Substantially Greater Carbon Emissions Estimated Based on Annual Land-Use Transition Data

Quantifying land-use and land-cover change (LULCC) effects on carbon sources and sinks has been very challenging because of the availability and quality of LULCC data. As the largest estuary in the United States, Chesapeake Bay is a rapidly changing region and is affected by human activities. A new annual land-use and land-cover (LULC) data product developed by the U.S. Geological Survey Land Change Monitoring and Analysis Program (LCMAP) from 2001 to 2011 was analyzed for transitions between agricultural land, developed land, grassland, forest land and wetland. The Land Use and Carbon Scenario Simulator was used to simulate effects of LULCC and ecosystem disturbance in the south of the Chesapeake Bay Watershed (CBW) on carbon storage and fluxes, with carbon parameters derived from the Integrated Biosphere Simulator. We found that during the study period: (1) areas of forest land, disturbed land, agricultural land and wetland decreased by 90, 82, 57, and 65 km2, respectively, but developed lands gained 293 km2 (29 km2 annually); (2) total ecosystem carbon stock in the CBW increased by 13 Tg C from 2001 to 2011, mainly due to carbon sequestration of the forest ecosystem; (3) carbon loss was primarily attributed to urbanization (0.224 Tg C·yr−1) and agricultural expansion (0.046 Tg C·yr−1); and (4) estimated carbon emissions and harvest wood products were greater when estimated with the annual LULC input. We conclude that a dense time series of LULCC, such as that of the LCMAP program, may provide a more accurate accounting of the effects of land use change on ecosystem carbon, which is critical to understanding long-term ecosystem carbon dynamics.

Download Full-text

Dynamics of forage and land cover changes in Teltele district of Borana rangelands, southern Ethiopia: using geospatial and field survey data

BMC Ecology ◽

10.1186/s12898-020-00320-8 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Yeneayehu Fenetahun ◽

Wang Yong-dong ◽

Yuan You ◽

Xu Xinwen

Keyword(s):

Land Use ◽

Land Cover ◽

Biomass Production ◽

Agricultural Land ◽

Southern Ethiopia ◽

Forest Land ◽

Lulc Change ◽

Grass Land ◽

Land Use Types ◽

Bare Land

Abstract Background The gradual conversion of rangelands into other land use types is one of the main challenges affecting the sustainable management of rangelands in Teltele. This study aimed to examine the changes, drivers, trends in land use and land cover (LULC), to determine the link between the Normalized Difference Vegetation Index (NDVI) and forage biomass and the associated impacts of forage biomass production dynamics on the Teltele rangelands in Southern Ethiopia. A Combination of remote sensing data, field interviews, discussion and observations data were used to examine the dynamics of LULC between 1992 and 2019 and forage biomass production. Results The result indicate that there is a marked increase in farm land (35.3%), bare land (13.8%) and shrub land (4.8%), while the reduction found in grass land (54.5%), wet land (69.3%) and forest land (10.5%). The larger change in land observed in both grassland and wetland part was observed during the period from 1995–2000 and 2015–2019, this is due to climate change impact (El-Niño) happened in Teltele rangeland during the year 1999 and 2016 respectively. The quantity of forage in different land use/cover types, grass land had the highest average amount of forage biomass of 2092.3 kg/ha, followed by wetland with 1231 kg/ha, forest land with 1191.3 kg/ha, shrub land with 180 kg/ha, agricultural land with 139.5 kg/ha and bare land with 58.1 kg/ha. Conclusions The significant linkage observed between NDVI and LULC change types (when a high NDVI value, the LULC changes also shows positive value or an increasing trend). In addition, NDVI value directly related to the greenness status of vegetation occurred on each LULC change types and its value directly linkage forage biomass production pattern with grassland land use types. 64.8% (grass land), 43.3% (agricultural land), 75.1% (forest land), 50.6% (shrub land), 80.5% (bare land) and 75.5% (wet land) more or higher dry biomass production in the wet season compared to the dry season.

