scholarly journals WATER PRODUCTIVITY ASSESSMENTS WITH LANDSAT 8 IMAGES IN THE NILO COELHO IRRIGATION SCHEME

Irriga ◽  
2015 ◽  
Vol 1 (2) ◽  
pp. 01-10 ◽  
Author(s):  
Antônio Heriberto De Castro Teixeira ◽  
Janice Freitas Leivas ◽  
Ricardo Guimarães Andrade ◽  
Fernando Braz Tangerino Hernandez
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Biomass Production ◽  
Water Productivity ◽  
Satellite Image ◽  
Natural Vegetation ◽  
Weather Data ◽  
Landsat 8 ◽  
Irrigation Scheme ◽  
Irrigated Crops

Water productivity assessments with Landsat 8 images in the Nilo Coelho irrigation scheme  ANTÔNIO HERIBERTO DE CASTRO TEIXEIRA1; JANICE FREITAS LEIVAS1; RICARDO GUIMARÃES ANDRADE1 E FERNANDO BRAZ TANGERINO HERNANDEZ2 ¹Pesquisador doutor, grupo de Geociências, Embrapa Monitoramento por Satélite, CNPM, [email protected], [email protected], [email protected]²Professor doutor, Laboratório de Hidráulica, Universidade Estadual Paulista, UNESP, [email protected]  1        Abstract The Nilo Coelho (NC) irrigation scheme, located in the Brazilian semi-arid region, is an important irrigated agricultural area. Land use change effects on actual evapotranspiration (ET), biomass production (BIO) and water productivity (WP) were quantified with Landsat 8 images and weather data in this scheme covering different thermohydrological conditions. The SAFER algorithm was used for ET acquirements while the Monteith’s radiation model was applied to retrieve BIO.  For classifying irrigated crops and natural vegetation, the SUREAL model was used with a satellite image representing the driest period of the year. The average values for ET, BIO and WP in irrigated crops, ranged, respectively, from 1.6 ± 1.9 to 4.2 ± 1.9 mm day-1; 59 ± 86 to 146 ± 91 kg ha-1 day-1;and 2.0 ± 1.5 to 3.0 ± 1.2 kg m-3. The corresponding ranges for natural vegetation (“Caatinga”) were from 1.2 ± 1.8 to 2.6 ± 1.8 mm day-1; 43 ± 78 to 76 ± 78 kg ha-1 day-1; and 1.6 ± 1.4 to 2.7 ± 1.1 kg m-3. The incremental values, which represent the effects of the replacement of natural vegetation by irrigated crops, were 40, 54 e 23%, for ET, BIO e WP, respectively. Keywords: evapotranspiration, biomass production, land use change  TEIXEIRA, A.H. de C.; LEIVAS, J.F.; ANDRADE, R.G.; HERNANDEZ, F.B.T.Análises da produtividade da água com imagens Landsat 8 no perímetro de irrigação Nilo Coelho  2        resumo O perímetro de irrigação Nilo Coelho (NC), localizado na região semiárida do Brasil, é uma importante área de agricultura irrigada. Os efeitos da mudança de uso da terra na evapotranspiração atual (ET), na produção de biomassa (BIO) e na produtividade da água (PA) foram quantificados com imagens Landsat 8 e dados climáticos neste perímetro cobrindo diferentes condições termo hidrológicas. O algoritmo SAFER foi usado para a obtenção da ET enquanto que o modelo da radiação de Monteith foi aplicado para a estnimativa da BIO. Para classificação em culturas irrigadas e vegetação natural o modelo SUREAL foi usado na imagem representativa do período mais seco do ano. Os valores médios da ET, BIO e PA nas culturas irrigadas variaram respectivamente de 1,6 ± 1,9 a 4,2 ± 1,9 mm dia-1; 59 ± 86 a 146 ± 91 kg ha-1 dia-1;e 2,0 ± 1,5 a 3,0 ± 1.2 kg m-3. Os valores correspondentes para vegetação natural (“Caatinga”) foram de 1,2 ± 1,8 a 2,6 ± 1,8 mm dia-1; 43 ± 78 a 76 ± 78 kg ha-1 dia-1; e 1,6 ± 1,4 a 2,7 ± 1,1 kg m-3. Os valores incrementais, representativos dos efeitos da substituição da vegetação natural por culturas irrigadas foram de 40, 54 e 23%, para respectivamente ET, BIO e PA. Palavras-chave: Evapotranspiração, produção de biomassa, mudança de uso da terra.

