012 .
[21] Zhe Guo,et al. What is the irrigation potential for Africa? A combined biophysical and socioeconomic approach , 2011 .
[22] Jeroen C. J. H. Aerts,et al. Adaptation strategies to climate change and climate variability: A comparative study between seven contrasting river basins , 2005 .
[23] P. Schmitter,et al. On-farm smallholder irrigation performance in Ethiopia: From water use efficiency to equity and sustainability , 2016 .
[24] Arno Schäpe,et al. Multiresolution Segmentation : an optimization approach for high quality multi-scale image segmentation , 2000 .
[25] U. Benz,et al. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information , 2004 .
[26] Christopher Conrad,et al. Per-Field Irrigated Crop Classification in Arid Central Asia Using SPOT and ASTER Data , 2010, Remote. Sens..
[27] M. Abuzar,et al. Mapping Irrigated Farmlands Using Vegetation and Thermal Thresholds Derived from Landsat and ASTER Data in an Irrigation District of Australia , 2015 .
[28] Prasad S. Thenkabail,et al. Ganges and Indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data , 2005 .
[29] Pedro Antonio Gutiérrez,et al. Object-Based Image Classification of Summer Crops with Machine Learning Methods , 2014, Remote. Sens..
[30] Yang Yang,et al. Remote Sensing of Irrigated Agriculture: Opportunities and Challenges , 2010, Remote. Sens..
[31] W. Mauser,et al. A global approach to estimate irrigated areas – a comparison between different data and statistics , 2018 .
[32] C. Vörösmarty,et al. Anthropogenic Disturbance of the Terrestrial Water Cycle , 2000 .
[33] Stéphane Dupuy,et al. A Combined Random Forest and OBIA Classification Scheme for Mapping Smallholder Agriculture at Different Nomenclature Levels Using Multisource Data (Simulated Sentinel-2 Time Series, VHRS and DEM) , 2017, Remote. Sens..
[34] Jessica L. McCarty,et al. Smallholder crop area mapped with wall-to-wall WorldView sub-meter panchromatic image texture: A test case for Tigray, Ethiopia , 2018, Remote Sensing of Environment.
[35] T. M. Lillesand,et al. Remote Sensing and Image Interpretation , 1980 .