Cropland abandonment between 1986 and 2018 across the United States: spatiotemporal patterns and current land uses
The data that support the findings of this study are openly available at the following URL/DOI: https://atlas.glbrc.org/.
agriculture↗
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On vegetation mapping in Alaska using LANDSAT imagery with primary concerns for method and purpose in satellite image-based vegetation and land-use mapping and the visual interpretation of imagery in photographic format
The author has identified the following significant results. A simulated color infrared LANDSAT image covering the western Seward Peninsula was used for identifying and mapping vegetation by direct visual examination. The 1:1,083,400 scale print used was prepared by a color additive process using positive transparencies from MSS bands 4, 5, and 7. Seven color classes were recognized. A vegetation map of 3200 sq km area just west of Fairbanks, Alaska was made. Five colors were recognized on the image and identified to vegetation types roughly equivalent to formations in the UNESCO classification: orange - broadleaf deciduous forest; gray - needleleaf evergreen forest; light violet - subarctic alpine tundra vegetation; violet - broadleaf deciduous shrub thicket; and dull violet - bog vegetation.
Anderson, J. H.↗
Monitoring Land Use and Degradation Using Satellite and Airborne Data
Data on the Manix Basin Area of the Mojave Desert have been collected by AVIRIS, AIRSAR, and Landsat TM. The purpose of this study is to use a fusion of a time series of satellite data with airborne data to provide a context for the airborne data. The satellite data time series will additionally help to validate the observation and analysis of time-dependent processes observed in the single AVIRIS image of fields abandoned for different periods of time.
land↗
Land use and turbine technology influences on wind potential in the United States
As clean energy ambitions have expanded, critically evaluating renewable energy supply has become increasingly important to the energy research community and stakeholders. This study examines the onshore wind resource potential for the conterminous United States and its sensitivity to siting constraints and turbine technology innovation. We compile localized regulatory information and use high-resolution data to present multiple siting regimes covering relatively constrained to unconstrained potentials. Our efforts reveal high sensitivity to these variables and sizable uncertainty in the overall wind energy resource potential. Specifically, we find that siting constraints may shift the total capacity available to commercial wind energy by 2.3–15.1 TW. Furthermore, our results illustrate that technology advancement could require larger setbacks from buildings and infrastructure, reducing the total available capacity potential by 20% relative to estimates using current technology, but that this reduction is largely offset by increased generation such that the net effect on generation is 1%. The observed sensitivity to and uncertainty resulting from the variables we analyze suggest there is value in continued study and development of increasingly sophisticated approaches to characterizing wind resource potential.
14 SOLAR ENERGY↗
Synthesizing land use and demographic change in Southeast Asia’s smaller urbanized areas from 2000–2015
The majority of the human population now reside in urban areas today. The United Nations estimates that nearly half of all urban dwellers currently live in cities smaller than 500 000 persons and the majority of future urban growth will take place in Asia and Africa, likely in these smaller urban areas, not mega cities. Thus, understanding the factors that influence urban demographic trajectories in small urban areas is critical to address sustainable and equitable policy initiatives related to food security, changing climate hazard exposure, and economic opportunities. Here we focus on Southeast Asia—a region historically characterized by lower urban population proportions, yet with a rapidly shifting dynamic demographic—to examine correlates of demographic change among smaller cities. We combine two open-source satellite-informed datasets: GHS urban center database (2015) and age-sex gridded data from WorldPop to calculate socio-demographic characteristics to model drivers of change in annualized urban population growth from 2000–2015 for 505 urbanized places. We find a general pattern of decreasing dependency ratios as city-size increases for most urban areas in Southeast Asia. Higher rates of growth and more variation is observed for smaller cities—those with fewer than 300 000 persons, the lowest population limit for UN data on urbanization. When examining covariates of urban population growth, we find significant statistical associations of population change in smaller urbanized areas with climatic, economic, and land cover/land use variables, but with country-specific variations. Characterizing a continuum of urban population development in the context of changing environmental, economic and climate conditions has been an important sustainable development and equity issue for decades, but newer analysis of city-level drivers allows for systematic inquiry thus moving beyond total population counts for policy-relevant insight.
