scholarly journals Use of Satellite Data to Study the Impact of Land-Cover/Land-Use Change in Madison County Alabama

2009 ◽  
Vol 6 (4) ◽  
pp. 656-660
Author(s):  
Tomas Ayala-Silv ◽  
Garry Gordon ◽  
Robert Heath
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Satellite Data ◽  
Madison County ◽  
The Impact

scholarly journals Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES)

2019 ◽  
Vol 12 (1) ◽  
pp. 179-193 ◽  
Author(s):  
Chantelle Burton ◽  
Richard Betts ◽  
Manoel Cardoso ◽  
Ted R. Feldpausch ◽  
Anna Harper ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Dynamics ◽  
Fire Disturbance ◽  
Substantial Contribution ◽  
Surface Model ◽  
The Impact

Abstract. Disturbance of vegetation is a critical component of land cover, but is generally poorly constrained in land surface and carbon cycle models. In particular, land-use change and fire can be treated as large-scale disturbances without full representation of their underlying complexities and interactions. Here we describe developments to the land surface model JULES (Joint UK Land Environment Simulator) to represent land-use change and fire as distinct processes which interact with simulated vegetation dynamics. We couple the fire model INFERNO (INteractive Fire and Emission algoRithm for Natural envirOnments) to dynamic vegetation within JULES and use the HYDE (History Database of the Global Environment) land cover dataset to analyse the impact of land-use change on the simulation of present day vegetation. We evaluate the inclusion of land use and fire disturbance against standard benchmarks. Using the Manhattan metric, results show improved simulation of vegetation cover across all observed datasets. Overall, disturbance improves the simulation of vegetation cover by 35 % compared to vegetation continuous field (VCF) observations from MODIS and 13 % compared to the Climate Change Initiative (CCI) from the ESA. Biases in grass extent are reduced from −66 % to 13 %. Total woody cover improves by 55 % compared to VCF and 20 % compared to CCI from a reduction in forest extent in the tropics, although simulated tree cover is now too sparse in some areas. Explicitly modelling fire and land use generally decreases tree and shrub cover and increases grasses. The results show that the disturbances provide important contributions to the realistic modelling of vegetation on a global scale, although in some areas fire and land use together result in too much disturbance. This work provides a substantial contribution towards representing the full complexity and interactions between land-use change and fire that could be used in Earth system models.

scholarly journals Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA using multi-satellite data fusion

2016 ◽  
Author(s):  
Yun Yang ◽  
Martha C. Anderson ◽  
Feng Gao ◽  
Christopher R. Hain ◽  
Kathryn A. Semmens ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
North Carolina ◽  
Land Use Change ◽  
Land Cover ◽  
Water Use ◽  
Satellite Data ◽  
Fusion System ◽  
Time Step ◽  
Heterogeneous Landscapes

Abstract. As a primary flux in the global water cycle, evapotranspiration (ET) connects hydrologic and biological processes and is directly affected by water and land management, land use change and climate variability. Satellite remote sensing provides an effective means for diagnosing ET patterns over heterogeneous landscapes; however, limitations on the spatial and temporal resolution of satellite data, combined with the effects of cloud contamination, constrain the amount of detail that a single satellite can provide. In this study, we describe an application of a multi-sensor ET data fusion system over a mixed forested/agricultural landscape in North Carolina, USA during the growing season of 2013. The fusion system ingests ET estimates from a Two-Source Energy Balance (TSEB) model applied to thermal infrared remote sensing retrievals of land surface temperature from multiple satellite platforms: hourly geostationary satellite data at 4-km resolution, daily 1-km imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS), and bi-weekly Landsat thermal data sharpened to 30-m. These multiple datastreams are combined using the Spatial-Temporal Adaptive Reflectance Fusion Model (STARFM) to estimate daily ET at 30-m resolution to investigate seasonal water use behavior at the level of individual forest stands and land cover patches. A new method, also exploiting the STARFM algorithm, is used to fill gaps in the Landsat ET retrievals due to cloud cover and/or the scan-line corrector (SLC) failure on Landsat 7. The retrieved daily ET timeseries agree well with observations at two AmeriFlux eddy covariance flux tower sites in a managed pine plantation within the modeling domain: US-NC2 located in a mid-rotation (20 year old) loblolly pine stand, and US-NC3 located in a recently clear cut and replanted field site. Root mean square errors (RMSE) for NC2 and NC3 were 0.99 mm d-1 and 1.02 mm d-1, respectively, with mean absolute errors of approximately 29 % at the daily time step, 12 % at the monthly time step, and 3 % over the full study period at two flux tower sites. Analyses of water use patterns over the plantation indicate increasing seasonal ET with stand age for young to mid-rotation stands up to 20 years, but little dependence on age for older stands. An accounting of consumptive water use by major land cover classes representative of the modeling domain is presented, as well as relative partitioning of ET between evaporation (E) and transpiration (T) components obtained with the TSEB. The study provides new insights about the effects of forest management and land use change on hydrological water balance, and the method developed has the potential to be used to routinely monitor hydrology and water use over heterogeneous landscapes using thermal remote sensing data.

