scholarly journals Application of Empirical Bathymetry Method on Sentinel 2A for Measuring Water Depth of Maninjau Lake

2021 ◽  
Vol 4 (1) ◽  
pp. 1-6
Author(s):  
Wendi Arifin ◽  
Febriandi Febriandi ◽  
Muhammad Hanif ◽  
Triyatno Triyatno ◽  
Ernieza Suhana Mokhtar ◽  
...  
Keyword(s):  
Field Measurements ◽  
Northern Region ◽  
Deep Basin ◽  
Sample Distribution ◽  
Water Index ◽  
Analysis Technique ◽  
Recording Process ◽  
Normalized Difference Water Index ◽  
Survey Sample ◽  
Sentinel 2A

Lake Maninjau is a lake formed by volcanic activity. Many human activities occur on the catchment area, but also in exploited waters. This study aims to mapping the depth of the waters in the Lake Maninjau and assess the effect of field sample distribution on the quality results of the image transformation. The data used are satellite imagery Sentinel 2A, results of point survey. The analysis technique uses the normalized difference water index algorithm, sun glint, empirical bathymetry method and linear regression. The result of the research which is has found that variations of distribution into the dispersion of the recording process of the depth of the object represented by cell. The depth of the water from the results of this transformation refers to the measurement sample in the field survey. The maximum depth of the waters is in the range of 107m. Shallow waters are predominantly distributed in the northern region which is the out late of Lake Maninjau. The southern area forms a deep basin. The distribution of this sample is in the form of an empirical bathymetry map and the relationship between the results of field measurements and the transformation with a regression value of 0.769, this indicates the consideration of total and distribution of survey sample is influence on quality of the results of the transformation.

scholarly journals Sensing Images for Assessing the Minimum Ecological Flux by Automatically Extracting River Surface Width

2020 ◽  
Vol 12 (18) ◽  
pp. 2899
Author(s):  
Wenting Xu ◽  
Qian Shen ◽  
Xuelei Wang ◽  
Qian Wang ◽  
Yue Yao ◽  
...  
Keyword(s):  
Water Surface ◽  
Large Scale ◽  
North China ◽  
Dynamic Monitoring ◽  
Water Index ◽  
River Waters ◽  
The North ◽  
Analysis Technique ◽  
Normalized Difference Water Index

Global warming and economic development have intensified the evaporation and exploitation of river waters, resulting in reduced global river runoff. In minimum ecological flux management, objective determination of the minimum ecological flux and evaluation of whether a river complies with standards are urgently required. Satellite remote sensing allows for rapid, large-scale, and dynamic monitoring. Herein, the Tangmazhai cross-section of the Taizi River was analyzed using the Chinese Gaofen (GF) series satellite that comprises panchromatic multi-spectral sensors and the Sentinel-2 multi-spectral images to automatically extract the water surface width. We applied the Normalized Difference Water Index (NDWI)-Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA) to 225 cloudless scenes from January 2015 to November 2019. We proposed a method to evaluate the minimum ecological flux using water surface width. The river surface width at this location increased from January 2015 to November 2019, and all widths exceeded the minimum river surface water width for the month. The degree of the minimum ecological flux guarantee was determined to be satisfactory. Because there are less clouds and rain in the North China than South China, our results may be used for evaluating the degree of minimum ecological flux guarantee of many river sections in the north China through monthly monitoring.

scholarly journals Damage assessment of chilli thrips using high resolution multispectral satellite data

2021 ◽  
Vol 21 (4) ◽  
pp. 480-487
Author(s):  
Mathyam Prabhakar ◽  
Merugu Thirupathi, ◽  
G. Srasvan Kumar ◽  
U. Sai Sravan ◽  
M. Kalpana ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Satellite Data ◽  
Land Surface ◽  
Vegetation Indices ◽  
Superior Performance ◽  
Water Index ◽  
Sensing Technology ◽  
Significant Difference ◽  
Normalized Difference Water Index ◽  
Sentinel 2A

