This article explores using Landsat imagery and spectral mixture analysis to map licit and illicit artisanal and small-scale gold mining (ASM) in Madre de Dios, Peru. The study finds that ASM operations are difficult to detect using traditional classification methods due to their small size, but spectral mixture analysis can extract information from mixed pixels to map ASM. The results indicate that approximately 65% of all ASM activity in the study area occurs outside of legally permitted mining concessions, highlighting the prevalence of illicit mining. Mapping ASM using these remote sensing methods provides insights into the extent of environmental impacts from mineral extraction in the region.
This document describes a predictive modeling study to identify areas of high probability for containing prehistoric archaeological sites in western Whatcom County, Washington. The study uses known site locations and environmental variables like slope, aspect, distance to water and land cover to develop a predictive model. The results divide the study area into three suitability levels: unsuitable, moderately suitable and highly suitable. Areas deemed highly suitable correlate well with known site locations and proximity to water bodies like the Nooksack River. The model identifies over 100 square kilometers of highly suitable land.
[International agrophysics] ground penetrating radar for underground sensing ...Minal Ghugal
This document reviews the use of ground penetrating radar (GPR) for underground sensing in agriculture. GPR provides non-invasive measurements of belowground properties and has been used to measure soil characteristics like moisture, texture, and compaction. While GPR has been widely used to detect coarse tree roots, measuring individual crop roots directly is difficult but GPR can detect root cohorts within a soil volume. GPR also shows potential for indirectly estimating root development by sensing related soil properties and coupling with soil water models. Further advances rely on integrating knowledge across disciplines to adapt GPR for agricultural management needs.
This document describes a study that used remote sensing and GIS techniques to assess land use and land cover changes in Madurai City, India between 2003 and 2008. Satellite imagery from 2003 and 2008 was analyzed using supervised classification to create land use/land cover maps for each time period. A change detection analysis was then conducted to identify changes between the two time periods. The results showed an 18% increase in built-up land and a 14.2% increase in crop land, while mixed built-up land and vacant land decreased. The study concluded that the urban area of Madurai City increased significantly from 2003 to 2008.
This document summarizes a research paper that evaluates rangeland suitability for livestock production in Dire District, Ethiopia using remote sensing and GIS techniques. Specifically, the study:
1) Analyzed environmental factors like land use/cover, soil, slope, and rainfall as well as socioeconomic factors including access to water, veterinary services, and markets.
2) Classified the study area into suitability classes (high, moderate, marginal, not suitable) for cattle, sheep, goats, and camels using these factors in a GIS multi-criteria analysis.
3) Found that 5.6-10.1% of land was highly suitable for different livestock, 44.7
Land Use Land Cover Change Detection of Gulbarga City Using Remote Sensing an...ijsrd.com
This document summarizes a study that analyzed land use and land cover change in Gulbarga City, India between 2001 and 2012 using remote sensing and GIS techniques. Satellite images from 2001 and 2012 were classified to identify changes in land cover categories such as vegetation, soil, water, and forest area. The study found expansion of urban areas led to losses of agricultural land, vegetation land, and water bodies. This urban sprawl also created environmental issues like decreased air quality and increased temperatures. The goal of the study was to understand land use and land cover change in Gulbarga City and quantify changes that occurred between 2001 and 2012 by comparing satellite image data from the two time periods.
Utilizing LiDar on Dos Hombres to Gran Cacao TransectAmber Wa
The document discusses utilizing LiDAR (Light Detection and Ranging) to map a 12.4 km transect between the Mayan archaeological sites of Dos Hombres and Gran Cacao in Belize. LiDAR uses lasers mounted on aircraft to generate highly accurate terrain models and maps. The project aims to provide training to students and faculty in LiDAR technology, while efficiently mapping the densely forested site. Previous successful uses of LiDAR at other Mesoamerican sites, like Caracol in Belize, demonstrated its ability to reveal hidden archaeological features through canopy cover.
Remote sensing has enabled mapping, monitoring and management of various resources like agriculture, forestry, water, and oceans over the last four decades. It has contributed significantly to development in India through applications like groundwater mapping, wasteland monitoring, flood mapping, agriculture monitoring, fisheries forecasting, snow and glacier studies, and forestry assessments. Current and future uses include urban planning through databases and indicators, and watershed development through projects like Sujala in Karnataka. Advances in remote sensing will continue to improve emergency response, mapping, and geospatial information.
Land use Land Cover change mapping using Remote Sensing and GIS: A case study...IRJET Journal
This document summarizes a study that used remote sensing and GIS techniques to analyze land use and land cover change in Gudur Mandal, Andhra Pradesh, India between 2000 and 2015. Supervised classification with maximum likelihood algorithm was used to classify Landsat satellite imagery into six land cover classes for each time period. Results found significant decreases in cultivated crop land (-35.88%), water bodies (-92.70%), and forest (-77.59%) between 2000 and 2015, along with increases in residential area (30.76%) and uncultivated crop land (151.68%). The changes indicate threats to the local agriculture and greater management of water resources will be needed.
This document describes a predictive modeling study to identify areas of high probability for containing prehistoric archaeological sites in western Whatcom County, Washington. The study uses known site locations and environmental variables like slope, aspect, distance to water and land cover to develop a predictive model. The results divide the study area into three suitability levels: unsuitable, moderately suitable and highly suitable. Areas deemed highly suitable correlate well with known site locations and proximity to water bodies like the Nooksack River. The model identifies over 100 square kilometers of highly suitable land.
[International agrophysics] ground penetrating radar for underground sensing ...Minal Ghugal
This document reviews the use of ground penetrating radar (GPR) for underground sensing in agriculture. GPR provides non-invasive measurements of belowground properties and has been used to measure soil characteristics like moisture, texture, and compaction. While GPR has been widely used to detect coarse tree roots, measuring individual crop roots directly is difficult but GPR can detect root cohorts within a soil volume. GPR also shows potential for indirectly estimating root development by sensing related soil properties and coupling with soil water models. Further advances rely on integrating knowledge across disciplines to adapt GPR for agricultural management needs.
This document describes a study that used remote sensing and GIS techniques to assess land use and land cover changes in Madurai City, India between 2003 and 2008. Satellite imagery from 2003 and 2008 was analyzed using supervised classification to create land use/land cover maps for each time period. A change detection analysis was then conducted to identify changes between the two time periods. The results showed an 18% increase in built-up land and a 14.2% increase in crop land, while mixed built-up land and vacant land decreased. The study concluded that the urban area of Madurai City increased significantly from 2003 to 2008.
This document summarizes a research paper that evaluates rangeland suitability for livestock production in Dire District, Ethiopia using remote sensing and GIS techniques. Specifically, the study:
1) Analyzed environmental factors like land use/cover, soil, slope, and rainfall as well as socioeconomic factors including access to water, veterinary services, and markets.
2) Classified the study area into suitability classes (high, moderate, marginal, not suitable) for cattle, sheep, goats, and camels using these factors in a GIS multi-criteria analysis.