Download Full-text

Accuracy, Bias, and Improvements in Mapping Crops and Cropland across the United States Using the USDA Cropland Data Layer

Remote Sensing ◽

10.3390/rs13050968 ◽

2021 ◽

Vol 13 (5) ◽

pp. 968 ◽

Cited By ~ 1

Author(s):

Tyler J. Lark ◽

Ian H. Schelly ◽

Holly K. Gibbs

Keyword(s):

United States ◽

Land Use ◽

Land Cover ◽

Agricultural Land ◽

The United States ◽

Error Rates ◽

Agricultural Landscapes ◽

Cropland Area ◽

Data Layer ◽

Cropland Data Layer

The U.S. Department of Agriculture’s (USDA) Cropland Data Layer (CDL) is a 30 m resolution crop-specific land cover map produced annually to assess crops and cropland area across the conterminous United States. Despite its prominent use and value for monitoring agricultural land use/land cover (LULC), there remains substantial uncertainty surrounding the CDLs’ performance, particularly in applications measuring LULC at national scales, within aggregated classes, or changes across years. To fill this gap, we used state- and land cover class-specific accuracy statistics from the USDA from 2008 to 2016 to comprehensively characterize the performance of the CDL across space and time. We estimated nationwide area-weighted accuracies for the CDL for specific crops as well as for the aggregated classes of cropland and non-cropland. We also derived and reported new metrics of superclass accuracy and within-domain error rates, which help to quantify and differentiate the efficacy of mapping aggregated land use classes (e.g., cropland) among constituent subclasses (i.e., specific crops). We show that aggregate classes embody drastically higher accuracies, such that the CDL correctly identifies cropland from the user’s perspective 97% of the time or greater for all years since nationwide coverage began in 2008. We also quantified the mapping biases of specific crops throughout time and used these data to generate independent bias-adjusted crop area estimates, which may complement other USDA survey- and census-based crop statistics. Our overall findings demonstrate that the CDLs provide highly accurate annual measures of crops and cropland areas, and when used appropriately, are an indispensable tool for monitoring changes to agricultural landscapes.

Download Full-text

Spatial Analysis of a Chesapeake Bay Sub-Watershed: How Land Use and Precipitation Patterns Impact Water Quality in the James River

Water ◽

10.3390/w13111592 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1592

Author(s):

Kristina A. Delia ◽

Christa R. Haney ◽

Jamie L. Dyer ◽

Varun G. Paul

Keyword(s):

Water Quality ◽

Land Use ◽

Land Cover ◽

Chesapeake Bay ◽

Quality Indicators ◽

Assessment Tool ◽

Residential Development ◽

Forest Land ◽

James River ◽

Water Quality Indicators

Changes in land cover throughout the Chesapeake Bay watershed, accompanied by variability in climate patterns, can impact runoff and water quality. A study was conducted using the Soil and Water Assessment Tool (SWAT) for the James River watershed in Virginia, the southernmost tributary of the Chesapeake Bay, from 1986 to 2018, in order to evaluate factors that affect water quality in the river. This research focuses on statistical analysis of land use, precipitation, and water quality indicators. Land cover changes derived from satellite imagery and geographic information system (GIS) tools were compared with water quality parameters throughout that timeframe. Marked decreases in forest land cover were observed throughout the watershed, as well as increased residential development. Our findings suggest strong links between land cover modification, such as residential development, and degraded water quality indicators such as nitrogen, phosphorus, and sediment. In addition, we note direct improvements in water quality when forest land areas are preserved throughout the watershed.

Download Full-text

Land Use/Land Cover Change Impact on Hydrological Process in the Upper Baro Basin, Ethiopia

Applied and Environmental Soil Science ◽

10.1155/2021/6617541 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Tewodros Getu Engida ◽

Tewodros Assefa Nigussie ◽

Abreham Berta Aneseyee ◽

John Barnabas

Keyword(s):

