Jeganathan Chockalingam

Birla Institute of Technology, Mesra | BIT Mesra · Department of Remote Sensing

The study explored the dependence of the spatio-temporal pattern of rainfall and its variability on the spatial distribution of forests in the central Indian landscape, which covers ~1 million km², includes five states, and supports a population of 329 million people. The monsoon rainfall is, thus, a crucial source of freshwater for these populatio...

Monitoring agriculture growth at different seasons (i.e., Rabi-winter crop, Zaid-summer crop, Kharif-monsoon crop) is an important requirement to understand annual cropping pattern dynamics for food security-related policy and strategy formulation. Cropping pattern is not uniform across a region and hence satellite observation of different time-per...

With advancement in the technologies, machine learning applications have exploded in past few decades and rapidly sprawling in almost every sector. Machine learning algorithms are widely used in modeling habitat suitability which contributes towards an integral a part of ecosystem science. In this study a comparative analysis of machine learning me...

Forest canopy height estimates, at a regional scale, help understand the forest carbon storage, ecosystem processes, the development of forest management and the restoration policies to mitigate global climate change, etc. The recent availability of the NASA’s Global Ecosystem Dynamics Investigation (GEDI) LiDAR data has opened up new avenues to as...

Quantification of the spatio-temporal trends in vegetation dynamics and its drivers is crucial to ensure sustainable management of ecosystems. The north-eastern state of Meghalaya possessing an idiosyncratic climatic regime has been undergoing tremendous pressure in the past decades considering the recent climate change scenario. A robust trend ana...

Environmental hazards like drought lead to degrading food production and adversely impact the agro-economy. This study investigates the contributions of different climatic and socio-economic variables to agricultural drought in Jharkhand. The three primary criteria, i.e., exposure (E), sensitivity (S), and adaptive capacity (AC), responsible for ag...

Context Accurate mapping of mountain agriculture is important for both a food-security and an environmental degradation perspective. Remote sensing provides a large and diverse data source for these complex regions and enables large-scale mapping of mountain agriculture. However, obtaining good mapping accuracy is challenging in mountain terrain....

The ‘Shadow Method’ is a tool to estimate the Atmospheric Optical Depth (AOD) on Mars from the brightness of shadows. This method is derived from the equations of radiative transfer, but there are several important simplifications that together invoke errors of several tens of percent. Work by us and by others show that these errors are largely sys...

Habitat of any species can be defined as the biotic and abiotic components present in an area that supports the survival and reproduction of the species[17]. If these factors are altered due to any of the natural or anthropogenic reasons, the habitat becomes unsuitable for their survival. As a result of which, they either need to get adapted to the...

About how migratory birds can get effected by various types of diseases and how they can spread those diseases on their migratory paths and destination

The Shuttle Radar Topography Mission (SRTM), Advanced Spaceborne Thermal Emission, and Reflection Radiometer (ASTER) are open-source data used as a global digital elevation model. These DEM models have a wide range of applications and are known to have less amount of unavoidable errors. Mostly systematic errors arise, and also errors that may be de...

This paper summarizes the development and application of spatial statistical models in satellite optical remote sensing. The paper focuses on the development of a conceptual model that includes the measurement and sampling processes inherent in remote sensing. We organized this paper into five main sections: introducing the basis of remote sensing,...

Time series analysis of Enhanced Vegetation Index (EVI) data using the Multi-Resolution Analysis (MRA) based Wavelet Transforms (WT) provides capacity to characterize the inter-annual and intra-annual vegetation variability on the ground at different scales and resolutions. The MRA was performed to decompose time series EVI at level 5 in order to a...

Understanding the spatio-temporal pattern of natural vegetation helps decoding the responses to climate change and interpretation on forest resilience. Satellite remote sensing based data products, by virtue of their synoptic and repetitive coverage, offer to study the correlation and lag effects of rainfall on forest growth in a relatively longer...

Regional as well as global cropland database at a high spatial resolution like 10 m is not available. This study aims to integrate the Sentinel-1 synthetic aperture radar (SAR) data and Sentinel-2 optical data in a more robust way to map the croplands at 10 m spatial resolution. It also examines the effectiveness of different derived products from...

Forests are considered important for controlling the global climate cycle through sequestering carbon in their biomass. Thus, monitoring forest biomass is a key challenge, specifically in areas of complex stand structure under varying environmental conditions. Remote sensing enables cost‐effective and rapid assessment of biomass over a large area....

