Calibration of METRIC Modeling for Evapotranspiration Estimation Using Landsat 8 Imagery Data

ABSTRACT: Research aims to determine the value of concentration and spread profile of chlorophyll-a in Birah-birahan Island waters. To process the spread profile data of chlorophyll-a concentration in Birah-Birahan Island waters, the data were used is Landsat 8 imagery data in 2018, i.e. February and August and February and October in 2019, data processing uses the er-mapper and arcgis application by using the Pentury algorithm and Hanintyo algorithm. Information was obtained that the value of chlorophyll-a concentration used the pentury algorithm in 2018, February on west monsoon, i.e. 0.06 mg/m3 and August on east monsoon, i.e. 0.07 mg/m3, in 2019 February on west monsoon, namely 0.06 mg/m3 and October on east monsoon is 0.07 mg/m3 and chlorophyll-a concentration value using the Hanintyo algorithm in 2018 February on west monsoon i.e. 0.22 mg/m3 and August in the east monsoon is 0.27 mg/m3, in 2019 February on west monsoon i.e. 0.25 mg/m3 and October on east monsoon i.e. 0.24 mg/m3. It can be concluded that the concentration value by the pentury and Hanintyo algorithm of two different years in west and east monsoon the highest chlorophyll-a concentration value were known based on Hanintyo algorithm. Keywords: Chlorophyll-a, Landsat 8, Spread, Birah-Birahan Island.

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Application of ASTER and Landsat 8 imagery data and mathematical evaluation method in detecting iron minerals contamination in the Chadormalu iron mine area, central Iran

Journal of Applied Remote Sensing ◽

10.1117/1.jrs.11.016027 ◽

2017 ◽

Vol 11 (1) ◽

pp. 016027 ◽

Cited By ~ 4

Author(s):

Arsia Moghtaderi ◽

Farid Moore ◽

Hojjatollah Ranjbar

Keyword(s):

Evaluation Method ◽

Central Iran ◽

Landsat 8 ◽

Mine Area ◽

Iron Minerals ◽

Iron Mine ◽

Mathematical Evaluation ◽

Imagery Data

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PENGGUNAAN SPATIAL MULTICRITERIA ANALYSIS UNTUK MENENTUKAN DAERAH RAWAN MALARIA DI KABUPATEN PURWOREJO (Application of Spatial Multicriteria Analysis Determining Malaria Vulnarable Area in Purworejo Regerency)

Jurnal Manusia dan Lingkungan ◽

10.22146/jml.24819 ◽

2018 ◽

Vol 24 (2) ◽

pp. 81

Author(s):

Prima Widayani ◽

Erika Yuliantari

Keyword(s):

Public Health ◽

Infectious Disease ◽

Data Processing ◽

Multicriteria Analysis ◽

Secondary Data ◽

Vulnerability Mapping ◽

Landsat 8 ◽

Special Concern ◽

Incident Cases ◽

Imagery Data

AbstrakMalaria merupakan salah satu penyakit menular endemis yang masih menjadi perhatian khusus pada kesehatan masyarakat di Indonesia, salah satunya di Kabupaten Purworejo. Tahun 2013, terdapat 615 kasus kejadian penyakit malaria pada semua rentang umur di kabupaten ini. Penanganan penyakit ini dilakukan dengan beberapa cara, contohnya adalah dengan surveilans malaria. Kegiatan surveilans bermaksud untuk melaksanakan tindakan penanggulangan yang cepat dan akurat disesuaikan dengan kondisi setempat. Salah satu tujuan kegiatan ini untuk mendapatkan gambaran distribusi penyakit malaria yang dapat dilakukan dengan pembuatan peta kerawanan penyakit malaria. Tujuan dari penelitian ini adalah menentukan kerawanan wilayah terhadap penyakit malaria dengan metode Spatial Multicriteria Analysis (SMCA). Penelitian ini memanfaatkan data Citra Landsat 8 dan beberapa data sekunder yang diolah dengan menggunakan software ILWIS. Hasil dari penelitian ini menunjukan bahwa metode SMCA dapat memetakan kerawanan penyakit malaria dan terdapat enam kecamatan di Kabupaten Purworejo yang rawan, yaitu Kecamatan – kecamatan Bruno, Bener, Gebang, Loano, Kaligesing, dan Bagelen.AbstractMalaria is one of endemic infectious disease that has been special concern in Indonesian public health, especially in Purworejo Regency. In 2013, there were 615 incident cases of malaria disease in all age ranges. There are several kinds of handling malaria disease, one of which is malaria surveillances. Surveillances activity intends to implement handling fast and accurate actions. One of this activity aims to obtain overview distribution of malaria disease which can be done with vulnerable mapping. This study aims to determine vulnerability of area with malaria disease using Spatial Multicriteria Analysis (SMCA). It has been done by utilizing Landsat 8 Imagery data and some of secondary data processing with ILWIS software. The result of this study showed that SMCA methods can be used to vulnerability mapping of malaria disease and found that there are six vulnerable districts, Bruno, Bener, Gebang, Loano, Kaligesing, and Bagelen District.

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Evapotranspiration Estimation with the S-SEBI Method from Landsat 8 Data against Lysimeter Measurements at the Barrax Site, Spain

Remote Sensing ◽

10.3390/rs13183686 ◽

2021 ◽

Vol 13 (18) ◽

pp. 3686

Author(s):

José Antonio Sobrino ◽

Nájila Souza da Rocha ◽

Drazen Skoković ◽

Pâmela Suélen Käfer ◽

Ramón López-Urrea ◽

...

Keyword(s):

Remote Sensing ◽

Hydrological Cycle ◽

Irrigation Scheduling ◽

Superior Performance ◽

Landsat 8 ◽

Climatic System ◽

Land Covers ◽

Sufficient Variation ◽

Evapotranspiration Estimation

Evapotranspiration (ET) is a variable of the climatic system and hydrological cycle that plays an important role in biosphere–atmosphere–hydrosphere interactions. In this paper, remote sensing-based ET estimates with the simplified surface energy balance index (S-SEBI) model using Landsat 8 data were compared with in situ lysimeter measurements for different land covers (Grass, Wheat, Barley, and Vineyard) at the Barrax site, Spain, for the period 2014–2018. Daily estimates produced superior performance than hourly estimates in all the land covers, with an average difference of 12% and 15% for daily and hourly ET estimates, respectively. Grass and Vineyard showed the best performance, with an RMSE of 0.10 mm/h and 0.09 mm/h and 1.11 mm/day and 0.63 mm/day, respectively. Thus, the S-SEBI model is able to retrieve ET from Landsat 8 data with an average RMSE for daily ET of 0.86 mm/day. Some model uncertainties were also analyzed, and we concluded that the overpass of the Landsat missions represents neither the maximum daily ET nor the average daily ET, which contributes to an increase in errors in the estimated ET. However, the S-SEBI model can be used to operationally retrieve ET from agriculture sites with good accuracy and sufficient variation between pixels, thus being a suitable option to be adopted into operational ET remote sensing programs for irrigation scheduling or other purposes.

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

Revista Brasileira de Engenharia Agrícola e Ambiental ◽

10.1590/1807-1929/agriambi.v25n3p149-155 ◽

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.

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