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The need for information on soil moisture at large scale to facilitate a sustainable intensification of agricultural land and to ensure food security due to increasing populations cannot be oversta...

Effective rain rate estimation using satellite-based measurement is imperative for many hydro-meteorological applications. With the recent advancement in satellite products and retrieving algorithm...

The dual polarimetric study including degree of polarization (mL) and energy span (λ1+ λ2) for vegetation targets infer the accuracy of vegetation algorithms. The Sentinel − 1 A and ALOS − 2 satell...

The global Earth Observations, remote sensing, geoscience, environmental and applied science communities celebrated the successful launch of LANDSAT 9 on Sept. 27, 2021. LANDSAT 1 (originally named...

Interband information overlapping enhances redundancy in hyperspectral data. This makes identification of application-specific optimal bands essential for obtaining accurate information about folia...

This study investigates the potential of different vegetation descriptors (V) in the modified water cloud model (MWCM), with a focus on comparing the Red – Edge vegetation indices (VI) based and ot...

In this study, a comparative analysis of three satellite precipitation products including the Tropical Rainfall Measuring Mission (TRMM-3B43 V7), the Precipitation Estimation from Remotely Sensed I...

Soil loss through erosion and its subsequent deposition is considered as an important challenge for watersheds. In this paper, attempt has been made to integrate the Revised Universal Soil Loss Equ...

This study aims to quantify the landscape spatio-temporal dynamics including Land Use/Land Cover (LULC) changes occurred in a typical Mediterranean ecosystem of high ecological and cultural significance in central Greece covering a period of 9 years (2001–2009). Herein, we examined the synergistic operation among Hyperion hyperspectral satellite imagery with Support Vector Machines, the FRAGSTATS® landscape spatial analysis programme and Principal Component Analysis (PCA) for this purpose. The change analysis showed that notable changes reported in the experimental region during the studied period, particularly for certain LULC classes. The analysis of accuracy indices suggested that all the three classification techniques are performing satisfactorily with overall accuracy of 86.62, 91.67 and 89.26% in years 2001, 2004 and 2009, respectively. Results evidenced the requirement for taking measures to conserve this forest-dominated natural ecosystem from human-induced pressures and/or natural hazard...

The vegetation water content (VWC) of kidney bean crop is retrieved using ground-based multi-temporal, multi-angular and co-polarized scatterometer data at X-band. An outdoor crop-bed was prepared to observe the scatterometer response at HH- and VV-polarizations in the angular range from 20° to 70°. The trend of scattering coefficient is found to decrease for the entire angular range. The present study is carried out to investigate the retrieval for VWC of a kidney bean crop at its nine different growth stages by an empirical relation based on least square optimization method using scatterometer data. The results are found promising for the retrieval of the VWC of kidney bean crop at its several growth stages.

This study aims to analyse the processes and patterns of peri-urbanization using diurnal earth observation data-sets from onboard DMSP–Operational Linescan System. In this study, multiple correlation, simple and conditional linear regression are used to find out the degree of relationship and spatial behavioural pattern of the factors responsible for the urbanization. All the factors are standardized using the Analytical Hierarchy Process (AHP) coupled fuzzy membership functions. AHP is used to derive the weighting of the factors to produce the urbanity index. In total three functional zones – urban, rural and urban shadow are generated based on factor standardization and spatial contiguity index. Urban fringe is sharing ≥ 60% of Urbanity Index followed by rural fringe (39.50–60% of urbanity index) and urban shadow

Crop classification is needed to understand the physiological and climatic requirement of different crops. Kernel-based support vector machines, maximum likelihood and normalised difference vegetation index classification schemes are attempted to evaluate their performances towards crop classification. The linear imaging self-scanning (LISS-IV) multi-spectral sensor data was evaluated for the classification of crop types such as barley, wheat, lentil, mustard, pigeon pea, linseed, corn, pea, sugarcane and other crops and non-crop such as water, sand, built up, fallow land, sparse vegetation and dense vegetation. To determine the spectral separability among crop types, the M-statistic and Jeffries–Matusita (J–M) distance methods have been utilised. The results were statistically analysed and compared using Z-test and χ2-test. Statistical analysis showed that the accuracy results using SVMs with polynomial of degrees 5 and 6 were not significantly different and found better than the other classifica...

An algorithm for ice cloud detection aided by support vector machine (AID-SVM) is presented. The AID-SVM algorithm is applied and tested for the Advanced Microwave Sounding Unit-A, microwave humidity sounder (MHS), and high resolution infrared radiation sounder (HIRS) instruments onboard NOAA-19 satellite. The algorithm is based on satellite brightness temperature measurements and developed as well as validated by using collocated ice/no-ice cloud information acquired from the CloudSat cloud-profiling radar. The algorithm is tested over both ocean and land surfaces. Overall, the results exhibit very promising potential to acquire ice/no-ice cloud information using the passive satellite sensors. It is found that infrared satellite sensor such as HIRS is more efficient in detecting ice clouds than the counterpart microwave satellite sensors. Furthermore, the combined measurements using microwave/infrared synergy perform no better than the infrared-only measurements.