Making Of Classification Land Cover Through Result Of Visual Data Satellite Image Analysis Landsat 8 OLI : Case Study in Tapaktuan District, South Aceh District

2021 ◽  
Vol 6 (1) ◽  
pp. 59-65
Author(s):  
Safridatul Audah ◽  
Muharratul Mina Rizky ◽  
Lindawati
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Image Classification ◽  
Satellite Image ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Sensing Technology ◽  
Open Land ◽  
Cover Class ◽  
Satellite Image Analysis

Tapaktuan is the capital and administrative center of South Aceh Regency, which is a sub-district level city area known as Naga City. Tapaktuan is designated as a sub-district to be used for the expansion of the capital's land. Consideration of land suitability is needed so that the development of settlements in Tapaktuan District is directed. The purpose of this study is to determine the level of land use change from 2014 to 2018 by using remote sensing technology in the form of Landsat-8 OLI satellite data through image classification methods by determining the training area of the image which then automatically categorizes all pixels in the image into land cover class. The results obtained are the results of the two image classification tests stating the accuracy of the interpretation of more than 80% and the results of the classification of land cover divided into seven forms of land use, namely plantations, forests, settlements, open land, and clouds. From these classes, the area of land cover change in Tapaktuan is increasing in size from year to year.

scholarly journals Urban Bare Land Classification Using NDBaI Index Based on Combination of Sentinel 2 MSI and Landsat 8 Multiresolution Images

2020 ◽  
Vol 36 (2) ◽  
Author(s):  
Trinh Le Hung
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Image ◽  
Urban Land ◽  
Landsat 8 ◽  
Land Classification ◽  
Infrared Band ◽  
Urban Land Cover ◽  
Bare Land ◽  
Sentinel 2

The classification of urban land cover/land use is a difficult task due to the complexity in the structure of the urban surface. This paper presents the method of combining of Sentinel 2 MSI and Landsat 8 multi-resolution satellite image data for urban bare land classification based on NDBaI index. Two images of Sentinel 2 and Landsat 8 acquired closely together, were used to calculate the NDBaI index, in which sortware infrared band (band 11) of Sentinel 2 MSI image and thermal infrared band (band 10) of Landsat 8 image were used to improve the spatial resolution of NDBaI index. The results obtained from two experimental areas showed that, the total accuracy of classifying bare land from the NDBaI index which calculated by the proposed method increased by about 6% compared to the method using the NDBaI index, which is calculated using only Landsat 8 data. The results obtained in this study contribute to improving the efficiency of using free remote sensing data in urban land cover/land use classification.

scholarly journals Land Cover Change Assessment of Vaal Harts Irrigation Scheme using Multi-temporal Satellite Sata

2013 ◽  
Vol 39 (4) ◽  
pp. 59-70 ◽  
Author(s):  
Fredrick Ao Otieno ◽  
Olumuyiwa I Ojo ◽  
George M. Ochieng
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Program ◽  
Land Use Land Cover ◽  
Irrigation Scheme ◽  
Multi Temporal

Abstract Land cover change (LCC) is important to assess the land use/land cover changes with respect to the development activities like irrigation. The region selected for the study is Vaal Harts Irrigation Scheme (VHS) occupying an area of approximately 36, 325 hectares of irrigated land. The study was carried out using Land sat data of 1991, 2001, 2005 covering the area to assess the changes in land use/land cover for which supervised classification technique has been applied. The Normalized Difference Vegetation Index (NDVI) index was also done to assess vegetative change conditions during the period of investigation. By using the remote sensing images and with the support of GIS the spatial pattern of land use change of Vaal Harts Irrigation Scheme for 15 years was extracted and interpreted for the changes of scheme. Results showed that the spatial difference of land use change was obvious. The analysis reveals that 37.86% of additional land area has been brought under fallow land and thus less irrigation area (18.21%). There is an urgent need for management program to control the loss of irrigation land and therefore reclaim the damaged land in order to make the scheme more viable.