3) Found that 5.6-10.1% of land was highly suitable for different livestock, 44.7
Land Use Land Cover Change Detection of Gulbarga City Using Remote Sensing an...ijsrd.com
This document summarizes a study that analyzed land use and land cover change in Gulbarga City, India between 2001 and 2012 using remote sensing and GIS techniques. Satellite images from 2001 and 2012 were classified to identify changes in land cover categories such as vegetation, soil, water, and forest area. The study found expansion of urban areas led to losses of agricultural land, vegetation land, and water bodies. This urban sprawl also created environmental issues like decreased air quality and increased temperatures. The goal of the study was to understand land use and land cover change in Gulbarga City and quantify changes that occurred between 2001 and 2012 by comparing satellite image data from the two time periods.
Utilizing LiDar on Dos Hombres to Gran Cacao TransectAmber Wa
The document discusses utilizing LiDAR (Light Detection and Ranging) to map a 12.4 km transect between the Mayan archaeological sites of Dos Hombres and Gran Cacao in Belize. LiDAR uses lasers mounted on aircraft to generate highly accurate terrain models and maps. The project aims to provide training to students and faculty in LiDAR technology, while efficiently mapping the densely forested site. Previous successful uses of LiDAR at other Mesoamerican sites, like Caracol in Belize, demonstrated its ability to reveal hidden archaeological features through canopy cover.
Remote sensing has enabled mapping, monitoring and management of various resources like agriculture, forestry, water, and oceans over the last four decades. It has contributed significantly to development in India through applications like groundwater mapping, wasteland monitoring, flood mapping, agriculture monitoring, fisheries forecasting, snow and glacier studies, and forestry assessments. Current and future uses include urban planning through databases and indicators, and watershed development through projects like Sujala in Karnataka. Advances in remote sensing will continue to improve emergency response, mapping, and geospatial information.
Land use Land Cover change mapping using Remote Sensing and GIS: A case study...IRJET Journal
This document summarizes a study that used remote sensing and GIS techniques to analyze land use and land cover change in Gudur Mandal, Andhra Pradesh, India between 2000 and 2015. Supervised classification with maximum likelihood algorithm was used to classify Landsat satellite imagery into six land cover classes for each time period. Results found significant decreases in cultivated crop land (-35.88%), water bodies (-92.70%), and forest (-77.59%) between 2000 and 2015, along with increases in residential area (30.76%) and uncultivated crop land (151.68%). The changes indicate threats to the local agriculture and greater management of water resources will be needed.
1. The document discusses a study that uses geographic information systems (GIS) to assess land suitability for growing pummelo trees in Nakornpathom province, Thailand.
2. The study analyzed factors like soil nutrients, pH, drainage and distance to transportation to classify lands as highly, moderately or poorly suitable for pummelo cultivation.
3. The results found that most areas in Nakornchaisri, Kampaengsaen, Don Tum and Muang districts were highly suitable, while most of Nakornpathom province was moderately suitable and some areas in Banglen district were poorly suitable.
This document summarizes a study that assessed the inter-relationships between vegetation productivity, rainfall, population, and land cover over the Bani River Basin in Mali, West Africa from 1982 to 2011. The study analyzed long-term trends in the Normalized Difference Vegetation Index (NDVI) and rainfall using the Mann-Kendall test. It also analyzed the relationships between NDVI and rainfall, and between NDVI and population density using Pearson correlation. Additionally, it computed land use/land cover conversion rates using Landsat imagery and ground surveys. The results showed that vegetation greening trends were associated with areas of natural vegetation, concurrent with increases in rainfall over the period, supporting the hypothesis that re-greening was due
Mapping and Monitoring Spatial-Temporal Cover Change of Prosopis Species Colo...inventionjournals
ABSTRACT: This study integrates Gis and remote sensing to detect, quantify and monitor the rate at which Prosopis species colonization has been taking place since its introduction. Multi-date Landsat 30m resolution imageries covering a period of 25 years were classified into four classes i.e. Prosopis species dominated canopy, mixed woodland, grass land and bush land and finally bare land and agricultural fields. Change detection analysis was performed using 10% threshold to identify and quantify areas where change or No change has occurred. The results indicate that the area under bare land and agricultural fields decreased at a rate of 18.22% per year from 29% in 1985 to 3% in 1990. Between 2005 and 2010 it decreased from 9% in 2005 to 5% in 2010 at a rate of 8.94% per year. Prosopis species colonization has been increasing since 1985 where it was at 0% increasing to 51% in 1990 at a rate of 58.18% per year. Between 2005 and 2010 it decreased from 56% in 2005 to stand at 44% in 2010 at a rate of 4.34% per year. The study found out that there is no threat of desertification in the study area as a result of Prosopis species colonizing the landscape. More studies to be done to identify sustainable method of controlling Prosopis species colonization to avoid more loss of agricultural land and grazing fields.
LAND USE /LAND COVER CLASSIFICATION AND CHANGE DETECTION USING GEOGRAPHICAL I...IAEME Publication
Land use and land cover change has become a central component in current strategies for managing natural resources and monitoring environmental changes. Geographical information system and image processing techniques used for the analysis of land use/land cover and change detection of Sukhana Basin of Aurangabad District, Maharashtra state. The tools used ArcGIS10.1 and ERDAS IMAGINE9.1, landsat images of 1996, 2003and 2014. From land use / land cover change detection it is found that during 1996-2014, water bodies cover have loss of 4 Sq. Km. Barren land have 146 Sq.Km. loss and forest area with 96 Sq.Km. loss. It is found that urbanization area has gain of 51 Sq.Km. and agricultural land cover also have gain of 195 Sq.Km.
This document summarizes a study that used remote sensing and GIS techniques to identify suitable alternative landfill sites for waste disposal around Mysore City, India. Seven new potential landfill sites were identified based on factors like soil type, lineaments, topography, land use, and distance from habitations and water bodies. The existing landfill site is located within a high risk core zone above a major lineament, potentially contaminating groundwater. The newly identified sites are located in the buffer zone in areas with clay-rich soils and gentle slopes, avoiding major lineaments and water resources to help ensure environmental protection.
This document discusses the use of geographic information systems (GIS), remote sensing (RS), and global positioning systems (GPS) for forest mapping and management. It explains that these technologies have revolutionized forest resource assessment by reducing time and costs. GIS is useful for tasks like resource management, harvest planning, fire management, and map production. RS provides accurate data over large areas, while GIS allows for spatial analysis and mapping. Together these tools provide crucial information for planning and managing forest resources. The document also outlines some future prospects and challenges for using these technologies in forestry.
Remote Sensing And GIS Application In Wetland MappingSwetha A
This document discusses remote sensing and GIS applications for wetland mapping. It begins by defining wetlands and describing some of the largest in the world. The three main criteria for identifying wetlands - hydric soils, hydrophytic vegetation, and hydrology - are introduced. Remote sensing data, including IRS P6 LISS III imagery, is used to map wetlands in Karnataka, India. Indices like NDWI, MNDWI, NDVI, and NDPI are calculated from the multi-spectral bands to identify wetland areas. GIS is then used to analyze and interpret the remote sensing data spatially and temporally. Final maps are produced showing the distribution and types of wetlands identified in India and specifically
Monitoring_and_Prediction_of_Land_Use_Lasanjoy roy
This document summarizes a study that used remote sensing and geospatial modeling to analyze land use/land cover change in the southeastern hilly region of Bangladesh between 1989-2014. Satellite imagery from 1989, 2000 and 2014 was classified to generate land use maps for each time period. Markov chain and cellular automata models were then used to model and predict land use change, showing decreases in forest land and increases in shrub land and cropland over time. The models were also used to simulate potential land use in 2028 and 2042 under current trends.
