Studying bio-thermal effects at and around MSW dumps using Satellite Remote Sensing and GIS

Waste Management xxx (2016) xxx–xxx

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Studying bio-thermal effects at and around MSW dumps using Satellite Remote Sensing and GIS Khalid Mahmood a,⇑, Syeda Adila Batool a, Muhammad Nawaz Chaudhry b a b

Remote Sensing and GIS Group, Department of Space Science, University of the Punjab, 54590 Lahore, Pakistan College of Earth and Environmental Sciences, University of the Punjab, 54590 Lahore, Pakistan

a r t i c l e

i n f o

Article history: Received 28 January 2016 Revised 4 April 2016 Accepted 18 April 2016 Available online xxxx Keywords: Land surface temperature Vegetation indices MSW dumping Bio-indicators Satellite Remote Sensing Spatial analysis

a b s t r a c t Estimating negative impacts of MSW dumps on its surrounding environment is the key requirement for any remedial measures. This study has been undertaken to map bio-thermal effects of MSW dumping at and around dumping facilities (non-engineered) using satellite imagery for Faisalabad, Pakistan. Thirty images of Landsat 8 have been selected after validation for the accuracy of their observational details from April 2013 to October 2015. Land Surface Temperature (LST), NDVI, SAVI and MSAVI have been derived from these images through Digital Image Processing (DIP) and have been subjected to spatiotemporal analysis in GIS environment. MSW dump has been found with average temperature elevation of 4.3 K and 2.78 K from nearby agriculture land and urban settlement respectively. Vegetation health has been used as the bio-indicator of MSW effects and is implemented through NDVI, SAVI, MSAVI. Spatial analyses have been used to mark boundary of bio-thermally affected zone around dumped MSW and measure 700 m. Seasonal fluctuations of elevated temperatures and boundary of the biothermally affected zones have also been discussed. Based on the direct relation found between vegetation vigor and the level of deterioration within the bio-thermally affected region, use of crops with heavy vigor is recommended to study MSW hazard influence using bio-indicators of vegetation health. Ó 2016 Elsevier Ltd. All rights reserved.

1. Introduction Although dumping of Municipal Solid Waste (MSW) is at bottom in the hierarchy of waste management solutions, yet it is the most used one. MSW dumps release environmental degrading emissions as a result of various biological and chemical transformations, in the form of gaseous and liquid compounds, over hundreds of years (Wang et al., 2012; Hard et al., 2013). These transformations are generally divided into hydrolysis, acidogenesis, acetogenesis and methanogenisis (Vaverkova and Adamcova, 2015). In general MSW dumping facilities are well established and engineered with well-designed monitoring systems i.e. groundwater monitoring, leachate collection, soil sampling and analysis etc. (Yan et al., 2014). Under these systems, to assess level of biodegradation stability, samples are regularly collected and analyzed for organic content, chemical and biological properties (Cobo et al., 2008). These assessments provide an understanding of the potential risks associated with MSW emissions and lead towards its ⇑ Corresponding author. E-mail addresses: [email protected] (K. Mahmood), aadila_batool@ yahoo.com (S.A. Batool), [email protected] (M.N. Chaudhry).

sustainable management. Worst scenario exists in the developing world where, due to limited resources, open dumping of MSW in very common (Ali et al., 2014; Mahmood et al., 2015). The open dumping (non-engineered landfills) of MSW poses grave consequences to both groundwater and nearby soils, that results in poor vegetation health (Bellezoni et al., 2014; Ali et al., 2014). The waste may contain different metals like Cd, Cu, Ni, Pb, and Zn that can affect plants by altering chemistry of soil (Shaylor et al., 2009). Fertility of soil may be damaged as a result of physiological disorders caused by metals absorbed through root system of plants, which retards their growth and vigor (Ali et al., 2014). Literature shows evidence of extreme hazards caused by open dumping of MSW to plant life and health leading towards irreversible erosion trends (Phil-Eze, 2010). Pollutants from MSW dumping start causing invisible injuries to plants by hindering their normal metabolism owing to which visible damage appears after some time (Ali et al., 2014). These consequences upset the naturally balanced ecosystem. One of the controlling factors of the ongoing decomposition of MSW is temperature at the dumping facility. It determines behavior of resulting leachate and gases i.e. elevated temperature reduces emission of methane by increasing its oxidation (Hanson et al., 2010; Bo-Feng et al., 2014). An extensive literature about

