scholarly journals Evapotranspiration of banana using the SEBAL algorithm in an irrigated perimeter from the Northeastern Brazil

2021 ◽  
Vol 25 (3) ◽  
pp. 149-155
Author(s):  
Tainara T. S. Silva ◽  
Hugo O. C. Guerra ◽  
Bernardo B. da Silva ◽  
Cris L. M. Santos ◽  
Jean P. Guimarães ◽  
...  
Keyword(s):  
Satellite Images ◽  
Surface Energy Balance ◽  
Northeastern Brazil ◽  
Landsat 8 ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Landsat 8 Oli ◽  
Irrigated Perimeter ◽  
Evapotranspiration Estimation ◽  
Mathematical Operations

ABSTRACT The study aimed to estimate the evapotranspiration of banana (Musa spp.) in an irrigated perimeter of the municipality of Barbalha, CE, Brazil, using the Surface Energy Balance Algorithm for Land (SEBAL) model and to compare these results with those estimated using the Penman-Monteith method. Landsat-8 OLI/TIRS satellite images of May 22, 2016, August 10, 2016, and October 29, 2016 and data on temperature, relative humidity, wind speed and solar irradiance, obtained from an automatic weather station, installed close to the experimental area were used. The bands were stacked, and the stacked images were cut, then mathematical operations and evapotranspiration estimation were performed, whose actual daily banana values, estimated by the SEBAL algorithm, were 4.70; 5.00 and 6.50 mm, respectively, for May 22, August 10, and October 29, 2016. Comparing the daily ETr given by SEBAL with that obtained by the Penman-Monteith method, absolute errors of 0.26, 0.44, and 0.64 mm d-1 were observed for May 22, August 10, and October 29, 2016, respectively. These errors are within the ranges accepted in the literature.

scholarly journals PROMICE automatic weather station data

2021 ◽  
Author(s):  
Robert S. Fausto ◽  
Dirk van As ◽  
Kenneth D. Mankoff ◽  
Baptiste Vandecrux ◽  
Michele Citterio ◽  
...  
Keyword(s):  
Surface Energy Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Atmospheric Conditions ◽  
Production Chain ◽  
Near Surface ◽  
Surface Mass ◽  
Future Assessment

Abstract. The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheetproperties since 2007. Currently the PROMICE automatic weather station network includes 25 instrumented sites in Greenland.Accurate measurements of the surface and near-surface atmospheric conditions in a changing climate is important for reliablepresent and future assessment of changes to the Greenland ice sheet. Here we present the PROMICE vision, methodology,and each link in the production chain for obtaining and sharing quality-checked data. In this paper we mainly focus on thecritical components for calculating the surface energy balance and surface mass balance. A user-contributable dynamic webbaseddatabase of known data quality issues is associated with the data products at (https://github.com/GEUS-PROMICE/PROMICE-AWS-data-issues/). As part of the living data option, the datasets presented and described here are available atDOI: 10.22008/promice/data/aws, https://doi.org/10.22008/promice/data/aws (Fausto and van As, 2019).

scholarly journals Estimation of PM10 Distribution using Landsat5 and Landsat8 Remote Sensing

Proceedings ◽  
2018 ◽  
Vol 2 (23) ◽  
pp. 1430
Author(s):  
V. M. Fernández-Pacheco ◽  
C. A. López-Sánchez ◽  
E. Álvarez-Álvarez ◽  
M. J. Suárez López ◽  
L. García-Expósito ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Air Pollutants ◽  
Satellite Images ◽  
Satellite Image ◽  
Remote Sensing Image ◽  
Regional Studies ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Landsat 5 Tm ◽  
Source Of Information

Air pollution is one of the major environmental problems, especially in industrial and highly populated areas. Remote sensing image is a rich source of information with many uses. This paper is focused on estimation of air pollutants using Landsat-5 TM and Landsat-8 OLI satellite images. Particulate Matter with particle size less than 10 microns (PM10) is estimated for the study area of Principado de Asturias (Spain). When a satellite records the radiance of the surface received at sensor, does not represent the true radiance of the surface. A noise caused by Aerosol and Particulate Matters attenuate that radiance. In many applications of remote sensing, that noise called path radiance is removed during pre-processing. Instead, path radiance was used to estimate the PM10 concentration in the air. A relationship between the path radiance and PM10 measurements from ground stations has been established using Random Forest (RF) algorithm and a PM10 map was generated for the study area. The results show that PM10 estimation through satellite image is an efficient technique and it is suitable for local and regional studies.

Water Quality Assessment Models for Dokan Lake Using Landsat 8 OLI Satellite Images

2016 ◽  
Vol 19 (3&4) ◽  
pp. 25-42 ◽  
Author(s):  
Hasti Shwan Abdullah Abdullah ◽  
◽  
Mahmoud S. Mahdi Mahdi ◽  
Hekmat M. Ibrahim Ibrahim ◽  
◽  
...  
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Satellite Images ◽  
Water Quality Assessment ◽  
Landsat 8 ◽  
Landsat 8 Oli

Kajian Metode Klasifikasi Citra Landsat-8 untuk Pemetaan Habitat Bentik di Kepulauan Padaido, Papua