Remote sensing technology offers an effective, rapid and reliable tool for assessing pest severity in vegetation. Ground based hyperspectral radiometry studies revealed significant difference in the reflectance spectra between healthy and thrip damaged vegetation. Space borne multispectral reflectance from Sentinel 2A satellite data of chilli thrip infested canopy has significant differences in red region (Band 4 – 664.6 nm), NIR region (Bands 5, 6, 7, 8 & 8A having central wavelengths at 704.1, 740.5, 782.8 & 832.8 nm, respectively) and SWIR region (Bands 11 & 12 having central wavelengths at 1613.7 and 2202.4 nm). In this study, an attempt was made to discriminate healthy and pest affected chilli crop in the multispectral satellite imagery using several multispectral vegetation indices. Of these, land surface water index, LSWI (p=0.018) and normalized difference water index, NDWI (p=0.001) were found significant. These indices were used to classify chilli fields in the satellite imagery into severe, moderate and healthy classes. Superior performance of LSWI over NDWI with overall accuracy of 93.80 and Kappa Coefficient of 0.89 was observed. Moran's Index was used to study the spatial distribution of chilli thrips and observed strong clustering (I= 0.9073, p=0.0001).

A waterline method to derive intertidal bathymetry from multispectral satellite images and its application to hydrodynamic modelling

2021 ◽  
Author(s):  
Wagner Costa ◽  
Karin Bryan ◽  
Giovanni Coco
Keyword(s):  
Satellite Images ◽  
Google Earth ◽  
Hydrodynamic Modelling ◽  
Water Index ◽  
High Data ◽  
Bathymetric Data ◽  
Tidal Propagation ◽  
Normalized Difference Water Index ◽  
Multispectral Satellite Images ◽  
Sentinel 2A

<p>Bathymetric data are a key parameter to assess shallow-water hydrodynamic processes. In-situ surveys provide high data quality; however, surveys are expensive and cover a limited spatial extent. To fill this gap, over recent years, the Satellite Derived Bathymetry (SDB) techniques have been developed. The present work aims to elaborate a technique to estimate bathymetric data from satellite images for intertidal zones. The method applied in this work is composed of 6 steps: (1) image querying and pre-processing is done through Google Earth Engine application (API) using Copernicus Sentinel 2A and B, product type 2A. (2) Identification of the intertidal zone for the study area by temporal variability of the Normalized Difference Water Index (NDWI). (3) Recognition of the waterline in each image by the use of an adaptive threshold technique; and assignment of the elevation for each detected waterline based on local observed tide heights. (4) Validation of the estimated bathymetry by comparison with LiDAR measurements. (5) Implementation of a SDB correction: numerical and/or statistical and, (6) assessment of the validity of SDB for hydrodynamic modelling. The SDB technique was applied to 4 different estuaries in New Zealand: Maketu, Ohiwa, Whitianga and Tauranga Harbour showing similar or better estimations in comparison to previous works using optical or synthetic aperture radar (SAR). For Tauranga Harbour, results from the statistical and dynamical corrections showed that the major error source is due to the image optical properties and environmental conditions when the image was acquired (35%). However, the tidal propagation can significantly decrease the SDB accuracy (13%). Finally, the use of the SDB in numerical simulations does not present huge differences in the predicted waterlevels in comparison to the use of survey bathymetry, showing that SDB could be potentially used for coastal flooding simulations.  </p>

scholarly journals Monitoring of coastline change using Sentinel-2A and Landsat 8 data, a case study of Cam Pha city - Quang Ninh province

2021 ◽  
Author(s):  
Duong Thi Loi ◽  
Dang Vu Khac ◽  
Dao Ngoc Hung ◽  
Nguyen Thanh Dong ◽  
Dinh Xuan Vinh ◽  
...  
Keyword(s):  
Google Earth ◽  
Landsat 8 ◽  
Small Areas ◽  
Water Index ◽  
Coastline Change ◽  
Combined Use ◽  
Normalized Difference Water Index ◽  
Sentinel 2A ◽  
Quang Ninh

