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Featured researches published by Anthony Whitbread.


International Journal of Digital Earth | 2016

Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data

Murali Krishna Gumma; Prasad S. Thenkabail; Pardhasaradhi Teluguntla; Mahesh N. Rao; Irshad A. Mohammed; Anthony Whitbread

ABSTRACT The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia, using MODIS 250u2005m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period. Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season (June–October), followed by a fallow during the rabi season (November–February). These cropland areas are not suitable for growing rabi-season rice due to their high water needs, but are suitable for a short -season (≤3 months), low water-consuming grain legumes such as chickpea (Cicer arietinum L.), black gram, green gram, and lentils. Intensification (double-cropping) in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands. Several grain legumes, primarily chickpea, are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region. The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers: (a) rice crop is grown during the primary (kharif) crop growing season or during the north-west monsoon season (June–October); (b) same croplands are left fallow during the second (rabi) season or during the south-east monsoon season (November–February); and (c) ability to support low water-consuming, short-growing season (≤3 months) grain legumes (chickpea, black gram, green gram, and lentils) during rabi season. Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season, because the moisture/water demand of these crops is too high. The study established cropland classes based on the every 16-day 250u2005m normalized difference vegetation index (NDVI) time series for one year (June 2010–May 2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using spectral matching techniques (SMTs), and extensive field knowledge. Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics. The producers’ and users’ accuracies of the cropland fallow classes were between 75% and 82%. The overall accuracy and the kappa coefficient estimated for rice classes were 82% and 0.79, respectively. The analysis estimated approximately 22.3u2005Mha of suitable rice-fallow areas in South Asia, with 88.3% in India, 0.5% in Pakistan, 1.1% in Sri Lanka, 8.7% in Bangladesh, 1.4% in Nepal, and 0.02% in Bhutan. Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.


Environmental Monitoring and Assessment | 2015

Temporal change in land use by irrigation source in Tamil Nadu and management implications

Murali Krishna Gumma; Kei Kajisa; Irshad A. Mohammed; Anthony Whitbread; Andrew Nelson; Arnel Rala; K. Palanisami

Interannual variation in rainfall throughout Tamil Nadu has been causing frequent and noticeable land use changes despite the rapid development in groundwater irrigation. Identifying periodically water-stressed areas is the first and crucial step to minimizing negative effects on crop production. Such analysis must be conducted at the basin level as it is an independent water accounting unit. This paper investigates the temporal variation in irrigated area between 2000–2001 and 2010–2011 due to rainfall variation at the state and sub-basin level by mapping and classifying Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day composite satellite imagery using spectral matching techniques. A land use/land cover map was drawn with an overall classification accuracy of 87.2xa0%. Area estimates between the MODIS-derived net irrigated area and district-level statistics (2000–2001 to 2007–2008) were in 95xa0% agreement. A significant decrease in irrigated area (30–40xa0%) was observed during the water-stressed years of 2002–2003, 2003–2004, and 2009–2010. Major land use changes occurred three times during 2000 to 2010. This study demonstrates how remote sensing can identify areas that are prone to repeated land use changes and pin-point key target areas for the promotion of drought-tolerant varieties, alternative water management practices, and new cropping patterns to ensure sustainable agriculture for food security and livelihoods.


Journal of Experimental Botany | 2018

Accelerating genetic gains in legumes for the development of prosperous smallholder agriculture: integrating genomics, phenotyping, systems modelling and agronomy

Rajeev K. Varshney; Mahendar Thudi; Manish K. Pandey; François Tardieu; Chris O. Ojiewo; Vincent Vadez; Anthony Whitbread; Kadambot H. M. Siddique; Henry T. Nguyen; Peter Carberry; David J. Bergvinson

Grain legumes form an important component of the human diet, provide feed for livestock, and replenish soil fertility through biological nitrogen fixation. Globally, the demand for food legumes is increasing as they complement cereals in protein requirements and possess a high percentage of digestible protein. Climate change has enhanced the frequency and intensity of drought stress, posing serious production constraints, especially in rainfed regions where most legumes are produced. Genetic improvement of legumes, like other crops, is mostly based on pedigree and performance-based selection over the past half century. To achieve faster genetic gains in legumes in rainfed conditions, this review proposes the integration of modern genomics approaches, high throughput phenomics, and simulation modelling in support of crop improvement that leads to improved varieties that perform with appropriate agronomy. Selection intensity, generation interval, and improved operational efficiencies in breeding are expected to further enhance the genetic gain in experimental plots. Improved seed access to farmers, combined with appropriate agronomic packages in farmers fields, will deliver higher genetic gains. Enhanced genetic gains, including not only productivity but also nutritional and market traits, will increase the profitability of farming and the availability of affordable nutritious food especially in developing countries.