2017 ◽  
Vol 2 (1) ◽  
pp. 1 ◽  
Author(s):  
Muhammad Hafizt ◽  
Marindah Yulia Iswari ◽  
Bayu Prayudha
Keyword(s):  
Coral Reefs ◽  
Satellite Remote Sensing ◽  
Satellite Images ◽  
Habitat Mapping ◽  
Benthic Habitat ◽  
Landsat 8 ◽  
Classification Methods ◽  
Landsat 8 Oli ◽  
Remote Sensing Technique ◽  
Object Based

<strong>Assessment of Landsat-8 Classification Method for Benthic Habitat Mapping in Padaido Islands, Papua.</strong> Indonesia is the biggest archipelagic country in the world with an area of coral reefs of 39,583 km.This area has to be managed effectively and efficiently utilizing satellite remote sensing technique capable of mapping of benthic habitat coverage, such as coral reefs, seagrasses, macroalgae, and bare substrates. The technique is supported by the availability of Landsat-8 OLI satellite images that have been recording the regions of Indonesia continuously every 16 days. This research was carried out in June 2015 in parts of Padaido Islands, Papua. This area was selected due to high coral reef damages. This study utilized Landsat-8 OLI to compare two classification methods, namely pixel based and object based methods using ‘maximum 2 likelihood’ (ML) and ‘example based feature extraction’ classifications, respectively, after water column correction (Lyzenga method).  The results showed that both methods produced benthic habitat maps with 7 class covers. The pixel-based classification resulted in a better overall accuracy (47.57%) in the mapping of benthic habitats than object-based classification approach (36.17%). Thus, the ML classification is applicable for benthic habitat mapping in Padaido Islands. However, the consistency of this method must be analyzed in many diffrent locations of Indonesian waters.

scholarly journals Estimation of Actual Evapotranspiration Using the Remote Sensing Method and SEBAL Algorithm: A Case Study in Ein Khosh Plain, Iran

Hydrology ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. 36
Author(s):  
Amir Ghaderi ◽  
Mehdi Dasineh ◽  
Maryam Shokri ◽  
John Abraham
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Surface Energy Balance ◽  
Sufficient Accuracy ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Landsat 8 ◽  
Irrigation Requirements

The aim of this study was to estimate evapotranspiration (ET) using remote sensing and the Surface Energy Balance Algorithm for Land (SEBAL) in the Ilam province, Iran. Landsat 8 satellite images were used to calculate ET during the cultivation and harvesting of wheat crops. The evaluation using SEBAL, along with the FAO-Penman–Monteith method, showed that SEBAL has a sufficient accuracy for estimating ET. The values of the Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), and correlation coefficient were 0.466, 2.9%, 0.222 mm/day, and 0.97, respectively. Satellite images showed that rainfall, except for the last month of cultivation, provided the necessary water requirements and there was no requirement for the use of other water resources for irrigation, with the exception of late May and early June. The maximum ET on the Ein Khosh Plain occurred in March. The irrigation requirements showed that the Ein Khosh Plain in March, which witnessed the highest ET, did not experience any deficiency of rainfall that month. However, during April and May, with maxima of 50 and 70 mm, respectively, water was needed for irrigation. During the plant growth periods, the greatest and least amount of water required were 231.23 and 19.47 mm/hr, respectively.

scholarly journals Retrieval of suspended sediment concentrations using Landsat-8 OLI satellite images in the Orinoco River (Venezuela)

2018 ◽  
Vol 350 (1-2) ◽  
pp. 20-30 ◽  
Author(s):  
Santiago Yepez ◽  
Alain Laraque ◽  
Jean-Michel Martinez ◽  
Jose De Sa ◽  
Juan Manuel Carrera ◽  
...  
Keyword(s):  
Suspended Sediment ◽  
Satellite Images ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Orinoco River ◽  
Suspended Sediment Concentrations

scholarly journals Space-temporal evaluation of biophysical parameters in the High Ipanema watershed by remote sensing

2018 ◽  
Vol 7 (6) ◽  
pp. 357
Author(s):  
Jose Diorgenes Alves Oliveira ◽  
Biancca Correia De Medeiros ◽  
Jhon Lennon Bezerra Da Silva ◽  
Geber Barbosa De Albuquerque Moura ◽  
Frederico Abraão Costa Lins ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Environmental Changes ◽  
The United States ◽  
Semiarid Region ◽  
United States Geological Survey ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Biophysical Parameters ◽  
Environmental Implications

The High Ipanema watershed is located in a semiarid region and because of this, becomes more vulnerable and susceptible to the effects of environmental changes and the degradation process, it has serious economic and socio-environmental implications. In recent years with the advancement of remote sensing based on satellite imagery or other platforms, it has become possible to monitor different and large areas of the various biomes in the world. The objective of this study was to identify changes in the vegetation cover conditions in the Alto Ipanema watershed, using spectral analyzes of Landsat-8 OLI / TIRS satellite images, using remote sensing techniques. Landsat-8 OLI / TIRS satellite images were obtained from the United States Geological Survey – USGS, on 10/12/2013, 14/01/2015 and 12/08/2016, where they were processed from ERDAS IMAGINE® Software, version 9.1. The thematic maps of biophysical parameters were processed by ArcGis® 10.2.2 Software. With the biophysical parameters analyzed, it was found that the northwest portion of the watershed presents a considerable area of exposed soils with indication of a high degree of susceptibility to degradation and that the biophysical parameters evaluated by the SEBAL algorithm are efficient in understanding the dynamics of spatial and temporal areas of semiarid environments.

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