How Earth observation can support monitoring wetlands and peatlandsCIFOR-ICRAF
Presented by Frank Martin Seifert of the European Space Agency at the Bonn Climate Change Conference on 11 May 2017, at a side event titled 'Re-discovering the magnificent carbon storage potential of wetlands and peatlands'.
This document discusses methods for inventorying and monitoring tree resources outside of forests using high-resolution aerial imagery. It summarizes research mapping trees in agricultural landscapes to quantify their ecosystem functions. The research uses object-based image analysis of National Agriculture Imagery Program imagery to map trees at county-scales. Functions like windbreaks and riparian areas are identified. Historical windbreak plantings are also digitized from archives to assess changes over time. The research aims to fill gaps in quantifying trees outside forests to better account for their benefits.
This document summarizes a study that used remote sensing to map land use and land cover in Tikamgarh district, Madhya Pradesh, India. Specifically, it used an unsupervised digital classification technique on IRS-1C PAN+LISS-III satellite imagery to generate a land use/land cover map for the region. The study area is described as covering 5,048 square km in northwestern Madhya Pradesh along the Betwa and Dhasan rivers. According to the classification, crop land comprised the largest area compared to other land uses. The goal was to understand local land use/cover changes over spatial and temporal scales to inform sustainable development recommendations.
This summarizes a document about change detection techniques in remote sensing for analyzing land use and land cover changes. Remote sensing using aerial photographs and satellite imagery allows efficient monitoring of land cover changes compared to traditional field surveys. Change detection involves identifying transformations of land cover types over time and space using multi-temporal remote sensing data. Common techniques include comparing imagery from Landsat, QuickBird and other satellite sensors to detect changes in agriculture, deforestation, urban growth and other human and natural impacts on the earth's surface.
1. Soil spectroscopy is being used in the Africa Soil Information Service (AfSIS) to monitor soils across Africa and identify soil properties and issues.
2. Infrared spectroscopy allows identification of mineral composition, organic matter, and other properties in soils to help with agricultural and environmental management.
3. AfSIS has established a network of soil spectral labs across Africa and provides online tools and services to analyze soil spectra and properties.
Long-term observed Precipitation Trends in Arid and Semi-arid Lands, Baringo ...Premier Publishers
The research was conducted to validate the pastoralists’ and agro-pastoralists’ claim that there has been an increasingly variable and changing climate in the study area. The station average and Theissen polygon methods were used to estimate the mean areal precipitation of the small (Mogotio and Baringo South Sub-counties) and the large area (Baringo County), respectively. The aim of the current study is to analyse rainfall time series over long term observed precipitation and a wide area, detecting potential trends and assessing their significance. Monthly precipitation data for the period 1974-2003 from six weather stations, located mainly in Mogotio and Baringo South sub-counties and covering 3906km2 were used in the analysis. The data were quality controlled to ensure no missing data and any inconsistencies. Linear regression analysis of the database highlighted that; the trends were predominantly negative, both where the average and Theissen polygon methods were used and over the whole reference period. The negative trends are not significant. This finding implies that the study area has been suffering a precipitation decrease especially in the period under review.
An expert system model for identifying and mapping tropical wetlands and peat...CIFOR-ICRAF
Presented by Rosa Maria Roman-Cuesta at the Bonn Climate Change Conference on 11 May 2017, at a side event title 'Re-discovering the magnificent carbon storage potential of wetlands and peatlands'.
Assessment of Land Use Land Cover Classification through Geospatial Approach:...Premier Publishers
Earth's land use/land cover (LC/LU) classification provides valuable information particularly on natural resources, mapping and its monitoring. There is a significant change on LC/LU across the globe due to the climatic changes, rapid increase in population and over demand of economic natural resources. Remote Sensing (RS) satellite data with its synoptic view and multispectral data provides essential information in proper planning of LU/LC conditions of larger areas. The study aims to map and monitor the existing LU/LC classification scientifically using geospatial tools in database generation, analyses and information extraction. Thematic maps of the study area are prepared using satellite images in conjunction with collateral data Survey of India (SoI) toposheets, forest and wasteland maps. An attempt have been made to delineate the Level-I, Level-II and Level-III LU/LC classification system through NRSC guidelines (2011) using both Digital Image Processing (DIP) and Visual Image Interpretation Techniques (VIIT) by GIS software’s with limited Ground Truth Check (GTC). More accurate classification is observed in case of digital technique as compared to that of visual technique in terms of area statistics. The final results highlight the potentiality of geospatial technique in optimal and sustainable land use planning of natural resource and its management.
The document describes a 3D rendering of a Viking longhouse created by Asher Ely. The longhouse features Nordic architecture and furnishings appropriate for the period, including mostly wood construction and a cast iron kettle. The scene aims to capture the feel of warmth inside during a cold winter morning. The creator seeks to add more props, weapons, and armor to bring more life to the space and rework some models.
Melissa Helms has 6 years of experience helping others reach their weight loss goals and become motivated. She teaches from her own experience and offers the opportunity to become an ItWorks distributor, which provides wholesale pricing on products, bonuses for recruiting customers and hitting sales ranks, and discounts for the holidays. Interested parties can contact Melissa at Inspire2bmore@gmail.com or place orders at www.inspire2bmore.com.
1. The document discusses a study that uses geographic information systems (GIS) to assess land suitability for growing pummelo trees in Nakornpathom province, Thailand.
2. The study analyzed factors like soil nutrients, pH, drainage and distance to transportation to classify lands as highly, moderately or poorly suitable for pummelo cultivation.
3. The results found that most areas in Nakornchaisri, Kampaengsaen, Don Tum and Muang districts were highly suitable, while most of Nakornpathom province was moderately suitable and some areas in Banglen district were poorly suitable.
This document summarizes a study that assessed the inter-relationships between vegetation productivity, rainfall, population, and land cover over the Bani River Basin in Mali, West Africa from 1982 to 2011. The study analyzed long-term trends in the Normalized Difference Vegetation Index (NDVI) and rainfall using the Mann-Kendall test. It also analyzed the relationships between NDVI and rainfall, and between NDVI and population density using Pearson correlation. Additionally, it computed land use/land cover conversion rates using Landsat imagery and ground surveys. The results showed that vegetation greening trends were associated with areas of natural vegetation, concurrent with increases in rainfall over the period, supporting the hypothesis that re-greening was due
Mapping and Monitoring Spatial-Temporal Cover Change of Prosopis Species Colo...inventionjournals
ABSTRACT: This study integrates Gis and remote sensing to detect, quantify and monitor the rate at which Prosopis species colonization has been taking place since its introduction. Multi-date Landsat 30m resolution imageries covering a period of 25 years were classified into four classes i.e. Prosopis species dominated canopy, mixed woodland, grass land and bush land and finally bare land and agricultural fields. Change detection analysis was performed using 10% threshold to identify and quantify areas where change or No change has occurred. The results indicate that the area under bare land and agricultural fields decreased at a rate of 18.22% per year from 29% in 1985 to 3% in 1990. Between 2005 and 2010 it decreased from 9% in 2005 to 5% in 2010 at a rate of 8.94% per year. Prosopis species colonization has been increasing since 1985 where it was at 0% increasing to 51% in 1990 at a rate of 58.18% per year. Between 2005 and 2010 it decreased from 56% in 2005 to stand at 44% in 2010 at a rate of 4.34% per year. The study found out that there is no threat of desertification in the study area as a result of Prosopis species colonizing the landscape. More studies to be done to identify sustainable method of controlling Prosopis species colonization to avoid more loss of agricultural land and grazing fields.
