Publications

A Climate Change Threshold for Forest Dieback in the African Sahel

No abstract is provided for this article.

Towards a Global Greenhouse Gas Information System (GHGIS)

No abstract is provided for this article.

Relationship of spectral data to grain yield variation

Two-band hand-held radiometer data from a winter wheat field, collected on 21 dates during the spring growing season, were correlated with within-field final grain yield. Significant linear relationships were found between various combinations of the red and photographic infrared radiance data collected and the grain yield. The spectral data explained about 64 percent of the within-field grain yield variation. This variation in grain yield could not be explained using meteorological data as these were similar for all areas of the wheat field. Most importantly, data collected early in the spring were highly correlated with grain yield, a five-week time window existed from stem elongation through anthesis in which the spectral data were most highly correlated with grain yield, and manifestations of wheat canopy water stress were readily apparent in the spectral data.

Structural stage in Pacific Northwest forests estimated using simple mixing models of multispectral images

We identified stages of regrowth in replanted clearcuts in Douglas-fir/western hemlock forests in the Gifford Pinchot National Forest, southern Washington, USA, using a simple four-endmember constrained linear spectral mixing model applied to a multispectral Landsat Thematic Mapper image in order to separate and quantify spectral contributions from significant scene components. Spectral unmixing produces images of the fractional amount of the spectral endmembers, which were green vegetation, nonphotosynthetic vegetation, soil and “shade,” which includes topographic shading and shadows. Changes in endmember fractions correspond to changes in surface composition (as viewed from above). Unresolved shadows comprise the primary indicator of canopy structure and hence, regrowth stage. To isolate shadows, shading predicted from a digital elevation model was removed from the image before mixture analysis. As stands regrow, the surface cover shifts from initial high proportion of slash and exposed soil, and low proportions of green vegetation and shadows, to low fractions of stems and soil with high fractions of green vegetation and shadows. This shift in surface composition defines a regrowth trend in an endmember fraction data space. Projection of data onto this line allows estimation of structural stage and stand age, and provides a framework for remote mapping and monitoring of forest regrowth. Field analysis of 495 forest stands, representing stand structural stages ranging from newly replanted cuts to stands greater than 250 years in age, was used to assess the accuracy and precision of predicted structural stages and stand ages. The spectral unmixing approach can be used to evaluate and monitor forest regrowth quickly over large areas of the Pacific Northwest forests, and is extendible to mapping basic vegetation community type as well as structural stage.

Rift Valley fever Outbreak in East Africa: Signature of Climate Extremes

No abstract is provided for this article.

Trends in North American net primary productivity derived from satellite observations, 1982–1998

Net primary productivity (NPP) in North America was computed for the years 1982–1998 using the Carnegie‐Ames‐Stanford approach (CASA) carbon cycle model. CASA was driven by a new, corrected satellite record of the normalized difference vegetation index at 8‐km spatial resolution. Regional trends in the 17‐year NPP record varied substantially across the continent. Croplands and grasslands of the Central Plains and eastern Canadian forests experienced summer increases in NPP. Peak NPP trends in Alaska and western Canada occurred in late spring or early summer, suggesting an earlier onset of the growing season in these regions. Forests and woodlands of the southeastern United States showed NPP increases in spring and fall, also suggesting an increase in the length of the growing season. An analysis of climate variables showed that summer precipitation increased in the Central Plains, indicating that climate changes probably play some role in increasing NPP in this region, though intensive management of agricultural ecosystems has also increased productivity. Similarly, increased summer precipitation possibly increased NPP in eastern Canada, but another possible explanation is forest recovery after insect damage. NPP in the southeastern United States increased in the absence of climate variation. Much of this region consists of aggressively managed forests, with young stand ages and intensive silviculture resulting in increased NPP. The high latitudes of western Canada and Alaska experienced spring warming that could have increased NPP in late spring or early summer.

SAFARI 2000 AVHRR DAILY SITE (1.5 KM) AND 15-DAY REGIONAL (1.5- AND 6-KM) IMAGERY

ORNL DAAC: The Global Inventory Mapping and Modeling (GIMMS) group at NASA/GSFC provided SAFARI 2000 with remotely sensed satellite data products at the site and regional level. These AVHRR data contain two main sets of data: site extracts of SAFARI core sites (Mongu, Etosha, Kasungu, Maun, Skukuza, and Tshane), and regional 15-day composites from sets of single-day images. These AVHRR data contain four main sets of data:1.5 km daily site extracts of SAFARI core sites (2000)1.5 km 15-day composites of SAFARI core sites (1998-2000)1.5 km 15-day composites of the southern African region (Mar, Sept 2000)6 km 15-day composites of the southern African region (1998-2000)The primary data layers for site extracts and regional composites are fire pixel counts and maximum NDVI. The fire product is different for the daily and for the composited products (see readme file) and a fire product is not included in the 1.5 km regional data set. NDVI composite-associated data layers for the regional data sets include land surface temperature, reflectance, solar zenith angle, view zenith angle, and relative azimuth angle. NDVI composite-associated data layers for the site extracts include these same variables as well as brightness temperature, fire mask composite, latitude, and longitude. The data are stored in binary image format files. There is a metadata file for each site and date/compositing period, in ASCII format.