scholarly journals Assessment of Deep Learning Techniques for Land Use Land Cover Classification in Southern New Caledonia

2021 ◽  
Vol 13 (12) ◽  
pp. 2257
Author(s):  
Guillaume Rousset ◽  
Marc Despinoy ◽  
Konrad Schindler ◽  
Morgan Mangeas
Keyword(s):  
Land Use ◽  
Deep Learning ◽  
Land Cover ◽  
Satellite Data ◽  
Data Augmentation ◽  
New Caledonia ◽  
Data Set ◽  
Detection Techniques ◽  
Learning Techniques ◽  
The Impact

Land use (LU) and land cover (LC) are two complementary pieces of cartographic information used for urban planning and environmental monitoring. In the context of New Caledonia, a biodiversity hotspot, the availability of up-to-date LULC maps is essential to monitor the impact of extreme events such as cyclones and human activities on the environment. With the democratization of satellite data and the development of high-performance deep learning techniques, it is possible to create these data automatically. This work aims at determining the best current deep learning configuration (pixel-wise vs semantic labelling architectures, data augmentation, image prepossessing, …), to perform LULC mapping in a complex, subtropical environment. For this purpose, a specific data set based on SPOT6 satellite data was created and made available for the scientific community as an LULC benchmark in a tropical, complex environment using five representative areas of New Caledonia labelled by a human operator: four used as training sets, and the fifth as a test set. Several architectures were trained and the resulting classification was compared with a state-of-the-art machine learning technique: XGboost. We also assessed the relevance of popular neo-channels derived from the raw observations in the context of deep learning. The deep learning approach showed comparable results to XGboost for LC detection and over-performed it on the LU detection task (61.45% vs. 51.56% of overall accuracy). Finally, adding LC classification output of the dedicated deep learning architecture to the raw channels input significantly improved the overall accuracy of the deep learning LU classification task (63.61% of overall accuracy). All the data used in this study are available on line for the remote sensing community and for assessing other LULC detection techniques.

scholarly journals Modeling change of Land use on Hydrological Response of River by Remedial Measures using Arc SWAT: Case of Weib Catchment, Ethiopia

2019 ◽  
Vol 8 (11) ◽  
pp. 2381-2390
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Assessment Tool ◽  
Base Flow ◽  
Coefficient Of Determination ◽  
Hydrological Response ◽  
Cultivated Land ◽  
Natural Ecosystems ◽  
The Impact

Ethiopia has altered natural ecosystems through experiencing a huge amount of land use change has effect on the hydrological condition. Therefore, this study was initiated to compare the past and potential future change of land use with its effect the hydrological response of the Weib catchment which is found in the upper Genale Dawa River basin which covers a total area of 7407.42km2. The Soil and Water Assessment Tool model was used to compare the impact of land use change on stream flow of the study area. The study was used model by using readily available spatial and temporal data and calibrated against measured discharge. The analysis of land use change has shown that the Settlement area has increased from 12.8% to 30.8%, cultivated land from 10.8% to 39.1% between 1986 and 2010, while area of Forest has reduced from 32.5% to 9.4 % and Grassland from 20.9% to 12.3%. The performance of the model was evaluated based on performance rating criteria, coefficient of determination, Nash and Sutcliff efficiency values for monthly runoff were 0.85 and 0.81during calibration, 0.88 and 0.87 during validation, respectively. The evaluation of the model response to changes indicated that the mean wet monthly flow for 2010 land cover enlarged by 40.7 % from 1986 land cover. Similarly, the 1986 land cover mean month flow was higher by 10% than the 1995 land cover flow for wet months. The dry average monthly flow was less by 45.2 %, for 2010 and 26 % for 1995 land covers when compared to that of 1986 land cover. The rapid conversion of Forest and Grassland cover to Urban and cultivated land resulted in higher peak flow and less base flow on Weib river hydrology.

scholarly journals MONITORING URBAN LAND COVER/LAND USE CHANGE IN ALGIERS CITY USING LANDSAT IMAGES (1987–2016)

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1083-1090 ◽  
Author(s):  
B. Bouchachi ◽  
Y. Zhong
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Environmental Sustainability ◽  
Urban Areas ◽  
Driving Forces ◽  
Urban Land ◽  
Support Vector ◽  
Urban Land Cover ◽  
The Impact