scholarly journals Projected water usage and land-use-change emissions from biomass production (2015–2050)

2020 ◽  
Vol 29 ◽  
pp. 100487 ◽  
Author(s):  
Martin Drews ◽  
Morten Andreas Dahl Larsen ◽  
Jenny Gabriela Peña Balderrama
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Biomass Production ◽  
Water Usage

The impact of recent land-use change in the Araucaria araucana forest in northern Patagonia

The Holocene ◽  
2020 ◽  
Vol 30 (8) ◽  
pp. 1101-1114 ◽  
Author(s):  
Ricardo Moreno-Gonzalez ◽  
Thomas Giesecke ◽  
Sonia L Fontana
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Vegetation Cover ◽  
Natural Vegetation ◽  
Northern Patagonia ◽  
Rumex Acetosella ◽  
Araucaria Araucana ◽  
The 1950S ◽  
The Impact ◽  
Nothofagus Dombeyi

Land-use change in the form of extensive Pinus plantations is currently altering the natural vegetation cover at the forest–steppe ecotone in northern Patagonia. Providing recommendations for conservation efforts, with respect to this recent and earlier land-use changes, requires a longer time perspective. Using pollen analysis, we investigated to what degree the colonization of the area by Euro-American settlers changed the forest composition and the vegetation cover, and to explore the spread of the European weed Rumex acetosella. This study is based on short sediment cores from six lakes in the Araucaria araucana forest region, across the vegetation gradient from the forest to the steppe. Results document that although Araucaria araucana has been extensively logged elsewhere, near the investigated sites, populations were rather stable and other elements of the vegetation changed little with the initiation of Euro-American settlements. A reduction of Nothofagus dombeyi-type pollen occurred at some sites presumably due to logging Nothofagus dombeyi trees, while toward the steppe, Nothofagus antarctica shrubs may have been removed for pasture. The appearance of Rumex acetosella pollen is consistent with the initiation of land use by Euro-American settlers in all cores, probably indicating the onset of animal farming. The rise of the Rumex acetosella pollen curve during the 1950s marks more recent land-use change. These observations indicate that the spread and local expansion of the weed requires disturbance. Overall, the study shows that the initial colonization of the area by Euro-American settlers had little effect on the natural vegetation structure, while developments since the 1950s are strongly altering the natural vegetation cover.

scholarly journals Study of Land Use Change from 1997 To 2014 Using Landsat Data In Bangli Regency

2018 ◽  
Vol 2 (2) ◽  
pp. 89
Author(s):  
Nuranita Naningsi ◽  
Takahiro Osawa ◽  
I Nyoman Merit
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Fresh Water ◽  
Paddy Field ◽  
Rapid Development ◽  
Landsat 8 ◽  
Landsat Data ◽  
Data Set ◽  
Dry Land ◽  
Bare Land