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Please cite this article in press as: Mahmood, K., et al. Studying bio-thermal effects at and around MSW dumps using Satellite Remote Sensing and GIS. Waste Management (2016), http://dx.doi.org/10.1016/j.wasman.2016.04.020

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production and toxic effects of leachate and gas can be found but very limited information is available on thermal behavior of dumped MSW (Hanson et al., 2010; Vaverkova and Adamcova, 2015). Dumped MSW is a three-phase complex system, running several biological, physical and chemical processes in parallel. All the three types of processes are responsible for the generation of heat (Faitli et al., 2015). Heat generation values for anaerobic and aerobic decomposition as measured by Hanson et al. (2013) are 0.38 and 11.3 W/m3 respectively. Yoshida and Rowe, 2003 have also reported a similar comparison of decomposition types. There are many other controlling factors of heat generation as well i.e. age of the waste (Hanson et al., 2008; Liu, 2007), size and height of the waste heap (Vaverkova and Adamcova, 2015). Most of the studies had simply used a constant elevated value of the dumping facilities to model performance of their environment protection level without incorporating seasonal effect that may generate a varying elevation value by controlling rates of decomposition (Doll, 1997; Southen and Rowe, 2005). Analytical solutions to study seasonal cycles of elevated temperature are also available in the literature (Carslaw and Jaeger, 1959; ORNL, 1981; Yesiller et al., 2005; Hanson et al., 2010). Most of the Land Surface Temperature (LST) data collected and studied by researchers is taken by limited ground measurements over MSW dumping sites (Hanson et al., 2010). In this regard a long list of in situ temperature measuring devices is presented in literature including thermocouples, piezometers, thermistors and a simple mercury thermometer (Yesiller et al., 2005; Koerner and Koerner, 2006; Han et al., 2007; Vaverkova and Adamcova, 2015). Implementation of proper monitoring systems requires up to date equipment and laboratories which demand budget and expert man power. Considering these limitations of cost and effort, researchers are attempting to find other feasible solutions for monitoring generation of thermal energy from dumped MSW. Use of remotely sensed satellite data has emerged as a supplementary and cost effective substitute of MSW dump monitoring even at large scale (Jones and Elgy, 1994; Gao and Liu, 2010; Yan et al., 2014). Satellites have onboard thermal sensors to measure thermal infra-red radiations coming from different land covers. Sensors that record spectral response of land covers are not limited only to thermal radiation and record response at other wavelengths as well. Measured radiations of these sensors are widely used to estimate Land Surface Temperature (LST) and to study biophysical behavior of target objects/land covers. Early researches in this regard, due to coarse spatial resolution of satellite data, have used aerial photographs to identify and characterize MSW piles using their texture and spectral response (Erb et al., 1981; Lyon, 1987; Bagheri and Hordon, 1988; Pope et al., 1996). Modern researches are using Geographic Information System (GIS) along with Digital Image Processing (DIP) of satellite data (Yan et al., 2014). Brivio et al. (1993) have used semivariogram method of spatial autocorrelation and contrast of MSW dumps to their surrounding land covers to delineate them as separate identities. Other analyses make use of spectral mixture modeling (Tromp and Epema, 1998), principal component analysis (Chikhaoui et al., 2005) and comparison of maps to quantify changes in degradation classes (Li et al., 2007). These analyses weresuccessfully used for explaining spatial changes in land-use classes, but quantification of their gradual degradation is much more important which these are not capable to extract (Röder et al., 2008). This quantification is possible through trend analysis of multiple satellite images having sufficient spatial resolution and captured at different times (Lambin and Linderman, 2006; Udelhoven, 2011). Remote sensing techniques are not limited to LST measurements and are in use to map vegetation health that can be used as an indicator of Landfill gas emission (Jones and Elgy, 1994; Im et al., 2012). Characterization of vegetation cover around MSW

