Special Issue "Global Croplands"

Guest Editor
Dr. Prasad S. Thenkabail
Research Geographer 14, U.S. Geological Survey, 114, W. Separation Canyon Trl. Flagstaff, Arizona 86001, USA
E-Mail:
Interests: remote sensing applications to: (a) agriculture, (b) water resources, (c) wetlands, (d) droughts, (e) land use\land cover, (f) forestry, (g) natural resources management, and (h) environments; global mapping of croplands (irrigated and rainfed); hyperspectral remote sensing of vegetation; characterization of large river basins and deltas; wetland characterization and mapping; terrestrial Carbon storage and flux

Dear Colleagues,

With the era of green revolution fast fading, the world is looking at innovative approaches to curb potentially catastrophic effects of a looming long-term food crisis. Food security is tightly linked to croplands and their water use. More recently, other factors have come into play: conversion of croplands to bio-fuel lands and urban lands, loss of croplands to salinization and soil erosion, changing cropping patterns, production limits of existing crop varieties, and above all climate change. As a result, increases in grain production are becoming more difficult to achieve. Further, increasing cropland areas to grow more food is not an option given environmental and ecological impacts. So, we need to answer a central question: how do we grow more food from existing croplands and water resources and continue to feed the ballooning populations expected to reach 10 billion by 2050 from current 6 billion?

The greatest quantity of water used by humans is for producing food from croplands. For example, nearly 80% of all blue water (water in lakes, rivers, reservoirs, and ground water) used by humans is for growing food in irrigated croplands. Similarly, overwhelming proportion of the green water (water in soil moisture) used by humans is for producing food from rainfed croplands. However, water used by croplands is a complex phenomenon and depends on crop types, soil types, latitudelocation, type of irrigation, and a host of other issues. So, a proper understanding of these issues need us to inter-link croplands to water use, and food production considering a changing climate and keeping in view environmental sustainability, ecological integrity, and continued robust growth of economy.

In order to address above issues of great significance for humanity, we need to put collective knowledge of the best experts working in the area to facilitate solutions for generations to come.
Thereby, this special issue on “Global Croplands” by Journal “Remote Sensing” is an effort to bring together the collective knowledge base of the best experts involved in ensuring our food security for future generations. Given this, the overarching goal of this special volume will be to ensure that these diverse state-of-art knowledge base is available in one place for decision makers, experts, and other users in order to make use of the same and to advance our knowledge further to find smart solutions to overcome food crisis and produce in plenty for future generations. Thereby, I would like to seek articles from best multi-disciplinary experts addressing multitude of issues that are of relevance to ensure a food secure world for many generations to come. Specific topics may include:

Global cropland areas

• irrigated
• rainfed

• Remote sensing: At various spatial, spectral, radiometric, and temporal resolutions
• Non-remote sensing

• linking croplands to water use
• surface energy balance models
• other approaches like water balance
• water use assessments without use of thermal data

• Remote sensing approaches
• Non remote sensing approaches

• link to rainfed croplands and food production

• link to irrigated croplands and food production

• achievements, current stagnation, future growth possibilities

• opportunities
• Food security model

• linking economy to croplands, water use, and food security

• in mapping, modeling, and assessments

All manuscripts should be submitted to remotesensing@mdpi.org with a copy to the Guest Editor. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed Open Access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this Open Access journal is 300 CHF per accepted paper. English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.

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• croplands
• water
• remote sensing
• global: food security
• surface energy balance models
• water productivity
• spatial modeling
• agriculture
• economy
• irrigated croplands
• rainfed croplands
• climate change

Type of Paper: Article
Title: Estimating Global Cropland Extent with Multi-year MODIS Data
Author: Prof. Matthew Hansen et al.
Affiliation: South Dakota State University (SDSU), United States Geological Survey Earth Resources Observation and Science (USGS/EROS), Geographic Information Science Center of Excellence, 1021 Medary Ave, Wecota Hall Box 506B, Brookings SD 57007, USA; E-Mail: Matthew.Hansen@sdstate.edu
Abstract: Nine years of MODIS data were used with training data derived from the GeoCover Landsat data set to estimate per MODIS pixel cropland probability. Areal extent was compared to multi-year mean acreages from USDA FAS data sets. Results illustrate the value of MODIS in monitoring industrial agriculture regions, while regions consisting of smaller field sizes and/or less intensive cultivation management practices were not well characterized. For the major agricultural production zones and countries, including Canada, the US, Brazil, Argentina, India and China, MODIS had training accuracies of X% and high matching probability thresholds with FAS data. MODIS data were less valuable in underdeveloped agricultural regions such as Africa. Of key commodities, corn and soy regions were mapped well, while rice growing regions were not.