LAND USE /LAND COVER CLASSIFICATION AND CHANGE DETECTION USING GEOGRAPHICAL I...IAEME Publication
Land use and land cover change has become a central component in current strategies for managing natural resources and monitoring environmental changes. Geographical information system and image processing techniques used for the analysis of land use/land cover and change detection of Sukhana Basin of Aurangabad District, Maharashtra state. The tools used ArcGIS10.1 and ERDAS IMAGINE9.1, landsat images of 1996, 2003and 2014. From land use / land cover change detection it is found that during 1996-2014, water bodies cover have loss of 4 Sq. Km. Barren land have 146 Sq.Km. loss and forest area with 96 Sq.Km. loss. It is found that urbanization area has gain of 51 Sq.Km. and agricultural land cover also have gain of 195 Sq.Km.
This document summarizes a study that used remote sensing and GIS techniques to identify suitable alternative landfill sites for waste disposal around Mysore City, India. Seven new potential landfill sites were identified based on factors like soil type, lineaments, topography, land use, and distance from habitations and water bodies. The existing landfill site is located within a high risk core zone above a major lineament, potentially contaminating groundwater. The newly identified sites are located in the buffer zone in areas with clay-rich soils and gentle slopes, avoiding major lineaments and water resources to help ensure environmental protection.
This document discusses the use of geographic information systems (GIS), remote sensing (RS), and global positioning systems (GPS) for forest mapping and management. It explains that these technologies have revolutionized forest resource assessment by reducing time and costs. GIS is useful for tasks like resource management, harvest planning, fire management, and map production. RS provides accurate data over large areas, while GIS allows for spatial analysis and mapping. Together these tools provide crucial information for planning and managing forest resources. The document also outlines some future prospects and challenges for using these technologies in forestry.
Remote Sensing And GIS Application In Wetland MappingSwetha A
This document discusses remote sensing and GIS applications for wetland mapping. It begins by defining wetlands and describing some of the largest in the world. The three main criteria for identifying wetlands - hydric soils, hydrophytic vegetation, and hydrology - are introduced. Remote sensing data, including IRS P6 LISS III imagery, is used to map wetlands in Karnataka, India. Indices like NDWI, MNDWI, NDVI, and NDPI are calculated from the multi-spectral bands to identify wetland areas. GIS is then used to analyze and interpret the remote sensing data spatially and temporally. Final maps are produced showing the distribution and types of wetlands identified in India and specifically
Monitoring_and_Prediction_of_Land_Use_Lasanjoy roy
This document summarizes a study that used remote sensing and geospatial modeling to analyze land use/land cover change in the southeastern hilly region of Bangladesh between 1989-2014. Satellite imagery from 1989, 2000 and 2014 was classified to generate land use maps for each time period. Markov chain and cellular automata models were then used to model and predict land use change, showing decreases in forest land and increases in shrub land and cropland over time. The models were also used to simulate potential land use in 2028 and 2042 under current trends.
How Earth observation can support monitoring wetlands and peatlandsCIFOR-ICRAF
Presented by Frank Martin Seifert of the European Space Agency at the Bonn Climate Change Conference on 11 May 2017, at a side event titled 'Re-discovering the magnificent carbon storage potential of wetlands and peatlands'.
This document discusses methods for inventorying and monitoring tree resources outside of forests using high-resolution aerial imagery. It summarizes research mapping trees in agricultural landscapes to quantify their ecosystem functions. The research uses object-based image analysis of National Agriculture Imagery Program imagery to map trees at county-scales. Functions like windbreaks and riparian areas are identified. Historical windbreak plantings are also digitized from archives to assess changes over time. The research aims to fill gaps in quantifying trees outside forests to better account for their benefits.
This document summarizes a study that used remote sensing to map land use and land cover in Tikamgarh district, Madhya Pradesh, India. Specifically, it used an unsupervised digital classification technique on IRS-1C PAN+LISS-III satellite imagery to generate a land use/land cover map for the region. The study area is described as covering 5,048 square km in northwestern Madhya Pradesh along the Betwa and Dhasan rivers. According to the classification, crop land comprised the largest area compared to other land uses. The goal was to understand local land use/cover changes over spatial and temporal scales to inform sustainable development recommendations.
This summarizes a document about change detection techniques in remote sensing for analyzing land use and land cover changes. Remote sensing using aerial photographs and satellite imagery allows efficient monitoring of land cover changes compared to traditional field surveys. Change detection involves identifying transformations of land cover types over time and space using multi-temporal remote sensing data. Common techniques include comparing imagery from Landsat, QuickBird and other satellite sensors to detect changes in agriculture, deforestation, urban growth and other human and natural impacts on the earth's surface.
1. Soil spectroscopy is being used in the Africa Soil Information Service (AfSIS) to monitor soils across Africa and identify soil properties and issues.
2. Infrared spectroscopy allows identification of mineral composition, organic matter, and other properties in soils to help with agricultural and environmental management.
3. AfSIS has established a network of soil spectral labs across Africa and provides online tools and services to analyze soil spectra and properties.
Long-term observed Precipitation Trends in Arid and Semi-arid Lands, Baringo ...Premier Publishers
The research was conducted to validate the pastoralists’ and agro-pastoralists’ claim that there has been an increasingly variable and changing climate in the study area. The station average and Theissen polygon methods were used to estimate the mean areal precipitation of the small (Mogotio and Baringo South Sub-counties) and the large area (Baringo County), respectively. The aim of the current study is to analyse rainfall time series over long term observed precipitation and a wide area, detecting potential trends and assessing their significance. Monthly precipitation data for the period 1974-2003 from six weather stations, located mainly in Mogotio and Baringo South sub-counties and covering 3906km2 were used in the analysis. The data were quality controlled to ensure no missing data and any inconsistencies. Linear regression analysis of the database highlighted that; the trends were predominantly negative, both where the average and Theissen polygon methods were used and over the whole reference period. The negative trends are not significant. This finding implies that the study area has been suffering a precipitation decrease especially in the period under review.
An expert system model for identifying and mapping tropical wetlands and peat...CIFOR-ICRAF
Presented by Rosa Maria Roman-Cuesta at the Bonn Climate Change Conference on 11 May 2017, at a side event title 'Re-discovering the magnificent carbon storage potential of wetlands and peatlands'.