Journal of remote sensing | 2016

Satellite imagery and household survey for tracking chickpea adoption in Andhra Pradesh, India

Murali Krishna Gumma; Kumara Charyulu Deevi; Irshad A. Mohammed; Rajeev K. Varshney; Pooran M. Gaur; Anthony Whitbread

ABSTRACT The objective of this study was to map the temporal changes in chickpea cropped area over the last decade in Andhra Pradesh using remote-sensing imagery. Moderate Resolution Imaging Spectroradiometer (MODIS) data composited for every 16 days were used to map the spatial distribution of seasonal crop extent in Andhra Pradesh. MODIS derived 16 day normalized difference vegetation index (NDVI) and maximum value composite (MVC) with seasonal ground survey information for the years 2005–2006 and 2012–2013 were used. A subset of ground survey information was also used to assess the pixel-based accuracies of the MODIS-derived major cropland extent. Chickpea-growing areas were identified and mapped based on their characteristic growing periods during the post-rainy season. Significant growth in the chickpea-growing areas was observed in the four districts of Andhra Pradesh between 2001 and 2012. The area cropped to chickpea almost tripled from 0.22 million ha during 2000–2001 to 0.6 million ha by 2012–2013. Furthermore, survey data were also used to assess the accuracy of the MODIS estimates of chickpea-growing areas. When compared with ground survey, the 10 land-use and land-cover classes derived from the MODIS temporal imagery resulted in overall accuracies of 86% of actual. The accuracy of areas identified as cropped to chickpea was 94%. To complement this remote-sensing study, a state-level representative primary household survey was conducted to elicit information on the socio-economic characteristics of chickpea-growing farmers, the extent of adoption of improved cultivars, costs and returns from chickpea cultivation, competitiveness of chickpea with other post-rainy crops, etc. during 2012–13. The findings revealed that nearly 98% of the chickpea cropped area is now under improved cultivars, with an average increase in yield of 37% over yields achieved with unimproved varieties. The average annual per capita incomes have increased to US


Giscience & Remote Sensing | 2018

Mapping cropland fallow areas in myanmar to scale up sustainable intensification of pulse crops in the farming system

Murali Krishna Gumma; Prasad S. Thenkabail; Kumara Charyulu Deevi; Irshad A. Mohammed; Pardhasaradhi Teluguntla; Adam Oliphant; Jun Xiong; Tin Aye; Anthony Whitbread

1.89 day−1 with this silent chickpea revolution across the rain-fed areas of Andhra Pradesh.


Remote Sensing | 2017

Urban Sprawl and Adverse Impacts on Agricultural Land: A Case Study on Hyderabad, India

Murali Gumma; Irshad Mohammad; Swamikannu Nedumaran; Anthony Whitbread; Carl Lagerkvist

Cropland fallows are the next best-bet for intensification and extensification, leading to increased food production and adding to the nutritional basket. The agronomical suitability of these lands can decide the extent of usage of these lands. Myanmar’s agricultural land (over 13.8 Mha) has the potential to expand by another 50% into additional fallow areas. These areas may be used to grow short-duration pulses, which are economically important and nutritionally rich, and constitute the diets of millions of people as well as provide an important source of livestock feed throughout Asia. Intensifying rice fallows will not only improve the productivity of the land but also increase the income of the smallholder farmers. The enhanced cultivation of pulses will help improve nutritional security in Myanmar and also help conserve natural resources and reduce environmental degradation. The objectives of this study was to use remote sensing methods to identify croplands in Myanmar and cropland fallow areas in two important agro-ecological regions, delta and coastal region and the dry zone. The study used moderate-resolution imaging spectroradiometer (MODIS) 250-m, 16-day normalized difference vegetation index (NDVI) maximum value composite (MVC), and land surface water index (LSWI) for one 1 year (1 June 2012–31 May 2013) along with seasonal field-plot level information and spectral matching techniques to derive croplands versus cropland fallows for each of the three seasons: the monsoon period between June and October; winter period between November and February; and summer period between March and May. The study showed that Myanmar had total net cropland area (TNCA) of 13.8 Mha. Cropland fallows during the monsoon season account for a meagre 2.4% of TNCA. However, in the winter season, 56.5% of TNCA (or 7.8 Mha) were classified as cropland fallows and during the summer season, 82.7% of TNCA (11.4 Mha) were cropland fallows. The producer’s accuracy of the cropland fallow class varied between 92 and 98% (errors of omission of 2 to 8%) and user’s accuracy varied between 82 and 92% (errors of commission of 8 to 18%) for winter and summer, respectively. Overall, the study estimated 19.2 Mha cropland fallows from the two major seasons (winter and summer). Out of this, 10.08 Mha has sufficient moisture (either from rainfall or stored soil water content) to grow short-season pulse crops. This potential with an estimated income of US