dumping facilities using leaf area index, vegetation type, canopy reflectance and normalized difference vegetation index are appropriate to study existence of methane (Noomen et al., 2008, 2012; Im et al., 2012). In addition to multi spectral satellite images, Synthetic Aperture Radar (SAR) is also in use for identifying waste sites (Ottavianelli, 2007). Use of Landsat time series data is already well established for the Bio-thermal investigation of MSW dumps by mapping Land Surface Temperature (LST) and vegetation indices (Kwarteng and Al-Enezi, 2004; Yang et al., 2008; Shaker et al., 2010; Yan et al., 2014). It is intended to evaluate environmental implications of open dumping of MSW using Landsat 8 data in the present study. 2. Material and methods 2.1. Study area This study has been undertaken for Faisalabad which is the second largest industrial city of Pakistan. With an area of about 1496 km2 and an approximate population of 2.86 million, it lies between longitudes 72.8–73.3°E and latitudes 31.15–31.63°N (WGS84) and an average altitude of 186 m above mean sea level. The climate of Faisalabad is hot and semi-arid with an average rainfall of 480 mm per year, peak rainfall is in the months of July and August, with an average of about 200 mm. On average, the maximum temperature found in summer (May to September) is 310.8 K with peak in June (313.7 K) and average of the minimum temperature found in winter (November to March) is 281 K with lowest in January (277.4 K). Being an industrial hub, the city of Faisalabad has about 3000 small, medium and large industrial units mostly dealing with the textile production. MSW generation rate is figured out as 0.48 kg/capita/day with main components as food waste, demolition/construction waste, paper and cardboard etc. The city does not possess a single scientifically managed waste disposal site. MSW is disposed off in a crude and primitive way. This practice creates complex and serious environmental problems, and grave consequences to public and vegetation health. At present there are two officially announced dumping sites, a main and relatively old dump site and a new young dump about a kilometer away from the old one as shown in Fig. 1. Main dump is the first government owned dumping facility in Faisalabad, lying at 31.386°N and 73.242°E, where MSW dumping started in 2003. It has an area of 140,580 sq. m and a dumped MSW of about 120,000 ton. New dumping facility at 31.398°N and 73.252°E is the proposed location by local government for constructing a proper engineered landfill but open dumping practice has already started. The area occupied by it till this time is about 69,000 sq. m, covered by a waste of about 59,500 ton. All the dumping of MSW in Faisalabad is currently carried out without any lithological barrier to prevent leachate percolation. There is no closure cover activity, no MSW gas collection system, ultimately no prevention for the protection of local environment. These twin dumping facilities are surrounded by agricultural land that is in use for cultivation of wheat, rice and sugarcane. Agriculture is fully dependent on canal water as the local groundwater is not suitable due to high salinity. The water is provided by sub branch of Lower Chenab Canal (East) originating from river Chenab, one of the five rivers of Punjab province. 2.2. Datasets and study scheme LandSat 8 data had been used in the study for the temporal window starting from April 2013, when the satellite sensors got operational and started delivering data. Row 038 and path 149 is the index reference of the image where the study area falls. 59 satellite

Please cite this article in press as: Mahmood, K., et al. Studying bio-thermal effects at and around MSW dumps using Satellite Remote Sensing and GIS. Waste Management (2016), http://dx.doi.org/10.1016/j.wasman.2016.04.020

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Fig. 1. Study area.

Table 1 Selected images for the study. No.

Acquisition date

No.

Acquisition date

No.