Land Use ◽

Land Cover ◽

Agricultural Land ◽

Swat Model ◽

The United States ◽

United States Geological Survey ◽

Hydrological Process ◽

Land Use Land Cover ◽

Validation Period ◽

The Impact

Understanding the hydrological process associated with Land Use/Land Cover (LU/LC) change is vital for decision-makers in improving human wellbeing. LU/LC change significantly affects the hydrology of the landscape, caused by anthropogenic activities. The scope of this study is to investigate the impact of LU/LC change on the hydrological process of Upper Baro Basin for the years 1987, 2002, and 2017. The Soil Water Assessment Tool (SWAT) model was used for the simulation of the streamflow. The required data for the SWAT model are soils obtained from the Food and Agriculture Organization; Digital Elevation Model (DEM) and LU/LC were obtained from the United States Geological Survey (USGS). The meteorological data such as Rainfall, Temperature, Sunshine, Humidity, and Wind Speeds were obtained from the Ethiopian National Meteorological Agency. Data on discharge were obtained from Ministry of Water, Irrigation and Electricity. Ecosystems are deemed vital. Landsat images were used to classify the LU/LC pattern using ERDAS Imagine 2014 software and the LU/LC were classified using the Maximum Likelihood Algorithm of Supervised Classification. The Sequential Uncertainty Fitting (SUFI-2) global sensitivity method within SWAT Calibration and Uncertainty Procedures (SWAT-CUP) was used to identify the most sensitive streamflow parameters. The calibration was carried out using observed streamflow data from 01 January 1990 to 31 December 2002 and a validation period from 01 January 2003 to 31 December 2009. LU/LC analysis shows that there was a drastic decrease of grassland by 15.64% and shrubland by 9.56% while an increase of agricultural land and settlement by 18.01% and 13.01%, respectively, for 30 years. The evaluation of the SWAT model presented that the annual surface runoff increased by 43.53 mm, groundwater flow declined by 27.58 mm, and lateral flow declined by 5.63 mm. The model results showed that the streamflow characteristics changed due to the LU/LC change during the study periods 1987–2017 such as change of flood frequency, increased peak flows, base flow, soil erosion, and annual mean discharge. Curve number, an available water capacity of the soil layer, and soil evaporation composition factor were the most sensitive parameters identified for the streamflow. Both the calibration and validation results disclosed a good agreement between measured and simulated streamflow. The performance of the model statistical test shows the coefficient of determination (R2) and Nash–Sutcliffe (NS) efficiency values 0.87 and 0.81 for calibration periods of 1990–2002 and 0.84 and 0.76 for the validation period of 2003 to 2009, respectively. Overall, LU/LC significantly affected the hydrological condition of the watershed. Therefore, different conservation strategies to maintain the stability and resilience of the ecosystem are vital.

Download Full-text

Exploring the Regional Dynamics of U.S. Irrigated Agriculture from 2002 to 2017

Land ◽

10.3390/land10040394 ◽

2021 ◽

Vol 10 (4) ◽

pp. 394

Author(s):

Dinesh Shrestha ◽

Jesslyn F. Brown ◽

Trenton D. Benedict ◽

Daniel M. Howard

Keyword(s):

Land Use ◽

Land Cover ◽

Vegetation Index ◽

Agricultural Land ◽

Crop Yields ◽

The United States ◽

Economic Incentives ◽

Irrigated Agriculture ◽

Periodic Patterns ◽

The U.S

The United States has a geographically mature and stable land use and land cover system including land used as irrigated cropland; however, changes in irrigation land use frequently occur related to various drivers. We applied a consistent methodology at a 250 m spatial resolution across the lower 48 states to map and estimate irrigation dynamics for four map eras (2002, 2007, 2012, and 2017) and over four 5-year mapping intervals. The resulting geospatial maps (called the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset or MIrAD-US) involved inputs from county-level irrigated statistics from the U.S. Department of Agriculture, National Agricultural Statistics Service, agricultural land cover from the U.S. Geological Survey National Land Cover Database, and an annual peak vegetation index derived from expedited MODIS satellite imagery. This study investigated regional and periodic patterns in the amount of change in irrigated agriculture and linked gains and losses to proximal causes and consequences. While there was a 7% overall increase in irrigated area from 2002 to 2017, we found surprising variability by region and by 5-year map interval. Irrigation land use dynamics affect the environment, water use, and crop yields. Regionally, we found that the watersheds with the largest irrigation gains (based on percent of area) included the Missouri, Upper Mississippi, and Lower Mississippi watersheds. Conversely, the California and the Texas–Gulf watersheds experienced fairly consistent irrigation losses during these mapping intervals. Various drivers for irrigation dynamics included regional climate fluctuations and drought events, demand for certain crops, government land or water policies, and economic incentives like crop pricing and land values. The MIrAD-US (Version 4) was assessed for accuracy using a variety of existing regionally based reference data. Accuracy ranged between 70% and 95%, depending on the region.