Climatic extremities like drought affect the agricultural sector as well as the economy of a country like India, where the major cropping season depends on the monsoon rainfall. Jharkhand is one of the states in India, where monsoon dependent agriculture is dominant. It is, therefore, necessary to continuously monitor the vegetation health to ensur...

The water footprint of a crop is defined as the total volume of water consumed for the production of the crop in the growing season. The total water footprint comprises of the three components, i.e. the rainwater (green water footprint), irrigated water (blue water footprint) and the polluted water (grey water footprint) usage for the production. T...

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Quantifying the leaf‑fall dynamics in the tropical deciduous forest will help in modeling regional energy balance and nutrient recycle pattern, but the traditional ground‑based leaf‑fall enumeration is a tedious and geographically limited approach. Therefore, there is a need for a reliable spatial proxy leaf‑fall (i.e., deciduousness) indicator. In...

Various soil moisture products (AMSR-E at 25 km, SMAP at 9 km, CCI at 25 km) available from different space agencies, derived using the active microwave remote sensing, may not be suitable for studies at a local level due to their coarse spatial resolution. Hence, an attempt has been made in this study to estimate the surface soil moisture at high...

This study analysed long-term rainfall data (1851–2006) over seven climatic zones of India at seasonal and annual scales based on three techniques: (i) linear regression, (ii) multifractal detrended fluctuation analysis (MFDFA) and (iii) Bayesian algorithm. The linear regression technique was used for trend analysis of short-term (30 years) and lon...

I am trying to predict the Earthquake Sensitive Dates in 2020. My focus is to predict Bigger magnitude Earthquakes only. The days mentioned have highly possibility to have Earthquakes of Magnitude > 6.0 in Richer Scale.

The changes in natural ecosystems provide opportunity to increase vegetation carbon sink capacity and thereby contribute to mitigation of climate change impacts. The Indian tropics and the large ecological variation within the country afford the advantage of diverse niches and offer opportunities to reveal the role of biotic factors at different le...

Sustainability of date palm trees based economy envisages regular monitoring of spatio-temporal variations of these trees over time. But, field based counting is a very old style of managing trees which is labour intensive, costly and time consuming while modern geo-spatial technologies provides a fast, cheaper and accurate mechanism. In this regar...

An optimal model was developed for accounting forest carbon stock from synergistic use of optical data from Landsat TM and synthetic aperture radar (SAR) data from COSMO-Skymed (X-band), Radarsat-2 (C-band) and ALOS PALSAR (L-band) sensors over a tropical deciduous heterogeneous forest of India. The best-fit integrated multiple linear regression mo...

The recent advances in earth observation technology has made the monitoring of vegetation stress due to drought related issues like soil moisture stress much easier. The meteorological drought occurs when the actual precipitation is less than the climatological mean by a specified threshold depending on the region. However, meteorological drought c...

Land Suitability analysis (LSA) is the process, to find the suitable area for a particular purpose taking into account different parameters affecting the purpose. This study focuses on identifying suitable areas for future expansion of agricultural practices due to demands of growing population. The integration of GIS techniques with Multi Criteria...

The objective of this study is to estimate the forest aboveground carbon (AGC) stock using integrated space-borne synthetic aperture radar (SAR) data from COSMO-Skymed (X band) and ALOS PALSAR (L band) with field inventory over a tropical deciduous mixed forest. Carbon acts as a vital constituent in the global decision making policy targeting the i...

The objective of this study is to precisely quantify the forest aboveground biomass (AGB) and carbon stock in a tropical deciduous forest with synergistic use of space-borne L-band ALOS PALSAR and X-band COSMO-Skymed SAR data, along with field inventory data. AGB serves as a decisive parameter for preparing global decision making policy targeting t...

The present study has analysed grassland phenology: start of greening (SOG), end of greening (EOG) and length of greening (LOG), and their rate of change in the western Himalaya in India (Himachal Pradesh) using MODIS NDVI time series data (2001–2015). These metrics were inspected at different stratification levels: state, elevation, climatic zones...

Estimation of Atmospheric Optical Depth through Shadow method

Agriculture is the prime requirement for sustaining human life on earth, and agriculture sustainability depends on soil health and suitable climatic variations. Human have adopted many local-weather-dependent crop types and its cultivation patterns based on knowledge about long term climatic and environmental conditions. Any anomaly in these factor...

Estimating the timing of the occurrence of events that characterize growth cycles in vegetation from time series of remote sensing data is desirable for a wide area of applications. For example, the timings of plant life cycle events are very sensitive to weather conditions and are often used to assess the impacts of changes in weather and climate....

