scholarly journals Three Decades after: Landscape Dynamics in Different Colonisation Models Implemented in the Brazilian Legal Amazon

2021 ◽  
Vol 13 (22) ◽  
pp. 4581
Author(s):  
Valdir Moura ◽  
Ranieli dos Anjos de Souza ◽  
Erivelto Mercante ◽  
Jonathan Richetti ◽  
Jerry Adriani Johann
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Tropical Rainforest ◽  
Road Construction ◽  
Landscape Dynamics ◽  
The State ◽  
Secondary Forests ◽  
Rapid Loss ◽  
Landsat Images

Several colonisation projects were implemented in the Brazilian Legal Amazon in the 1970s and 1980s. Among these colonisation projects, the most prominent were those with the “fishbone” and “topographic” models. Within this scope, the settlements known as Anari and Machadinho stand out because they are contiguous areas with different models and structures of occupation and colonisation. The main objective of this work was to evaluate the dynamics of Land-Use and Land-Cover (LULC) in two different colonisation models, implanted in the State of Rondônia in the 1980s. The fishbone and topographic or Disorganised Multidirectional models were implemented in the Anari and Machadinho settlements, respectively. A 36-year time series of Landsat images (1984–2020) was used to evaluate the rates and trends in the LULC process in the different colonisation models. In the analysed models, a rapid loss of primary and secondary forests (anthropized areas) was observed, mainly due to the dynamics of its use, established by the Agriculture/Pasture relation with a heavy dependence on road construction. Understanding these two forms of occupation can help the future programs and guidelines of the Brazilian Legal Amazon and any tropical rainforest across the globe.

scholarly journals Application of Time Series Landsat Images to Examining Land-use/Land-cover Dynamic Change

2012 ◽  
Vol 78 (7) ◽  
pp. 747-755 ◽  
Author(s):  
Dengsheng Lu ◽  
Scott Hetrick ◽  
Emilio Moran ◽  
Guiying Li
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Dynamic Change ◽  
Land Use Land Cover ◽  
Landsat Images

scholarly journals Perceived Human-Induced Causes of Landslide in Chattogram Metropolitan Area in Bangladesh

2021 ◽  
Author(s):  
Zia Ahmed ◽  
A H M Belayeth Hussain ◽  
Mufti Nadimul Quamar Ahmed ◽  
Rafiul Alam ◽  
Hafiz-Al Rezoan ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Metropolitan Area ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Weak Soil ◽  
Landsat Images ◽  
Level Of Education ◽  
Steep Hill

Abstract This study investigates Land Use Land Cover changes in the Chattogram metropolitan area, the second largest city in Bangladesh. Using a questionnaire survey of 150 local inhabitants, the study explores perceived human-induced causes of landslides. Using time series Landsat images this study also analyzes Land Use Land Cover changes from 1990 to 2020. The analysis reveals built-up area extended rapidly during 1990 to 2020. In 1990, total built up area was 82.13km², which in 30 years, stood at 451.34km². Conversely, total vegetative area decreased rapidly. In 1990, total vegetation area was 364.31km², which reduced to 130.44 km² in 2020. The survey respondents identified extensive rainfall, hill cutting, steep hill, and weak soil texture as several reasons for landslide. Findings show that age and experience of facing landslide are two significant predictors to explain whether excessive hill cutting is solely responsible for landslide. Level of education and experience of facing landslide are statistically significant in explaining building infrastructure as solitary cause to landslide. Gender, age and income of the respondents significantly explain deforestation as the only responsible for landslide. Finally, gender, level of education, and income of the respondents significantly explain only excessive sand collection causes landslide.

scholarly journals Land Use and Land Cover Change Assessment in the Context of Flood Hazard in Lagos State, Nigeria

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1105
Author(s):  
Dorcas Idowu ◽  
Wendy Zhou
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Flood Hazard ◽  
The State ◽  
Land Cover Type ◽  
Lulc Change ◽  
Cover Type ◽  
Lulc Changes ◽  
Lagos State ◽  
Very High