Download Full-text

Modeling Land Use and Land Cover Change: Using a Hindcast to Estimate Economic Parameters in gcamland v2.0

10.5194/gmd-2020-338 ◽

2020 ◽

Author(s):

Katherine V. Calvin ◽

Abigail Snyder ◽

Xin Zhao ◽

Marshall Wise

Keyword(s):

Land Use ◽

Land Use Change ◽

Land Cover ◽

Agricultural Production ◽

Agricultural Land ◽

Crop Yields ◽

Economic Models ◽

The United States ◽

Historical Period ◽

Large Set

Abstract. The world has experienced a vast increase in agricultural production since the middle of the last century. Agricultural land area has also increased at the expense of natural lands over this period, though at a lower rate than production. Future changes in land use and cover have important implications not only for agriculture but for energy, water use, and climate. However, these future changes are driven by a complex combination of uncertain socioeconomic, technological, and other factors. Estimates of future land use and land cover differ significantly across economic models of agricultural production, and efforts to evaluate these economic models over history have been limited. In this study, we use an economic model of land use, gcamland, to systematically explore a large set of model parameter perturbations and alternate methods for forming expectations about uncertain crop yields and prices. We run gcamland simulations with these parameter sets over the historical period in the United States to explore model fitness and to identify combinations that improve fitness. We find that an adaptive expectation approach minimizes the error between simulated outputs and observations, with parameters that suggest that for most crops landowners put a significant weight on previous information. Interestingly, for corn, where ethanol policies have led to a rapid growth in demand, the resulting parameters show that a larger weight is placed on more recent information. We conclude with the observation that historical modeling exercises such as this study are valuable both for understanding real world drivers of land use change and for informing modeling of future land use change.

Download Full-text

Land Use/Land Cover Change and Its Driving Forces in Shenkolla Watershed, South Central Ethiopia

The Scientific World JOURNAL ◽

10.1155/2021/9470918 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Belayneh Bufebo ◽

Eyasu Elias

Keyword(s):

Land Use ◽

Land Use Change ◽

Land Cover ◽

Agricultural Land ◽

Driving Forces ◽

Land Cover Changes ◽

Land Use Land Cover ◽

Forest Land ◽

Central Ethiopia ◽

South Central

Land use change is one of the challenges that aggravate environmental problems. Understanding the scope of land use change, driving forces, and consequences is very crucial for proper management of land resources. We investigated land use/land cover changes using remote sensing data (for the years 1973, 1995, and 2017), and field observation, household survey, key informant interview, and focus group discussion were used to determine the drivers and consequences of land use/land cover changes in Shenkolla watershed, south central Ethiopia. Unsupervised and supervised classification techniques were employed to get thematic information from satellite imagery. ArcGIS 10.3 and QGIS v 3.0 softwares were used to accomplish the analysis. The results disclosed that Shenkolla watershed has changed significantly during the past 4 decades between 1973 and 2017. This observed change indicates a reduction in forest land and an increase in agricultural land. Forest land was reduced from 29.51% in 1973 to 20.52% in 2017, but agricultural land was expanded from 70.49% in 1973 to 79.48% in 2017. Agricultural expansion, policy change and social unrest, population pressure, shortage of farm land, and biophysical factors were major driving forces of the LU/LC changes. Environmental implications such as climate change, biodiversity loss, scarcity of basic forest products, habitat alteration, decline in quality and availability of water, and crop yield reduction are the consequences of the LU/LC change. The expansion of agricultural land at the expense of forest cover in Shenkolla watershed has negative implications on the natural resources and the livelihood of local people. Hence, appropriate measures need to be employed to reduce the dramatic change in land use and to harmonize environmental conservation with human livelihood.

