J. Adinarayana

A rule-based soil erosion model for a hilly catchment

Abstract Catchment resources, generated from multi-source data (remotely-sensed, map- and ground-based systems), were input to a raster-based Geographical Information Systems (GIS) after geometrically co-registered to a standard grid (pixel). The GIS used was the PC-based, indigenously-developed package, called GRAM (Geo-Referenced Area Management). A set of knowledge-based rules, for assessing the soil erosion of this heterogeneous hilly catchment, were formulated from the knowledge of the multi-disciplinary resource-experts and the knowledge of the local catchment resources, in addition to the field observations. This rule-based model, which is hopefully fast and cost-effective and without effect of the individual bias, helped in inferring the erosion intensity units that most likely to occur at any given pixel in the system. Finally, the catchment was grouped into four different erosion intensity units namely very severe, severe, moderate to severe and slight to moderate. The quantitative soil loss (t ha−1 year−1) ranges, estimated by USLE model by a spatial information analysis approach (GIS), were also computed: (a) Very severe (>50): (b) Severe (40–50); (c) Moderate to severe (20–40); and (d) Slight to moderate (

Integration of multi-seasonal remotely-sensed images for improved landuse classification of a hilly watershed using geographical information systems

Abstract Information on existing landuse pattern and its spatial distribution is a pre-requisite for any watershed management programme. With the advent of remote sensing tools, with their inherent characteristics, it has been possible to prepare this dynamic resource map at various levels of confidence. But the application of multi-spectral classification techniques in vegetation discrimination has been the subject of discussion for many years. The paper describes a methodology developed to compile agricultural landuse map of a hilly watershed (where the rainfall erosivity is an ever-present threat) using geographical information systems (GIS). Multi-seasonal (monsoon—Kharif and post-monsoon—Rabi) and multi-sensor remotely-sensed data were used for mapping a landuse pattern of the watershed. The rasterised classified images, and the relevant watershed resources, were input and stored as separate layers in the GIS and then geometrically co-registered to a regular 30 m grid. Knowledge-based rules were deve...

Data mining and wireless sensor network for agriculture pest/disease predictions

Data driven precision agriculture aspects, particularly the pest/disease management, require a dynamic crop-weather data. An experiment was conducted in a semi-arid region to understand the crop-weather-pest/disease relations using wireless sensory and field-level surveillance data on closely related and interdependent pest (Thrips) - disease (Bud Necrosis) dynamics of groundnut crop. Data mining techniques were used to turn the data into useful information/knowledge/relations/trends and correlation of crop-weather-pest/disease continuum. These dynamics obtained from the data mining techniques and trained through mathematical models were validated with corresponding surveillance data. Results obtained from 2009 & 2010 kharif seasons (monsoon) and 2009–10 & 2010–11 rabi seasons (post monsoon) data could be used to develop a real to near real-time decision support system for pest/disease predictions.

An integrated approach for prioritisation of watersheds

Watershed management programmes, in terms of conservation planning over a large watershed, must identify the subsets of hydrologic units that are contributing most sediment load in the watershed. It is these priority or critical hydrologic units or sub-watersheds that need preferential soil and water conservation measures to reduce maximum sediment load in the watershed, particularly in arid/semi-arid fragile environments. The semi-quantitative method of the Sediment Yield Index (SYI) model, developed by the All India Soil and Land Use Survey of the Government of India for priority delineation in River Valley Projects, is used in India and studies have revealed that there is an overall reduction of sediment outflows of up to 60%. The paper describes a new concept of introducing Integrated Resources Units (IRUs) in the model. An IRU is the smallest, but viable, planning unit which leads to strategies ideally suited for scientific development of a watershed. The IRUs encompass all the relevant watershed resources, generated from map-, ground- and space-based systems, and is the strategic unit for assigning the erosivity and transportability values of the detached material in the SYI model for gradation of priority classes of sub-watersheds. The IRU approach is also helpful in monitoring the dynamic aspects of the watershed and the consequent redefinement of management strategies. The paper also envisages some future studies for watershed management policies.

GeoSense: A Multimode Information and Communication System

Recent technological developments allowed to envision the low-power (solar power) and low-cost (open hardware) sensor devices (Agrisens/FieldServer/Flux Tower/FieldTwitter) with multimode (ZigBee/WiFi/3G/WebGIS) information and communication technologies (ICTs), a model in which is christened as GeoSense. Integrating these multimode and multi-level communication systems with distributed ambient sensory network location-based service (LBS) is a challenging task, which could be a potential technology for monitoring various natural phenomena. This integrated model is introduced to provide and assist the rural stakeholders with real-time decision support system (DSS) with dynamic information and modeling services for precision agriculture through GeoSense cloud service. This GeoSense research has been experimented in semiarid tropics in India under Indo-Japan initiative on multi-disciplinary ICT program.

