scholarly journals Application of remote sensing and GIS technique to analyze the land-use change: the case of Phu Giao district, Binh Duong province

2017 ◽  
Vol 8 (3) ◽  
pp. 151-155
Author(s):  
Trong Dieu Hien Le ◽  
Gia Huan Pham ◽  
Tien Dat Nguyen ◽  
Xuan Truong Nguyen ◽  
Van Tat Pham
Keyword(s):  
Land Use ◽  
Maximum Likelihood ◽  
Water Body ◽  
Land Use Changes ◽  
Satellite Image ◽  
Image Data ◽  
Urban Land ◽  
United States Geological Survey ◽  
Perennial Plant ◽  
Multi Temporal

Digital change detection is a helpful technique using multi-temporal satellite image for analyzing landscape exchange. The objective of this study is an attempt to assess the land-use changes in Phu Giao district, Binh Duong province, Vietnam in the period of fifteen years, from 2001 to 2015. Landsat Thematic Mapper (TM) image data files of years from 2001 to 2015 were collected on website of United States Geological Survey (USGS). Then, the images supervised were classified into five classes including perennial plant, annual plant, barren and urban land, and water body using Maximum Likelihood classification method in ENVI 4.7, and mapped using ArcGIS. The results show that during fifteen years, perennial land and urban land have been increased by 39.83% and 10.32%, while annual land and water body have been decreased by 1.37% and 5.35% accordingly, respectively. Phát hiện thay đổi số hóa là một kỹ thuật hiệu quả sử dụng hình ảnh vệ tinh đa thời gian cho phân tích thay đổi cảnh quan. Bài viết này là một sự cố gắng nhằm đánh giá sự thay đổi đất sử dụng ở huyện Phú Giáo, tỉnh Bình Dương, Việt Nam trong khoảng thời gian mười lăm năm từ năm 2001 đến năm 2015. Các file dữ liệu ảnh Landsat TM của các năm từ 2001 đến 2015 đã được thu thập trên trang web nghiên cứu Địa chất Hoa Kỳ (USGS). Sau đó, các hình ảnh giám sát được phân thành năm lớp bao gồm cả cây trồng lâu năm, cây trồng hàng năm, đất đô thị cằn cỗi và vùng nước sử dụng phương pháp phân loại Maximum Likelihood trong ENVI 4.7, và lập bản đồ bằng sử dụng ArcGIS. Kết quả cho thấy rằng trong suốt mười lăm năm, diện tích đất trồng cây lâu năm, đất đô thị đã được tăng tương ứng là 39,83% và 10,32%, trong khi đất đai hàng năm và vùng nước giảm 1,37% và 5,35%.

Prediction Changes for Nonstationary Multi-Temporal Satellite Images using HMM

2017 ◽  
pp. 387-406
Author(s):  
Ali Ben Abbes ◽  
Imed Riadh Farah
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Satellite Image ◽  
Remotely Sensed ◽  
High Temporal Resolution ◽  
Remotely Sensed Data ◽  
Vegetation Monitoring ◽  
Area Of Interest ◽  
Multi Temporal ◽  
The Difference

Due to the growing advances in their temporal, spatial, and spectral resolutions, remotely sensed data continues to provide tools for a wide variety of environmental applications. This chapter presents the benefits and difficulties of Multi-Temporal Satellite Image (MTSI) for land use. Predicting land use changes using remote sensing is an area of interest that has been attracting increasing attention. Land use analysis from high temporal resolution remotely sensed images is important to promote better decisions for sustainable management land cover. The purpose of this book chapter is to review the background of using Hidden Markov Model (HMM) in land use change prediction, to discuss the difference on modeling using stationary as well as non-stationary data and to provide examples of both case studies (e.g. vegetation monitoring, urban growth).

Prediction Changes for Nonstationary Multi-Temporal Satellite Images Using HMM

2019 ◽  
pp. 1178-1197
Author(s):  
Ali Ben Abbes ◽  
Imed Riadh Farah
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Satellite Image ◽  
Remotely Sensed ◽  
High Temporal Resolution ◽  
Remotely Sensed Data ◽  
Vegetation Monitoring ◽  
Area Of Interest ◽  
Multi Temporal ◽  
The Difference

Due to the growing advances in their temporal, spatial, and spectral resolutions, remotely sensed data continues to provide tools for a wide variety of environmental applications. This chapter presents the benefits and difficulties of Multi-Temporal Satellite Image (MTSI) for land use. Predicting land use changes using remote sensing is an area of interest that has been attracting increasing attention. Land use analysis from high temporal resolution remotely sensed images is important to promote better decisions for sustainable management land cover. The purpose of this book chapter is to review the background of using Hidden Markov Model (HMM) in land use change prediction, to discuss the difference on modeling using stationary as well as non-stationary data and to provide examples of both case studies (e.g. vegetation monitoring, urban growth).