Incessant flooding is a major hazard in Lagos State, Nigeria, occurring concurrently with increased urbanization and urban expansion rate. Consequently, there is a need for an assessment of Land Use and Land Cover (LULC) changes over time in the context of flood hazard mapping to evaluate the possible causes of flood increment in the State. Four major land cover types (water, wetland, vegetation, and developed) were mapped and analyzed over 35 years in the study area. We introduced a map-matrix-based, post-classification LULC change detection method to estimate multi-year land cover changes between 1986 and 2000, 2000 and 2016, 2016 and 2020, and 1986 and 2020. Seven criteria were identified as potential causative factors responsible for the increasing flood hazards in the study area. Their weights were estimated using a combined (hybrid) Analytical Hierarchy Process (AHP) and Shannon Entropy weighting method. The resulting flood hazard categories were very high, high, moderate, low, and very low hazard levels. Analysis of the LULC change in the context of flood hazard suggests that most changes in LULC result in the conversion of wetland areas into developed areas and unplanned development in very high to moderate flood hazard zones. There was a 69% decrease in wetland and 94% increase in the developed area during the 35 years. While wetland was a primary land cover type in 1986, it became the least land cover type in 2020. These LULC changes could be responsible for the rise in flooding in the State.

scholarly journals Historical Changes in Land Use and Suitability for Future Agriculture Expansion in Western Bahia, Brazil

2021 ◽  
Vol 13 (6) ◽  
pp. 1088
Author(s):  
Fernando Martins Pimenta ◽  
Allan Turini Speroto ◽  
Marcos Heil Costa ◽  
Emily Ane Dionizio
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Suitability ◽  
Agricultural Area ◽  
Landsat Images ◽  
Historical Changes ◽  
Cropland Area ◽  
Irrigated Area ◽  
Agriculture Expansion ◽  
Forest Code

Western Bahia is a critical region in Brazil’s recent expansion of agricultural output. Its outstanding increase in production is associated with strong growth in cropland area and irrigation. Here we present analyses of Western Bahian historical changes in land use, including irrigated area, and suitability for future agricultural expansion that respects permanent protection areas and the limits established by the Brazilian Forest Code in the Cerrado biome. For this purpose, we developed a land use and land cover classification database using a random forest classifier and Landsat images. A spatial multicriteria decision analysis to evaluate land suitability was performed by combining this database with precipitation and slope data. We demonstrate that between 1990 and 2020, the region’s total agricultural area increased by 3.17 Mha and the irrigated area increased by 193,480 ha. Throughout the region, the transition between the different classes of land use and land cover followed different pathways and was strongly influenced by land suitability and also appears to be influenced by Brazil’s new Forest Code of 2012. We conclude that even if conservation restrictions are considered, agricultural area could nearly double in the region, with expansion possible mostly in areas we classify as moderately suitable for agriculture, which are subject to climate hazards when used for rainfed crops but are otherwise fine for pastures and irrigated croplands.

scholarly journals IDENTIFYING LAND USE AND LAND COVER (LULC) CHANGE FROM 2000 TO 2025 DRIVEN BY TOURISM GROWTH: A STUDY CASE IN BALI

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1621-1627
Author(s):  
A. B. Rimba ◽  
T. Atmaja ◽  
G. Mohan ◽  
S. K. Chapagain ◽  
A. Arumansawang ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Growth Direction ◽  
Landsat 8 ◽  
Open Area ◽  
Landsat Images ◽  
Lulc Change ◽  
Tourism Activity ◽  
Accuracy Of Prediction

