Multi-temporal analysis of a mangrove ecosystem in Southeastern Brazil using object-based classification applied to IKONOS II data

Author(s):  
Adriano de Oliveira Vasconcelos ◽  
Luiz Landau ◽  
Fernando Pellon de Miranda
Author(s):  
Rokhis Komarudin ◽  
Agung Indrajit

Abstract.  The  objectives  of  this  research  were  to  develop  and  improve  methods  for determination  of  settlements  area  with  focus  on  synthetic  aperture  radar  (SAR)  data. Remote  sensing  settlement  classification  has  made  great  progress,  both  for  optical  and radar  data  as  well  for  their  fusion.  Yet,  in  radar  imagery,  settlement  classification  still contains  some  problems.  Several  studies  on  application  of  radar  imagery  have  been conducted  using  techniques  such  as  textural  analysis,  multi-temporal  analysis,  statistical model,  spatial  indexes,  and  object-based  classification.  Most  of  the  development  methods have several problems in the specific area especially in the tropical country. Several studies also  showed  that  settlement  classification  accuracies  were  just  below  60%.    This  was  not sufficient    enough  to  classify  settlement  areas  using  SAR  imagery.  Therefore,  in  this research, we proposed a new method i.e., the combination of the speckle divergence and the neighborhood  analysis.  The  proposed  method  was  applied  to  classify  settlement  area  in Cilacap  and  Padang  Districts  of  Indonesia.  The  results  showed  that  the  proposed  method produced a good accuracy i.e., 85.5% for Cilacap Districts and 78.1% for Padang Districts. 


2021 ◽  
Vol 12 ◽  
pp. 100536
Author(s):  
Erica Zanardo Oliveira-Andreoli ◽  
Mayra Cristina Prado de Moraes ◽  
Alexandre da Silva Faustino ◽  
Anaí Floriano Vasconcelos ◽  
Carlos Wilmer Costa ◽  
...  

2021 ◽  
Vol 13 (11) ◽  
pp. 2123
Author(s):  
Aaron Aeberli ◽  
Kasper Johansen ◽  
Andrew Robson ◽  
David Lamb ◽  
Stuart Phinn

Unoccupied aerial vehicles (UAVs) have become increasingly commonplace in aiding planning and management decisions in agricultural and horticultural crop production. The ability of UAV-based sensing technologies to provide high spatial (<1 m) and temporal (on-demand) resolution data facilitates monitoring of individual plants over time and can provide essential information about health, yield, and growth in a timely and quantifiable manner. Such applications would be beneficial for cropped banana plants due to their distinctive growth characteristics. Limited studies have employed UAV data for mapping banana crops and to our knowledge only one other investigation features multi-temporal detection of banana crowns. The purpose of this study was to determine the suitability of multiple-date UAV-captured multi-spectral data for the automated detection of individual plants using convolutional neural network (CNN), template matching (TM), and local maximum filter (LMF) methods in a geographic object-based image analysis (GEOBIA) software framework coupled with basic classification refinement. The results indicate that CNN returns the highest plant detection accuracies, with the developed rule set and model providing greater transferability between dates (F-score ranging between 0.93 and 0.85) than TM (0.86–0.74) and LMF (0.86–0.73) approaches. The findings provide a foundation for UAV-based individual banana plant counting and crop monitoring, which may be used for precision agricultural applications to monitor health, estimate yield, and to inform on fertilizer, pesticide, and other input requirements for optimized farm management.


Geomorphology ◽  
2019 ◽  
Vol 345 ◽  
pp. 106844 ◽  
Author(s):  
Sara Cucchiaro ◽  
Federico Cazorzi ◽  
Lorenzo Marchi ◽  
Stefano Crema ◽  
Alberto Beinat ◽  
...  

2021 ◽  
Vol 2 (2) ◽  
pp. 56-64
Author(s):  
Iqbal Eko Noviandi ◽  
Ramadhan Alvien Hanif ◽  
Hasanah Rahma Nur ◽  
Nandi

Indonesia is a developing country whose construction and development are centered on the island of Java, especially in West Java Province. Sukabumi City is one of the areas in West Java. The development of urban areas is expanding due to various human needs to carry out the construction of buildings. Remote sensing that can be used to store developments with multi-temporal analysis with materials is Landsat imagery from 2001 to 2020. The method used is the Normalized Difference Built-up Index (NDBI). The purpose of this study is to map the development of the built-up land from year to year and predict the following years. The results of the research on the significant changes in built-up land occurred between 2013-2020, while from 2001 to 2013 there was not much change. Based on the research results, the total growth of built-up land was 1.539% per year with a population growth rate of 1.4% per year. The results of the analysis show that the area of ​​land built in Sukabumi City in 2028 is 186,7194 km2 or has increased by 21,2808 km2 since 2020.


