ALBERT

Description: 〈p〉〈em〉Developing Countries like India has more than half of the population engaged in fishery, agriculture etc. and agriculture drives the economy of the Nation. Traditional survey methods are tedious and time consuming, however, with advancement in Remote Sensing Technology data for Agriculture monitoring can be obtained at local and regional scale. The present study demonstrates the use of multi-year multi-date Sentinel-2 MSI data for winter crop monitoring in in Visnagar taluka Mahesansa district of Gujarat state. Multi-temporal Sentinel-2 data covering study area for the winter crop period from November-2018 to March-2019 was downloaded from 〈/em〉〈a href="https://earthexplorer.usgs.gov/"〉〈em〉https://earthexplorer.usgs.gov/〈/em〉〈/a〉〈em〉.The major objective of this study was to monitor site-specific crop growth in different villages of Visnagar Taluka by generating Normalized Difference Vegetation Index (NDVI) profiles of major winter crops. 〈/em〉〈em〉The spectral behavior of wheat, mustard, Fennel and castor crops during active growth stages was studied. The results indicated that different winter crops can be discriminated using the data during the early growth phases like flag-leaf emergence to flowering stages of these crops. Even 〈/em〉〈em〉it was observed that the spectral response of normal-sown and late-sown wheat crop have quite distinct spectral behavior as compared to other winter crops. In this study, the NDVI profiles of different winter crops indicated that 〈/em〉〈em〉Last week of January to first week of February, when all the winter crops were at grand growth stages of grain filling and grain-milk, pod formation (mustard & castor) stages have similar NDVI values, therefore during this period major winter crops in this region may not be possible to discriminate using single date satellite data.〈/em〉〈em〉〈/em〉〈/p〉

Description: 〈p〉〈em〉Sylhet Sadar suffers from excessive rainfall causing the enormous soil loss in this area. C-factor is one of the most important parameter of the Universal Soil Loss Equation (USLE) and revised version of USLE for estimating soil loss. The current study was conducted for determining the crop management factor (C) using remote sensing (RS) and geographical information system (GIS) tools. Satellite images (Landsat 7 ETM+ of 2000, 2010 and Landsat 8 OLI-TIRS of 2020) of the study area were analyzed using ArcGIS 10.5 and ENVI 5.1 software to generate maps for land use and land cover (LULC), normalized differential vegetative index (NDVI) and crop management factor (C). 〈/em〉〈em〉Results showed that the percentage of each LULC classes from 2000 to 2020 was changed over time.〈/em〉〈em〉 There was rapid growth in crop land, water bodies and settlement areas between 2000 and 2020 while the same period observed lessening in vegetation coverage. The relationship between C-factor and vegetation indices such as NDVI was identified. As NDVI and C-factor values are correlated, both lowest and highest NDVI (-0.506–0.629) and C-factor value (0.185–0.753) was found at the same year (2000). By the next 20 years in 2020, the highest NDVI value reduced to 0.373 and lowest C-factor value increased to 0.314 indicates that vegetation coverage of the study area is decreasing. To ensure proper soil management it is therefore imperative to encourage forest regeneration activities, tree planting exercises, crop rotation, conservation tillage practices and shrub growth schemes. 〈/em〉〈/p〉

Description: 〈p〉〈em〉The all-time imaging ability of SAR systems which can penetrate cloud cover and free availability of Sentinel C-Band data are very useful in deriving critical spatial information for flood disaster management in tropical areas such as Malawi. This study shows how Sentinel-1 data has been used to map flood extents by utilizing VH and VV polarizations and enhance risk mapping during the years 2015 to 2020 in Nsanje district. Multi-dated Sentinel-1 images were acquired, pre-processed, and analyzed through Change Detection and Thresholding technique to interpret backscattered radiation thereby distinguishing flooded and non-flooded areas. The VV Polarization result shows that percentage of land that remained under flood water in Nsanje district was 3.97% in 2015, 5.91% in 2019 and 2.05% in 2020. On the other hand, VH Polarization result shows about 7.71% and 2.02% of land remained under flood water in 2019 and 2020 respectively.Sentinel-2 pre-flood image was used to determine major land cover classes in the district. MNDWI derived from Landsat 8 imagery of the same date as 2019 Sentinel-1 crisis imagery was used for flood extent validation. Overall Accuracy of flood extent delineation was 96% and 90% for VH and VV polarization respectively. Flooding frequency in specific areas was observed to determine physical vulnerability and hence figure out the risk to a possible repetition of flood disaster. Further, social data were used to aid a better understanding of the capacity to cope with a possible flood hazard in the study area.〈/em〉〈/p〉

Description: 〈p〉〈em〉Reservoirs are storage structures for water and are useful for irrigation, navigation, hydroelectric power, water supply for drinking, flood control, etc. But reservoir sedimentation is the gradual accumulation of the incoming sediment load from rivers and causes serious problem on the environment, flood management, economy and the long term efficiency of reservoirs also gets reduced. So, we have to aware of these critical complications and for that the causes of sedimentation, calculation of existing sedimentation volume, estimation of possibilities of sediment increment in future and remedial measures are some of considerable key parameters in reservoir sustainability. From the literature collection, some of important models and techniques are discussed for prediction of reservoir sedimentation in this review paper.〈/em〉〈/p〉

Description: 〈p〉〈em〉Information on crop acreage statistics and distribution of crops in different districts is required for planning and implementation of various government schemes. Further, information is also required on kharif fallow areas to enhance the cropping intensity. Therefore, in this context acreage assessment in different agriculture seasons i.e., kharif, rabi and zaid has been carried out in Jharkhand State using Landsat-8 OLI remote sensing data. Estimation was carried out for the year 2015–16, 2016–17 and 2017–18. Gross cropped area in the State varied from 19526 Sq.km. in the year 2015–16 to 24089 sq.km. in the year 2017–18. The Gross cropped area and Net Sown Area was highest in Ranchi and West Singhbhum districts in different years. District-wise analysis of kharif fallow showed highest area in West Singhbhum district. Further, suitability analysis for pulses and other appropriate crops needs to be carried out to convert the post fallow kharif areas to double crop areas and more than two crop areas to increase the cropping intensity. 〈/em〉〈/p〉