This paper tries to inform the users about pitfalls and challenges involved in using time-series remote sensing data/products. Freely existing products need to be carefully used. It is observed that many young researchers from the developing countries are using such products without really understanding the technicalities behind each product and th...

Supervised multi-class classification (MCC) approach is widely being used for regional-level land use–land cover (LULC) mapping and monitoring. However, it becomes inefficient if the end user wants to map only one particular class. Therefore, an improved single-class classification (SCC) approach is required for quick and reliable map production pu...

Land cover change analysis was carried out using Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time series data for the period 2005-2014. MODIS EVI data coupled with Quality Assessment Science Data Sets (QASDS) was de-noised with Savitzky-Golay filter while enhancing quality and preserving the temporal profil...

Increase in extreme events due to recent climatic pattern at a global scale has led to ecosystem loss and imbalance. This may further accelerate global warming and eventually threat on sustenance of life on this planet earth India is a land of mega biodiversity with different landforms. However, increasing pressure from the population may drive the...

Agriculture has been the backbone of the growth of any civilization since ages, especially in a country like India, where the majority of the rural population is based on the agricultural and allied activities. Agriculture not only contributes to the economy of the country, but it is the most important way to feed the huge and ever growing world po...

The study attempts to extract Mountain Agriculture using an optimized Dynamic Time Warping (DTW) algorithm having endpoint constraints. The DTW was applied over a time-series annual stack of Normalized Differential Vegetation Index (NDVI) using a set of reference time series profiles for three agriculture classes (i.e., double cropping, single crop...

The T. melanocephalus is one among the poorly studied threatened pheasant of the world. It is endemic to North Western Himalaya with a narrow range from Hazara in north Pakistan through Jammu & Kashmir to Garhwal in India. The study was a part of multidisciplinary research project undertaken in the Great Himalayan National Park Conservation Area (G...

The existing earthquake prediction techniques depends mainly on the pre-cursors i.e., symptoms occurring few hours or days before the event either on the surface/beneath of the earth or in the atmosphere. But the cause behind the abnormality in these pre-cursor values are not yet really understood. In our study we have hypothesized that the main ca...

Conflicts between people and elephants are common in some parts of tropical Asia. This may occur when the elephant population is concentrated or increases, in regions with high human population densities or intensive land use. Dalma Wildlife Sanctuary, located near Jamshedpur city in the Jharkhand State of India is known for its elephant (Elephas m...

Health and spread of natural forest is decreasing over time, especially in the developing nations. Without knowing information about actual status of forest cover and its dynamics it would not be easy to control rate of degradation and associated global warming. In this regard, the study attempts to quantify the spatio-temporal dynamics in forest c...

The Third Edition of this book retains the basic principles of remote sensing, introduced in the earlier editions. It covers all aspects of the subject from electromagnetic radiation, its interaction with objects, various sensors, platforms, data processing, data product generation and end utilisation for earth resource monitoring and management. A...

Accurate estimates of forest biomass are increasingly important in relation to sequestration of carbon by forest trees. Satellite remote sensing is a useful tool for biomass estimation and monitoring of forest ecological processes. Microwave synthetic aperture radar (SAR) can increase the accuracy of estimations of forest biomass in comparison to o...

The spatial coarseness of time-series satellite data (≥250 m) and land cover mixing within a pixel poses difficulties in identifying a unique reference profile for each land cover class in regional level mapping. This problem is exaggerated further in a hilly terrain with different topographic, climatic, environmental conditions, and landscape comp...

Civil Engineering is one of the oldest and important branches of engineering, comprises of many sub-divisions such as surveying (topographic/cadastral/natural resources etc.), construction (urban/rural/municipal infrastructure/materials etc.), transportation (roads/bridges/traffic etc.), water resources (water supply/treatment/ canals/dams/storm/se...

Agriculture is the prime requirement for sustaining human life on earth, and agriculture sustainability depends on soil health and suitable climatic variations. Human have adopted many local-weather-dependent crop types and its cultivation patterns based on knowledge about long term climatic and environmental conditions. Any anomaly in these factor...

Moderate Resolution Imaging Spectro-radiometer (MODIS) time-series Normalized Differential Vegetation Index (NDVI) products are regularly used for vegetation monitoring missions and climate change analysis. However, satellite observation is affected by the atmospheric condition, cloud state and shadows introducing noise in the data. MODIS state fla...

This study analysed Heliocentric and Geocentric positions of all planets in 2017, and calculated the Earthquake Probable Dates. Gravity Perturbation Theory as proposed in Jeganathan et al. (2015) may reveal the concept behind this prediction. This prediction mainly focus on Earthquakes with Magnitude Greater than 6.0 in Richter Scale. Our predictio...

