Geospatial alternatives for quantification of bio-thermal influence zone in the vicinity of a solid waste dump.

Owing to the release of toxic gases, leachate and thermal emissions that originate from waste dumps, these sites significantly impact environmental sustainability. The study attempts to assess the deleterious impact of municipal solid waste (MSW) dump on surrounding forested landscape by employing geospatial technologies, which are cost and time-effective. For this purpose, temporal period ranging from 2015 to 2020, having 41 valid satellite observations has been selected for study. Firstly, the radii of intense hazardous zone and hazardous zone have been measured, as two separate parameters, which are 580 ± 30 m and 1260 ± 30 m, respectively. Secondly, average spatial extent of bio-influence zone is measured to be 1262 m while the average thermal influence zone extends up to 530 m around the MSW dumping site. A detailed analysis of influence zone variations reveals that the bio-influence zone depends on multitude of meteorological parameters, whereas the thermal influence zone relies mainly on seasonal temperature fluctuations. Moreover, the level of severity of emissions from MSW decomposition directly depends upon temperature. The long-term variability analysis of these hazardous zones reveals the stationarity of their spatial extents, signifying forest resilience. This study has proved significance of geospatial techniques as an alternate of expensive and time intensive assessment methods involving in situ measurements. So the proposed technique is beneficial for environmentalists, decision-makers and municipal authorities for analysing the extent and severity of MSW pollutants for forest community to address the problem of ecological degradation.

A comparison of satellite-based indices for hazard assessment of MSW open dumps using spatial analysis.

This study compares the suitability of different satellite-based vegetation indices (VIs) for environmental hazard assessment of municipal solid waste (MSW) open dumps. The compared VIs, as bio-indicators of vegetation health, are normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), and modified soil adjusted vegetation index (MSAVI) that have been subject to spatio-temporal analysis. The comparison has been made based on three criteria: one is the exponential moving average (EMA) bias, second is the ease in visually finding the distance of VI curve flattening, and third is the radius of biohazardous zone in relation to the waste heap dumped at them. NDVI has been found to work well when MSW dumps are surrounded by continuous and dense vegetation, otherwise, MSAVI is a better option due to its ability for adjusting soil signals. The hierarchy of the goodness for least EMA bias is MSAVI> SAVI> NDVI with average bias values of 101 m, 203 m, and 270 m, respectively. Estimations using NDVI have been found unable to satisfy the direct relationship between waste heap and hazardous zone size and have given a false exaggeration of 374 m for relatively smaller dump as compared to the bigger one. The same false exaggeration for SAVI and MSAVI is measured to be 86 m and -14 m, respectively. So MSAVI is the only VI that has shown the true relation of waste heap and hazardous zone size. The best visualization of distance-dependent vegetation health away from the dumps is also provided by MSAVI.

Geospatial passives for dynamic vegetation monitoring around thermal power plants.

As point sources of pollution, thermal power plants (TPPs) emanate hazardous gaseous and particulate matter that are of significant detriment to surrounding biological landscapes. To provide support to ecological conservation and resource management in developing countries, this study aims to establish a cost effective and robust geospatial methodology for dynamic vegetation monitoring of local pollution zones around TPPs using passive satellite-based indicators. The extent and severity of hazardous bio-influence around four TPPs is identified and monitored for a period of 5 years, using vegetation indices (VIs). High correlations of vegetation health with distance from TPPs have also been identified, signifying the hazardous impact of TPP emissions to surrounding vegetation. Variations in behavior of zones of high pollutant concentration are observed both in space and time, as a response to local seasonal weather, nature of fuel used in TPP, and type and areal coverage of vegetation around the power plants. Winter and Monsoon seasons have been identified to create favorable conditions for sustaining high pollution concentration around TPPs, and hence, the extent of hazardous bio-influence zones in these seasons is maximum. Moreover, oil-based power plant is revealed to be associated with large radial zones of degraded vegetation around it and, therefore, poses greater ecological hazard than gas-powered TPPs. The average bio influence zone measured for the test sites has been found to be 1660 m that ranges from 1600 to 1730 m for different power plants, explaining variable behavior of the used fuel and surrounding vegetation conditions. In this way, the study stresses upon the importance of geospatial data and analytical frameworks in reliable and economical monitoring of environmental pollution associated with anthropogenic sources, using passive environmental indices derived from remote data.