scholarly journals Land-cover change research at the U.S. Geological Survey-assessing our nation's dynamic land surface

Fact Sheet ◽  
2011 ◽  
Author(s):  
Tamara S. Wilson
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Geological Survey ◽  
The U.S

scholarly journals Hotter Drought Escalates Tree Cover Declines in Blue Oak Woodlands of California

2021 ◽  
Vol 3 ◽  
Author(s):  
Francis K. Dwomoh ◽  
Jesslyn F. Brown ◽  
Heather J. Tollerud ◽  
Roger F. Auch
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Climatic Variability ◽  
Tree Cover ◽  
Quercus Douglasii ◽  
Oak Woodlands ◽  
Vegetation Communities ◽  
Blue Oak ◽  
Climate Risks

California has, in recent years, become a hotspot of interannual climatic variability, recording devastating climate-related disturbances with severe effects on tree resources. Understanding the patterns of tree cover change associated with these events is vital for developing strategies to sustain critical habitats of endemic and threatened vegetation communities. We assessed patterns of tree cover change, especially the effects of the 2012–2016 drought within the distribution range of blue oak (Quercus douglasii), an endemic tree species to California with a narrow geographic extent. We utilized multiple, annual land-cover and land-surface change products from the U.S. Geological Survey (USGS) Land Change Monitoring, Assessment and Projection (LCMAP) project along with climate and wildfire datasets to monitor changes in tree cover state and condition and examine their relationships with interannual climate variability between 1985 and 2016. Here, we refer to a change in tree cover class without a land-cover change to another class as “conditional change.” The unusual drought of 2012–2016, accompanied by anomalously high temperatures and vapor pressure deficit, was associated with exceptional spikes in the amount of both fire and non-fire induced tree cover loss and tree cover conditional change, especially in 2015 and 2016. Approximately 1,266 km2 of tree cover loss and 617 km2 of tree cover conditional change were recorded during that drought. Tree cover loss through medium to high severity fires was especially large in exceptionally dry and hot years. Our study demonstrates the usefulness of the LCMAP products for monitoring the effects of climatic extremes and disturbance events on both thematic and conditional land-cover change over a multi-decadal period. Our results signify that blue oak woodlands may be vulnerable to extreme climate events and changing wildfire regimes. Here, we present early evidence that frequent droughts associated with climate warming may continue to affect tree cover in this region, while drought interaction with wildfires and the resulting feedbacks may have substantial influence as well. Consequently, efforts to conserve the blue oak woodlands, and potentially other vegetation communities in the Western United States, may benefit from consideration of climate risks as well as the potential for climate-fire and vegetation feedbacks.

The Decline In Summer Fallow In The Northern Plains Cooled Near-Surface Climate But Had Minimal Impacts On Precipitation

2021 ◽  
Author(s):  
Gabriel Bromley ◽  
Andreas F. Prein ◽  
Shannon E. Albeke ◽  
Paul C. Stoy
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Great Plains ◽  
Land Management ◽  
North American ◽  
Land Surface ◽  
Convective Cloud ◽  
Cloud Formation ◽  
Near Surface ◽  
Summer Fallow

Abstract Land management strategies can moderate or intensify the impacts of a warming atmosphere. Since the early 1980s, nearly 116,000 km2 of crop land that was once held in fallow during the summer is now planted in the northern North American Great Plains. To simulate the impacts of this substantial land cover change on regional climate processes, convection-permitting model experiments using the Weather Research and Forecasting (WRF) model were performed to simulate modern and historical amounts of summer fallow, and were extensively validated using multiple observational data products as well as eddy covariance tower observations. Results of these simulations show that the transition from summer fallow to modern land cover lead to ~1.5 °C cooler temperatures and decreased vapor pressure deficit by ~0.15 kPa during the growing season, which is consistent with observed cooling trends. The cooler and wetter land surface with vegetation leads to a shallower planetary boundary layer and lower lifted condensation level, creating conditions more conducive to convective cloud formation and precipitation. Our model simulations however show little widespread evidence of land surface changes effects on precipitation. The observed precipitation increase in this region is more likely related to increased moisture transport by way of the Great Plains Low Level Jet as suggested by the ERA5 reanalysis. Our results demonstrate that land cover change is consistent with observed regional cooling in the northern North American Great Plains but changes in precipitation cannot be explained by land management alone.