Southeast Asia synthesis↗
A Global Assessment of Long-Term Greening and Browning Trends in Pasture Lands Using the GIMMS LAI3g Dataset
Pasture ecosystems may be particularly vulnerable to land degradation due to the high risk of human disturbance (e.g., overgrazing, burning, etc.), especially when compared with natural ecosystems (non-pasture, non-cultivated) where direct human impacts are minimal. Using maximum annual leaf area index (LAImax) as a proxy for standing biomass and peak annual aboveground productivity, we analyze greening and browning trends in pasture areas from 1982-2008. Inter-annual variability in pasture productivity is strongly controlled by precipitation (positive correlation) and, to a lesser extent, temperature (negative correlation). Linear temporal trends are significant in 23% of pasture cells, with the vast majority of these areas showing positive LAImax trends. Spatially extensive productivity declines are only found in a few regions, most notably central Asia, southwest North America, and southeast Australia. Statistically removing the influence of precipitation reduces LAImax trends by only 13%, suggesting that precipitation trends are only a minor contributor to long-term greening and browning of pasture lands. No significant global relationship was found between LAImax and pasture intensity, although the magnitude of trends did vary between cells classified as natural versus pasture. In the tropics and Southern Hemisphere, the median rate of greening in pasture cells is significantly higher than for cells dominated by natural vegetation. In the Northern Hemisphere extra-tropics, conversely, greening of natural areas is 2-4 times the magnitude of greening in pasture areas. This analysis presents one of the first global assessments of greening and browning trends in global pasture lands, including a comparison with vegetation trends in regions dominated by natural ecosystems. Our results suggest that degradation of pasture lands is not a globally widespread phenomenon and, consistent with much of the terrestrial biosphere, there have been widespread increases in pasture productivity over the last 30 years.
ecosystems↗
The life cycle land use of natural gas-fired electricity in the US Western interconnection
Land presents a critical yet often overlooked constraint to energy development.
Dai, Tao↗
Greenhouse Gas Emissions from Food Systems: Building the Evidence Base
New estimates of greenhouse gas (GHG) emissions from the food system were developed at the country level, for the period 1990–2018, integrating data from crop and livestock production, on-farm energy use, land use and land use change, domestic food transport and food waste disposal. With these new country-level components in place, and by adding global and regional estimates of energy use in food supply chains, we estimate that total GHG emissions from the food system were about 16 CO2eq yr−1 in 2018, or one-third of the global anthropogenic total. Three quarters of these emissions, 13 Gt CO2eq yr−1, were generated either within the farm gate or in pre- and post-production activities, such as manufacturing, transport, processing, and waste disposal. The remainder was generated through land use change at the conversion boundaries of natural ecosystems to agricultural land. Results further indicate that pre- and post-production emissions were proportionally more important in developed than in developing countries, and that during 1990–2018, land use change emissions decreased while pre- and post-production emissions increased. We also report results on a per capita basis, showing world total food systems per capita emissions decreasing during 1990–2018 from 2.9 to 2.2 t CO2eq cap−1, with per capita emissions in developed countries about twice those in developing countries in 2018. Our findings also highlight that conventional IPCC categories, used by countries to report emissions in the National GHG inventory, systematically underestimate the contribution of the food system to total anthropogenic emissions. We provide a comparative mapping of food system categories and activities in order to better quantify food-related emissions in national reporting and identify mitigation opportunities across the entire food system.
greenhouse gas emissions↗
Robust Flight Path Determination for Mars Precision Landing Using Genetic Algorithms
This paper documents the application of genetic algorithms (GAs) to the problem of robust flight path determination for Mars precision landing. The robust flight path problem is defined here as the determination of the flight path which delivers a low-lift open-loop controlled vehicle to its desired final landing location while minimizing the effect of perturbations due to uncertainty in the atmospheric model and entry conditions. The genetic algorithm was capable of finding solutions which reduced the landing error from 111 km RMS radial (open-loop optimal) to 43 km RMS radial (optimized with respect to perturbations) using 200 hours of computation on an Ultra-SPARC workstation. Further reduction in the landing error is possible by going to closed-loop control which can utilize the GA optimized paths as nominal trajectories for linearization.