Article Type: Review
Title: Remote Sensing and Geospatial Technological Applications for Site-specific Management of Fruit and Nut Crops: A Review
Authors: Sudhanshu S. Panda, Gerrit Hoogenboom, Joel O. Paz
Affiliation: Department of Science, Engineering, and Technology, Gainesville State College, Oakwood, Georiga 30566, USA
Department of Biological and Agricultural Engineering, the University of Georgia, Griffin, Georgia 30223, USA; E-Mail: spanda@gsc.edu; gerrit@uga.edu
Abstract: Precision agriculture is defined as the observation, impact assessment, and the timely strategic response for detecting minute variation in agricultural production and subsequent remedial measures. It is applied for a range of applications such as crop production, horticultural production, livestock and dairy farming, and forest management. Site-specific crop management (SSCM) is one facet of precision agriculture that involves spatial referencing, crop and climate monitoring, attribute mapping, decision support system like soil and environmental management, land use land cover evaluation and management, water availability and usage, etc., and consequent differential action. Geospatial technologies, such as remote sensing, geographic information system (GIS), and global positioning system (GPS) provide for a much greater degree of precision for SSCM. SSCM is very common for management of traditional field crops, but its use and application in horticultural crops, especially fruit and nut crops, is not very common. A successful application of SSCM use in fruit and nut crops has the potential for increasing net returns and optimizing resource use. However, this will require a careful integration of aerial or satellite imaging, along with GPS and GIS. The delineation of nuts and fruit orchards and spatial analysis using geospatial technology can provide a means for decision making, such as fruit yield determination, the quantification of appropriate fertilizer and irrigation requirements and application scheduling, and integrated pest management. This paper will review the use and application of geospatial technology, especially remote sensing for conducting SSCM in horticultural crops, including oranges, peaches, pecans, apples, grapes, blueberries, and other nut and fruit crops in United States and other parts of the world.

Title: The Future of Global Cropland Monitoring and Moderate Resolution Earth Observations
Author: James R. Irons ¹, Bradley Doorn ²
Affiliations: ¹ NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA; E-mail: james.r.irons@nasa.gov
² NASA Headquarters, Washington, DC, 20546-0001, USA; E-mail: bradley.doorn@nasa.gov
Abstract: Since the early 1970’s satellite remote sensing has been critical to monitoring global food supplies. Global markets and governments have relied on the objectivity, reliability, and timeliness of space-based earth observations to focus food access for the world’s poorest and ensure market information is fair and open. The Landsat (moderate resolution) satellite program has been a prominent source of space-based earth observations for global cropland monitoring during this time.
Today, the Landsat program and its users are transitioning to new earth observation capabilities and new analysis processes. For instance, USDA now acquires much of its satellite data from the Indian RESOURCESAT-1 satellite, particularly from its Advanced Wide Field Sensors (AWiFS). The near future will provide many more options for global cropland monitoring from space. International plans include the U.S. launch of the Landsat Data Continuity Mission (LDCM) in late 2012 to replace Landsat 7, the European Space Agency (ESA) launch of two Sentinel-2 satellites beginning in 2012, and the Indian launch of a RESOURCESAT-2 satellite in 2009 or 2010, just to name a few. These and other moderate resolution satellite systems can increase the frequency and reliability of cropland observations potentially leading to improved forecasts of global food supplies. This paper will discuss LDCM’s role in this new era and the impact of these future satellite systems on cropland monitoring.