scholarly journals Training Data Selection for Annual Land Cover Classification for the Land Change Monitoring, Assessment, and Projection (LCMAP) Initiative

2020 ◽  
Vol 12 (4) ◽  
pp. 699 ◽  
Author(s):  
Qiang Zhou ◽  
Heather Tollerud ◽  
Christopher Barber ◽  
Kelcy Smith ◽  
Daniel Zelenak
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Classification Accuracy ◽  
Training Data ◽  
Land Change ◽  
Auxiliary Data ◽  
Surface Change ◽  
Land Cover Map ◽  
The U.S ◽  
Change Monitoring

The U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) initiative involves detecting changes in land cover, use, and condition with the goal of producing land change information to improve the understanding of the Earth system and provide insights on the impacts of land surface change on society. The change detection method ingests all available high-quality data from the Landsat archive in a time series approach to identify the timing and location of land surface change. Annual thematic land cover maps are then produced by classifying time series models. In this paper, we describe the optimization of the classification method used to derive the thematic land cover product. We investigated the influences of auxiliary data, sample size, and training from different sources such as the U.S. Geological Survey’s Land Cover Trends project and National Land Cover Database (NLCD 2001 and NLCD 2011). The results were evaluated and validated based on independent data from the training dataset. We found that refining the auxiliary data effectively reduced artifacts in the thematic land cover map that are related to data availability. We improved the classification accuracy and stability considerably by using a total of 20 million training pixels with a minimum of 600,000 and a maximum of 8 million training pixels per class within geographic windows consisting of nine Analysis Ready Data tiles (450 by 450 km2). Comparisons revealed that the NLCD 2001 training data delivered the best classification accuracy. Compared to the original LCMAP classification strategy used for early evaluation (e.g., Trends training data, 20,000 samples), the optimized classification strategy improved the annual land cover map accuracy by an average of 10%.

scholarly journals Research on Land Surface Thermal-Hydrologic Exchange in Southern China under Future Climate and Land Cover Scenarios

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Jianwu Yan ◽  
Baozhang Chen ◽  
Min Feng ◽  
John L. Innes ◽  
Guangyu Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Southern China ◽  
Future Climate ◽  
Land Surface Water ◽  
Hydrologic Exchange ◽  
Heat Exchanges

Climate change inevitably leads to changes in hydrothermal circulation. However, thermal-hydrologic exchanging caused by land cover change has also undergone ineligible changes. Therefore, studying the comprehensive effects of climate and land cover changes on land surface water and heat exchanges enables us to well understand the formation mechanism of regional climate and predict climate change with fewer uncertainties. This study investigated the land surface thermal-hydrologic exchange across southern China for the next 40 years using a land surface model (ecosystem-atmosphere simulation scheme (EASS)). Our findings are summarized as follows. (i) Spatiotemporal variation patterns of sensible heat flux (H) and evapotranspiration (ET) under the land cover scenarios (A2a or B2a) and climate change scenario (A1B) are unanimous. (ii) BothHand ET take on a single peak pattern, and the peak occurs in June or July. (iii) Based on the regional interannual variability analysis,Hdisplays a downward trend (10%) and ET presents an increasing trend (15%). (iv) The annual averageHand ET would, respectively, increase and decrease by about 10% when woodland converts to the cultivated land. Through this study, we recognize that land surface water and heat exchanges are affected greatly by the future climate change as well as land cover change.

scholarly journals Assessment and simulation of land use and land cover change impacts on the land surface temperature of Chaoyang District in Beijing, China

