scholarly journals A LONG-TERM LAND COVER AND LAND USE MAPPING METHODOLOGY FOR THE ANDEAN AMAZON

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 373-378
Author(s):  
M. O. Borja ◽  
R. Camargo ◽  
N. Moreno ◽  
E. Turpo ◽  
S. Villacis
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Large Scale ◽  
Methodological Approach ◽  
Remote Sensing Data ◽  
The Novel ◽  
Water Index ◽  
Small Water ◽  
The Andes ◽  
Fractional Abundance

Abstract. The data developed by the MapBiomas Amazon initiative ( http://amazonia.mapbiomas.org/ ) led by the Amazon Geo-referenced Socio-environmental Information Network’s (RAISG) is of unprecedented spatial and temporal resolution for the Andes region. It’s comprised by a series of annual maps for the years 2000 to 2017 that allow to monitor the extent of transformation in this region using a single regional methodological approach. Several variables were included to solve Andes-specific methodological challenges and they represent adaptations of RAISG’s Amazonian methodology to the Andean region. Among such, is the use of the novel NDFIb index (Turpo, 2018), an adaptation of the NDFI index that aims at mapping Andean Wetlands. Glaciers identification was aided by the fractional abundance of snow (Turpo, 2018), as well as small water bodies identification with McFeeters (1996) NDWI water index. This experience unfolds promising accessibility to novel land cover and land use regional reconstructions and comparisons possible only by the use of large-scale cloud-computing data processing tools, open source technology, spatially and temporally comprehensive remote sensing data, along with RAISG’s standardized protocols and frameworks.

scholarly journals Conservation Measures for Improving Land Use and Land Cover in Dalvoy Lake Environs of Mysore City

2021 ◽  
Vol 10 (1) ◽  
pp. 173-177
Author(s):  
Akshatha N* ◽  
Shankar B
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Remote Sensing Data ◽  
Living Condition ◽  
Water Bodies ◽  
Large Cities ◽  
Small Water ◽  
The People ◽  
Erdas Imagine ◽  
The City

In recent years of Indian urbanization, the structure of large cities is undergoing rapid land use and land cover changes in lake environs, particularly in Mysore. Mysore is one of the fastest growing tier II cities, located in southern part of Karnataka. The city comprises of several large and small water bodies viz, Karanji Lake, Dalvoy Lake, Kukkarahalli Lake and Devanoor Lake. These lakes play an important role in recharging ground water, regulates microclimate, home for flora and fauna, recreational place for each neighborhood involving in community participation, improve aesthetic of the city and finally influence living condition of the people. Due to rapid transformation of land use and landcover in Mysore has resulted in degradation of water bodies. Dalvoy Lake is one of the major Lakes in Mysore City and it is deteriorating as a result of land use change, growth of industries and urbanization pressures. The total catchment area of Dalvoy Lake is 2165 acres. According to sixth sustainable development goals (clean water and sanitation) targets to protect and restore water-related ecosystems, including wetlands, rivers, and lakes. This paper deals with land use and landcover changes and its analyzing around Dalvoy Lake and its catchment using Remote sensing data and ERDAS imagine software and propose sustainable strategies for environmental improvement and management of the lake.

scholarly journals Environmental Differences between Migratory and Resident Ungulates—Predicting Movement Strategies in Rocky Mountain Mule Deer (Odocoileus hemionus) with Remotely Sensed Plant Phenology, Snow, and Land Cover

2019 ◽  
Vol 11 (17) ◽  
pp. 1980
Author(s):  
Benjamin Robb ◽  
Qiongyu Huang ◽  
Joseph Sexton ◽  
David Stoner ◽  
Peter Leimgruber
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Snow Cover ◽  
Large Scale ◽  
Mule Deer ◽  
Life History Strategy ◽  
Odocoileus Hemionus ◽  
Remotely Sensed ◽  
Land Use Impacts ◽  
Human Land Use

Migration is a valuable life history strategy for many species because it enables individuals to exploit spatially and temporally variable resources. Globally, the prevalence of species’ migratory behavior is decreasing as individuals forgo migration to remain resident year-round, an effect hypothesized to result from anthropogenic changes to landscape dynamics. Efforts to conserve and restore migrations require an understanding of the ecological characteristics driving the behavioral tradeoff between migration and residence. We identified migratory and resident behaviors of 42 mule deer (Odocoileus hemionus) based on GPS locations and correlated their locations to remotely sensed indicators of forage quality, land cover, snow cover, and human land use. The model classified mule deer seasonal migratory and resident niches with an overall accuracy of 97.8% and cross-validated accuracy of 81.2%. The distance to development was the most important variable in discriminating in which environments these behaviors occur, with resident niche space most often closer to developed areas than migratory niches. Additionally, snow cover in December was important for discriminating summer migratory niches. This approach demonstrates the utility of niche analysis based on remotely sensed environmental datasets and provides empirical evidence of human land use impacts on large-scale wildlife migrations.