Title: Mapping Mekong Land Cover at 250m Resolution Without in Situ Observation
Authors: Kithsiri Perera¹, Srikantha Herath², Armando Apan¹
Affiliations: ¹ Faculty of Engineering and Surveying, University of Southern Queensland, West Street, Toowoomba 4350 QLD Australia; E-mails: perera@usq.edu.au; apana@usq.edu.au
² Environment and Sustainable Development, United Nations University, 5-53-70,Jingumae, Shibuya-ku, Tokyo 150-0001, Japan; E-mail: hearath@hq.unu.edu
Abstract: The Lower Mekong River basin, which covers about 75% of 0.8 million sq km of the whole basin, is the home for about 60 million riparian population. The fertile soil of the basin is the lifeline of the region, which annually produces enough rice to feed 300 million people. However, Mekong often suffers from devastating floods causing extensive damage to human life and agriculture. On the other hand, increased human interactions have reduced the forests cover (by about 50% from 1970 to 1990) in recent years, aggravating environmental damage. The mitigation of flood hazard and sustainable use of the river basin is the ultimate challenge that Mekong basin inhabitants are facing today. Mapping the land cover at a high resolution is a top priority in this regard, which can be the base for many other GIS studies. However, vast disparities in geo-climatic features of the huge lower Mekong basin and less-accessible remote areas are causing mapping a formidable task. Thus, the use of remote sensing data is seen as a practical approach for such mapping activities. The present study used MODIS TERRA and Aqua 250m satellite data as a suitable platform to extract land cover information. Images, precipitation data, and river discharge data of 12 months (March 2004 to Feb 2005) were examined and dates around February were selected to gather cloud-free data. Through visual observation of true color (B1: R, B4: G, B3: B) images from late January to early March, images with least cloud cover and low disturbances from biomass fire smoke gathered. To overcome the need for costly and time consuming in-situ field observations for ground truth and accuracy assessment data, freely available super-resolution data sets from Google map were utilized. Image potions were individually classified using maximum likelihood classifier to maximize the classification accuracy. A modified classification scheme of IGBP land cover classification with 12 classes used for the map, which helped to conduct accuracy assessment against IGBP product. The results gave highly matching land cover information with IGBP 1km Land cover data set but with greater details, especially in paddy cultivated Mekong Delta. The map will help to enhance existing 1992/93 AVHRR, 1996/97 Satellite hard copy base (Mekong River Commission) land cover data sets too. Also, the new land cover data set will be useful in flood mitigation studies and also a base data set to be developed as a series of data sets through updates. The methodology of present research shows possibilities of mapping large regions at a satisfactory level of accuracy using freely available MODIS data and without costly field observations.

Type of Paper: Article
Title: Assessing Land Cover Change in an Area of Large Surface Mines Detected Using a Landsat 7 Time Series
Author: Lubos Matejicek
Affiliation: Institute for Environmental Studies, Charles University in Prague, Faculty of Natural Science, Benatska 2, 12801 Prague 2, Czech Republic; E-Mail: lmatejic@natur.cuni.cz
Abstract: Geographic information systems and satellite remote sensing information are emerging technologies in land cover change assessment. Nowadays, they offer the opportunity to gain insight into land cover change properties through the spatio-temporal data captured during decades. A time series of Landsat 7 ETM+ data covering the period 2000-2008 is used to explore the impacts of surface mining and reclamation, which is the dominant driver of land cover change in North-western regions of the Czech Republic. Advanced quantification of the extent of mining activities is important for assessing how this land cover change affects ecosystem services such as biodiversity and croplands. The used images from 2000, 2002, 2004, 2005, 2007 and 2008 (Landsat 7 ETM+ scenes captured after May 31, 2003 with the scan line corrector off can be still used, because the area of interest is within the central portion of the given scenes) assist to map the extent of surface mines and mine reclamation for a large surface coal mine. The standard image processing techniques extended by classification algorithms in conjunction with actual digital maps and aerial images are used to track changes through time. The spatio-temporal analysis based on derived land cover images shows a decrease of croplands in the study area for 2008 approximately -5.5% relative to 2000, which is partly compensated by an increase of reclamation sites. The land cover changes are compared with key resources indicators such as a normalized difference vegetation index and an enhanced vegetation index. The trend analysis of the key resources indicators indicates moderately decreasing trends in close proximity to the mining development. This study highlights the use of satellite imaginary and GISs in mapping and analysis of land cover, as well as the identification of key issues related to imaginary classification, spatial processing, and the quantification of cropland transformation processes by mining development.
Keywords: environmental impact assessment; land cover; surface mining; GIS