Abstract. Bali has been open to tourism since the beginning of the 20th century and is known as the first tourist destination in Indonesia. The Denpasar, Badung, Gianyar, and Tabanan (Sarbagita) areas experience the most rapid growth of tourism activity in Bali. This rapid tourism growth has caused land use and land cover (LULC) to change drastically. This study mapped the land-use change in Bali from 2000 to 2025. The land change modeller (LCM) tool in ArcGIS was employed to conduct this analysis. The images were classified into agricultural land, open area, mangrove, vegetation/forest, and built-up area. Some Landsat images in 2000 and 2015 were exploited in predicting the land use and land cover (LULC) change in 2019 and 2025. To measure the accuracy of prediction, Landsat 8 OLI images for 2019 were classified and tested to verify the LULC model for 2019. The Multi-Layer Perceptron (MLP) neural network was trained with two influencing factors: elevation and road network. The result showed that the built-up growth direction expanded from the Denpasar area to the neighbouring areas, and land was converted from agriculture, open area and vegetation/forest to built-up for all observation years. The built-up was predicted growing up to 43 % from 2015 to 2025. This model could support decision-makers in issuing a policy for monitoring LULC since the Kappa coefficients were more than 80% for all models.

scholarly journals Change Detection Analysis Using Surveying and Geoinformatics Techniques

2018 ◽  
Vol 2 (1) ◽  
pp. 28-38
Author(s):  
I. C. Onuigbo ◽  
J. Y. Jwat
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Research Work ◽  
Temporal Data ◽  
Landsat Images ◽  
Detection Analysis ◽  
Ground Truthing ◽  
Landsat Satellite ◽  
Geoinformatics Techniques

The study was on change detection using Surveying and Geoinformatics techniques. For effective research study, Landsat satellite images and Quickbird imagery of Minna were acquired for three periods, 2000, 2005 and 2012. The research work demonstrated the possibility of using Surveying and Geoinformatics in capturing spatial-temporal data. The result of the research work shows a rapid growth in built-up land between 2000 and 2005, while the periods between 2005 and 2012 witnessed a reduction in this class. It was also observed that change by 2020 may likely follow the trend in 2005 – 2012 all things being equal. Built up area may increase to 11026.456 hectares, which represent 11% change. The study has shown clearly the extent to which MSS imagery and Landsat images together with extensive ground- truthing can provide information necessary for land use and land cover mapping. Attempt was made to capture as accurate as possible four land use and land cover classes as they change through time.

scholarly journals Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine

2020 ◽  
Vol 12 (17) ◽  
pp. 2735 ◽  
Author(s):  
Carlos M. Souza ◽  
Julia Z. Shimbo ◽  
Marcos R. Rosa ◽  
Leandro L. Parente ◽  
Ane A. Alencar ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Time Series Data ◽  
Google Earth ◽  
Series Data ◽  
Data Series ◽  
Forest Conversion ◽  
Pixel Resolution ◽  
Historical Land Use

Brazil has a monitoring system to track annual forest conversion in the Amazon and most recently to monitor the Cerrado biome. However, there is still a gap of annual land use and land cover (LULC) information in all Brazilian biomes in the country. Existing countrywide efforts to map land use and land cover lack regularly updates and high spatial resolution time-series data to better understand historical land use and land cover dynamics, and the subsequent impacts in the country biomes. In this study, we described a novel approach and the results achieved by a multi-disciplinary network called MapBiomas to reconstruct annual land use and land cover information between 1985 and 2017 for Brazil, based on random forest applied to Landsat archive using Google Earth Engine. We mapped five major classes: forest, non-forest natural formation, farming, non-vegetated areas, and water. These classes were broken into two sub-classification levels leading to the most comprehensive and detailed mapping for the country at a 30 m pixel resolution. The average overall accuracy of the land use and land cover time-series, based on a stratified random sample of 75,000 pixel locations, was 89% ranging from 73 to 95% in the biomes. The 33 years of LULC change data series revealed that Brazil lost 71 Mha of natural vegetation, mostly to cattle ranching and agriculture activities. Pasture expanded by 46% from 1985 to 2017, and agriculture by 172%, mostly replacing old pasture fields. We also identified that 86 Mha of the converted native vegetation was undergoing some level of regrowth. Several applications of the MapBiomas dataset are underway, suggesting that reconstructing historical land use and land cover change maps is useful for advancing the science and to guide social, economic and environmental policy decision-making processes in Brazil.

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