Ron Mahabir

Remote sensing-derived national land cover land use maps: a comparison for Malawi

Reliable land cover land use (LCLU) information, and change over time, is important for Green House Gas (GHG) reporting for climate change documentation. Four different organizations have independently created LCLU maps from 2010 satellite imagery for Malawi for GHG reporting. This analysis compares the procedures and results for those four activities. Four different classification methods were employed; traditional visual interpretation, segmentation and visual labelling, digital clustering with visual identification and supervised signature extraction with application of a decision rule followed by analyst editing. One effort did not report classification accuracy and the other three had very similar and excellent overall thematic accuracies ranging from 85 to 89%. However, despite these high thematic accuracies there were very significant differences in results. National percentages for forest ranged from 18.2 to 28.7% and cropland from 40.5 to 53.7%. These significant differences are concerns for both remote-sensing scientists and decision-makers in Malawi.

The study of slums as social and physical constructs: challenges and emerging research opportunities

Abstract Over 1 billion people currently live in slums, with the number of slum dwellers only expected to grow in the coming decades. The vast majority of slums are located in and around urban centres in the less economically developed countries, which are also experiencing greater rates of urbanization compared with more developed countries. This rapid rate of urbanization is cause for significant concern given that many of these countries often lack the ability to provide the infrastructure (e.g., roads and affordable housing) and basic services (e.g., water and sanitation) to provide adequately for the increasing influx of people into cities. While research on slums has been ongoing, such work has mainly focused on one of three constructs: exploring the socio-economic and policy issues; exploring the physical characteristics; and, lastly, those modelling slums. This paper reviews these lines of research and argues that while each is valuable, there is a need for a more holistic approach for studying slums to truly understand them. By synthesizing the social and physical constructs, this paper provides a more holistic synthesis of the problem, which can potentially lead to a deeper understanding and, consequently, better approaches for tackling the challenge of slums at the local, national and regional scales.

Comparison and integration of spaceborne optical and radar data for mapping in Sudan

The purpose of this study was to determine how different procedures and data, such as multiple wavelengths of radar imagery and radar texture measures, independently and in combination with optical imagery influence land-cover/use classification accuracies for a study site in Sudan. Radarsat-2 C-band and phased array L-band synthetic aperture radar (PALSAR) L-band quad-polarized radar were registered with ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) optical data. Spectral signatures were obtained for multiple landscape features, classified using a maximum-likelihood decision rule, and thematic accuracies were obtained using separate validation data. There were surprising differences between the thematic accuracies of the two radar data sets, with Radarsat-2 only having a 51% accuracy and PALSAR 73%. In contrast, the optical ASTER overall accuracy was 81%. Combining the original radar and a variance texture measure increased the Radarsat-2 to 78% and PALSAR to 80%, whereas the two original radar bands together had an accuracy of 87%. Sensor fusion of optical and radar obtained an accuracy of 93%. Based on these results, the use of multiwavelength quad-polarized radar imagery combined or integrated with optical imagery has great potential in improving the accuracy of land-cover/use classifications. In tropical and high-latitude regions of the world, where persistent cloud cover hinders the use of optical satellite systems, land management programmes may find this research promising.

Radar and optical remote sensing data evaluation and fusion; a case study for Washington, DC, USA

The recent increase in the availability of spaceborne radar in different wavelengths with multiple polarisations provides new opportunities for land surface analysis. This research effort explored how different radar data, and derived texture values, independently and in combination with optical imagery influence land cover/use classification accuracies for a study site in Washington, DC, USA. Two spaceborne radar images, Radarsat-2L-band and Palsar C-band quad-polarised radar, were registered with Aster optical data for this study. Traditional methods of classification were applied to various components and combinations of this data set, and overall and class-specific thematic accuracies obtained for comparison. The results for the two despeckled radar data sets were quite different, with Radarsat-2 obtaining an overall accuracy of 59% and Palsar 77%, while that of the optical Aster was 90%. Combining the original radar and a variance texture measure increased the accuracy of Radarsat-2 to 71% but that of Palsar only to 78%. One of the sensor fusions of optical and radar obtained an accuracy of 93%. For this location, radar by itself does not obtain classification accuracies as high as optical data, but fusion with optical imagery provides better overall thematic accuracy than the optical independently, and results in some useful improvements on a class-by-class basis. For those regions with high cloud cover, quad polarisation radar can independently provide viable results but it may be wavelength-dependent.