Soil is a vital part of the natural environment and is always responding to changes in environmental factors, along with the influences of anthropogenic factors and land use changes. The long-term change in soil properties will result in change in soil health and fertility, and hence the soil productivity. Hence, the main aim of this paper focuses on the analysis of land use/land cover (LULC) change pattern in spatial and temporal perspective and to present its impact on soil properties in the Merawu catchment over the period of 18 years. Post classification change detection was performed to quantify the decadal changes in historical LULC over the periods of 1991, 2001 and 2009. The pixel to pixel comparison method was used to detect the LULC of the area. The key LULC types were selected for investigation of soil properties. Soil samples were analysed in situ to measure the physicochemical soil properties. The results of this study show remarkable changes in LULC in the period of 18 years. The effect of l...

Acquiring information on the spatio-temporal variability of soil moisture is of key importance in extending our capability to understand the Earth system’s physical processes, and is also required in many practical applications. Earth observation (EO) provides a promising avenue to observe the distribution of soil moisture at different observational scales, with a number of products distributed at present operationally. Validation of such products at a range of climate and environmental conditions across continents is a fundamental step related to their practical use. Various in situ soil moisture ground observational networks have been established globally providing suitable data for evaluating the accuracy of EO-based soil moisture products. This study aimed at evaluating the accuracy of soil moisture estimates provided from the Soil Moisture and Ocean Salinity Mission (SMOS) global operational product at test sites from the REMEDHUS International Soil Moisture Network (ISMN) in Spain. For this purpose,...

This paper presents a novel non-parametric pattern recognition method to screen rain/no rain status for satellite-borne passive microwave radiometers in the 19–85 GHz channels. The method is based on randomized decision trees with bootstrap aggregation (Random Forests (RF) algorithm). It relies on pragmatic associations between the input features using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) calibrated brightness temperatures and precipitation radar (PR) rain/no rain information as targets. Both these instruments are carried on board the TRMM satellite. In order to develop the method, first, the 10 most significant input features are selected by using feature importance criteria through out-of-bag (OOB) statistics from a total of 17 input features. The input features include the brightness temperatures, as well as some computed signatures – polarization differences (PD), polarization-corrected temperatures (PCT), and scattering indices (SI) at in the 19–85 GHz channels. The featu...

The morphometric analysis of river basin helps to explore the interrelationship between hydraulic parameters and geomorphologic characteristics. The study has been conducted in the Upper Tons basin of Northern Foreland of Peninsular India. The river basin has been characterized using the topographical maps, CARTOSAT satellite image integrated using the GIS techniques. The drainage density analysis indicates lower values in the north-eastern regions and thus these regions can be categorized as better ground water potential zone. There are in total 10 sub-watersheds which have been delineated; SW-4 has maximum drainage density (4.75), stream frequency (5.61) and drainage texture (26.64) followed by SW-6–10. The prioritized sub-watershed numbers SW-4 and SW-6–10 need conservation practices because of their high erodibility and run-off. SW-1–3 and SW-5 regions have better permeable bed rocks and hence good for water harvesting. The areal parameter indicates elongated shape of basin and moderate to steeper gro...

Appropriate assessment of groundwater is important to ensure sustainable and safe use of this natural resource. However, evaluating overall groundwater quality is difficult due to the spatial variability of multiple contaminants. This research proposes a geographical information system (GIS)-based groundwater quality pollution mapping technique, which synthesizes different available water quality data, normalized with the World Health Organization (WHO) standards. The normalized difference index (NDI) is used to perform the normalization process. This study utilizes a multi-criteria evaluation (MCE) script (MATLAB 10.0), developed to assign weights to each of the analysed water quality parameters. The consistency of judgments of weight assignment is further analysed using the consistency ratio (CR) and consistency index (CI) techniques. The Shuttle Radar Topography Mission (SRTM) C-band radar and Landsat TM satellite image data are used to derive a digital elevation model (DEM) and land-use/land-...

Biomass obtained from arsenic resistant gram positive bacteria Rhodococcus sp. WB-12 was studied for the removal of arsenite from aqueous solution. The biomass sorption characteristic was investigated as a function of biomass doses, contact time, and pH. The Langmiur Freundlich, and Dubinin-Radushkevich (D-R) models were applied to describe the biosorption isotherm. The biosorption capacity of the biomass for As(III) was found to be 77.3 mg/g (pH 7.0) using 1 g/L biomass with the contact time of 30 min at 30°C. Kinetic evaluation of experimental data showed biosorption of As (III) followed pseudo-second-order kinetics. The Fourier transform infrared spectroscopy (FT-IR) analysis indicated the involvement of possible functional groups (-OH, -C=O, -NH) in the arsenite biosorption process. Thus, biomass derived from Rhodococcus sp. WB-12 cells has potential for use as biosorbent for the removal of arsenic from contaminated water.

In this work remote sensing, geographic information systems (GIS) and fieldwork techniques are combined in an attempt to identify groundwater potential zones in the hilly terrain of the Pavagarh region. The various thematic maps prepared for delineating groundwater potential zones are lineament density, drainage density, digital elevation model (DEM), slope map and land use/land cover (LULC). A multi-criteria evaluation technique (MCE) is used to investigate a number of choice possibilities and evaluate suitability according to the associated weight of each factor. A map is obtained which shows the classification of the area into good, moderate and low groundwater potential zones.