Acquisition date

1 2 3 4 5 6 7 8 9 10

April 16, 2013 May 2, 2013 May 18, 2013 September 23, 2013 October 25, 2013 November 10, 2013 November 26, 2013 December 12, 2013 December 28, 2013 January 29, 2014

11 12 13 14 15 16 17 18 19 20

March 18, 2014 April 3, 2014 May 5, 2014 May 21, 2014 June 6, 2014 August 5, 2014 September 26, 2014 October 12, 2014 November 13, 2014 January 6, 2015

21 22 23 24 25 26 27 28 29 30

February 1, 2015 February 17, 2015 March 21, 2015 May 8, 2015 May 24, 2015 June 9, 2015 June 25, 2015 September 13, 2015 September 29, 2015 October 15, 2015

observations for the study area exist till October 2015. All the observational images were validated for the accuracy of their observational details by looking at them one by one for cloud covers over the study area. In addition to looking at visible bands of images they were further subjected to check for the cirrus clouds that are transparent for visible bands but affect thermal bands. All the apparently cloud free images were downloaded and processed to derive brightness temperature products for both band10 and band-11 of Thermal Infrared Sensor (TIRS) in ENVI 5.1. Temperature products were then visually analyzed for further scrutiny of the valid satellite observational images to be used for this study. Dates for the selected images are given in Table 1. The valid observational dates were selected for furnishing a request for Landsat Surface Reflectance High Level Data Products of Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and Modified Soil Adjusted Vegetation Index (MSAVI) to USGS (Landsat Surface Reflectance products courtesy of the U.S. Geological Survey). Raster calculator has been used to standardize units of downloaded Landsat Surface Reflectance High

Level Data Products that requires multiplication of every pixel value to a scale factor 0.0001. Variation in Land Surface Temperature (LST) for four land cover types consisting of the main dumping site, the nearby vegetation, residential area and location of the new dumping facility has been studied. Relative location of these land covers along with their distance from main dump is shown in Fig. 2. Quick Bird imagery has been utilized to digitize polygons of respective land covers. Initially, the location of new dumping facility was a barren land that started receiving a growing pile of MSW after its declaration as a place for building landfill site. Zonal stat operation has been applied to each valid temperature observation, brightness temperature extracted from band 10, using land type polygons as zones of measurement. The BT used in this study is the one extracted from Band 10 of the Thermal Infrared Sensor (TIRS) as it is more stable against atmospheric absorption. Infact both of the TIRS bands fall at the longwave edge of the thermal infrared window where influence of Carbon dioxide absorption is high. Band 11 (11.5–12.51 lm), being closer to the powerful 15 lm band of

Please cite this article in press as: Mahmood, K., et al. Studying bio-thermal effects at and around MSW dumps using Satellite Remote Sensing and GIS. Waste Management (2016), http://dx.doi.org/10.1016/j.wasman.2016.04.020

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Fig. 2. Relative locations of thermal land covers.

Table 2 Seasonal windows used for the study. No.

Season

Starting date

Ending date

Number of days

1 2 3 4 5

Spring Dry summer Monsoon Wet summer Winter

11th March 1st May 7th July 16th September 16th November

30th April 6th July 15th September 15th November 10th March

51 67 70 61 116

Carbon dioxide is more influenced by the atmospheric absorption than band 10 (10.6–11.19 lm). The measured temperature variation has been plotted against time for both, continuous as well as seasonal changes. The seasonal windows specified by local

meteorological department have been used for this study and are given in Table 2. To study heat generation effect on surroundings of MSW dumping facility for which it may act as a source of heat, distance dependent variation of temperature from main dumping facility has also been taken into account. This is done by drawing multi ring buffer around the dumping site. As the sensitivity of nearby locations to the generated heat is maximum and decreases with the increase in distance, therefore, to pick the heat variation sensibly first 10 buffers to the dumping facility are of 10 m radial distance, followed by 11 buffers of 100 m and finally the outer buffer is of 300 m. The location of the new dumping facility also falls in the 300 m buffer zone, the buffers are shown in Fig. 3. All the valid brightness temperature raster data sets were resampled at 5 m spatial resolution

Fig. 3. Multi ring buffers around main dumping facility.

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Fig. 4. Time dependent thermal comparison of different land covers.