Assessment of Land Use Land Cover Classification through Geospatial Approach:...Premier Publishers
Earth's land use/land cover (LC/LU) classification provides valuable information particularly on natural resources, mapping and its monitoring. There is a significant change on LC/LU across the globe due to the climatic changes, rapid increase in population and over demand of economic natural resources. Remote Sensing (RS) satellite data with its synoptic view and multispectral data provides essential information in proper planning of LU/LC conditions of larger areas. The study aims to map and monitor the existing LU/LC classification scientifically using geospatial tools in database generation, analyses and information extraction. Thematic maps of the study area are prepared using satellite images in conjunction with collateral data Survey of India (SoI) toposheets, forest and wasteland maps. An attempt have been made to delineate the Level-I, Level-II and Level-III LU/LC classification system through NRSC guidelines (2011) using both Digital Image Processing (DIP) and Visual Image Interpretation Techniques (VIIT) by GIS software’s with limited Ground Truth Check (GTC). More accurate classification is observed in case of digital technique as compared to that of visual technique in terms of area statistics. The final results highlight the potentiality of geospatial technique in optimal and sustainable land use planning of natural resource and its management.
The document describes a 3D rendering of a Viking longhouse created by Asher Ely. The longhouse features Nordic architecture and furnishings appropriate for the period, including mostly wood construction and a cast iron kettle. The scene aims to capture the feel of warmth inside during a cold winter morning. The creator seeks to add more props, weapons, and armor to bring more life to the space and rework some models.
Melissa Helms has 6 years of experience helping others reach their weight loss goals and become motivated. She teaches from her own experience and offers the opportunity to become an ItWorks distributor, which provides wholesale pricing on products, bonuses for recruiting customers and hitting sales ranks, and discounts for the holidays. Interested parties can contact Melissa at Inspire2bmore@gmail.com or place orders at www.inspire2bmore.com.
This curriculum vitae is for Ali Akbar, a safety officer with over 10 years of experience. He has a diploma in industrial safety and health and seeks to utilize his skills and experience in a challenging position at a reputable organization. His responsibilities include ensuring safety compliance and regulations, conducting inspections, managing safety reporting and training, and coordinating emergency response. He is proficient in problem solving, information processing, experimentation, creativity, and teamwork.
Prashant Jadhav is a technical support executive with over 3 years of experience in customer support roles. He currently works for Wipro Limited in Pune, India, where his responsibilities include handling network issues, data maintenance, client interaction, and training new team members. Previously he has worked for Ultratech Limited, Spectrum Business Support Ltd, and IBM in technical support, IT consulting, and customer service roles. He holds a Diploma in Computer Engineering and is looking to leverage his experience in utilizing resources effectively to improve efficiency.
This document discusses urbanization trends globally and examines why some countries have undergone rapid urbanization without corresponding increases in GDP per capita. It notes that while cities were historically symbols of wealth and power, many of today's largest megacities have emerged in developing countries without significant economic growth. Maps and data from the UN show urban growth rates over 3% concentrated in Asia and Africa since 1990. The top contributors to projected urban population increases by 2050 will be China, India, Nigeria and other developing nations across a wide range of income levels. This suggests urbanization has become decoupled from national wealth, with potential risks for poor megacities lacking strong institutions.
1) The document is a nomination for "Best Hygienist (West Midlands) 2012" and describes the career and qualifications of Rebecca Jane Gumm.
2) Gumm has over 12 years of experience as a dental hygienist and has worked in a variety of settings including general dental practices, dental hospitals, and community dental services.
3) She is praised for her communication skills, commitment to patient care, and efforts to improve oral health education.
We all know that consumers love mail. They love it even more when it's out of the ordinary. If you're planning or even thinking about using direct mail for your next marketing campaign, check out these 10 mail pieces for great inspiration.
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Radar and optical remote sensing data evaluation and fusion; a case study for...rsmahabir
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INTEGRATED TECHNOLOGY OF DATA REMOTE SENSING AND GIS TECHNIQUES ASSESS THE LA...acijjournal
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Subset using Imagery software to clip the study area. The clipped satellite imagery has Send to prepare the
land use and land cover map using supervised classification.
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Forecasting Model of Flood Inundated Areas along Sharda River in U.P.iosrjce
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Environment and Development are the two wheels of the cart. However, they become antagonists at some
points. It has been witnessed many a times that development is done at the cost of environment. Analysis and
assessment tools like GIS along with Remote Sensing have proved to be very efficient and effective and hence
useful for management of natural resources. Groundwater is a precious resource of limited extent. In order to
ensure a judicious use of groundwater, proper evaluation is required. There is an urgent need of planned and
optimal development of water resources. An appropriate strategy is required to develop water resources with
planning based on conjunctive use of surface and subsurface water resources. Integrated remote sensing and GIS
can provide the appropriate platform for convergent analysis of diverse data sets for decision making in
groundwater management and planning. Sustainable water resources development and management necessarily
depends on proper planning, implementation, operation and maintenance. The interpretation of remote sensing
data in conjunction with conventional data and sufficient ground truth information makes it possible to identify
and outline various ground features such as geological structures, geomorphic features and their hydrologic
characters that may serve as direct or indirect indicators of the presence of ground and surface water. Remotely
sensed data provides unbiased information on geology, geomorphology, structural pattern and recharging
conditions, which logically define the groundwater regime of an area. Groundwater resource potential has been
evaluated in Pulivendula-Sanivaripalli, Kadapa district, Andhra Pradesh, India, using remote sensing and
Geographic information system. Under this study, three thematic maps viz. Geological map (Lithology and
Structure), Geomorphological map and Hydro morphological maps were prepared. These thematic maps have
been integrated with the help of GIS. Appropriate weightage has been assigned to various factors controlling
occurrence of groundwater to assess the groundwater potential in each segment of the study area. The area has
been classified into high potential, moderate potential, low potential and non-potential zones landforms ground
water development on the basis of hydromorphological studies. Some of the favorable locations have been
suggested to impound the excessive run off so as to augment the ground water resources of the area.
Evaluation of Groundwater Resource Potential using GIS and Remote Sensing App...IJERA Editor
Environment and Development are the two wheels of the cart. However, they become antagonists at some
points. It has been witnessed many a times that development is done at the cost of environment. Analysis and
assessment tools like GIS along with Remote Sensing have proved to be very efficient and effective and hence
useful for management of natural resources. Groundwater is a precious resource of limited extent. In order to
ensure a judicious use of groundwater, proper evaluation is required. There is an urgent need of planned and
optimal development of water resources. An appropriate strategy is required to develop water resources with
planning based on conjunctive use of surface and subsurface water resources. Integrated remote sensing and GIS
can provide the appropriate platform for convergent analysis of diverse data sets for decision making in
groundwater management and planning. Sustainable water resources development and management necessarily
depends on proper planning, implementation, operation and maintenance. The interpretation of remote sensing
data in conjunction with conventional data and sufficient ground truth information makes it possible to identify
and outline various ground features such as geological structures, geomorphic features and their hydrologic
characters that may serve as direct or indirect indicators of the presence of ground and surface water. Remotely
sensed data provides unbiased information on geology, geomorphology, structural pattern and recharging
conditions, which logically define the groundwater regime of an area. Groundwater resource potential has been
evaluated in Pulivendula-Sanivaripalli, Kadapa district, Andhra Pradesh, India, using remote sensing and
Geographic information system. Under this study, three thematic maps viz. Geological map (Lithology and
Structure), Geomorphological map and Hydro morphological maps were prepared. These thematic maps have
been integrated with the help of GIS. Appropriate weightage has been assigned to various factors controlling
occurrence of groundwater to assess the groundwater potential in each segment of the study area. The area has
been classified into high potential, moderate potential, low potential and non-potential zones landforms ground
water development on the basis of hydromorphological studies. Some of the favorable locations have been
suggested to impound the excessive run off so as to augment the ground water resources of the area.