2018 ◽  
Vol 21 (2) ◽  
pp. 97
Author(s):  
Nurul Latifah ◽  
Sigit Febrianto ◽  
Hadi Endrawati ◽  
Muhammad Zainuri

Mapping of Classification and Analysis of Changes in Mangrove Ecosystem Using Multi-Temporal Satellite Images in Karimunjawa, Jepara, Indonesia  Mangrove ecosystem is one of the three ecosystem in the coastal area which has important ecological role in supporting marine life and fisheries resources. These important roles include spawning ground and nursery ground for various marine organisms. However, in the last decades, mangrove ecosystem has been undergoing significant degradation. The aim of this research is to quantify the changes of mangrove coverage and density in Karimunjawa as well as key-factors leading to the changes. Supervised classification method (83% accuracy and Kappa coefficient 0.73%) was applied to satellite images to identify the temporal changes in mangrove coverage. Mangrove density was quantified using NDVI algorithm and NIR-RED wavelength. The result shows that during three periods of observed data, changes in mangrove coverage were significant: 126.81 ha increase (1992 – 2003); 82.37 ha decrease (1992 – 2017); and 209.18 ha decrease (2003 – 2017). Mangrove density in most part of Karimunjawa belongs to the category of ‘low’ (NDVI value: -1 – 0.33). Key factors contributing to the decrease mangrove coverage are deforestation, natural phenomena, land conversion into fish ponds and hotels. The only increase in the year 1992 – 2003 was caused by high sedimentation level that allows more mangroves to grow. Overall, the methods in this research could be used as an approach to describe to effectively monitor the changes of mangrove coverage in an area as basic data for sustainable environmental management. Ekosistem mangrove merupakan salah satu dari tiga ekosistem pesisir yang memiliki peranan ekologis penting dalam mendukung kehidupan dan keberlangsungan dari sumberdaya perikanan.  Hal tersebut dikarenakan fungsi mangrove sebagai tempat memijah dan asuhan bagi banyak biota air. Beberapa dekade terakhir keberadaan dari ekosisitem mangrove mengalami degradasi yang sangat signifikan. Tujuan dari penelitian ini adalah untuk mengetahui perubahan luasan dan kerapatan mangrove dan mengidentifikasi faktor penyebabnya.  Metode analisa perubahan luasan mangrove menggunakan citra satelit multi temporal dengan dilakukan pembuatan klasifikasi menggunakan metode supervised classification dengan nilai akurasi total 83% dengan Kappa koefisien 0,73%.  Setelah terseleksi antara mangrove dan non mangrove maka dilakukan perhitungan kerapatan tajuk menggunakan algoritma NDVI dengan memanfaatkan panjang gelombang NIR dan RED.  Hasil analisa spasial dengan rentang 3 tahun berbeda didapatkan perubahan penurunan dan penambahan luasan mangrove terjadi secara signifikan: tahun 1992 – 2003 telah terjadi penambahan luasan sebesar 126,81 ha; tahun 1992–2017 terjadi perubahan luasan sebesar 82,37 ha;  tahun 2003–2017 terjadi perubahan luasan sebesar 209,18 ha.  Kerapatan mangrove di Karimunjawa sebagian besar tergolong kategori kerapatan jarang dengan nilai NDVI antara -1 – 0,33. Faktor utama penyebab penurunan luasan mangrove antara lain penebangan liar, faktor alam, perubahan fungsi lahan menjadi pertambakan dan perhotelan.  Penambahan luasan mangrove terjadi pada antara tahun1992 sampai 2003 hal tersebut disebabkan sedimentasi yang menumpuk di pantai dan sudah ditumbuhi oleh mangrove.  Secara keseluruhan metode ini dapat menggambarkan perubahan secara efektif serta hasilnya dapat dipergunakan untuk pemantauan dan perencanaan ekosistem mangrove di suatu wilayah. 


Author(s):  
Antonio Tomao ◽  
Barbara Ermini ◽  
Marcela Prokopov ◽  
Adriano Conte

Negative environmental changes generally addressed as ‘syndromes’ are evaluated in the context of Soil Degradation (SD) and interpreted by using a ‘Land-Use/Land Cover Changes’ (LULCCs) framework in order to disentangle ‘past trajectories’, ‘present patterns’, and ‘future changes’. This approach allows to discuss the potential impact on SD processes and it represents an informed basis for identifying measurable outcomes of SD. This study focuses on the case of Emilia Romagna, a region located in the North of Italy with high-value added agricultural productions. A multi-temporal analysis of land-use changes between 1954 and 2008 has been proposed, discussing the evolution of associated SD syndromes in Emilia Romagna. The contributing information have been used as a baseline for Sustainable Land Management (SLM) strategies. This framework of analysis provides useful tools to investigate and to monitor the effects of SD in the Mediterranean basin where several regions underwent common development patterns yelding global pathological symptoms of environmental degradation.


Sign in / Sign up

Export Citation Format

Share Document