Bayard, David S.↗
Impacts of a Changing Climate and Land Use on Reindeer Pastoralism: Indigenous Knowledge and Remote Sensing
The Arctic is home to many indigenous peoples, including those who depend on reindeer herding for their livelihood, in one of the harshest environments in the world. For the largely nomadic peoples, reindeer not only form a substantial part of the Arctic food base and economy, but they are also culturally important, shaping their way of life, mythologies, festivals and ceremonies. Reindeer pastoralism or husbandry has been practiced by numerous peoples all across Eurasia for thousands of years and involves moving herds of reindeer, which are very docile animals, from pasture to pasture depending on the season. Thus, herders must adapt on a daily basis to find optimal conditions for their herds according to the constantly changing conditions. Climate change and variability plus rapid development are increasingly creating major changes in the physical environment, ecology, and cultures of these indigenous reindeer herder communities in the North, and climate changes are occurring significantly faster in the Arctic than the rest of the globe, with correspondingly dramatic impacts (Oskal, 2008). In response to these changes, Eurasian reindeer herders have created the EALAT project, a comprehensive new initiative to study these impacts and to develop local adaptation strategies based upon their traditional knowledge of the land and its uses - in targeted partnership with the science and remote sensing community - involving extensive collaborations and coproduction of knowledge to minimize the impacts of the various changes. This chapter provides background on climate and development challenges to reindeer husbandry across the Arctic and an overview of the EALAT initiative, with an emphasis on indigenous knowledge, remote sensing, Geographic Information Systems (GIS), and other scientific data to 'co-produce' datasets for use by herders for improved decision-making and herd management. It also provides a description of the EALAT monitoring data integration and sharing system and portal being developed for reindeer pastoralism. In addition, the chapter provides some preliminary results from the EALAT Project, including some early remote sensing research results.
Maynard, N. G.↗
Texture measurements from Seasat - SAR images for urban land use interpretation
Different grey tones in Seasat Synthetic Aperture Radar (SAR) images for the same type of urban land cover considerably impair the possibilities of establishing automatic classification procedures for these types of data. Since the orientation of the main features like street patterns and buildings with respect to the azimuth angle of the radar antenna is the crucial factor for the observed differences in grey tone, prior information on these elements and special processing of the data would be required to eliminate this effect. Another approach suggested in this paper is to make use of the textural information in the image rather than of its grey tone. For different study sites within the Los Angeles urbanized area texture measures could be derived which result in characteristic values for specific types of land cover and are largely independent of the azimuth angle effect. At the same time the results for the study area indicate an improvement of the overall separability for the different land cover types included in the analysis.
Fasler, F.↗
Feasibility of collision warning, precision approach and landing using GPS, volume 1
The use of GPS, with an appropriately configured data link, to enhance general aviation avionic functions encountered in the terminal area and on approach was investigated with emphasis on approach and landing guidance and collision warning. The feasibility of using differential GPS to obtain the precision navigation solutions required for landing was studied. Results show that the concept is sound. An experimental program was developed to demonstrate this concept. The collision avoidance/warning concept was examined through the development of a functional system specification.
Ruedger, W. H.↗
Development of a Land Use Mapping and Monitoring Protocol for the High Plains Region: A Multitemporal Remote Sensing Application
The purpose of this project was to develop a practical protocol that employs multitemporal remotely sensed imagery, integrated with environmental parameters to model and monitor agricultural and natural resources in the High Plains Region of the United States. The value of this project would be extended throughout the region via workshops targeted at carefully selected audiences and designed to transfer remote sensing technology and the methods and applications developed. Implementation of such a protocol using remotely sensed satellite imagery is critical for addressing many issues of regional importance, including: (1) Prediction of rural land use/land cover (LULC) categories within a region; (2) Use of rural LULC maps for successive years to monitor change; (3) Crop types derived from LULC maps as important inputs to water consumption models; (4) Early prediction of crop yields; (5) Multi-date maps of crop types to monitor patterns related to crop change; (6) Knowledge of crop types to monitor condition and improve prediction of crop yield; (7) More precise models of crop types and conditions to improve agricultural economic forecasts; (8;) Prediction of biomass for estimating vegetation production, soil protection from erosion forces, nonpoint source pollution, wildlife habitat quality and other related factors; (9) Crop type and condition information to more accurately predict production of biogeochemicals such as CO2, CH4, and other greenhouse gases that are inputs to global climate models; (10) Provide information regarding limiting factors (i.e., economic constraints of pumping, fertilizing, etc.) used in conjunction with other factors, such as changes in climate for predicting changes in rural LULC; (11) Accurate prediction of rural LULC used to assess the effectiveness of government programs such as the U.S. Soil Conservation Service (SCS) Conservation Reserve Program; and (12) Prediction of water demand based on rural LULC that can be related to rates of draw-down of underground water supplies.