The main purpose of this study is to evaluate the performance of Sentinel - 2A and Landsat 8 data in monitoring coastline change from 1999 to 2018 at Cam Pha city, Quang Ninh province. Both data were collected under similar conditions of time and weather features to minimize the differences in interpretation results caused by these factors. The coastline was extracted from Sentinel-2A and Landsat 8 in 2018 by using the Normalized Difference Water Index (NDWI). Coastline map from Quang Ninh Department of Natural Resources and Environment with a scale of 1: 50.000 in 1999 was used as a reference of the same mask and overlaid on coastline maps in 2018 to identify the changes in the study area. The data from fieldwork and Google Earth was used to evaluate the accuracy and make comparative comments. The results presented that changes dramatically occurred between 1999 and 2018 with the accretion process prevailing. This process took place quite strongly on the East and Southeast coast while the erosion process only occurred with small areas at scattered points in the study area. The results also showed that the overall classification accuracy of Sentinel-2A imagery (95.0%) was slightly higher than that of Landsat-8 (87.5%). The combined use of Landsat-Sentinel-2 imagery is expected to generate reliable data records for continuous detecting of coastline changes.

Developing land-state maps of Tram Chim National Park in Vietnam based on monitoring results

2020 ◽  
Vol 963 (9) ◽  
pp. 53-64
Author(s):  
V.F. Kovyazin ◽  
Thi Lan Anh Dang ◽  
Viet Hung Dang
Keyword(s):  
National Park ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Likelihood Method ◽  
Wetland Area ◽  
Water Index ◽  
Effi Ciency ◽  
Normalized Difference Water Index ◽  
Specially Protected Natural Areas ◽  
Protected Natural Areas

Tram Chim National Park in Southern Vietnam is a wetland area included in the system of specially protected natural areas (SPNA). For the purposes of land monitoring, we studied Landsat-5 and Sentinel-2B images obtained in 1991, 2006 and 2019. The methods of normalized difference vegetation index (NDVI) and water objects – normalized difference water index (NDWI) were used to estimate the vegetation in National Park. The allocated land is classifi ed by the maximum likelihood method in ENVI 5.3 into categories. For each image, a statistical analysis of the land after classifi cation was performed. Between 1991 and 2019, land changes occurred in about 57 % of the Tram Chim National Park total area. As a result, the wetland area has signifi cantly reduced there due to climate change. However, the area of Melaleuca forests in Tram Chim National Park has increased due to the effi ciency of reforestation in protected areas. Melaleuca forests are also being restored.

scholarly journals Modeling of Durum Wheat Yield Based on Sentinel-2 Imagery

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1486
Author(s):  
Chris Cavalaris ◽  
Sofia Megoudi ◽  
Maria Maxouri ◽  
Konstantinos Anatolitis ◽  
Marios Sifakis ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Model Development ◽  
Wheat Yield ◽  
Growth Period ◽  
Yield Data ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Sentinel 2

In this study, a modelling approach for the estimation/prediction of wheat yield based on Sentinel-2 data is presented. Model development was accomplished through a two-step process: firstly, the capacity of Sentinel-2 vegetation indices (VIs) to follow plant ecophysiological parameters was established through measurements in a pilot field and secondly, the results of the first step were extended/evaluated in 31 fields, during two growing periods, to increase the applicability range and robustness of the models. Modelling results were examined against yield data collected by a combine harvester equipped with a yield-monitoring system. Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were examined as plant signals and combined with Normalized Difference Water Index (NDWI) and/or Normalized Multiband Drought Index (NMDI) during the growth period or before sowing, as water and soil signals, respectively. The best performing model involved the EVI integral for the 20 April–31 May period as a plant signal and NMDI on 29 April and before sowing as water and soil signals, respectively (R2 = 0.629, RMSE = 538). However, model versions with a single date and maximum seasonal VIs values as a plant signal, performed almost equally well. Since the maximum seasonal VIs values occurred during the last ten days of April, these model versions are suitable for yield prediction.

