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.
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.
"Cover Maximum normalized difference vegetation index images for sub-Saharan Africa for 1983-1985." International Journal of Remote Sensing, 7(11), pp. 1383–1384
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.
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.
We report the latest study for small glaciers, using Turkey as an example, and update previous studies of glaciers in Turkey from the 1970s to 2012–2013. We used seventy-two Landsat scenes from the Multispectral Scanner (MSS), Return Beam Vidicon-3 (RBV-3), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+), and Operational Land Imager (OLI); five Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images; and forty-one commercial satellite images. IKONOS, Quickbird-2, GeoEye-1, and WorldView-1 and -2 commercial satellite images were used to evaluate mapping accuracies, to understand debris-covered glacial margins, to map glacier margins in shadows, and to better determine the area of the smaller glaciers in Turkey. We also used nine Landsat-5 simultaneously acquired TM and MSS images to more accurately process MSS imagery from the 1970s. The area of the glaciers in Turkey decreased from 25km2 in the 1970s to 10.85km2 in 2012–2013. By 2012–2013, five glaciers had disappeared, six were less than 0.5km2, one was 0.8km2, and only two were 3.0km2 or larger. No trends in 1980 to 2012 annual precipitation, 1980 to 2012 winter precipitation, and 1980 to 2008 cloud cover extent were found, while surface temperatures increased, with summer minimum temperatures showing the greatest increases. We attribute glacier recession in Turkey from the 1970s to 2012–2013 to increasing summer minimum temperatures with no changes in precipitation or cloud cover over this time period.
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.
No abstract is provided for this article.
The first four Landsat-D thematic mapper sensors were evaluated and compared to the RBV and MSS sensors from Landsats-1, 2, and 3, Colvocoresses' proposed 'operational Landsat' three band system, and the French SPOT three band system using simulation/integration techniques and in situ collected spectral reflectance data. Sensors were evaluated by their ability to discriminate vegetation biomass, chlorophyll concentration, and leaf water content. The thematic mapper and SPOT bands were superior in a spectral resolution context to the other three sensor systems for vegetational applications. Significant improvements are expected for vegetational analyses from Landsat-D thematic mapper and SPOT imagery over MSS and RBV imagery.
No abstract is provided for this article.