Title: Monitoring Global Croplands with Coarse Resolution Earth Observations: The Global Agriculture Monitoring (GLAM) Project
Authors: Inbal Becker-Reshef, Chris Justice, Compton Tucker, Assaf Anyamba, Matthew Hansen, Brad Doorn and Curt Reynolds
Affiliation: Geography Department, University of Maryland, USA; E-Mails: ireshef@hermes.geog.umd.edu; justice@hermes.geog.umd.edu
Abstract: In recent years there has been a dramatic increase in the demand for timely, comprehensive global agricultural intelligence as world food consumption has outweighed production for most of the past decade. Timely information on global crop production is indispensable for combating the growing stress on the world’s crop production and for securing both short-term and long-term stable and reliable access to food.
Global agriculture monitoring systems are critical to providing this kind of intelligence and earth observations are an essential component of an effective global agricultural monitoring system as they offer timely, objective, global information on croplands distribution, crop development and conditions as the growing season progresses.
The Global Agriculture Monitoring Project (GLAM), a joint NASA, USDA, UMd, and SDSU initiative, has built a global agricultural monitoring system that provides the USDA Foreign Agricultural Service (FAS) scientifically validated, near-real-time, earth observations data, analysis tools, and croplands distribution maps for crop condition monitoring and production assessment. This system serves as an integral component to the USDA’s FAS Decision Support System (DSS) for agriculture, as it enables analysts to monitor crop conditions, locate and track the factors impairing agricultural productivity, and to forecast crop yields prior to harvest. Satellite data are used in a ‘convergence of evidence’ approach with meteorological data, crop models and field reports. The USDA FAS is currently the only operational provider of timely, objective crop production forecasts at the global scale. These forecasts are routinely used by the other US Federal government agencies as well as by commodity trading companies, farmers, relief agencies and foreign governments playing a vital role within the global agricultural market. This paper will discuss the various components and recent advances of the GLAM monitoring system and the needs and future role of earth observations in global agricultural monitoring.

Type of Paper: Article
Title: Potential of Using Remote Sensing Techniques to Global Assessment of Water Footprint of Crops
Authors: M. Romaguera^1,2, A.Y. Hoekstra¹, Z. Su², M.S. Krol¹ and M.S. Salama²
Affiliations: ¹ Department of Water Engineering and Management, University of Twente, Enschede, The Netherlands; E-Mails: M.RomagueraAlbentosa@ctw.utwente.nl, A.Y.Hoekstra@ctw.utwente.nl, M.S.Krol@ctw.utwente.nl
² International Institute for Geo-Information Science and Earth Observation, Enschede, The Netherlands; E-Mails: b_su@itc.nl, salama@itc.nl
Abstract: Remote sensing techniques have shown to be a useful tool in global applications since they provide physical-based worldwide spatial information. This paper discusses the potential of using these techniques in the research field of water management, particularly for ‘Water Footprint’ (WF) studies. The WF of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rainfed and irrigated water respectively. Hydrology-related parameters such as precipitation, actual evapotranspiration and soil moisture are used in this paper to obtain the maps of actual irrigation. A straightforward evapotranspiration method is used to show the potential of the remote sensed data, by using images from the geostationary satellite Meteosat-9. This work represents an innovative approach for global irrigation mapping, which allows for the estimation of evapotranspiration on an appropriate time scale distinguishing between green and blue water.

Type of Paper: Article
Title: Determination of Regional Evapotranspiration by Using Remote Sensing Parameters and the Penman-Monteith Equation
Author: Antônio H. de C. Teixeira
Affiliation: Embrapa Semi-Arid, Petrolina-PE, Brazil; E-Mail: heribert@cpatsa.embrapa.br
Abstract: To achieve sustainable development and to ensure water availability in hydrological basins, the water managers need tools to determine the actual evapotranspiration (ET) at large scale. Field energy balances from irrigated and natural ecosystems together with a net of agrometeorological stations were used to elaborate two models for ET quantification at basin scale based on the Penman-Monteith equation. The first model uses the resistances to the latent heat fluxes estimated from satellite measurements and weather variables, while the second one is based on the ratio of ET to the reference evapotranspiration (ET0) and its relation with remote sensing parameters. The models were applied in the semi-arid region of the Low-Middle São Francisco River basin and after comparison with field results, the best was used to analyse the regional ET at daily and annual scales, making use of Landsat images and a geographic information system for different soil moisture conditions.