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9115 ◽  
Author(s):  
Muhammad Amir Siddique ◽  
Liu Dongyun ◽  
Pengli Li ◽  
Umair Rasool ◽  
Tauheed Ullah Khan ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Cover Change ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Rapid Urbanization ◽  
K Value ◽  
Vegetation Water ◽  
Landsat Satellite

Rapid urbanization is changing the existing patterns of land use land cover (LULC) globally, which is consequently increasing the land surface temperature (LST) in many regions. The present study is focused on estimating current and simulating future LULC and LST trends in the urban environment of Chaoyang District, Beijing. Past patterns of LULC and LST were identified through the maximum likelihood classification (MLC) method and multispectral Landsat satellite images during the 1990–2018 data period. The cellular automata (CA) and stochastic transition matrix of the Markov model were applied to simulate future (2025) LULC and LST changes, respectively, using their past patterns. The CA model was validated for the simulated and estimated LULC for 1990–2018, with an overall Kappa (K) value of 0.83, using validation modules in IDRISI software. Our results indicated that the cumulative changes in built-up to vegetation area were 74.61 km2 (16.08%) and 113.13 km2 (24.38%) from 1990 to 2018. The correlation coefficient of land use and land cover change (LULCC), including vegetation, water bodies and built-up area, had values of r =  − 0.155 (p > 0.005), −0.809 (p = 0.000), and 0.519 (p > 0.005), respectively. The results of future analysis revealed that there will be an estimated 164.92 km2 (−12%) decrease in vegetation area, while an expansion of approximately 283.04 km2 (6% change) will occur in built-up areas from 1990 to 2025. This decrease in vegetation cover and expansion of settlements would likely cause a rise of approximately ∼10.74 °C and ∼12.66 °C in future temperature, which would cause a rise in temperature (2025). The analyses could open an avenue regarding how to manage urban land cover patterns to enhance the resilience of cities to climate warming. This study provides scientific insights for environmental development and sustainability through efficient and effective urban planning and management in Beijing and will also help strengthen other research related to the UHI phenomenon in other parts of the world.

scholarly journals STUDY INFLUENCE OF LAND COVER CHANGE IN WETLAND AND VEGETATION ON LAND SURFACE TEMPERATURE

2021 ◽  
Vol 12 (2) ◽  
pp. 66-74
Author(s):  
Ricky Anak Kemarau ◽  
Oliver Valentine Eboy
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Cover Change ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Geographical Information ◽  
Gis Technology ◽  
Heat Effects ◽  
Urban Heat ◽  
The Impact

Wetlands are a vital component of land cover in reducing impacts caused by urban heat effects and climate change. Remote sensing technology provides historical data that can study the impact of development on the environment and local climate. The studies of wetland in reducing Land Surface Temperature (LST) in a tropical climate are still lacking. The objective of the study is to examine the influence of land cover change wetland and vegetation on land surface temperature between the years 1988 and 2019. First of all, step, pre-processing, namely geometric correction, atmosphere correction, and radiometric correction, were performed before retrieval of the LST dataset from thermal band Landsat 5 and 8. Then, Iso Cluster, unsupervised was chosen to produce the land cover map for 1988 and 2019. Geographical Information System (GIS) technology was utilized to determine changes to land cover and LST change between the years 1988 and 2019. With GIS technology, a study of the impact of wetland deforestation on local temperatures at a local scale was carried out. Next to that, correlations between LST and the wetland were analyzed. The results indicated the different land cover between the years 1988 and 2019. The areas of land cover for wetland and vegetation decrease and while area of urban increased. The land cover changed the influences of LST significantly in the study area. The LST increased with the decreasing in areas wetland areas for every 5-kilometer square (km²) wetland lost an increase in 1-degree Celsius of LS was estimated. The size of wetland influence on LST was significant. Wetland and vegetation function in reducing the urban heat island effect was vital in providing a comfortable environment to the Kuching population and indirectly reduce the demand for power energy.

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