Monitoring the Urban Land Cover/Land Use change detection is important as one of the main driving forces of environmental change because Urbanization is the biggest changes in form of Land, resulting in a decrease in cultivated areas. Using remote sensing ability to solve land resources problems. The purpose of this research is to map the urban areas at different times to monitor and predict possible urban changes, were studied the annual growth urban land during the last 29 years in Algiers City. Improving the productiveness of long-term training in land mapping, were have developed an approach by the following steps: 1) pre-processing for improvement of image characteristics; 2) extract training sample candidates based on the developed methods; and 3) Derive maps and analyzed of Algiers City on an annual basis from 1987 to 2016 using a Supervised Classifier Support Vector Machine (SVMs). Our result shows that the strategy of urban land followed in the region of Algiers City, developed areas mostly were extended to East, West, and South of Central Regions. The urban growth rate is linked with National Office of Statistics data. Future studies are required to understand the impact of urban rapid lands on social, economy and environmental sustainability, it will also close the gap in data of urbanism available, especially on the lack of reliable data, environmental and urban planning for each municipality in Algiers, develop experimental models to predict future land changes with statistically significant confidence.

scholarly journals Impact of land-use land cover dynamics on runoff in Panchnoi River basin, North East India

GeoScape ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 19-29
Author(s):  
Monoj Kumar Jaiswal ◽  
Nurul Amin
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Use Change ◽  
Land Cover ◽  
River Basin ◽  
Alluvial Plain ◽  
Land Use Land Cover ◽  
Runoff Generation ◽  
Land Cover Dynamics ◽  
The Impact

Abstract Alteration of land-use land cover pattern causes severe consequences on the hydrological system by modifying the rainfall-runoff pattern in a region. The study aimed to investigate the impact of land-use land-cover dynamics on runoff generation in different geomorphic divisions of Panchnoi River basin. The study used the Soil Conservation Service-Curve Number method to estimate runoff generation in the Panchnoi River basin in a GIS platform. This study observed that the conversion of the land-use pattern in the geomorphic zones significantly enhances runoff. The Piedmont experience highest land-use change, where 64.17 km2 forest cover lost to cropland and built-up lands, leads to a notable increase in runoff generation, i.e. from 1 076 mm (52.82% of rainfall) in 1990 to 1 467 mm (70.46% of rainfall) in 2015. The Flood plain and New alluvial plain generates high runoff in the basin as it mostly occupied by human-induced land-uses, i.e. 1 444 mm (72.72% of rainfall) and 1 360 mm (71.70% of rainfall) respectively in 1990, which increase to 1588 mm (79.20%) and 1507 mm (78.69%) runoff respectively in 2015, due to alteration of cropland to built-up lands. In the Old alluvial plain, a marginal land-use change observed resulted in moderate growth in runoff from 1 272 mm (62.35%) to 1 404 mm (66.79%). The study indicates land-use land-cover change invokes to increase runoff generation can give rise severe environmental and economic problems in the river basin, through the occurrence of flashflood and soil erosion. Highlights for public administration, management and planning: • Evaluation of the impact of land-use land cover dynamics on runoff is essential for containing flash flood and water resource management on a basin scale. • Alteration of natural land covers has severe implications in the form of flood, soil erosion, and loss of biodiversity. • Enhanced runoff due to land-use dynamics reduces groundwater recharge rate that may cause drinking water scarcity in the dry season shortly.

scholarly journals The Change of Land Cover and Biocapacity of CO2 Gas Emission Absorption in Gresik Urban Area

2019 ◽  
Vol 1 (3) ◽  
pp. 3-14
Author(s):  
Achmad Ghozali ◽  
Fery Irfan Nurrahman ◽  
Eko Budi Santoso
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Urban Area ◽  
Land Cover Change ◽  
Gas Emission ◽  
Gas Emissions ◽  
Co2 Gas ◽  
The Impact

Gresik urban area is dominated by industrial, housing, trade and services activities. The growth of activities contributes to the land use change from green open spaces into built-up areas. The impact of land use change influence the level of air pollution and CO2 gas emission in Gresik urban area. The previous study briefly shows that this urban area produces 50.37% of the total CO2 gas emissions. The production of CO2 gas emissions should be controlled to reduce the impact of climate change in urban areas such as increasing urban temperature, hydrological cycle anomaly, drought, land degradation and other social and environmental issues. The green open space can recycle the CO2 gas emissions and can increase the absorption capacity of the CO2 gas emissions (bio-capacity). The land cover change for built-up area potentially reduces the absorption of CO2 gas emissions in Gresik urban area. Therefore the identification of the land cover change on CO2 emission absorption becomes an objective of this study. The preliminary study can formulate the strategic steps in the development of Gresik urban area that supports urban greenery and adaptive effort to respond the climate change. The study is conducted in two steps. The first step is to analysis the land cover change based on the Landsat satellite imagery analysis. The second step is to measure the dynamic change of the region's ability(bio-capacity) to absorb CO2 emissions by using ecological footprint analysis. The results show that Gresik urban area has a high development of developed land to the North area, Manyar Sub District. The growth of the developed land is more converting the fishpond land. The green areas in this regiontend to be influenced by farming activities which also convert into fishpond land. Bio-capacity of CO2 gas emission absorption increases from 2003 of 3.548 gha to 5.656 gha but the comparison between bio-capacity of CO2 gas emission absorption and developed land shows the declining tendency in each year. In 2003, the comparison score is 1.59 gha/ha of developed land. In 2014, the score is declining into 1.48 gha/ha or developed land.

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