Type of Paper: Article
Title: World Water and Food Security Under Climate Change and Carbon Trading: Perspectives, Pathways, Opportunities and Challenges for Remote Sensing Applications
Authors: Munir A. Hanjra¹, Prasad S. Thenkabail²
Affiliations: ¹ International Centre of Water for Food Security, Charles Stuart University, NSW 2678, Australia; E-Mail: mahanjra@hotmail.com, mahanjra@gmail.com, mhanjra@csu.edu.au
² Southwest Geographic Science Center, U.S. Geological Survey, Flagstaff, AZ, USA; E-Mail: pthenkabail@usgs.gov, thenkabail@gmail.com
Abstract: World water and food security are intimately linked. Past investments in irrigation and related support measures were instrumental in expanding the croplands and boosting crop yields and insulating the communities against famine and hunger. The progress made towards food security over the last half century has already been threatened in recent years. Further, some 850 million people around the world remain malnourished. Many forces are working against food and water security today. These include slowing productivity growth, falling investment in irrigation and agriculture worldwide, loss of genetic diversity, salinization, land degradation, land use changes and water scarcity, population growth, urbanization and industrialization, ageing workforce, and economic and financial crisis. These forces are confounded by various drivers of global change, including climate change, climate shift and limits on the use of agricultural knowledge, science, and technology, as well as the outcomes of global change processes, including impacts on water resources and food security. Food entitlements are being redefined as millions more enter into the flat world, with changing food consumption style and westernization of diets that are putting immense pressure on croplands and water resources devoted to food production. Biofeuls are directly competing with land, water, and investments that would otherwise be allocated to food production, worsening the already alarming situation. Policies for tackling the climate change including continental and regional carbon trading schemes are emerging, with direct and indirect consequences for food production, prices, and consumption. From the Kyoto Protocol to Copenhagen, there is a quest to have no loose carbon sector in the global economy and pursue a sustainable growth path with a low carbon footprint; agriculture is likely to be included in the future negotiations on climate change. Yet there are almost no tools and technologies to quantify, define, validate, and report carbon credits in agriculture. Satellite remote sensing can revolutionize the way towards accounting and reporting the integrated water and carbon footprints across various spatial and temporal scales. Remote sensing is now a key technology for mapping land use and land cover, croplands, tracking the spread of salinity, monitoring crop health and yield, and the estimation of crop water use. This paper presents a policy framework for remote sensing applications to quantify the carbon credits in agriculture. Linkage of remote sensing and carbon estimates by integrated models or repeat measurements is envisaged as a potential method. It is argued that remote sensing technology has the potential for mapping surface states (e.g. soil moisture, surface temperature, vegetation cover), crop yields and water, and energy carbon fluxes from field and farm to river basin, and regional scales, using emission factors from global defaults, local defaults or by direct measurement or model. These technologies could be part of the platform for a global carbon monitoring and accounting system. Such integrated and more holistic assessment of water and carbon footprints can improve long term agricultural sustainability and global food security. The challenges include policy directions and institutional support measures for protecting the future food security and responding to climate change and global change issues through effective dialogue and stakeholder participation.
Keywords: food security; poverty; climate change; carbon market; carbon footprints