Radar speckle reduction and derived texture measures for land cover/use classification: a case study

Abstract This study examined the appropriateness of radar speckle reduction for deriving texture measures for land cover/use classifications. Radarsat-2 C-band quad-polarised data were obtained for Washington, DC, USA. Polarisation signatures were extracted for multiple image components, classified with a maximum-likelihood decision rule and thematic accuracies determined. Initial classifications using original and despeckled scenes showed despeckled radar to have better overall thematic accuracies. However, when variance texture measures were extracted for several window sizes from the original and despeckled imagery and classified, the accuracy for the radar data was decreased when despeckled prior to texture extraction. The highest classification accuracy obtained for the extracted variance texture measure from the original radar was 72%, which was reduced to 69% when this measure was extracted from a 5 × 5 despeckled image. These results suggest that it may be better to use despeckled radar as original data and extract texture measures from the original imagery.

Relative value of radar and optical data for land cover/use mapping: Peru example

ABSTRACT This study determined using divergence measures the best individual and combinations of various numbers of bands for six land cover/use classes around the city of Arequipa, Peru. A 15 band data stack consisting of PALSAR L-band dual-polarised radar, Landsat optical data, as well as six variance texture measures extracted from the PALSAR images, was used in this study. Spectral signatures were obtained for each class for the divergence examination. The band having the highest separability was the Landsat visible red band followed by the two largest window PALSAR texture measures. The best three band combination included three very different data types, Landsat visible red, near infrared and the PALSAR HH variance texture from a 17 × 17 pixel window. There was no need based upon the divergence values to use more than five bands for classification.

Coral Reefs: Challenges, Opportunities and Evolutionary Strategies for Surviving Climate Change in the Caribbean

Coral reefs are some one of the most diverse marine ecosystems on Earth. They are renowned hotspots of species biodiversity and provide home to a large array of marine plants and animals. Over the past 100 years in many tropical regions sea surface temperatures have increased by almost 1°C and are currently increasing at about 1–2°C per century. Corals have very specific thermal thresholds beyond which their temperature sensitive symbiot Zooxanthellae becomes affected and causes corals to bleach. Mass bleaching has already caused significant losses to live coral in many parts of the world. This paper looks at the key role that temperature plays in affecting the health and spatial distribution of coral in the Caribbean. The relationship between coral and symbiot is examined, in addition to some of the evolutionary strategies necessary to ensure the future survival of coral with changing climate.

An evaluation of Radarsat-2 individual and combined image dates for land use/cover mapping

Abstract Various land use/cover types exhibit seasonal characteristics which can be captured in remotely sensed imagery. This study examined how different seasons of Radarsat-2 data influence land use/cover classification accuracies for two study sites. Two dates of Radarsat-2 C-band quad-polarised images were obtained for Washington, DC, USA and Wad Madani, Sudan. Spectral signatures were extracted and used with a maximum likelihood decision rule for classification and thematic accuracies were then determined. Both despeckled radar and derived texture measures were examined. Thematic accuracies for the two despeckled image dates were similar with a difference of 3% for Washington and 6% for Sudan. Merging the despeckled images for both seasons increased overall accuracy by 2% for Washington and 9% for Sudan. Further combining the original radar for both seasons with derived texture measures increased overall accuracies by 9% for Washington and 16% for Sudan for final overall accuracy values of 73 and 82%.