Data Mining - Concepts and Techniques.

Observations of backscattered near-ultraviolet radiation from the Total Ozone Mapping Spectrometer (TOMS) on board the Nimbus-7 (1979‐92) and the Earth Probe (mid-1996 to present) satellites have been used to derive a long-term record of aerosol optical depth over oceans and continents. The retrieval technique applied to the TOMS data makes use of two unique advantages of near-UV remote sensing not available in the visible or nearIR: 1) low reflectivity of all land surface types (including the normally bright deserts in the visible), which makes possible aerosol retrieval over the continents; and 2) large sensitivity to aerosol types that absorb in the UV, allowing the clear separation of carbonaceous and mineral aerosols from purely scattering particles such as sulfate and sea salt aerosols. The near-UV method of aerosol characterization is validated by comparison with Aerosol Robotic Network (AERONET) ground-based observations. TOMS retrievals of aerosol optical depth over land areas (1996‐2000) are shown to agree reasonably well with AERONET sun photometer observations for a variety of environments characterized by different aerosol types, such as carbonaceous aerosols from biomass burning, desert dust aerosols, and sulfate aerosols. In most cases the TOMS-derived optical depths of UV-absorbing aerosols are within 30% of the AERONET observations, while nonabsorbing optical depths agree to within 20%. The results presented here constitute the first long-term nearly global climatology of aerosol optical depth over both land and water surfaces, extending the observations of aerosol optical depth to regions and times (1979 to present) not accessible to ground-based observations.

/pdf/a-long-term-record-of-aerosol-optical-depth-from-toms-52jmzndo7i.pdf

A Long-Term Record of Aerosol Optical Depth from TOMS Observations and Comparison to AERONET Measurements

Problem Given the number of times in which an unknown event has happened and failed: Required the chance that the probability of its happening in a single trial lies somewhere between any two degrees of probability that can be named. SECTION 1 Definition 1. Several events are inconsistent, when if one of them happens, none of the rest can. 2. Two events are contrary when one, or other of them must; and both together cannot happen. 3. An event is said to fail, when it cannot happen; or, which comes to the same thing, when its contrary has happened. 4. An event is said to be determined when it has either happened or failed. 5. The probability of any event is the ratio between the value at which an expectation depending on the happening of the event ought to be computed, and the value of the thing expected upon it’s 2 happening.

An essay towards solving a problem in the doctrine of chances. [Facsimil]

https://pure.mpg.de/pubman/item/item_3033361_3/component/file_3033369/1-s2.0-S0034425719300689-main.pdf

Historical background and current developments for mapping burned area from satellite Earth observation

Obtaining global sea surface temperature (SST) fields for the ocean boundary condition in numerical weather prediction (NWP) models and for climate research has long been problematic. Historically, such fields have been constructed by a blending of in situ observations from ships and buoys and satellite infrared observations from the Advanced Very High Resolution Radiometer (AVHRR) that has been operational on NOAA satellites since November 1981. The resolution of these global SST fields is limited by the sparse coverage of in situ observations in many areas of the World Ocean and cloud contamination of AVHRR observations, which can exceed 75% over the subpolar oceans. As clouds and aerosols are essentially transparent to microwave radiation, satellite microwave observations can greatly improve the sampling and resolution of global SST fields. The Advanced Microwave Scanning Radiometer on the NASA Earth Observing System (EOS) Aqua satellite (AMSR-E) is providing the first highly accurate and glob...

/pdf/global-microwave-satellite-observations-of-sea-surface-4bg86lmcp5.pdf

Global Microwave Satellite Observations of Sea Surface Temperature for Numerical Weather Prediction and Climate Research

Fire risk assessment using satellite data

Burned area mapping time series in Canada (1984-1999) from NOAA-AVHRR LTDR: A comparison with other remote sensing products and fire perimeters

We investigate the effects of various types of atmospheric aerosols on satellite- derived sea surface temperature (SST) retrievals. The association between aerosol presence identified by the Earth Probe Total Ozone Mapping Spectrometer (TOMS) aerosol index (AI) and systematic errors in Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST retrievals is explored. We find a significant increase in systematic PFSST errors in the presence of dust aerosols. Average errors range from 0.34˚C for AI values between 0.5 and 1.0 to 1.74˚C for AI≥1.5. The bias is introduced by the AVHRR channel brightness temperature difference (T4 - T5) which is intended to correct for atmospheric absorption normally due primarily to water vapor. Our study shows that (T4 - T5) is sensitive to the dust aerosols (i.e., TOMS AI values). In contrast, smoke aerosols do not seem to have a significant effect on PFSST errors.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2000GL012446

Relationship between errors in AVHRR-derived sea surface temperature and the TOMS aerosol index

A Bayesian classifier mapped the Burned Area (BA) in the Northeastern Siberian boreal forest (70°N 120°E–60°N 170°E) from 1982 to 2015. The algorithm selected the 0.05° (~5 km) Long-Term Data Record (LTDR) version 3 and 4 data sets to generate 10-day BA composites. Landsat-TM scenes of the entire study site in 2002, 2010, and 2011 assessed the spatial accuracy of this LTDR-BA product, in comparison to Moderate-Resolution Imaging Spectroradiometer (MODIS) MCD45A1 and MCD64A1 BA products. The LTDR-BA algorithm proves a reliable source to quantify BA in this part of Siberia, where comprehensive BA remote sensing products since the 1980s are lacking. Once grouped by year and decade, this study explored the trends in fire activity. The LTDR-BA estimates contained a high interannual variability with a maximum of 2.42 million ha in 2002, an average of 0.78 million ha/year, and a standard deviation of 0.61 million ha. Going from 6.36 in the 1980s to 10.21 million ha BA in the 2010s, there was a positive linear BA trend of approximately 1.28 million ha/decade during these last four decades in the Northeastern Siberian boreal forest.

/pdf/estimation-of-burned-area-in-the-northeastern-siberian-hnrm1xlrly.pdf

Estimation of Burned Area in the Northeastern Siberian Boreal Forest from a Long-Term Data Record (LTDR) 1982–2015 Time Series

Forest fires constitute an important problem for the environment degradation. In this paper, we propose a Dynamic Fire Risk Index (DFRI) that takes into account different static and dynamic factors of risk for fire occurrence. Variables like insolation hours, vegetation cover, altitude, slope, proximity to main roads, and fire statistics have been used to develop a Static Fire Risk Index (SFRI) using a logistic regression model. Using satellite data to derive water stress of forest, a new dynamic index is defined weighting the static index with the actual value of water stress indicators. This methodology has been previously tested for some fires in the Canary Islands (Spain), and, in this case, we prove its usefulness using both NOAA-AVHRR and Terra-MODIS sensors data. As test sites, two different fires that took place in September 2005 on La Palma Island and August 2007 on Tenerife Island (Canary Islands, Spain) have been considered in order to validate the suitability of these tools for a regional scale application, in an area where multiple microclimates are present mainly due to its steep orography and the trade winds.

Manuel Arbelo

Papers

Fire risk assessment using satellite data

Burned area mapping time series in Canada (1984-1999) from NOAA-AVHRR LTDR: A comparison with other remote sensing products and fire perimeters

Relationship between errors in AVHRR-derived sea surface temperature and the TOMS aerosol index

Estimation of Burned Area in the Northeastern Siberian Boreal Forest from a Long-Term Data Record (LTDR) 1982–2015 Time Series

Synergy of GIS and Remote Sensing Data in Forest Fire Danger Modeling