Similar to Elmes_Yarleque_Mapping_licit_illicit_gold_mining_in_madre_de_dios_Peru (20)
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Mapping licit and illicit mining activity
in the Madre de Dios region of Peru
Arthur Elmes
a
, Josué Gabriel Yarlequé Ipanaqué
a
, John Rogan
a
,
Nicholas Cuba
a
& Anthony Bebbington
a
a
Graduate School of Geography, Clark University, Worcester, MA
01610, USA
Published online: 20 Oct 2014.
To cite this article: Arthur Elmes, Josué Gabriel Yarlequé Ipanaqué, John Rogan, Nicholas Cuba &
Anthony Bebbington (2014) Mapping licit and illicit mining activity in the Madre de Dios region of
Peru, Remote Sensing Letters, 5:10, 882-891, DOI: 10.1080/2150704X.2014.973080
To link to this article: http://dx.doi.org/10.1080/2150704X.2014.973080
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4. ASM monitoring methods, especially in locations where no regulatory information is available
(Hilson 2002, 2005; Bebbington et al. 2008). The goal of this paper is to develop methods for
use with freely available Landsat imagery, Advanced Spaceborne Thermal Emission and
Reflection Radiometer (ASTER) elevation data and ancillary GIS data, to identify ASM
mining operations and to quantify the extent of licit versus illicit ASM in Madre de Dios.
Few studies have quantified the extent and magnitude of surface mining activities
associated with ASM, as there has been more focus on larger-scale, industrialized mining
(e.g. Latifovic et al. 2005; Slonecker et al. 2010; Erener 2011). For example, Latifovic
et al. (2005) used post-classification change detection of Landsat-5 Thematic Mapper
(TM) and Lansat-7 Enhanced Thematic Mapper Plus (ETM+) imagery to track decreasing
trends in vegetation productivity related to land change caused by oil sand processing in
the Athabasca oil sands region in Canada. Baynard (2011) and Baynard, Ellis, and Davis
(2013) addressed direct and indirect landscape effects of petroleum exploration and
extraction activities in tropical South America, using a combination of Landsat TM/
ETM+ imagery and GIS data to create Landscape Infrastructure Footprints. This work
highlights the importance of infrastructure development (e.g. roads, clearings, tailing
piles, parking zones) and regulation as an explanatory variable for predicting landscape
fragmentation and degradation in a mining context. Swenson et al. (2011) used Landsat-5
TM imagery (2003–2009) to map deforestation in the Department of Madre de Dios,
indicating that in this time period approximately 6600 ha of primary tropical forest and
wetlands were converted to mine-related ponds and tailings. The rate of forest conversion
was shown to increase six-fold from 2003–2006 to 2006–2009, and it was linked to an
annual increase in global gold prices during the period (Swenson et al. 2011).
While research in remote sensing of illicit mining has been promising, the principal
challenge lies in detection of the small, remote and intentionally clandestine patches of
disturbance typical of ASM, using moderate spatial resolution (~30 m) imagery (Asner
et al. 2013). While several large-scale mining areas exist in the study area (Figure 1) on
the order of 100 km2
, ASM operations often occur on scales of tens of km2
, meaning that
many ASM sites may go undetected using conventional hard-classification methods. It is
important to monitor the proliferation of these smaller ASM locations, since they are
contributing to the rapid fragmentation of the region’s forest cover (Southworth et al.
2011; Swenson et al. 2011; Asner et al. 2013). The larger and more permanent mining
operations, known as Huepetuhe, Guacamayo and Delta-1, are easily captured by mod-
erate spatial resolution data and commonly used classification methods, such as maximum
likelihood classification. Conversely, the smaller, distributed nature of much ASM in
Madre de Dios results in predominantly mixed pixels, making detection difficult or
impossible with such methods. By spectrally unmixing these pixels into proportional
surface features, it is possible to extract valuable information from moderate spatial
resolution imagery, to produce maps of ASM. Although legally permitted mineral con-
cession areas have been delineated by the Peruvian government, the extent of mineral
extraction within these areas, that is, the proportion of legal exploitation, has not been
monitored, nor has the incidence of ASM outside of permitted concessions been mapped.
ASM in Madre de Dios has caused an estimated 320 km2
(32,000 ha) of forest loss
(Fraser 2009), with the rate of loss increasing from 292 ha/yr in 2006 to 1915 ha/yr in
2009, yielding a total estimate of 15,500 ha of ASM in 2009 (Swenson et al. 2011). ASM
areas are spatially and spectrally distinct based on their proximity to stream channels and a
high degree of exposed soil, in and around the associated ponds and tailings (Swenson
et al. 2011). The Huepetuhe, Guacamayo and Delta-1 mining areas represent these
characteristics and are easily detected, as they cover areas on the order of 100 km2
.
Remote Sensing Letters 883
Downloadedby[JosuéYarlequéIpanaqué]at15:4224December2014
5. Conversely, many smaller ASM sites (<10 km2
) dot the study area. Asner et al. (2013)
estimate approximately 45,000 ha of ASM in 2011, far more than the Swenson et al.
(2011) estimate; this larger estimate reflects the increased detection rate of ASM using
subpixel methods. The primary goal of this study is to further refine the detection of these
small ASM locations and to assess their extent relative to legal mining concessions.
2. Study area
The study area is a 57,000 km2
subset of the Madre de Dios Department of Peru
(Figure 1). Both licit and illicit gold mining have been carried out in this region since
the 1980s, with a rapid increase in ASM activity in the last decade (Asner et al. 2010,
2013; Swenson et al. 2011; Damonte et al. 2013). Although initially supported by the
Peruvian government with legal concessions, much ASM is now carried out illegally, as
focus has shifted to larger-scale mines operated with foreign investments (Damonte 2008,
135–74). Nevertheless, ASM has continued to expand, due to both the increase in
international gold prices and the overall weakness of government in Madre de Dios
(Swenson et al. 2011; Damonte 2014). Indeed, in Peru (Mosquera, Chávez, and Pachas
2009; Pachas 2011) and elsewhere (e.g. Hilson 2005), efforts to monitor ASM and foster
its formalization have been hindered by limited government capacity and a more general
inadequacy of knowledge regarding the composition and organization of the ASM sector.
