Mapping Direct Seeded Rice in Raichur District of Karnataka, India

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

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

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

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

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 87.2 %. Area estimates between the MODIS-derived net irrigated area and district-level statistics (2000–2001 to 2007–2008) were in 95 % agreement. A significant decrease in irrigated area (30–40 %) 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

Scaling-up agriculture water management interventions for building system resilience in Bundelkhand region of Central India

This case study provides evidence for combating drought, and achieving sustainable crop intensification, in rainfed areas of Bundelkhand region, Central India. The Garkundar-Dabar and Parasai-Sindh watersheds were developed as proof of concept by the Indian Council of Agriculture Research-Central Agroforestry Research Institute (ICAR-CAFRI) and the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) between 2006 and 2016. This study indicates pathways for harnessing the potential of rainfed areas by implementing various agricultural water management (AWM) interventions. Rainwater harvesting measures, especially rejuvenation of the haveli system (traditional rainwater harvesting system of the region), along with various in situ water harvesting interventions, were found promising for addressing water scarcity and strengthening various ecosystem services. Water harvesting measures, improved agricultural practices (such as balanced fertilizer application, introduction of climate-smart crop cultivars, weed and pest management) and supplemental irrigation, enhanced crop yield by 30-50% and cropping intensity from 80 to 150%. Enhanced groundwater availability (2-2.5 m additional head) helped to reduce crop risk, through the availability of supplemental irrigation and enhanced cropping intensity, as large areas of fallow land were converted to cultivation. AWM interventions also helped to enhance base flow (35-42 days to 110-122 days), control floods, soil erosion and land degradation (by about 33%), and enhance land and water use efficiency (40-70%). Since 2017, lessons from these model watersheds have been scaled up in all seven districts of Uttar Pradesh Bundelkhand region, by an ICRISAT-led consortium. This study explores the potential of rainfed areas that are achievable through the adoption of AWM interventions. It suggests that the role of extension, through capacity building and exposure of various stakeholders to AWM, is key to harnessing the potential of drylands. In order to further scale up such innovations to the entire region, it is important to involve knowledge generating and knowledge dissemination institutes, along with central and federal machineries. Involvement of private and non-governmental organizations as well will help achieve system level outcomes

Prioritization of Watersheds across Mali Using Remote Sensing Data and GIS Techniques for Agricultural Development Planning

Implementing agricultural water management programs over appropriate spatial extents can have positive effects on water access and erosion management. Lack of access to water for domestic and agricultural uses represents a major constraint on agricultural productivity and perpetuates poverty and hunger in sub-Saharan Africa (SSA). This lack of access is the result of erratic precipitation, poor water management, limited knowledge of hydrological systems, and inadequate investment in water infrastructure. Water management programs should be made by multi-disciplinary teams that consider the interrelationship between hydraulic and anthropogenic factors. This paper proposes a method to prioritize watersheds for water management and agricultural development across Mali (Western Africa) using remote sensing data and GIS tools. The method involves deriving a set of relevant thematic layers from satellite imagery. Satellite images from Landsat ETM+ were used to generate thematic layers such as land use/land cover. Slope and drainage density maps were derived from Shuttle RADAR Topography Mission (SRTM) Digital Elevation Model (DEM) at 90 m spatial resolution. Population grids were available from the Global rural-urban mapping project (GRUMP) database for the year 2000 and mean rainfall maps were extracted from Tropical rainfall measuring mission (TRMM) grids for each year between 1988 and 2014. Each thematic layer was divided into classes that were assigned a rank for agriculture and livelihoods development provided by experts in the relevant field (e.g., Soil scientist ranking the soil classes) and published literature on those themes. Zones of priority were delineated based on the combination of high scoring ranks from each thematic layer. Five categories of priority zones ranging from “very high” to “very low” were determined based on total score percentages. Field verification was then undertaken in selected categories to check the priority assigned to each class using a random sampling method. Watershed boundaries were prepared at 1000 ha scale and overlaid on the priority map to identify watersheds that were in a very high priority zone. The importance and efficiency of using remote sensing to prioritize watershed interventions across countries is critical due to the limited technical and financial resources available in sub-Saharan Africa (SSA)

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

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

Monitoring of Spatio-temporal Dynamics of Rabi Rice Fallows in South-Asia using Remote Sensing

Cereals and grain legumes are the most important part of human diet and nutrition. The rural population of low income groups in dry land areas of South Asia depends on these staples. Expansion of grain legumes with improved productivity to cater the growing population’s nutritional security is of prime importance and need of the hour. Rice-fallows are best niche areas with residual moisture to grow short duration legumes there by achieving intensification. Identifying suitable areas for grain legumes and cereal grains is important in this region. In this context, the goal of this study was to map fallow lands followed by rainy season (kharif) rice cultivation or post rainy (rabi) fallows in rice growing environments between 2005 and 2015 using temporal moderate-resolution imaging Spectroradiometer (MODIS) data applying Spectral matching techniques. This study was conducted in South Asia where different rice eco-systems exist. MODIS 16-days normalized difference vegetation index (NDVI) at 250m spatial resolution and season wise intensive ground survey data were used to map rice systems and the fallows thereafter (rabi-fallows) in South Asia. The rice maps were validated with independent ground survey data and compared with available sub-national level statistics. Overall accuracy and kappa coefficient estimated for rice classes were 81.5% and 0.79 respectively with ground survey data. The derived physical rice area and irrigated areas were highly correlated with the sub-national statistics with R2 values of 84% at the district level for the year 2005-06 and 2015-16. Results clearly show that rice-fallows areas increased from 2005 to 2015. The results show spatial distribution of rice-fallows in South Asia which are identified as target domains for sustainable intensification of short duration grain legumes, fixing the soil nitrogen and increasing incomes of small holder farmers

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

The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia, using MODIS 250 m 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 250 m 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 22.3 Mha 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

Simulation of water-limited growth of the forage shrub saltbush (Atriplex nummularia Lindl.) in a low-rainfall environment of southern Australia

Old man saltbush (Atriplex nummularia Lindl.) is a useful forage shrub for livestock in the low-rainfall areas of the world, and particularly in Australia. In these semi-arid and arid environments, saltbush is valuable for increasing the production from otherwise marginal areas of the farm and during drought periods when there are few feed alternatives. The ability to predict the growth and development of perennial forages such as old man saltbush in response to rainfall, soils and farm management is necessary for farming system planning and design purposes. A field experiment was conducted at Waikerie, South Australia, to inform the development of a new forage shrub model for use in the APSIM framework. The model takes into account the common setup of saltbush plantations in alley systems, by simulating light interception and water uptake for interacting shrub and inter-row zones separately. This is done by modelling the canopy and root system development. Field data across three soil types along a landscape catena showed that the model was able to satisfactorily predict daily biomass accumulation, partitioning into leaf and woody biomass, and regrowth after grazing. The model was sensitive to properties associated with the root system, and with limited parameterisation can be tailored to simulate different clonal cultivars. The model can now be used in the APSIM framework to assess temporal and spatial dynamics of forage systems combining shrubs with herbaceous pasture components

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

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