Fig. 5. Seasonal variations of temperature for different land covers.

using nearest neighborhood algorithm. Statistics for the variety of temperature values laying in each of the buffer zone are computed using operation of zonal statistics. The resampling of the original pixel size from 30 m to 5 m was done to ensure reading of maxi-

mum number of true temperature values by the zonal statistics algorithm even in buffers of 10 m radial distance. To conceptualize the effect of soil and air detrition, health of the vegetation surrounding main dump facility has been taken as the

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Fig. 6. Distance dependent temperature profiles around main dumping facility.

bio-indicator. NDVI, SAVI and MSAVI are the vegetation health measuring spectral indices used in the study and are interpreted as indicators of environmental degradation. All these Vegetation Indices (VI), belong to slope-based class of spectral indices combining information from two strongly contrasting bands for vegetation, Near Infrared (NIR) and red. Although the indices have limitations due to choices of band width and location but these are widely used for monitoring, mapping and analyzing spatiotemporal variations in biophysical characteristics of vegetation. The vegetation characteristics studied through these indices include canopy greenness, composite of leaf chlorophyll, leaf area index (LAI), vegetation fraction (VF), fraction of absorbed photosynthetically active radiation, and overall production (Muneni et al., 1997; Gitelson et al., 2002; Wu, 2014). NDVI is the most simple and basic in this category, whereas SAVI has additional function of eliminating intrusion of soil reflectance and finally, the MSAVI (Modified SAVI) is more sensitive to dynamics of soil- vegetation ratio than SAVI. Detail of these indices can be found in Muneni et al. (1997), Gitelson et al. (2002) and Wu (2014). The same buffer zones used to study spatial trend of temperature variation have been used for picking up the vegetation health

status as function of distance from the dumping facility. All the valid data sets of the used indices were resampled from 30 m to 5 m. Stats for the variety of values in each of the buffer zone is computed using zonal statistics operation. Mean value of each of the vegetation health parameter is drawn as a function of buffer sequence. Mean value is considered for discussion to avoid any anomaly caused by other controlling factors of vegetation health i.e. vegetation type, soil type, availability of water, pesticides etc. 3. Results and discussions The results obtained from Bio-thermal analysis at and around main MSW dumping facility of Faisalabad have been divided into following sections for analysis and discussion. 3.1. Thermal comparison A comparison between different land covers, having same climatic condition, have been made for their thermal behavior from April 2013 to October 2015. Time based thermal profiles of main

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Fig. 7. Distance dependent NDVI profiles around main dumping facility.

dumping facility, new dumping facility, agriculture and urban area are shown in Fig. 4. In general temperature of main dumping facility is recorded to be the highest throughout the study period, residential area coming next to main dump and agriculture remaining the coolest among all the compared land covers. Behavior of the new dumping site has continuously changed from start of the study period till the end. This has happened due to the change in land cover at this location. The place has transformed during this period from barren land to a MSW dump, and hence the thermal behavior has changed. Although size and volume of dumped MSW at new facility is very small compared to the main facility but even this amount is as effective as the main dump since more heat is generated by young waste as compared to the older one (Hanson et al., 2008; Liu, 2007). Fig. 4D compares temperatures of main and new dumping facilities, the temperature difference reduced over time and turned almost negligible at the end. This temperature difference has reduced with the increase in MSW dumping at new facility, showing heat producing ability of dumped MSW. Whereas no such development has been found in case of vegetation (Fig. 4B) and urban area (Fig. 4C). Difference of temperature between MSW

dump and nearby agriculture ranges from 2 K to 8 K with an average of 4.3 K. Similarly, the temperature difference between MSW dump and urban area varies from 0 K to 5.5 K with an average of 2.78 K. Although, dominance of main MSW dump for high temperature has remained a permanent feature throughout, but the difference has shrunk during phases when overall temperature was rising due to seasonal change, especially around June 2014. The same set of temperature observations have been put into seasonal comparison as shown in Fig. 5. Maximum temperature contrast is observed in spring season followed by dry summers. Minimum temperature is observed in winter, when the studied land covers have been divided in two groups, urban and agriculture lands with nearly equal low temperatures, main and new dumps with nearly equal higher temperatures. Temperature profiles of both the dumping facilities were almost overlapped from monsoon 2014 onwards, as was expected by the increase of MSW dumped in new facility. In the light of these results, it is evident that the dumping facilities are very prominent sources of heat. The effect of heat source on its surroundings is obvious and of great importance to be studied in order to have an insight into the micro climatic conditions

