An Improvement Method to Study the Spatio—Temporal Dynamics of Rancho Luna Beach´ Shoreline Applying Remote Sensing Tools

Author(s):  
Laura Castellanos Torres ◽  
Alain Muñoz Caravaca ◽  
Iván Figueroa Reyes ◽  
Eugenio Olalde Chang ◽  
Minerva Sánchez Llull ◽  
...  
Wetlands ◽  
2014 ◽  
Vol 34 (4) ◽  
pp. 787-801 ◽  
Author(s):  
Guilin Liu ◽  
Luocheng Zhang ◽  
Qian Zhang ◽  
Zipporah Musyimi ◽  
Qinghu Jiang

2019 ◽  
pp. 6731-6746 ◽  
Author(s):  
Amadou SALL ◽  
Assize TOURE ◽  
Alioune KANE ◽  
Awa Niang Fall

L’objectif de cette étude est d’établir à partir de la télédétection et des SIG, la dynamique spatio-temporelle des terres de cultures et d’explorer les futurs possibles de l’occupation du sol dans trois communes rurales de la région de Thiès (Fandène, Notto Diobass et Taiba Ndiaye). Une classification multidate des images landsat (1988, 2002 et 2014) a permis de quantifier les changements d’occupation des terres. Les résultats montrent que les zones de culture de Fandène sont passées entre 1988 et 2014 de 62% à 52% de la superficie totale de la commune. A l’opposée la commune de Taiba Ndiaye connait une expansion des zones de culture entre ces deux dates. Les changements enregistrés à Notto sont négligeables. Les simulations, faites sur la base des probabilités pour que la valeur d’une cellule i reste inchangée ou prenne la valeur d’une autre cellule j à l’horizon 2035, révèlent que les terres de culture de Fandène ont 69% de probabilité d’évoluer vers d’autres classes d’occupation du sol. ABSTRACT The objective of this study is to quantify from remote sensing and GIS the spatio temporal dynamics of cultivated land and explore possible futures of land use in three rural municipalities of Thies (Fandene, Notto Diobass, and Taiba Ndiaye). A multidate classification Landsat images (1988, 2002 et 2014) was used to quantify change in land cover. The results show that between 1988 and 2014 Fandene cropping areas have passed from 62% to 52% of the total area. At the opposite the commune of Taiba Ndiaye has known an expansion of cropping areas between these two dates. Minor changes are noted in Notto district. Simulations carried out on the basis of probabilities for a unit i to stay in the same cell or to be converted to another unit j in 2035, reveals that the probability for a cultivated land unit to be transformed into a another land cover category is high in Fandene (69 %).


2020 ◽  
Vol 168 ◽  
pp. 115162 ◽  
Author(s):  
Jie Xu ◽  
Shaohua Lei ◽  
Shun Bi ◽  
Yunmei Li ◽  
Heng Lyu ◽  
...  

2020 ◽  
Vol 12 (16) ◽  
pp. 2649
Author(s):  
Rafael Jiménez-Lao ◽  
Fernando J. Aguilar ◽  
Abderrahim Nemmaoui ◽  
Manuel A. Aguilar

The total area of plastic-covered crops of 3019 million hectares has been increasing steadily around the world, particularly in the form of crops maintained under plastic-covered greenhouses to control their environmental conditions and their growth, thereby increasing production. This work analyzes the worldwide research dynamics on remote sensing-based mapping of agricultural greenhouses and plastic-mulched crops throughout the 21st century. In this way, a bibliometric analysis was carried out on a total of 107 publications based on the Scopus database. Different aspects of these publications were studied, such as type of publication, characteristics, categories and journal/conference name, countries, authors, and keywords. The results showed that “articles” were the type of document mostly found, while the number of published documents has exponentially increased over the last four years, growing from only one document published in 2001 to 22 in 2019. The main Scopus categories relating to the topic analyzed were Earth and Planetary Sciences (53%), Computer Science (30%), and Agricultural and Biological Sciences (28%). The most productive journal in this field was “Remote Sensing”, with 22 documents published, while China, Italy, Spain, USA, and Turkey were the five countries with the most publications. Among the main research institutions belonging to these five most productive countries, there were eight institutions from China, four from Italy, one from Spain, two from Turkey, and one from the USA. In conclusion, the evolution of the number of publications on Remote Sensing of Agricultural Greenhouses and Plastic-Mulched Farmland found throughout the period 2000–2019 allows us to classify the subject studied as an emerging research topic that is attracting an increasing level of interest worldwide, although its relative significance is still very limited within the remote sensing discipline. However, the growing demand for information on the arrangement and spatio-temporal dynamics of this increasingly important model of intensive agriculture is likely to drive this line of research in the coming years.


2021 ◽  
Vol 12 (1) ◽  
pp. 026-031
Author(s):  
Snehalata Chaware ◽  
◽  
Nitin Patil ◽  
Gajanan Satpute ◽  
M. R. Meshram ◽  
...  

Land resources in India are under severe pressure and it is widely believed that marginal lands are being brought under cultivation. The extent of such changes needs to be known for better land use planning decisions. The present study illustrates the spatio-temporal dynamics of land use land cover of Nagjhari watershed in Bhatkuli block of Amravati, Maharashtra. Multi-temporal high resolution of Sentinel and Landsat satellite data were used to identify the significant positive and negative Land use land cover changes over a decade of 2007 to 2017. From 2007 to 2017, the ‘habitation’ class increased by 34% due to increasing population pressure. There was a decrease in ‘wasteland’ by 10.3%, while the area under ‘agriculture’ decreased by approximately 4.7% because of the increased area under ‘habitation’ and ‘water body’ at Nagjhari watershed. The biggest change occurred in land use class ‘water body’ increased sharply from 2013-17 by 62.7 per cent due to consequence of state policy of watershed development that was implemented after 2014. The forest class recorded maximum loss (18.3%) due to increasing population maximum land converted into habitation. The study shows overall classification accuracy as 85.46% and kappa coefficient (K) of 0.85. Kappa coefficient indicated that land use land cover assessment from remote sensing data show the best accuracy. These finding will help in deciding land use policy for future and its impact on land management of the watershed.


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