Download Full-text

Dynamics of forage and land cover changes in Teltele rangeland Southern, Ethiopia. Using geospatial and field survey data

10.21203/rs.3.rs-21275/v1 ◽

2020 ◽

Author(s):

Yeneayehu Fenetahun ◽

Wang Yong-dong ◽

Yuan You ◽

Xu Xinwen

Keyword(s):

Land Use ◽

Land Cover ◽

Biomass Production ◽

Agricultural Land ◽

Southern Ethiopia ◽

Forest Land ◽

Lulc Change ◽

Grass Land ◽

Land Use Types ◽

Bare Land

Abstract The gradual conversion of rangelands into other land use types is one of the main challenges affecting the sustainable management of rangelands in Teltele. This study aimed to examine the changes, drivers, trends in land use and land cover (LULC), to determine the link between the Normalized Difference Vegetation Index (NDVI) and forage biomass and the associated impacts of forage biomass production dynamics on the Teltele rangelands in Southern Ethiopia. A Combination of remote sensing data, field interviews, discussion and observations data were used to examine the dynamics of LULC between 1992–2019 and forage biomass production. The Results indicate that there is a marked increase in farm land (35.3%), bare land (13.8%) and shrub land (4.8%), while the reduction found in grass land (54.5%), wet land (69.3%) and forest land (10.5%). The larger change in land observed in both grassland and wetland part was observed during the period from 1995–2000 and 2015–2019, this is due to climate change impact (El-Niño) happened in Teltele rangeland during the year 1999 and 2016 respectively. The quantity of forage in different land use/cover types, grass land had the highest average amount of forage biomass of 2,092.3 kg/ha, followed by wetland with 1,231 kg/ha, forest land with 1,191.3 kg/ha, shrub land with 180 kg/ha, agricultural land with 139.5 kg/ha and bare land with 58.1 kg/ha. The significant linkage observed between NDVI and LULC change types (when a high NDVI value, the LULC changes also shows positive value or an increasing trend). In addition, NDVI value directly related to the greenness status of vegetation occurred on each LULC change types and its value directly linkage forage biomass production pattern with grassland land use types. 64.8% (grass land), 43.3% (agricultural land), 75.1% (forest land), 50.6% (shrub land), 80.5% (bare land) and 75.5% (wet land) more or higher dry biomass production in the wet season compared to the dry season.

Download Full-text

Dynamics of forage and land cover changes in Teltele rangeland Southern, Ethiopia. Using geospatial and field survey data

10.21203/rs.3.rs-21275/v2 ◽

2020 ◽

Author(s):

Yeneayehu Fenetahun ◽

Wang Yong-dong ◽

Yuan You ◽

Xu Xinwen

Keyword(s):

Land Use ◽

Land Cover ◽

Biomass Production ◽

Agricultural Land ◽

Southern Ethiopia ◽

Forest Land ◽

Lulc Change ◽

Grass Land ◽

Land Use Types ◽

Bare Land

Abstract Background: The gradual conversion of rangelands into other land use types is one of the main challenges affecting the sustainable management of rangelands in Teltele. This study aimed to examine the changes, drivers, trends in land use and land cover (LULC), to determine the link between the Normalized Difference Vegetation Index (NDVI) and forage biomass and the associated impacts of forage biomass production dynamics on the Teltele rangelands in Southern Ethiopia. A Combination of remote sensing data, field interviews, discussion and observations data were used to examine the dynamics of LULC between 1992-2019 and forage biomass production. Results: The result indicate that there is a marked increase in farm land (35.3%), bare land (13.8%) and shrub land (4.8%), while the reduction found in grass land (54.5%), wet land (69.3%) and forest land (10.5%). The larger change in land observed in both grassland and wetland part was observed during the period from 1995-2000 and 2015-2019, this is due to climate change impact (El-Niño) happened in Teltele rangeland during the year 1999 and 2016 respectively. The quantity of forage in different land use/cover types, grass land had the highest average amount of forage biomass of 2,092.3 kg/ha, followed by wetland with 1,231 kg/ha, forest land with 1,191.3 kg/ha, shrub land with 180kg/ha, agricultural land with 139.5 kg/ha and bare land with 58.1 kg/ha. Conclusions: The significant linkage observed between NDVI and LULC change types (when a high NDVI value, the LULC changes also shows positive value or an increasing trend). In addition, NDVI value directly related to the greenness status of vegetation occurred on each LULC change types and its value directly linkage forage biomass production pattern with grassland land use types. 64.8% (grass land), 43.3% (agricultural land), 75.1% (forest land), 50.6% (shrub land), 80.5% (bare land) and 75.5% (wet land) more or higher dry biomass production in the wet season compared to the dry season.

Download Full-text