Bangli Regency is one of Regency in the Bali Province. The total area of  Bangli Regency is 52,081 hectares (9.24%) of total area of Bali Province (563,666 ha). The Growth and the development of the region Bangli Regency the positive impacts on the economy of the community, and the negative impacts on the environment. Land use change is one of the negative issue of development Bangli Regency. This study conduted the calculation of land use change from 1997 to 2014 using Landsat data in Bangli Regency. Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 OLI/TIRS imageries were used to determine the land use map based, on using supervised classification method. The field data set the nine classes were classtuded based, on the classification were fresh water, bare land, forest, residential, bushes, irrigated paddy field, non irrigated paddy field, dry land and plantation. There results showed in land use changes from 1997 to 2014 that plantation increased (19,486.33 ha (36.89%)), and residential increased (1,872.00 ha (3.47%)), there is also a vast to reduction in dry land  (-10,868.90 ha (-21.21%)), forest (-6,333.34 ha (-12.24%)), irrigated paddy field (-1,619.50 ha (-3.17%)), bushes (-1,637.30 ha (-3.27%)), bare land (-63.00 ha (-0.17%)), non irrigated paddy field (-113.59 ha ( -0.26%)) and fresh water (-2.70 ha (-0.05%). The results accuracy rate was 89.45%. Anslyse of land use showed that the significant decrease of plantation area in Bangli Regency hill due to rapid development of infrastrusture of tourism and extensive residential area has increased particularly in sub district of the Kintamani District.

Determination of Drought Threshold for Agricultural Land-use using Satellite Image Analysis Techniques

2020 ◽  
Author(s):  
Jieun Kim ◽  
Jaehyung Yu ◽  
Sang Kee Seo ◽  
Jin-Hee Baek ◽  
Byung Chil Jeon
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Near Infrared ◽  
Agricultural Land ◽  
Irrigation Management ◽  
Satellite Image ◽  
Agricultural Drought ◽  
Agricultural Land Use ◽  
Landsat 8 ◽  
Eastern Area

<p>The climate change causes major problems in natural disasters such as storms and droughts and has significant impacts on agricultural activities. Especially, global warming changed crops cultivated causing changes in agricultural land-use, and droughts along with land-use change accompanied serious problems in irrigation management. Moreover, it is very problematic to detect drought impacted areas with field survey and it burdens irrigation management. In South Korea, drought in 2012 occurred in western area while 2015 drought occurred in eastern area. The drought cycle in Korea is irregular but the drought frequency has shown an increasing pattern. Remote sensing approaches has been used as a solution to detect drought areas in agricultural land-use and many approaches has been introduced for drought monitoring. This study introduces remote sensing approaches to detect agricultural drought by calculation of local threshold associated with agricultural land-use. We used Landsat-8 satellite images for drought and non-drought years, and Vegetation Health Index(VHI) was calculated using red, near-infrared, and thermal-infrared bands. The comparative analysis of VHI values for the same agricultural land-use between drought year and non-drought year derived the threshold values for each type of land-use. The results showed very effective detection of drought impacted areas showing distinctive differences in VHI value distributions between drought and non-drought years.</p>

scholarly journals NDVI Based Assessment of Land Cover Changes Using Remote Sensing and GIS (A case study of Srinagar district, Kashmir)

2020 ◽  
Author(s):  
Perminder Singh ◽  
Ovais Javeed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Spectral Signature ◽  
Landsat 8 ◽  
Thematic Mapping

Normalized Difference Vegetation Index (NDVI) is an index of greenness or photosynthetic activity in a plant. It is a technique of obtaining  various features based upon their spectral signature  such as vegetation index, land cover classification, urban areas and remaining areas presented in the image. The NDVI differencing method using Landsat thematic mapping images and Landsat oli  was implemented to assess the chane in vegetation cover from 2001to 2017. In the present study, Landsat TM images of 2001 and landsat 8 of 2017 were used to extract NDVI values. The NDVI values calculated from the satellite image of the year 2001 ranges from 0.62 to -0.41 and that of the year 2017 shows a significant change across the whole region and its value ranges from 0.53 to -0.10 based upon their spectral signature .This technique is also  used for the mapping of changes in land use  and land cover.  NDVI method is applied according to its characteristic like vegetation at different NDVI threshold values such as -0.1, -0.09, 0.14, 0.06, 0.28, 0.35, and 0.5. The NDVI values were initially computed using the Natural Breaks (Jenks) method to classify NDVI map. Results confirmed that the area without vegetation, such as water bodies, as well as built up areas and barren lands, increased from 35 % in 2001 to 39.67 % in 2017.Key words: Normalized Difference Vegetation Index,land use/landcover, spectral signature 

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