Price, Kevin P.↗
Comparative evaluation of ERTS-A imagery for resource inventory in land use planning
There are no author-identified significant results in this report. Evaluation has begun on ERTS-1 imagery of Crook County for use in landform interpretation and geologic mapping and interpretation. Outside of Crook County the geology team has been impressed by the display of fault patterns in southeastern Oregon and has begun preliminary analyses of these. Using the color combiner a complete timber type map of (1) all the forest land within Crook County, and (2) all the Ochoco National Forest has been completed. The timber types consist of five density classes which are correlated with different species compositions as the first step in the multistage forest inventory. Using the ERTS magnetic tape data the computer center has produced a 12 by 25 mile strip printout of bands 5, 6, and 7. The computer printouts are to be analyzed for different timber types and possible insect damage. Other results are: (1) limited number of clearcuts in eastern Oregon and in Cascades evident; (2) positive transparencies of band 5 appear to be too dark for maximum information of forested areas; and (3) much more information in the computer printouts of bands 6 and 7, than 5, when analyzing forest conditions.
Simonson, G. H.↗
Monitoring land use and degradation using satellite and airborne data
In July 1990 AVIRIS and AIRSAR data were collected over the Manix Basin Area of the Mojave Desert to study land degradation in an arid area where centerpivot irrigation had been in use. The Manix Basin is located NE of Barstow, California, along Interstate-15 at 34 deg 57 min N 116 deg 35 min W. This region was covered by a series of lakes during the Late Pleistocence and Early Holocene. Beginning in the 1960's, areas were cleared of the native creosote bush-dominated plant community to be used for agricultural purposes. Starting in 1972 fields have been abandoned due to the increased cost of electricity needed to pump the irrigation water, with some fields abandoned as recently as 1988 and 1992. These circumstances provide a time series of abandoned fields which provide the possibility of studying the processes which act on agricultural fields in arid regions when they are abandoned. Ray et al. reported that polarimetric SAR (AIRSAR) could detect that the concentric circular planting furrows plowed on these fields persists for a few years after abandonment and then disappear over time and that wind ripples which form on these fields over time due to wind erosion can be detected with polarimetric radar. Ray et al. used Landsat Thematic Mapper (TM) bandpasses to generate NDVI images of the Manix Basin which showed that the fields abandoned for only a few years had higher NDVI's than the undisturbed desert while the fields abandoned for a longer time had NDVI levels lower than that of the undisturbed desert. The purpose of this study is to use a fusion of a time series of satellite data with airborne data to provide a context for the airborne data. The satellite data time series will additionally help to validate the observation and analysis of time-dependent processes observed in the single AVIRIS image of fields abandoned for different periods of time.
Ray, Terrill W.↗
Investigation of environmental change pattern in Japan. Observation of present state of agricultural land-use by analysing LANDSAT data
The author has identified the following significant results. Species and ages of grasses in pastures were identified, and soils were classified into several types using LANDSAT data. This data could be used in a wide area of cultivation, reclamation, or management planning on agricultural land.
Maruyasu, T.↗
Predictability of Malaria Transmission Intensity in the Mpumalanga Province, South Africa, Using Land Surface Climatology and Autoregressive Analysis
There has been increasing effort in recent years to employ satellite remotely sensed data to identify and map vector habitat and malaria transmission risk in data sparse environments. In the current investigation, available satellite and other land surface climatology data products are employed in short-term forecasting of infection rates in the Mpumalanga Province of South Africa, using a multivariate autoregressive approach. The climatology variables include precipitation, air temperature and other land surface states computed by the Off-line Land-Surface Global Assimilation System (OLGA) including soil moisture and surface evaporation. Satellite data products include the Normalized Difference Vegetation Index (NDVI) and other forcing data used in the Goddard Earth Observing System (GEOS-1) model. Predictions are compared to long- term monthly records of clinical and microscopic diagnoses. The approach addresses the high degree of short-term autocorrelation in the disease and weather time series. The resulting model is able to predict 11 of the 13 months that were classified as high risk during the validation period, indicating the utility of applying antecedent climatic variables to the prediction of malaria incidence for the Mpumalanga Province.
Grass, David↗
Identification of phenological stages and vegetative types for land use classification
The author has identified the following significant results. A large grassland was located on the Kenai Peninsula which may be a potential grazing land. Two 1:250,000 vegetation maps were constructed from ERTS-1 scenes 1049-20505 and 1066-20453 using 70 mm MSS chips and black and white prints for an area of 3.5 million acres. Another area (464,000 acres) was mapped using digital data. The latter map is the most accurate and detailed vegetation map of that area produced to date. Areal extents of identified vegetation types were derived for the area mapped from digital data. Early spring (prior to leafing out of the deciduous trees) is suspected as being the best time for mapping Alaskan vegetation from MSS data due to the radiometrically distinctness of the vegetation communities at that time.
Branton, C. I.↗