Photogrammetric Engineering and Remote Sensing | 2015

Mapping Direct Seeded Rice in Raichur District of Karnataka, India

Murail Krishna Gumma; Deepika Uppala; Irshad A. Mohammed; Anthony Whitbread; Ismail Rafi Mohammed

300 per hectare, if exploited sustainably, is estimated to bring an additional net income of about US


Theoretical and Applied Climatology | 2018

Spatio-temporal variability and trends of precipitation and extreme rainfall events in Ethiopia in 1980–2010

Sridhar Gummadi; K. P. C. Rao; Jemal Seid; G. Legesse; M. D. M. Kadiyala; Robel Takele; Tilahun Amede; Anthony Whitbread

1.5 billion to Myanmar per year if at least half (5.04 Mha) of the total cropland fallows (10.08 Mha) is covered with short season pulses.


Archive | 2018

Monitoring of Spatiotemporal Dynamics of Rabi Rice Fallows in South Asia Using Remote Sensing

Murali Krishna Gumma; Prasad S. Thenkabail; Pardhasaradhi Teluguntla; Anthony Whitbread

Many Indian capitals are rapidly becoming megacities due to industrialization and rural–urban emigration. Land use within city boundaries has changed dynamically, accommodating development while replacing traditional land-use patterns. Using Landsat-8 and IRS-P6 data, this study investigated land-use changes in urban and peri-urban Hyderabad and their influence on land-use and land-cover. Advanced methods, such as spectral matching techniques with ground information were deployed in the analysis. From 2005 to 2016, the wastewater-irrigated area adjacent to the Musi river increased from 15,553 to 20,573 hectares, with concurrent expansion of the city boundaries from 38,863 to 80,111 hectares. Opportunistic shifts in land-use, especially related to wastewater-irrigated agriculture, emerged in response to growing demand for fresh vegetables and urban livestock feed, and to easy access to markets due to the city’s expansion. Validation performed on the land-use maps developed revealed 80–85% accuracy.


Ecological Indicators | 2016

Empirical evaluation of sustainability of divergent farms in the dryland farming systems of India

Amare Haileslassie; P. Q. Craufurd; Ramilan Thiagarajah; Shalander Kumar; Anthony Whitbread; Abhishek Rathor; Michael Blümmel; Polly Ericsson; Krishna Reddy Kakumanu

Across South Asia, the cost of rice cultivation has increased due to labor shortage. Direct seeding of rice is widely promoted in order to reduce labor demand during crop establishment stage, and to benefit poor farmers. To facilitate planning and to track farming practice changes, this study presents techniques to spatially distinguish between direct seeded and transplanted rice fields using multiple-sensor remote sensing imagery. The District of Raichur, a major region in northeast Karnataka, Central India, where irrigated rice is grown and direct seeded rice has been widely promoted since 2000, was selected as a case study. The extent of cropland was mapped using Landsat-8, Moderate Resolution Imaging Spectroradiometer (modis) 16-day normalized difference vegetation index (ndvi) time-series data and the cultivation practice delineated using risat-1 data for the year 2014. Areas grown to rice were mapped based on the length of the growing period detected using spectral characteristics and intensive field observations. The high resolution imagery of Landsat-8 was useful to classify the rice growing areas. The accuracy of land-use/landcover (lulc) classes varied from 84 percent to 98 percent. The results clearly demonstrated the usefulness of multiple-sensor imagery from mod09q1, Landsat-8, and risat-1 in mapping the rice area and practices accurately, routinely, and consistently. The low cost of imagery backed by ground survey, as demonstrated in this paper, can also be used across rice growing countries to identify different rice systems.

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Irshad A. Mohammed

International Crops Research Institute for the Semi-Arid Tropics

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Murali Krishna Gumma

International Crops Research Institute for the Semi-Arid Tropics

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Vincent Vadez

International Crops Research Institute for the Semi-Arid Tropics

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Pardhasaradhi Teluguntla

United States Geological Survey

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Prasad S. Thenkabail

United States Geological Survey

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Kumara Charyulu Deevi

International Crops Research Institute for the Semi-Arid Tropics

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Pooran M. Gaur

International Crops Research Institute for the Semi-Arid Tropics

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Rajeev K. Varshney

International Crops Research Institute for the Semi-Arid Tropics

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Ramadjita Tabo

International Crops Research Institute for the Semi-Arid Tropics

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Shalander Kumar

International Crops Research Institute for the Semi-Arid Tropics

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