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Fig. 8. Distance dependent SAVI profiles around main dumping facility.

formed around MSW dumps. Distance dependent seasonal profiles of temperature around main dumping facility for the studied period have been shown in Fig. 6. A general trend of temperature decrease with the increasing distance from the source is observed for all the 30 valid observations without any exception. On average, the effect of elevated temperatures above normal temperature during seasons around the main dump have been observed up to a distance of 700 m. It implies that the thermal effect of MSW dumping at the main facility exists up to 700 m surrounding land. Range of this boundary varies from 500 m in spring to 1100 m in rainy season of monsoon. It may be concluded here that the rate of MSW degradation and hence the amount of heat generation are season dependent. Maximum elevated temperatures are found for spring with an average bias of 4.67 K. Dry summer (D. Summer) and monsoon have same average elevated temperature of 3.67 K, whereas wet summer (W. Summer) and winter had averages of 3 K and 2.5 K respectively. A progressive increase in the average temperature of outer buffers (from 1000 m to 1500 m) has been observed in the years of 2014 and 2015. This rise of temperature is governed by the development of new dumping facility in the eastern part

of outer buffers. The resultant averages are not as high as they were found around the main dump because of the large sizes of circular buffers away from the new dump of MSW. The new developing source of heat is only influencing a part of this outer set of buffer zones and so results into a small increment of about half a degree in buffer averages of temperature. It was possible to incorporate thermal effects of new MSW dump by taking merged buffers around both the sites. The issue with merged buffer analysis would arise for the year 2013 when this patch of the land was barren, with no heat producing ability. In that case resultant buffer averages of temperature led to the inappropriate representation of heat sources and their effect to neighborhood. This rising temperature effect is most prominent for winter and spring, when any addition of heat from MSW dump is more conspicuous due to low seasonal temperatures. 3.2. Bio-indicators MSW dumping has widely been reported to affect surrounding vegetation as a consequence of air and soil pollution (Shaylor et al., 2009; Phil-Eze, 2010; Ali et al., 2014). Pollutants from degradation

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Fig. 9. Distance dependent MSAVI profiles around main dumping facility.

of MSW disturb normal metabolism in plants which results into poor vigor of vegetation that can be detected through VIs of NDVI, SAVI and MSAVI. The results of bio-indicators for assessing hazardous impacts of open dumping are discussed under the following headings. 3.2.1. NDVI Distance dependent variations of NDVI from edges of the main dumping facility to a distance of 1600 m is shown in Fig. 7. The NDVI profiles have been studied from spring, 2013 to wet summer, 2015. There may exist cases where the sowing dates for the surrounding fields were different as the land belongs to different farmers. A date shift may also exist in overall sowing of crops due to some weather condition or the availability of canal water. These shifts may also be the reason of finding differences in NDVI averages. So, in order to avoid these differences, the results have been put into seasonal comparison by averaging out the valid observations found in each of the seasonal window. An incremental improvement in the value of NDVI has been observed with the increasing distance from the dumping site. Although incremental

rates were varying but no exception has been found for any of the valid observation that does not comply with this increasing trend of NDVI value. As large areas around the dumping site are harvested with the same crop in a season so an increasing value of NDVI is actually a measure of improving vegetation vigor. The increasing trends of vegetation vigor, translating into its health, have been observed away from the MSW dump, lying in the center for all the outward extended buffers. Hence, decreasing vigor towards the center is controlled by byproducts of the decomposition of MSW. It might be the soil pollution or the air pollution or most probably a combination of both that contributes to such a situation. Their resultant outcome has been successfully mapped using vegetation health as a bio-indicator. The increase in NDVI averages flatten after a certain distance or tend to be independent of the increasing distance, it may be marked as boundary of the MSW polluted zone that affects vegetation health. If related to distance based thermal profiles, these boundaries are peripheries of the affected region by the dumped MSW. An average boundary extent of this region is about 700 m that varies from 500 m in winter to 800 m in dry summers.