The study aims to predict landslide hazard zones near Tehri Dam in Uttarakhand State located in the Western Himalayas in India. Four different models were analysed: Weight Factor Model (M1), Multiple Factor Model (M2), Statistical Bivariate model (M3) and Analytical Hierarchical Processes (AHP) model (M4). Five different combination of reference la...

The study aims to predict landslide hazard zones near Tehri Dam in Uttarakhand State located in the Western Himalayas in India. Four different models were analysed: Weight Factor Model Model (M2) resulted in a consistently high accuracy in all the combinations. Finally, the 20 different model outputs were integrated to derive unified hazard zonatio...

Increasing frequency of drought events coupled uncertainty imparted by climate change pose grave threat to agriculture and thereby overall food security. This is especially true in South Asian region where world's largest concentration of people depends on agriculture for their livelihood. Indices derived from remote sensing datasets signifying dif...

Increasing population and natural disasters like drought, flood, cyclone etc., has impacted global agriculture area and hence continuously modifying cropping pattern and associated statistics. The present study analysed agriculture dynamics over one of the densely populated and disaster prone state (Bihar) in India and derived vital statistics (sin...

Forest stand biomass serves as an effective indicator for monitoring REDD (reducing emissions from deforestation and forest degradation). Optical remote sensing data have been widely used to derive forest biophysical parameters inspite of their poor sensitivity towards the forest properties. Microwave remote sensing provides a better alternative ow...

For sustainable management and development of ecosystems, a comprehensive knowledge about species and their spatial distributions is highly required. In this regard, many researchers have found Species Distribution Model (SDM) as an effective way to predict occurrences of a particular species through the knowledge of geographical and environmental...

Forest loss is one of the major influencing factor for carbon emission as well as in global climate change. Today there is a gap between the deforestation rate and forest cover estimation. So, for reducing/controlling carbon emission, information about actual status of forest cover and its dynamic is very much essential (under REDD). In this regard...

Agriculture is the main primary economic source in India where more than 70% of the population directly dependent on agriculture. Food demand is becoming high with the increasing population growth from last five decades. For food security perspective the comprehensive, efficient and precise crop, as well as horticulture monitoring, is required. Reg...

Groundwater is an important requirement for the massive population of India. Generally the groundwater level is monitored by using monitoring wells. In this study, Gravity Recovery and Climate Experiment (GRACE) Terrestrial Water Storage (TWS), Land surface state variable GLDAS and Soil Moisture (SM) data were tested for estimating ground water inf...

The main objective of the survey is to Study the emerging classifiers like Random Forest (RF) and Particle Swarm Optimization (PSO) and its application to Satellite Imageries to achieve enhanced and highly accurate Land Cover Classification Model. RF is an ensemble type voting based machine learning algorithm. RF algorithm considers single pixels f...

Abstract Free availability of time-series satellite data enabled the current study to quantify decadal macro-variations (i.e., trend and percent change) in vegetation vigour in the forested environment of Palamu district based on 11 years (2001 to 2011) of fortnightly data of Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation...

The study has analysed the spatio-temporal positions (helio-centric and geo-centric) and configurations of all the planets on every day basis over the whole year 2015. Gravitational forces are invisible and undetectable, and hence it is very difficult to map the presence of these forces. The study has made a bold attempt in conceptualising indirect...

Growing evidences about global warming, decreasing availability of surface and ground water, and erratic rainfall induced droughts are questioning agriculture sustainability. Over the past few decades, drought has become a major disaster in many parts of South Asia and regular monitoring system is needed for the whole South Asia and in this regard...

Abstract Forest plays a vital role in regulating climate through carbon sequestration in its biomass. Biomass reflects the health and environmental conditions of a forest ecosystem. In context to the climate change mitigation mechanisms like REDD (reducing emissions from deforestation and forest degradation), an extensive forest monitoring campaig...

A seamless vegetation type map of India (scale 1: 50,000) prepared using medium-resolution IRS LISS-III images is presented. The map was created using an on-screen visual interpretation technique and has an accuracy of 90%, as assessed using 15,565 ground control points. India has hitherto been using potential vegetation/forest type map prepared by...

All the existing commercial software only provide a tool to process individual snap shot images from satellite data. They do not have any customised package which can help a novice user to process time-series satellite data. Considering the huge availability of free time-series data on one hand and on the other hand gap in processing, we have devel...