For the purpose of this study, the Madre de Dios study area was defined by the
intersection of four Landsat scenes and the Peru national border with Bolivia and Brazil,
as indicated by Figure 1. Dominant vegetation comprises mostly tropical lowland rain-
forest with high biodiversity, and the area is one of the largest remaining uninterrupted
72° 0′ 0″ W 71° 0′ 0″ W 70° 0′ 0″ W
72° 0′ 0″ W 71° 0′ 0″ W 70° 0′ 0″ W
69° 0′ 0″ W
13° 0′ 0″ S
12° 0′ 0″ S
11° 0′ 0″ S
10° 0′ 0″ S
Major Roads
Major Rivers
Study Area
Active Concessions as of 2011
0 50 100 km
13° 0′ 0″ S
12° 0′ 0″ S
11° 0′ 0″ S
10° 0′ 0″ S
69° 0′ 0″ W
Figure 1. The location of the study area in Madre de Dios, Peru.
884 A. Elmes et al.
Downloadedby[JosuéYarlequéIpanaqué]at15:4224December2014
6. expanses of rainforest in the region (Swenson et al. 2011). Three major rivers, critical
water supplies for ASM, cross the study area: the Madre de Dios from west to east and
Colorado and Inambari from south to north. The study area is topographically flat, with a
mean slope of 7% and a mean elevation of 330 m. The recently constructed Interoceanic
Highway crosses through the southeastern portion of the region; this has helped spur
deforestation for land development (Naughton-Treves 2004; Southworth et al. 2011).
3. Data
Landsat-5 TM imagery provided the primary data for this mapping project. The study area
comprised tiles from path/row 2/68, 2/29, 3/68, 3/69, with imagery captured on 27 August
2011 and 3 September 2011. These image dates correspond to the mid-dry season
(SENAMHI 2011), aiding in detection of ASM areas against the vegetation background.
The imagery was downloaded from the USGS EarthExplorer website (http://earthexplorer.
usgs.gov/) as pre-atmospherically corrected and radiometrically calibrated reflectance images
and was then mosaicked and clipped to the study area boundaries. Ancillary data include
active mining concession polygons for 2011 (http://geocatmin.ingemmet.gob.pe/geocatmin/),
an ASTER 30-m digital elevation model and derived slope map, stream channel polygon data
obtained from the Peruvian Ministry of the Environment (MINAM) Geoserver and a major
roads polygon data-set. The streams and roads polygons were used to create distance rasters
for the image classification process. Map validation relied on two fine spatial imagery data-
sets comprising 17 individual tiles covering approximately 12,000 km2
, consisting of 2.5 m
QuickBird and 2 m WorldView-2 multispectral, as well as 1 m WorldView-1 panchromatic
imagery, acquired between August 2010 and August 2012 (DigitalGlobe 2010–2012).
4. Methods
4.1 Spectral mixture analysis
SMA was carried out on the Landsat-5 TM imagery to extract sub-pixel information of
proportional coverage of each endmember class per pixel. SMA yields a set of images
equal to the number of endmembers, plus one image showing residual values per pixel,
indicating how well the combination of endmembers represents the pixel’s actual reflec-
tance values. Spectral unmixing was deemed to be acceptably accurate based on the
overall low residuals throughout the study area (<0.05). Much of the residual error was
deemed to be noise, with little geographic coherence, except along rivers, which showed
some degree of clustered, comparatively high residual values.
The endmembers were selected based on contextual scene knowledge and trial-and-
error iteration, ultimately yielding the following endmembers: photosynthetic vegetation,
non-photosynthetic vegetation, water and three soil types, as shown Figure 2. The mineral
composition of the soil endmembers is unknown; however, they are representative of the
dominant soil signals in the imagery. The spectral responses of soil types 1 and 3 are similar
in shape, differing mostly in magnitude, and conform to the iron-dominated reflectance
curves of many soils (Hunt 1977). Soil type 2 is similar through bands 1 to 4, but shows a
marked reflection decrease in the shortwave infrared bands, indicating either mineral-based
or water-based absorption. ASM produces a somewhat heterogeneous land cover, consist-
ing primarily of purification pools interspersed with exposed soil; overall, exposed soil and
turbid water dominate the spectral response for these sites (Asner et al. 2013). The SMA
process was iterated with different endmembers and different endmember training pixels
until the overall residuals image showed residual values no greater than 0.05.
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7. 4.2 Image classification
CTA was carried out using the six fraction images, as well as the elevation, slope, distance to
rivers and distance to roads images. The CTA used the Gini splitting rule, which maximizes
node purity (Zambon et al. 2006). Five categories were used for the final classification: ASM,
water, agriculture, forest and natural alluvial deposits. A 3 × 3 mode filter was used on the
land-cover map to reduce speckle caused by topographic and other shading influences.
4.3 Active concessions overlay
The extent of licit mineral exploration was determined by overlaying the ASM classifica-
tion map with a polygon data-set of active mining concession areas. Locations within the
study area that did not fall within the active concessions polygon were deemed ‘illicit’,
while those within were deemed ‘licit’ (Cuba et al. 2014).
4.4 Map validation
QuickBird, WorldView-1 and WorldView-2 imagery were used to validate the Landsat-
derived land-cover map. This imagery was acquired for a coincident time period, with
panchromatic and multispectral images from August 2010 to August 2012. A categori-
cally and spatially stratified sampling design used 580 validation points that were
randomly generated within the study region, with a minimum of 50 points per land-
cover category. Further, the points were constrained to a 2 km buffer of stream channels,
in order to avoid a spuriously inflated accuracy estimate caused by the forest class, which
is both the most abundant and the most spectrally distinct. This spatial stratification relies
on the observation that ASM activities require proximity to a major water source for
operation (Cuba et al. 2014). For each validation point, the true land cover was ascer-
tained by manual interpretation of the fine spatial resolution imagery. The mapped and
true cover was then cross-tabulated for accuracy assessment, yielding commission error,
omission error and overall accuracy, shown in Table 3. Because the distribution of
reference samples per category was not proportional to the area of that category in the
map, the per-category accuracies were weighted based on their areal proportion to
calculate the overall accuracy. For example, since forest class dominates the study area,
its relative contribution to overall accuracy is much higher than agriculture, which covers
much less area.
TM Band Number
Reflectance
0.00
1 2 3 4 5 6
Water
Vegetation
Soil 3
Soil 2
Soil 1
NPV
0.10
0.20
0.30
0.40
0.50
0.60
Figure 2. Endmember spectral signatures used to unmix Landsat imagery in this study.
886 A. Elmes et al.
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8. 5. Results
Based on the reference imagery, the overall area-weighted map accuracy was 96% (87%
raw overall accuracy) (Table 3). The omission error for ASM was 29%, and the commission
error was 31%. Classification tree results showed primary decision splits for the distance-to-
rivers, proportion vegetation and proportion water, indicating that these variables most
clearly separate the target categories. All input variables contributed to the classification
tree, with elevation being least important. For the entire study area, 65,000 ha were mapped
as ASM, with 23,000 ha falling within active concessions (Table 1). This shows that 36% of
all ASM area falls within the active legal mineral extraction concessions. The classification
error matrix is shown in Table 2. Classification confusion exists between ASM and natural
alluvium and also between alluvium and river categories.
Three previously mapped areas of larger-scale mining – Huepetuhe, Guacamayo and
Delta-1 (Swenson et al. 2011; Asner et al. 2013) – were detected successfully (Figure 3).
The more numerous smaller extent (>10 km2
) ASM locations were also detected success-
fully (Figure 4), based on validation using interpretation of the fine-resolution imagery.
