Assessment of land cover changes in Lampedusa Island (Italy) using Landsat TM and OLI data

Mei, Alessandro; Manzo, Ciro; Fontinovo, Giuliano; Bassani, Cristiana; Allegrini, Alessia; Petracchini, Francesco

doi:10.1016/j.jafrearsci.2015.05.014

Cited by 40 publications

(18 citation statements)

References 37 publications

(2 reference statements)

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“…Transitions among forests and grasslands/meadows were considered evidences of both reforestation and deforestation or fragmentation. Conversions from natural areas (forests, grasslands/meadows) to semi-natural areas (agricultural areas) or impervious surfaces (roads, urban areas) are major information of environmental impact assessment and adaptation strategies [55].…”

Section: Discussionmentioning

confidence: 99%

Spatio-temporal Analysis of Land Cover Changes of Izmir Province of Turkey Using Landsat TM and OLI Imagery

Kara¹

2017

JGEESI

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Izmir province has experienced a tremendous increase in population such as other metropolitan cities of Turkey due to migration issues in last 30 years. Land use and land cover (LULC) of Izmir was affected from this unplanned population increase in province scale, natural ecosystems were destroyed by settlement, and agricultural activities of that doubled population. The aim of this study was determining LULC changes in Izmir and 30 m spatial resolution Landsat images were used as the main data along with geographic information systems (GIS) and remote sensing (RS) procedures. Satellite images from 1986 to 2015 were used to investigate LULC change patterns and a transition matrix was created. Object-based image classification technique was used for creating segments before classification. Segments, created by multi-resolution segmentation approach, were classified by visual analysis by the help of old maps, high-resolution imagery, Google Earth, and Landsat images. GIS-RS based hybrid method provided a very high accuracy (about 93%) in satellite image classification and maintained a transition matrix of changing dynamics. The results showed that increased impervious surfaces and decreased natural areas such as forests and meadows were the main features of LULC change in study area.

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Section: Discussionmentioning

confidence: 99%

Spatio-temporal Analysis of Land Cover Changes of Izmir Province of Turkey Using Landsat TM and OLI Imagery

Kara¹

2017

JGEESI

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“…The NDVI results in an index image with a range from -1 to +1. A healthy vegetation corresponds to values around 0.2 and 0.8, but only the scores equal to or greater than 0.5 represent forest vegetation with biomass concentration (ROUSE et al, 1974;MEI et al, 2015). The photochemical reflectance of the fragments was mapped based on the Photochemical Reflectance Index (PRI), identifying the areas of highest photosynthetic efficiency through the relationship between the absorption feature in the blue electromagnetic spectrum and the peak reflectance of the vegetation in the green electromagnetic spectrum, as proposed by Gamon (1992) where: PRI is the photochemical reflectance index; BLUE is the sensor band in the blue range; and GREEN is the sensor band in the green range.…”

Section: Spectral Evaluation Of Forest Fragmentsmentioning

confidence: 99%

Spatial Dynamics of Atlantic Forest Fragments in a River Basin

Lopes

Sousa

Souza

et al. 2019

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Considering the intrinsic relationship between vegetation and conservation of water resources, we evaluated the natural vegetation of an Atlantic Forest fragment through landscape metrics and spectral vegetation indices, indicating ways for its conservation in the Una river basin, Ibiúna, São Paulo, Brazil. We analyzed landscape metrics and the extraction of mean altitude, slope, and distance from the drainage network for each fragment based on the vectors of forest fragments in the river basin, using ArcGis 10.3. Normalized difference vegetation indices, photochemical production, and carbon flux were estimated by combining red, green, blue, and infrared spectral bands near the RapidEye satellite image. The results showed 197 fragments with sizes ranging from 1 to 306 hectares and irregularly shaped. The largest fragments are few in number, but account for 52% of the river basin's vegetation cover area. The vegetation presented high levels of biomass but moderate photosynthetic production, coinciding for a moderate carbon flux. The best scores were related to fragments at higher altitudes, in sloping areas next to drainage sites. Actions to conserve the fragments of larger areas and draw up environmental awareness measures should be encouraged, since high agricultural vocation may incite the reduction of these areas to increase economic production.

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“…The results of the study demonstrate the potential of the phenology-based paddy rice-mapping algorithm, through integrating MODIS and Landsat 8 OLI images, to map paddy rice fields in complex landscapes of paddy rice and natural wetland in the study area. The sole use of only Landsat time-series imagery (Dong et al, 2015;Mei et al, 2016;Xu et al, 2016;Zhu et al, 2016) or in combination with similar optical satellite sensors such as MODIS or Sentinel-2 has become common practice in agricultural applications in recent times (Novelli et al, 2016;Sibanda et al, 2016). Zhang et al (2017) recently mapped the annual paddy rice planting areas for China and India from 2000 to 2015 using time series MODIS data and a phenology-based rice algorithm.…”

Section: High Temporal Optical Satellite Sensors For Agriculturementioning

confidence: 99%

Applications of satellite ‘hyper-sensing’ in Chinese agriculture: Challenges and opportunities

Onojeghuo

Blackburn

Huang

et al. 2018

International Journal of Applied Earth Observation and Geoinfor

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Ensuring adequate food supplies to a large and increasing population continues to be the key challenge for China. Given the increasing integration of China within global markets for agricultural products, this issue is of considerable significance for global food security. Over the last 50 years, China has increased the production of its staple crops mainly by increasing yield per unit land area. However, this has largely been achieved through inappropriate agricultural practices, which have caused environmental degradation, with deleterious consequences for future agricultural productivity. Hence, there is now a pressing need to intensify agriculture in China using practices that are environmentally and economically sustainable. Given the dynamic nature of crops over space and time, the use of remote sensing technology has proven to be a valuable asset providing end-users in many countries with information to guide sustainable agricultural practices. Recently, the field has experienced considerable technological advancements reflected in the availability of 'hyper-sensing' (high spectral, spatial and temporal) satellite imagery useful for monitoring, modelling and mapping of agricultural crops. However, there still remains a significant challenge in fully exploiting such technologies for addressing agricultural problems in China. This review paper evaluates the potential contributions of satellite 'hyper-sensing' to agriculture in China and identifies the opportunities and challenges for future work. We perform a critical evaluation of current capabilities in satellite 'hyper-sensing' in agriculture with an emphasis on Chinese sensors. Our analysis draws on a series of in-depth examples based on recent and ongoing projects in China that are developing 'hyper-sensing' approaches for (i) measuring crop phenology parameters and predicting yields; (ii) specifying crop fertiliser requirements; (iii) optimising management responses to abiotic and biotic stress in crops; (iv) maximising yields while minimising water use in arid regions; (v) large-scale crop/cropland mapping; and (vi) management zone delineation. The paper concludes with a synthesis of these application areas in order to define the requirements for future research, technological innovation and knowledge exchange in order to deliver yield sustainability in China.

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Assessment of land cover changes in Lampedusa Island (Italy) using Landsat TM and OLI data

Cited by 40 publications

References 37 publications

Spatio-temporal Analysis of Land Cover Changes of Izmir Province of Turkey Using Landsat TM and OLI Imagery

Spatio-temporal Analysis of Land Cover Changes of Izmir Province of Turkey Using Landsat TM and OLI Imagery

Spatial Dynamics of Atlantic Forest Fragments in a River Basin

Applications of satellite ‘hyper-sensing’ in Chinese agriculture: Challenges and opportunities

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