Current Science

R. N. Sahoo ¹, S. S. Ray ², K. R. Manjunath ³

Affiliations
1 Indian Agricultural Research Institute, New Delhi 110 012, IN
2 Mahalanobis National Crop Forecast Centre, Pusa Campus, New Delhi 110 012, IN
3 Space Applications Centre, ISRO, Ahmedabad 380 015, IN

Abstract

Remote sensing is being increasingly used in different agricultural applications. Hyperspectral remote sensing in large continuous narrow wavebands provides significant advancement in understanding the subtle changes in biochemical and biophysical attributes of the crop plants and their different physiological processes, which otherwise are indistinct in multispectral remote sensing. This article describes spectral properties of vegetation both in the optical and thermal range of the electromagnetic spectrum as affected by its attributes. Different methods have been discussed to reduce data dimension and minimize the information redundancy. Potential applications of hyperspectral remote sensing in agriculture, i.e. spectral discrimination of crops and their genotypes, quantitative estimation of different biophysical and biochemical parameters through empirical and physical modelling, assessing abiotic and biotic stresses as developed by different researchers in India and abroad are described.

Keywords

Agriculture, Biotic And Abiotic Stress, Hyperspectral Remote Sensing, Spectral Reflectance.

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B. S. Das ¹, M. C. Sarathjith ¹, P. Santra ², R. N. Sahoo ³, R. Srivastava ⁴, A. Routray ¹, S. S. Ray ⁵

Affiliations
1 Indian Institute of Technology Kharagpur, Kharagpur 721 302, IN
2 Central Arid Zone Research Institute, Jodhpur 342 003, IN
3 Indian Agricultural Research Institute, Pusa, New Delhi 110 012, IN
4 National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, IN
5 Mahalanobis National Crop Forecast Centre, Pusa Campus, New Delhi 110 012, IN

Abstract

Rapid and reliable assessment of soil characteristics is an important step in agricultural and natural resource management. Over the last few decades, diffuse reflectance spectroscopy (DRS) has emerged as a new tool to obtain both qualitative and quantitative information on soil in a non-invasive manner. The DRS approach is attractive because both the proximal and remote mode of measurements may be adopted to estimate multiple attributes of soil such as physical and chemical soil properties and nutrient contents from a single reflectance spectrum. Hyperspectral imaging cameras onboard remote sensing platforms are already providing hundreds of narrow, contiguous bands of reflectance values and the technology is becoming popular as the hyperspectral remote sensing (HRS) approach. The main objective of this review is to summarize the preparedness and opportunities for using the HRS approach for soil assessment in India. Detailed literature review suggests that the HRS approach requires large spectral databases and robust spectral algorithms in addition to the capability to interpret HRS images. Over the last decade, few efforts have been made to create spectral libraries for Indian soils. However, most of these libraries are very small, precluding the development of robust spectral algorithms. Specifically, the availability of HRS data and robust retrieval algorithms for soil properties from HRS data through unmixing procedures require special attention. With several global initiatives to make HRS data available, coordinated efforts are needed in India to build comprehensive spectral libraries, algorithms and create trained human resources to take full advantage of this emerging technology. Specifically, a dedicated spaceborne mission will provide quality hyperspectral data for the effective application of HRS for soil assessment in India.

Keywords

Hyperspectral Remote Sensing, Reflectance Spectroscopy, Soil Assessment, Spectral Databases and Algorithms.

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S. K. Singh ¹, Rajat Saxena ¹, Akhilesh Porwal ¹, Neetu ¹, S. S. Ray ¹

Affiliations
1 Mahalanobis National Crop Forecast Centre, Department of Agriculture, Cooperation and Farmers’ Welfare, Pusa Campus, New Delhi 110 012, IN

Abstract

Heavy rainfall and hailstorm events occurred in major wheat-growing areas of India during February and March 2015 causing large-scale damages to the crop. An attempt was made to assess the impact of hailstorms in the states of Punjab, Haryana, Uttar Pradesh (UP), Rajasthan and Madhya Pradesh (MP) using remote sensing data. Multi-year remote sensing data from Resourcesat 2 AWiFS was used for the purpose. Wheat crop map, generated by the operational FASAL project, was used in the study. Normalized difference vegetation index (NDVI) deviation images were generated from the NDVI images of a similar period in 2014 and 2015. This was combined with the gridded data of cumulative rainfall during the period. The logical modelling approach was used for damage classification into normal, mild, moderate and severe. It was found that the northern and southern districts in Haryana were severely affected due to rainfall/ hailstorm. Eastern Rajasthan and western MP were also highly affected. Western UP was mildly affected. Crop cutting experiments (CCE) were carried out in two districts of MP. The CCE data showed that the affected fields had 7% lower yield than the unaffected fields. Empirical yield model was developed between wheat yield and NDVI using CCE data. This model was used to compute the loss in state-level wheat production. This showed that there was a reduction of 8.4% in national wheat production. The production loss estimated through this method matched with the Government estimates.

Keywords

Crop Cutting Experiments, Hailstorm, Rainfall, Remote Sensing, Wheat.

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Nilima R. Chaube ¹, Sasmita Chaurasia ¹, Rojalin Tripathy ¹, Dharmendra Kumar Pandey ¹, Arundhati Misra ¹, B. K. Bhattacharya ¹, Prakash Chauhan ², Kiran Yarakulla ³, G. D. Bairagi ⁴, Prashant Kumar Srivastava ⁵, Preeti Teheliani ⁶, S. S. Ray ⁶

Affiliations
1 Space Applications Centre, ISRO, Ahmedabad 380 015, IN
2 Indian Institute of Remote Sensing, Dehradun 248 001, IN
3 Vellore Institute of Technology, Vellore 632 014, IN
4 M.P. Council of Science and Technology, Bhopal 462 003, IN
5 Banaras Hindu University, Varanasi 221 005, IN
6 Mahalanobis National Crop Forecast Centre, Delhi 110 012, IN

Abstract

SCATSAT-1 measures the backscattering coefficient over land surfaces, which is a function of vegetation structure, surface roughness, soil moisture content, incidence angle and dielectric properties of vegetation. Scatterometer image reconstruction techniques provide fine resolution data to explore the emerging applications over land by using ambiguous backscatter from land. In this paper, 2 km resolution products of ISRO’s scatterometer SCATSAT-1 are exploited for land target detection, rice crop phenology stages detection for kharif and rabi seasons and estimation of relative soil moisture over parts of India. Temporal and spatial backscatter changes are due to seasonal and changes in Land Use Land Cover. Crop phenology stages such as transplanting, maximum tillering, panicle emergence and physiological maturity stages are identified by analysing SCATSAT-1 time series along with NDVI and findings are supported by appropriate ground truth observations and crop cutting experiment (CCE) data. The relative soil moisture change detection is validated with in situ ground truth measurements using Hydraprobe, carried for SCATSAT-1 ascending and descending passes.

Keywords

Crop Phenology, Gamma-0, Rice, Sigma-0, Soil Moisture, Vegetation Dynamics.

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