Relationship of red and photographic infrared spectral radiances to alfalfa biomass, forage water content, percentage canopy cover, and severity of drought stress

Red and photographic infrared spectral data were collected using a handheld radiometer for two cuttings of alfalfa. Significant linear and non-linear correlation coefficients were found between the spectral variables and plant height, biomass, forage water content, and estimated canopy cover for the earlier alfalfa cutting. The alfalfa of later cutting experienced a period of severe drought stress which limited growth. The spectral variables were found to be highly correlated with the estimated drought scores for this alfalfa cutting.

Monitoring corn and soybean crop development by remote sensing techniques

A system for spectrally monitoring the stages of crop development for corn and soybeans based upon red and photographic infrared spectral radiances is proposed. The red and photographic infrared spectral radiance, highly correlated with the green leaf area index or green leaf biomass, enable nondestructive monitoring of the crop canopy throughout the growing season. Five distinct periods are apparent which are related to crop development for corn and soybeans.

A consistent assessment of trees inside and outside forests improves estimates of total tree cover in Africa

The consistent monitoring of trees both inside and outside of forests is key to mitigating climate change. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we make use of the PlanetScope nanosatellite constellation, which delivers global very high-resolution daily imagery, to map both forest and non-forest tree cover for continental Africa using images from a single year. Our prototype map of 2019 demonstrates that a precise assessment of all tree-based systems is possible at continental scale, and reveals that 29% of tree cover is found outside areas previously classified as tree cover, such as in croplands and grassland. Such accurate mapping of tree cover at metric resolution down to the level of individual trees and consistent among countries has the potential to redefine land use impacts, move beyond the need for forest definitions, build the basis for natural climate solutions, and provide a new scientific basis for tree related studies.

Seasonal to interannual variability of vegetation and fires at SAFARI 2000 sites inferred from advanced very high resolution radiometer time series data

NOAA advanced very high resolution radiometer data are used to place the SAFARI 2000 and SAFARI 1992 intensive campaigns in the context of the interannual variability of vegetation conditions in southern Africa. Normalized difference vegetation index (NDVI) measurements and sea surface temperature (SST) indices of El Niño/Southern Oscillation (ENSO) are compared and the connections explained. The paper shows the vegetation evolution for the 2000 growing season, with unprecedented high and persistent NDVI anomalies associated with a cold phase of ENSO (La Niña) and above average rainfall between November and May, south of 15°S. In contrast, the 1992 season showed marked negative NDVI anomalies associated with an extreme drought in the southern part of the region, associated with the warm phase of ENSO (El Niño). These differences in NDVI patterns resulted in different patterns of fire distribution. More satellite detections of active fires were observed in 2000 than in 1992, especially for Botswana, Namibia, southern Zimbabwe, and southern Mozambique. Comparisons between in situ airborne measurements collected in 2000 and 1992 require an understanding of the extremely different vegetation and fire conditions associated with those years. Generalizations from results of the two SAFARI campaigns should be made with careful consideration of the extreme differences in conditions and the large interannual variability encountered in southern Africa, as depicted by the long‐term record of satellite vegetation measurements.

Applications and User Development on Solar-Induced Chlorophyll Fluorescence (SIF) Data Products from Spaceborne Platforms

No abstract is provided for this article.

Use of near infrared/red radiance ratios for estimating vegetation biomass and physiological status

The application of photographic infrared/red (ir/red) reflectance or radiance ratios for the estimation of vegetation biomass and physiological status were investigated by analyzing in situ spectral reflectance data from experimental grass plots. Canopy biological samples were taken for total wet biomass, total dry biomass, leaf water content, dry green biomass, dry brown biomass, and total chlorophyll content at each sampling date. Integrated red and photographic infrared radiances were regressed against the various canopy or plot variables to determine the relative significance between the red, photographic infrared, and the ir/red ratio and the canopy variables. The ir/red ratio is sensitive to the photosynthetically active or green biomass, the rate of primary production, and actually measures the interaction between the green biomass and the rate of primary production within a given species type. The ir/red ratio resulted in improved regression significance over the red or the ir/radiances taken separately. Only slight differences were found between ir/red ratio, the ir-red difference, the vegetation index, and the transformed vegetation index. The asymptotic spectral radiance properties of the ir, red, ir/red ratio, and the various transformations were evaluated.

30 years of remote sensing imagery in Sahel confronted to field observations (Gourma, Mali)

North American NPP from 1982-1998 Using a New Satellite Record: Trends and Comparisons With Field Measurements

A Non-Stationary 1981-2012 AVHRR NDVI%28sub 3g%29 Time Series

No abstract is provided for this article.

Satellite Mapping of Land Degradation In Senegal, Uganda, Kenya, and Tanzania

Land degradation has been highlighted as a key development challenge by numerous international bodies, including the United Nations Convention to Combat Desertification or the UNCCD, the Convention on Biological Diversity, the United Nations Framework Convention on Climate Change, and is one of the so-called Sustainable Development Goals. The UNCCD aims to avoid, reduce, and reverse land degradation, especially desertification and deforestation, by providing support to sustainable land management. Sustainable land management implements practices that maintain vegetative cover, build soil organic matter, make efficient use of inputs, such as water, nutrients and pesticides, and minimize off-site impacts. In the context of Land Degradation Neutrality or Sustainable Development Goal 15.3, three indicators have been identified to quantify land degradation: trends in land cover; trends in carbon stocks above and below ground; and trends in land productivity.

Limits to the Use of NDVI in Land Degradation Assessment

No abstract is provided for this article.