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Maximum distance dependent improvement in vegetation vigor is found for winter and spring, when an average increase of 0.2 in NDVI values has been observed. These are the seasons when the wheat crop starts greening up and reaches flowering stage, consequently the value of NDVI reaches 0.6, and the effect of any damage to vegetation health becomes more prominent. Average improvement in NDVI value found for dry summer, monsoon and wet summer are 0.08, 0.12 and 0.09 respectively whereas average of the maximum values of NDVI observed within buffers zones are 0.25, 0.35 and 0.32 respectively. There seems to exist a direct relation between maximum values of NDVI and damage caused by MSW dumping hazards. Comparing springs of all three studied years, the effect of new dumping facility is as prominent as was for changing temperature with distance. The peak NDVI value is pushed by development of new MSW facility towards the main dump in the later years. The same change is visible for other seasons as well. The effect is more pronounced and clear for dry summer, wet summers and monsoon, showing higher decomposition rates and hence the higher pollution concentration in these seasons. 3.2.2. SAVI Variations in SAVI with the increasing distance from main dump is shown in Fig. 8. Similar to NDVI all the trends of increasing values with distance and micro climate boundary shift due to the development of new dumping facility have been found for SAVI as well. Because of SAVI’s ability to eliminate soil, the graphs have more edges than were observed in Fig. 6. The other difference found is the peak values for each of the valid seasonal observation. Average increase of 0.12, 0.043, 0.08, 0.056 and 0.115 with average peak values of 0.29, 0.175, 0.243, 0.21 and 0.235 have been observed for spring, dry summer, monsoon, wet summer and winter respectively. 3.2.3. MSAVI Distance vise distribution of buffered averages for MSAVI around main dump are shown in Fig. 9. Average increase in MSAVI of 0.127, 0.04, 0.09, 0.057 and 0.11 with average peak values at 0.273, 0.157, 0.237, 0.19 and 0.21 are observed for spring, dry summer, monsoon, wet summer and winter respectively. A direct relation of vegetation vigor and the level of destruction caused by the open dumping of waste have been observed for all the three vegetation indices. The most affected crop under these conditions is wheat, especially in spring season. Effect of the development at outer buffer is also well prominent for wheat in spring. These results and discussion have led to conclude that for studying environmental degradation caused by open dumping of MSW using bio-indicators vegetation of heavy vigor i.e. wheat is the best option. 4. Conclusion This research has been designed to study bio-thermal behavior of MSW dumped in Faisalabad using satellite imagery of Landsat 8. Use of remotely sense data for environment impact assessment of dumped MSW has been verified. A permanent elevation in temperature of the dumping facility has been observed and found to be 2–8 K with an average of 4.3 K higher than agriculture and 0–5.5 K with an average of 2.78 K higher than urban area. Maximum temperature contrast between studied land covers has been observed in spring season followed by dry summers, whereas minimum is observed in winter. Comparison of temperatures of new and the main dumping facilities has verified that the rise in temperature is purely due to bio-chemical degradation of dumped MSW, as the temperature of both the dumps becomes more similar with