Temporal changes of vegetal cover in Indian semi-arid tropics through Landsat images

This paper deals with the mapping and assessment of vegetal cover including notified forests of semi-arid tropics over a period of 12 years from 1975–1986. Five classes have been identified and delineated from Landsat images, using visual interpretation techniques. Final maps have been prepared for 1975, 1981 and 1986, and the areal extent of each class has been computed. The comparison of these maps and analysis of areal extent of different classes indicate three patterns of changes. The reasons and impact of these changes on desertification of the area and preventive measures have been discussed.

Temporal analysis of Touzi parameters for wheat crop characterization using L-band AgriSAR 2006 data

Synthetic aperture radar (SAR) has shown promising results in characterizing different crops. Multi-temporal SAR data is often useful for studying the sensitivity of the electromagnetic (EM) waves to the structural and the dielectric variation of both crops and the underlying soil at different phenological stages. Physical information about crops and soil can be interpreted in terms of scattering mechanisms using polarimetric descriptors. In this study, the potential of the Touzi eigenvalue-eigenvector decomposition parameters is analyzed for Leaf Area Index (LAI) and soil moisture variations over the phenophases of wheat crop. The AgriSAR 2006 campaign E-SAR L-band full polarimetric SAR data were used in this study. It was observed that the crop phenological parameters could be justifiably associated with the two dominant Touzi parameters, symmetric scattering type magnitude (αs1) and the phase (ϕαs1), for phenological assessment.

Disease stress detection on citrus using a leaf optical model and field spectroscopy

As citrus is progressively contributing to horticultural production, wealth and economy of a country, it is necessary to understand the factors impacting citrus production. Gummosis is one of the most serious diseases causing considerable loss of overall citrus production and yield quality. A qualitative and quantitative analysis of citrus leaf biochemical properties are necessary to monitor the crop health, disease /pest stress and production. Total leaf chlorophyll content (Cab) represents one of the key biochemical factors which contributes in water, carbon, and energy exchange processes. Photosynthesis process in citrus will be disturbed as gummosis disease life cycle progresses. It is important to study Cab to evaluate the photosynthesis rate and disease stress. In this study the potential of Radiative Transfer (RT) PROSPECT model to retrieve Cab in citrus orchards was undertaken at different sites. The main goal is to evaluate the relationship between Cab and gummosis disease stress for citrus at various phenological stages. Inversion of PROSPECT model on measured hyperspectral data is carried out to extract the leaf level parameters influencing the disease. This model was inverted with the ground truth hyperspectral reading. The testing was separately initiated for healthy and infected plant leaves. This can lead to understand the disease stress on citrus leaves. For accuracy, raw spectra are filtered and processed which is an input parameter for Inversion PROSPECT model. Here, retrieved Cab content was correlated with gummosis disease stress in terms of oozing with R2 = 0.6021 and RMSE= 0.481272.

Nitrogen use efficiency of unirrigated barley as affected by shortage of water

The moisture use pattern and efficiency (MUE) of four barley cultivars (two hulled and two hull-less) were studied when the crops were grown in winter under unirrigated conditions at Varanasi, India, with different rates of application of nitrogen fertilizer. Increase in moisture use with age of the crop due to vegetative growth was recorded. Influence of varieties on consumptive use of water was found to be negligible except in the 1st year between 65 days after sowing and after harvest of the crop, when differences were due to differences in duration of the crop growth and rainfall which was received at the time of maturity. The moisture mining capacity of the barley crop from the profile (up to 120 cm) was increased with increase in the rate of nitrogen application. MUE of barley cultivars closely paralleled the grain yields, being more with hulled cultivars than hull-less ones. Higher MUE of barley was observed in the 2nd than in the 1st year of experimentation because of a better distribution of rainfall and moisture availability at the time of sowing, which boosted yields. Nitrogen application increased both yield and MUE of barley.

The effect of rate of application of nitrogen fertilizer on soil copper uptake by barley under unirrigated conditions

Field experiments were conducted on four barley cultivars (two hulled and two hullless) grown under unirrigated conditions in Varanasi, India, to observe the effect of rate of application of nitrogen on copper concentration and uptake in plants and soils. The copper concentration in both plants and soil decreased with age of crop because of the dilution effect of more vegetative growth. Varieties did not differ in copper concentration of plants but increasing application of nitrogen decreased copper concentration in the plants. Since the hulled varieties yielded more than the hull-less ones, they removed more copper from the soil. Similarly yield was increased linearly by the application of N fertilizer and this led to a linear increase in depletion of available copper.