Type of Paper: Article
Title: Need of Medium Resolution Satellite Sensors Based Mapping of Cropland Dynamics for Harmonized Statistics in India
Authors: Obi Reddy P. Gangalakunta¹, Prasad, S. Thenkabail², Jagadeesha Chinagudi³, Venkateswarlu Dheeravath⁴, Adinarayana, Jagarlapudi⁵, Muralikrishna Gumma⁶, Chandrakantha Gurappa⁷, Maji A. Kumar¹ and Sarkar Dipak¹
Affiliations: ¹ Natioanl Bureau of Soil Survey and land Use Planning (ICAR), Amravati Road, Nagpur -440 010, India; E-Mail: obireddygp@gmail.com (O.R.P.G.)
² U.S. Geological Survey (USGS), Flagstaff, AZ 86001, USA
³ Regional Remote Sensing Service Centre, (ISRO), Bangalore- 560 070, India
⁴ United Nations Joint Logistics Center, Juba, Sudan
⁵ Indian Institute of Technology, Bombay, Powai, Mumbai - 400 076, India
⁶ International Water Management Institute (IWMI), Regional Office, Hyderabad, India
⁷ Department of Applied Geology, Kuvempu University, Karnataka, India
Abstract: The need of precise and periodical cropland maps and statistics on a near-real-time basis at national, regional and local levels will be of immense help in an era of stagnated green revolution, increasing population, quantum leap in consumption patterns in rapidly growing economy, and changing climatic conditions. In conventional estimation of cropland areas in the country, the Directorate of Economics & Statistics (DES) of the Department of Agriculture and Cooperation, Ministry of Agriculture, Government of India is the nodal agency for collection, compilation and publication of statistics on croplands under agricultural census. On the basis of data received from the States, the consolidated all India estimates are generated by the DES and made available to various users with a time log of two to three years period. It is a time-consuming, resources-intensive process and difficult to visualize the spatial pattern of cropland areas in the statistical data of any administrative unit. However, in recent times, with increase in spatial, spectral and temporal resolutions of the satellite sensors, medium resolution satellite sensors provides valuable information on location, spatial distribution and extent of cropland areas in the country for accurate and unbiased mapping and to analyze their spatio-temporal dynamics. There are many issues and challenges involved in croplands mapping, which includes sensors resolutions, scale and season of mapping, minimum mapping unit and landholding sizes, which needs to be addressed in precise croplands mapping. In recent times, efforts made by international organizations like FAO based on national statistics and IWMI based on NOAA AVHRR, MODIS 500m data in irrigated areas mapping and national organization like NRSC in land use/land cover mapping using Resourcesat-1 AWiFS data shows considerable variation in croplands statistics in the country. Though it is a huge task, keeping their significance, it necessitates mapping the cropland areas using medium resolution satellite sensors data through developing innovative methods and techniques for precise, consistent and harmonized estimates of croplands over space and time for their proper planning and management. The paper highlights the present scenario in availability of croplands statistics, croplands estimates of different sources, ongoing efforts in cropland mapping and conceptual issues and challenges in mapping the cropland areas in India using the medium resolution satellite sensors data.
Keywords: croplands; satellite sensors; minimum mapping unit; scales and resolutions; harmonized cropland statistics

Title: Remote Sensing of Irrigated Agriculture: Opportunities and Challenges
Authors: Mutlu Ozdogan, Yang Yang, and Chelsea Cervantes
Affiliation: Center for Sustainability and the Global Environment (SAGE), University of Wisconsin-Madison, 1710 University Avenue, Madison WI 53726, USA; E-Mail: ozdogan@wisc.edu (M.O.)
Abstract: Over the last several decades, remote sensing has emerged as an effective tool for monitoring irrigated lands under a variety of climatic conditions and locations. The objective of this review paper, which summarizes the methods and the results of existing remote sensing studies, is to synthesize main findings and the state of the art. We take a taxonomic approach to categorize existing studies based on location, scale, inputs, methods, and timing, in an effort to categorize different approaches in an analytical framework. The review highlights the ability of remote sensing to provide synoptic and timely coverage of irrigated lands in several spectral regions and the value of archived data that allow comparison of images across dates, yielding change. The results of the reviewed studies also indicate that remote sensing-based monitoring of irrigation is at a mature stage of development. For instance, there is overwhelming consensus on the efficacy of vegetation indices in identifying irrigated fields, especially at continental and global scales. At local scales, on the other hand, single date imagery, acquired at the height of the peak irrigation season, may be sufficient to identify irrigation. To distinguish different irrigated crop types however, multi-date data is necessary. The review also highlights the challenges of remote sensing for mapping irrigated lands, particularly in fragmented landscapes, where the spatial scale of observations are pitted against the need for high frequency temporal acquisitions.