increasing amount of MSW at the new facility. Maximum difference of temperatures between studied land covers has been observed above atmospheric temperature of 315 K. A trend of decreasing temperature with the increase in distance from the source is observed for all the 30 valid observations without any exception. These distance dependent temperature profiles have been successfully used not only to mark boundary of the thermally influenced zone around MSW, but also to study its seasonal fluctuations. Average radius of this zone around main dumping facility is measured to be 700 m that varies from 500 m in spring to 1100 m in monsoon. Put to seasonal comparison, maximum elevated temperature is found for spring with a bias of 4.67 K. Dry summer and monsoon have same bias of 3.67 K, whereas wet summer and winter have shown biases of 3 K and 2.5 K respectively. Years of 2014 and 2015 have been marked with a progressive rise in average temperatures of outer buffers due to development of new dumping facility. It may be concluded here that the rate of MSW degradation and hence the amount of heat generation are season dependent. To study environmental damage done by open dumping of MSW through bio-indicators of plant health, satellite data has been found to be very effective, reliable and economical alternative. Study of Vegetation indices like NDVI, SAVI and MSAVI to map vegetation health is found to be more effective if put into seasonal comparison so as to minimize effect of any anomaly caused by factors other than the MSW dumping hazards. All the three studied VIs have shown an improvement in vegetation vigor with increasing distance from the main dumping facility for all the 30 valid observation without any exception. This disturbing influence to vegetation health around the source has been observed to range up to 700 m of surrounding land on average. This radius of the surrounding affected land is season dependent and varies from 500 m in winter to 800 m in dry summers. Maximum improvement in vegetation vigor has been observed for wheat, around its flowering stage, in winter and spring when an average increase of 0.2 in NDVI, 0.12 and 0.115 respectively in SAVI, 0.127 and 0.11 respectively in MSAVI have been found. For dry summer, monsoon and wet summer; NDVI has improved by 0.08, 0.12 and 0.09, SAVI by 0.043, 0.08 and 0.056, MSAVI by 0.04, 0.09 and 0.057 respectively. Comparing maximum values of VIs with average increase for each of the seasons, a direct relation between vegetation vigor and the level of destruction caused by the open dumping of waste has been observed. The crop most influenced by this scenario is wheat, especially in spring season. Therefore this research concludes that for studying environmental degradation caused by open dumping of MSW using bio-indicators of vegetation health, crops with heavy vigor i.e. wheat are the best option. References Ali, S.M., Pervaiz, A., Afzal, B., Hamid, N., 2014. Open dumping of municipal solid waste and its hazardous impacts on soil and vegetation diversity at waste dumping site of Islamabad city. J. King Saud Univ. – Sci. 26, 59–65. Bagheri, S., Hordon, R., 1988. Hazardous waste site identification using aerial photography: a pilot study in Burlington Country, New Jersey, USA. Environ. Manage. 12 (1), 119–125. Bellezoni, R.A., Iwai, C.K., Elis, V.R., Paganini, W.D.S., Hamada, J., 2014. Small-scale landfills: impacts on groundwater and soil. Environ. Earth Sci. 71, 2429–2439. Bo-Feng, C., Jian-Guo, L., Qing-Xian, G., Dong, C., Lan-Cui, L., Ying, Z., Zhan-Sheng, Z., 2014. Estimation of methane emissions from municipal solid waste landfills in China based on point emission sources. Adv. Clim. Change Res. 5 (2), 81–91. Brivio, P., Doria, I., Zilioli, E., 1993. Aspect of spatial autocorrelation of Landsat TM data for the inventory of waste-disposal site in rural environment. Photogramm. Eng. Rem. Sens. 59 (9), 1377–1382. Carslaw, H.S., Jaeger, J.C., 1959. Conduction of Heat in Solids, second ed. Oxford University Press, Oxford. Chikhaoui, M., Bonn, F., Bokoye, A.I., Merzouk, A., 2005. A spectral index for land degradation mapping using ASTER data: application to a semi-arid Mediterranean catchment. Int. J. Appl. Earth Obs. Geoinf. 7 (2), 140–153. Cobo, N., Lopez, A., Lobo, A., Zamorano, M., Brebbia, C., Kungolos, A., Popov, V., Itoh, H., et al., 2008. Biodegradation stability of organic solid waste

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Please cite this article in press as: Mahmood, K., et al. Studying bio-thermal effects at and around MSW dumps using Satellite Remote Sensing and GIS. Waste Management (2016), http://dx.doi.org/10.1016/j.wasman.2016.04.020