Remote Sensing for Land Use Mapping, Case of The Study Area: Urban Commune of Saada, Morocco

2021 ◽  
Vol 2 (1) ◽  
pp. 36-43
Author(s):  
Abdelouhed Farah ◽  
Ahmed Algouti ◽  
Abdellah Algouti ◽  
Essaadia Adaze ◽  
Mohammed Ifkirne
Keyword(s):  
Land Use ◽  
Urban Area ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Satellite Image ◽  
Image Data ◽  
Machine Learning Algorithms ◽  
Exponential Population Growth ◽  
Landsat Satellite ◽  
The City

The phenomenon of urban planning in favor of agricultural land on the outskirts of the city of Marrakech is in full expansion. The study of land use changes is of pivotal interest for the knowledge, management, monitoring, surveillance, and evaluation of our environment. Indeed, the city of Marrakech has been experiencing exponential population growth for several decades. This phenomenon has led to a dynamic urban characterized by the increase and densification of urbanized areas (e.g. buildings and infrastructures) which leads to the occupation of natural spaces. To this end, this study aims at highlighting the mapping and evolution of land use in the city of Marrakech from Landsat satellite image data (1989, 2005 and 2020) through the application of the Image classification using Machine Learning algorithms with the QGis Orfeo Toolbox, which facilitate the production of land use maps at three dates as well as an evolution map of the conurbation and also to quantify the obtained results. The directions of extension of the urban area were defined and thus demonstrate its impact on the agricultural land located in the peri-urban area.

scholarly journals Analysis on Impact of Land Use Change on Urban Waterlogging Caused by Floods

2021 ◽  
Vol 233 ◽  
pp. 03036
Author(s):  
Yanan Liu ◽  
Maohui Zheng ◽  
Nianqing Zhou
Keyword(s):  
Land Use ◽  
Rainfall Intensity ◽  
Land Use Changes ◽  
Satellite Image ◽  
Image Data ◽  
Storm Water Management Model ◽  
Topographic Features ◽  
Land Use Types ◽  
Drainage Pipe ◽  
Satellite Image Data

In recent years, ultra-high-intensity rainfall at home and abroad has caused frequent urban waterlogging disasters, posing a severe threat to people’s lives, property and city’s safety. Based on the satellite image data of Shanghai Waigaoqiao Free Trade Zone in different periods and the Storm Water Management Model (SWMM), this paper establishes a model of heavy rainfall under the underlying surface of a complex city, and analyses topographic features, different land use types, rainfall infiltration intensity and the characteristics of the drainage pipe network. The rainwater accumulation under different rainstorms and urbanization levels is simulated and analysed. The research results show that urban rainstorm accumulation is closely related to land use changes. With the increase of surface impermeability and rainfall intensity, the risk of waterlogging in the study area tends to increase: From 1994 to 2019, the construction area has increased from 2.5096km2 to 5.8662km2 in the study area. Compared with 1994, under the same rainfall conditions, the simulated flooding node and runoff coefficient in 2019 both increased significantly.

scholarly journals Correction to: The impacts of agricultural and urban land-use changes on plant and bird biodiversity in Costa Rica (1986–2014)

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Andrea Montero ◽  
Joan Marull ◽  
Enric Tello ◽  
Claudio Cattaneo ◽  
Francesc Coll ◽  
...  
Keyword(s):  
Land Use ◽  
Costa Rica ◽  
Land Use Changes ◽  
Urban Land ◽  
Urban Land Use

Urban land market and land-use changes in post-reform China: A case study of Beijing

2014 ◽  
Vol 124 ◽  
pp. 118-128 ◽  
Author(s):  
Jinfeng Du ◽  
Jean-Claude Thill ◽  
Richard B. Peiser ◽  
Changchun Feng
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Urban Land ◽  
Land Market ◽  
Urban Land Market

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.

Land Planning, Agro-forest Systems, and Implications for Ecosystem Services: Insights from Northern Italy

2021 ◽  
Author(s):  
Antonio Tomao ◽  
Barbara Ermini ◽  
Marcela Prokopov ◽  
Adriano Conte
Keyword(s):  
Land Use ◽  
Environmental Changes ◽  
Land Use Changes ◽  
Value Added ◽  
Temporal Analysis ◽  
Land Use Land Cover ◽  
Development Patterns ◽  
The North ◽  
Multi Temporal ◽  
Potential Impact

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.

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