Tracking the Land Use/Land Cover Change in an Area with Underground Mining and Reforestation via Continuous Landsat Classification

2019 ◽  
Vol 11 (14) ◽  
pp. 1719 ◽  
Author(s):  
Jiaxin Mi ◽  
Yongjun Yang ◽  
Shaoliang Zhang ◽  
Shi An ◽  
Huping Hou ◽  
...  
Keyword(s):  
Land Use ◽  
Random Forest ◽  
Land Cover ◽  
Large Scale ◽  
Underground Mining ◽  
Mining Area ◽  
Random Forest Classifier ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Mining Areas

Understanding the changes in a land use/land cover (LULC) is important for environmental assessment and land management. However, tracking the dynamic of LULC has proved difficult, especially in large-scale underground mining areas with extensive LULC heterogeneity and a history of multiple disturbances. Additional research related to the methods in this field is still needed. In this study, we tracked the LULC change in the Nanjiao mining area, Shanxi Province, China between 1987 and 2017 via random forest classifier and continuous Landsat imagery, where years of underground mining and reforestation projects have occurred. We applied a Savitzky–Golay filter and a normalized difference vegetation index (NDVI)-based approach to detect the temporal and spatial change, respectively. The accuracy assessment shows that the random forest classifier has a good performance in this heterogeneous area, with an accuracy ranging from 81.92% to 86.6%, which is also higher than that via support vector machine (SVM), neural network (NN), and maximum likelihood (ML) algorithm. LULC classification results reveal that cultivated forest in the mining area increased significantly after 2004, while the spatial extent of natural forest, buildings, and farmland decreased significantly after 2007. The areas where vegetation was significantly reduced were mainly because of the transformation from natural forest and shrubs into grasslands and bare lands, respectively, whereas the areas with an obvious increase in NDVI were mainly because of the conversion from grasslands and buildings into cultivated forest, especially when villages were abandoned after mining subsidence. A partial correlation analysis demonstrated that the extent of LULC change was significantly related to coal production and reforestation, which indicated the effects of underground mining and reforestation projects on LULC changes. This study suggests that continuous Landsat classification via random forest classifier could be effective in monitoring the long-term dynamics of LULC changes, and provide crucial information and data for the understanding of the driving forces of LULC change, environmental impact assessment, and ecological protection planning in large-scale mining areas.

Wildfires in Europe: the role of land use/land cover changes

2020 ◽  
Author(s):  
Joana Parente ◽  
Marj Tonini ◽  
Zoi Stamou ◽  
Nikos Koutsias ◽  
Mário Pereira
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Methodological Approach ◽  
Environmental Drivers ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Climate Conditions ◽  
European Forest ◽  
Burnt Areas ◽  
Land Cover Maps

<p>Wildfire (WF) has the potential to occur in more than 30% of the worldwide land area, in many different biomes/ecosystems/land cover types, where it is controlled mainly by the environmental drivers such as vegetation structure, meteorological/climate conditions, and human activities. On the other hand, land use/land cover changes (LULCC) are one of the most important global alterations of the environment. In the last decades, Europe registered significant-high fire incidence and LULCC between all land cover classes. In the 2000 – 2018 period, according to the European Forest Fire Information System (EFFIS), Europe was affected by 18 882 WFs which burned 6 887,713 ha. According to CORINE land cover maps, the observed LULCC area in Europe for the same period was of 23,510,075 ha. Recent studies suggested that regional LULCC in the last decades promoted the occurrence of more and larger WF, in some European regions. Therefore, the main objectives of this study were to assessed the LULCC in and around burnt areas (BAs) during the 2000–2018 period. This study benefits from the use of reliable CORINE inventories and EFFIS BA product. A geospatial methodological approach was implemented to identify and quantify LULCC and to characterize the relationship between LULCC and WFs in Europe. This research provides a detailed characterization of the LULCC in and around BAs in Europe, and attempts to contribute to a better management of the landscape, urbanization and wildland-urban interface to reduce related losses in the natural and human system including losses of life, property and assets.</p>

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