Spatio-temporal Analysis of Forests under Different Management Regimes using Landsat and IRS Images

Institute for Social and Economic Change, Bangalore, Working paper 213, 2009

“Following the empirical study, cloud-free satellite data were used to study the forests in multi-temporal dimensions. Use of remote sensing data with visual observation/ground truth data is an advanced tool to study and understand the development patterns of the forests. Based on the vegetation index and land cover map a sound development has been observed in the community conserved forest (CCF) in comparison to other forests of the region. Community-based conservation would contribute to new conservation approaches that facilitate achieving the goal of sustainable landscape development in the mountains of the Indian Himalayan region.”

Evapotranspiration and Water Use Efficiency in a Chesapeake Bay Wetland under Carbon Dioxide Enrichment

Global Change Biology, Volume 16 Issue 1 , Pages 234-245 (January 2010)


“Wetlands evapotranspire more water than other ecosystems, including agricultural, forest and grassland ecosystems. However, the effects of elevated atmospheric carbon dioxide (CO2) concentration (Ca) on wetland evapotranspiration (ET) are largely unknown. Here, we present data on 12 years of measurements of ET, net ecosystem CO2 exchange (NEE), and ecosystem water use efficiency (EWUE, i.e. NEE/ET) at 13:00–15:00 hours in July and August for a Scirpus olneyi (C3 sedge) community and a Spartina patens (C4 grass) community exposed to ambient and elevated (ambient+340 μmol mol−1) Ca in a Chesapeake Bay wetland. Although a decrease in stomatal conductance at elevated Ca in the S. olneyi community was counteracted by an increase in leaf area index (LAI) to some extend, ET was still reduced by 19% on average over 12 years. In the S. patens community, LAI was not affected by elevated Ca and the reduction of ET was 34%, larger than in the S. olneyi community. For both communities, the relative reduction in ET by elevated Ca was directly proportional to precipitation due to a larger reduction in stomatal conductance in the control plants as precipitation decreased. NEE was stimulated about 36% at elevated Ca in the S. olneyi community but was not significantly affected by elevated Ca in S. patens community. A negative correlation between salinity and precipitation observed in the field indicated that precipitation affected ET through altered salinity and interacted with growth Ca. This proposed mechanism was supported by a greenhouse study that showed a greater Ca effect on ET in controlled low salinity conditions compared with high salinity. In spite of the differences between the two communities in their responses to elevated Ca, EWUE was increased about 83% by elevated Ca in both the S. olneyi and S. patens communities. These findings suggest that rising Ca could have significant impacts on the hydrologic cycles of coastal wetlands.”

The Potential for Gray Wolves to Return to Pennsylvania Based on GIS Habitat Modeling

Papers in Resource Analysis, Volume 11, 2009

Jared G. Beerman

“The gray wolf is an animal that is often misunderstood. Due to negative stereotypes of gray wolves, they were hunted to the brink of extinction in the contiguous United States of America. Presently, numerous states (Minnesota, Wisconsin, Michigan, Idaho, Montana, and Wyoming) are implementing reintroduction and management plans to rebuild the wolf population. Geographic Information Systems (GIS) were used to identify potential areas for wolf expansion based on habitat requirements in the state of Pennsylvania. This study used information from research compiled on existing wolf packs in the contiguous United States, along with management and reintroduction plans to locate suitable land for gray wolves located in the state of Pennsylvania. The approach was to use numerous data layers to determine if any land could support wolf existence and where these ranges would be located. Key layers used to locate wolf pack ranges in this study included: road density, human density, and land cover. The suitable locations were then examined to determine: water availability, prey density, and total range size. Once these locations had been identified, an approximation of potential pack size was then determined based on range size. The results of this study show there are multiple ranges which could potentially be used for gray wolf habitation in Pennsylvania.”

Spatial and Temporal Analysis of Drought and Summer Precipitation in Nepal under Climate Change

IOP Conference Series: Earth and Environmental Science, Volume 6, Session 29, 2009

Madan Sigdel and M. Ikeda

“Agricultural production and water resources in Nepal are highly influenced by precipitation for an entire year. In addition to dominant rainfall during summer monsoon over Nepal (SMRN), drought indices, which were normalized with the mean rainfall, were analyzed in association with large-scale atmospheric patterns using various statistical analyses. The indices at 3-month and 12-month represent agricultural and hydrological time scales, respectively. A dominant oscillation in SMRN exists in the range of 2.5–2.8 years indicating El Nino and Southern Oscillation (ENSO): i.e., less rain over eastern and central Nepal during El Nino. The analyses of horizontal patterns of moisture transport regressed on the SMRN revealed that the SMRN variability is more closely related with the moisture flux in a near-surface layer from Bay of Bengal under influences of ENSO rather than the moisture flux from the Arabian Sea. The 12-month drought index is basically equivalent with SMRN. On the other hand, the 3-month index additionally exhibits less rain in winter over western Nepal associated with weak westerly. Therefore, higher probability of the drought risk is suggested for agricultural production in western Nepal. While Indian Ocean Dipole was also investigated, its influence on Nepal is limited. These results suggest to us to prepare more appropriate mitigation methods for high risk of drought under climate change in different ways between western Nepal and the other regions.”

Spatial-temporal Analysis of Moving Polygons

Colin John Robertson, Masters thesis

“There are few methods available for the spatial-temporal analysis of polygon data. This research develops a new method for spatial-temporal analysis of moving polygons (STAMP). Using an event-based framework, polygons from neighboring time periods are related by spatial overlap and proximity. The proximity spatial relation is defined by an application specific distance threshold. STAMP is demonstrated in the spatial-temporal analysis of a wildfire burning over small spatial and temporal scales, and in the spatial-temporal analysis of mountain pine beetle (Dendroctonus ponderosae Coleoptera: Hopkins) movement patterns over large spatial and temporal scales. The mountain pine beetle analysis found that short range movement patterns of mountain pine beetles occurred at different beetle population levels. Spot proliferation occurred most when beetle presence was increasing slowly, perhaps moving into new areas for the first time. When beetle presence increased rapidly, local expansion, or spot growth, was a more common movement pattern. In the Pine Pass study area. long range dispersal markedly extended the northeast border of the mountain pine beetle range.”

GIS Priority Map Set to Focus WetlandCare Australia’s Resource Management Projects

Environmental Observer, Spring 2010

Ian Foreman, GHD

“WetlandCare Australia is improving New South Wales (NSW), Australia’s wetland environments and biodiversity through natural resource management projects. It commissioned the Central West Catchment Management Authority (CWCMA) to develop an access database that would enable staff members to prioritize and rank 113 wetland complexes. This information would help them in their rehabilitation and protection efforts. CWCMA created a tabular database that contained more than 32,000 individual polygons and 32 attributes. This data was used in calculating a weighted assessment. Rankings were then included in a wetland site priority index.”