scholarly journals Non-Binary Snow Index for Multi-Component Surfaces

2021 ◽  
Vol 13 (14) ◽  
pp. 2777
Author(s):  
Mario Arreola-Esquivel ◽  
Carina Toxqui-Quitl ◽  
Maricela Delgadillo-Herrera ◽  
Alfonso Padilla-Vivanco ◽  
Gabriel Ortega-Mendoza ◽  
...  
Keyword(s):  
Spectral Characteristics ◽  
Ice Cover ◽  
Landsat 8 ◽  
Water Index ◽  
Bare Land ◽  
Snow Water ◽  
Precision Assessment ◽  
Normalized Difference Snow Index ◽  
Sentinel 2A ◽  
Water Vegetation

A Non-Binary Snow Index for Multi-Component Surfaces (NBSI-MS) is proposed to map snow/ice cover. The NBSI-MS is based on the spectral characteristics of different Land Cover Types (LCTs), such as snow, water, vegetation, bare land, impervious, and shadow surfaces. This index can increase the separability between NBSI-MS values corresponding to snow from other LCTs and accurately delineate the snow/ice cover in non-binary maps. To test the robustness of the NBSI-MS, regions in Greenland and France–Italy where snow interacts with highly diversified geographical ecosystems were examined. Data recorded by Landsat 5 TM, Landsat 8 OLI, and Sentinel-2A MSI satellites were used. The NBSI-MS performance was also compared against the well-known Normalized Difference Snow Index (NDSI), NDSII-1, S3, and Snow Water Index (SWI) methods and evaluated based on Ground Reference Test Pixels (GRTPs) over non-binarized results. The results show that the NBSI-MS achieved an overall accuracy (OA) ranging from 0.99 to 1 with kappa coefficient values in the same range as the OA. The precision assessment confirmed the performance superiority of the proposed NBSI-MS method for removing water and shadow surfaces over the compared relevant indices.

scholarly journals Changes in surface water drive the movements of Shoebills

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marta Acácio ◽  
Ralf H. E. Mullers ◽  
Aldina M. A. Franco ◽  
Frank J. Willems ◽  
Arjun Amar
Keyword(s):  
Surface Water ◽  
Optimal Foraging ◽  
Animal Movement ◽  
Bird Species ◽  
Individual Variability ◽  
Home Ranges ◽  
Age Classes ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Conservation Actions

AbstractAnimal movement is mainly determined by spatial and temporal changes in resource availability. For wetland specialists, the seasonal availability of surface water may be a major determinant of their movement patterns. This study is the first to examine the movements of Shoebills (Balaeniceps rex), an iconic and vulnerable bird species. Using GPS transmitters deployed on six immature and one adult Shoebills over a 5-year period, during which four immatures matured into adults, we analyse their home ranges and distances moved in the Bangweulu Wetlands, Zambia. We relate their movements at the start of the rainy season (October to December) to changes in Normalized Difference Water Index (NDWI), a proxy for surface water. We show that Shoebills stay in the Bangweulu Wetlands all year round, moving less than 3 km per day on 81% of days. However, average annual home ranges were large, with high individual variability, but were similar between age classes. Immature and adult Shoebills responded differently to changes in surface water; sites that adults abandoned became drier, while sites abandoned by immatures became wetter. However, there were no differences in NDWI of areas used by Shoebills before abandonment and newly selected sites, suggesting that Shoebills select areas with similar surface water. We hypothesise that the different responses to changes in surface water by immature and adult Shoebills are related to age-specific optimal foraging conditions and fishing techniques. Our study highlights the need to understand the movements of Shoebills throughout their life cycle to design successful conservation actions for this emblematic, yet poorly known, species.

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