6. Discussion and conclusions
Mapping ASM locations with Landsat imagery is challenging due to their small areal extent
and spectral similarity to natural alluvial features. The combination of SMA and CTA
methods presented here sought to overcome these challenges by extracting physically based
land-cover proportions and invoking ancillary data for physical context. These methods
produced plausible results, based on the random sampling validation and also a holistic visual
interpretation of the CTA map with the fine spatial resolution data, shown in Figure 4. The
large, previously documented mining areas are seen clearly in Figure 3 and exhibit a
Table 1. Land use category areal extents (ha) inside and outside of mining concessions as of 2011.
Land-cover class
Forest Agriculture ASM Alluvium River Total
Mining
concession
status
Entire study
area
5,493,000 79,400 65,100 50,500 25,200 5,713,300
96.1% 1.4% 1.1% 0.9% 0.4% 100%
No concession 5,084,300 68,400 41,800 33,000 11,300 5,238,700
97.1% 1.3% 0.8% 0.6% 0.2% 100%
Active
concession
408,700 11,000 23,400 17,500 13,900 474,500
86.1% 2.3% 4.9% 3.7% 2.9% 100%
Table 2. Accuracy assessment cross tabulation, based on the classification output (rows) and the
fine resolution reference imagery (columns).
Reference image
Forest Agriculture ASM Alluvium River Total
Classification output Forest 321 1 4 4 2 332
Agriculture 10 33 5 3 0 51
ASM 1 4 24 2 3 34
Alluvium 0 5 1 41 15 62
River 0 0 1 4 20 25
Total 332 43 35 54 40 504
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9. heterogeneous pattern caused by interspersed agriculture, non-ASM soil and water, and what
appear to be abandoned older mines. Compared to a previous ASM map produced by
Swenson et al. (2011), the Guacamayo site appears to have extended southwards across the
newly constructed Interoceanic Highway; this extension is excluded from legal concession
areas, as illustrated in Figure 5, and is an example of illicit mining activity. Numerous small
70° 30′ 0″ W 70° 20′ 0″ W 70° 10′ 0″ W 70° 0′ 0″ W
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13° 0′ 0″ S
12° 50′ 0″ S
12° 40′ 0″ S
0 5 10 km
Major Roads
Forest
Agriculture
ASM
Alluvium
River
Figure 3. Final CTA output showing three previously documented mining locations: Huepetuhe,
Guacamayo and Delta-1.
69° 40′ 0″ W 69° 38′ 0″ W 69° 36′ 0″ W 69° 34′ 0″ W
69° 40′ 0″ W 69° 38′ 0″ W 69° 36′ 0″ W 69° 34′ 0″ W
12° 44′ 0″ S
12° 42′ 0″ S
12° 40′ 0″ S
12° 44′ 0″ S
12° 42′ 0″ S
12° 40′ 0″ S
0 2 4 km
Agriculture
ASM
Alluvium
Figure 4. Enhanced image of artisanal small-scale Mining and agriculture areas along the Madre
de Dios River. The eastern portion of the figure shows ASM, agriculture and natural alluvium,
overlaid with QuickBird imagery, while the western portion shows only the imagery, with a ring
around a typical ASM location.
888 A. Elmes et al.
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10. patches of ASM are visible along the Madre de Dios River. These locations are spatially
coherent and appear to be well classified, based on comparison to the QuickBird imagery
shown in Figure 4. Overall, 65,129 ha of ASM was predicted for the study area, considerably
larger than the 15,500 ha predicted by Swenson et al. (2011). This discrepancy is likely due to
the improved detection of small ASM patches using the proposed SMA/CTA methods and
also due to the temporal offset between the two studies. Asner et al. (2013) reported roughly
45,000 ha of forest to ASM conversion in Madre de Dios by 2011, and while this estimate is
much closer to that presented here, the study area extent used by Asner et al. was more limited.
The distance-to-rivers and distance-to-roads variables were particularly useful for dis-
criminating ASM from natural alluvium, as ASM typically occurs in intentionally remote and
obscured locations, but also requires access to water and transportation. These small, clandes-
tine ASM locations are the primary target for this mapping effort, since the Huepetuhe,
Guacamayo and Delta-1 mining locations are plainly visible in Landsat imagery and can
easily be classified with more traditional methods. As shown in Figures 4 and 5, ASM
locations are typically associated with small-scale agriculture activities, also discriminated
from other spectrally similar classes on the basis of their distance from rivers and roads. ASM/
alluvium confusion is problematic for parts of the scene, most likely due to the similar spectral
responses of the soil exposed by mining and that exposed by natural erosion processes. These
categories were separated fairly well based on the distance-to-rivers variable, since ASM
locations tend to be slightly farther away from rivers; however, this decision rule did not
perfectly distinguish all cases of these two land-uses. Alluvium/water confusion also reduced
overall accuracy and was likely caused by shallow water with a high spectral contribution
from the underlying river sediment or by ephemeral streams and seasonal river depth changes
associated with precipitation.
Some degree of classification confusion between ASM and other categories was
caused by the mismatch in spatial resolution of the output map (30 m) and the validation
imagery (~0.5 to 2.5 m); this mismatch is particularly relevant for validation points falling
close to the edge of a landscape patch or ASM area. Such points potentially introduce
spurious errors due to the nature of hard classification of inherently mixed pixels.
Therefore, the accuracy estimates provided in Tables 2 and 3 may be overly pessimistic.
ASM activity is not well confined by legal mining concessions in Madre de Dios, as
illustrated in Figure 5, which shows active mining concessions. This image is centred on the
southern expansion of the Guacamayo mining area and shows the expansion of licit opera-
tions into new, illicit areas. This figure also shows smaller-scale mining occurring outside but
adjacent to legal concessions, in this case along the Malinowski River in the southern portion
of the map. In total, 64% of mapped ASM occurs in areas with no active mining concessions.
Even allowing for commission error of ASM, the proportion of illicit mining is very high in
the study area, with 64% of ASM occurring in non-concession areas.
Due to the logistical difficulties of in situ monitoring of illicit mining activities in the
remote Madre de Dios region, Landsat imagery, together with other free, publically
Table 3. Accuracy report for classification.
Class Omission Error Commission Error Overall Accuracy
Forest 3.31% 3.31% 95.6%
Agriculture 23.26% 35.29%
ASM 31.43% 29.41%
Alluvium 24.07% 33.87%
River 50% 20%
Note: The overall accuracy figure accounts for the relative abundance of each land use type in the study area.
Remote Sensing Letters 889
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11. available ancillary data-sets, presents a practical and effective alternative. The use of SMA
and CTA for this classification proved to be effective based on validation using fine
spatial resolution imagery. Furthermore, the small patches of ASM located in the output
classification are consistent with the type of mining that is occurring in this region, as
shown by previous research (e.g. Asner et al. 2013) and by the fire resolution imagery. As
these methods rely on free, easily accessible data and straightforward methods, it is
reasonable to assume that they could successfully be implemented in other areas experi-
encing similar ASM activity. Future research will explore this possibility, as well as the
potential for expanding temporal coverage using Landsat-8 imagery.
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