ERDAS Imagine Research Articles

GIS-based hydrological modelling to assess runoff yields in ancient-agricultural terraced wadi fields (central Negev desert)

Thousands of ancient agricultural terraced fields exist in ephemeral stream valleys in the central Negev desert. Their stone terrace walls captured runoff water, flowing from the surrounding hillslope catchments, to increase moisture in the loess soils of the terraced fields. Geoarchaeological research at the site of Horvat Haluqim discovered evidence for ancient farming and soil manuring in this arid desert region during various archaeological periods. Geographic Information Systems (GIS) and Digital Elevation Models (DEM) enable the development of hydrological models to investigate every ancient terraced field in a non-invasive manner, without disturbing the archaeological remains. We developed a GIS-based hydrological model, coupled with the D-Infinity (Tau DEM) algorithm, to evaluate annual runoff yields in 13 ancient terraced fields at the rural archaeological site of Horvat Haluqim. Our model precisely determined the runoff catchment area, ranging between 0.10 ha and 0.36 ha, of each individual terraced field. Supervised land cover classification, using Erdas Imagine, showed the surface percentages of crusted loess soil and exposed bedrock. Following an evaluation of runoff coefficients established by conventional hydrological studies in the region, we present results of model-calculated runoff overland flow yields. We modelled runoff amounts for each of the agricultural fields during an average year (1989–90) with 88 mm precipitation, a very wet year (1991–92) with 188 mm, and a severe drought year (1999–2000) with only 34 mm rainfall. Our initial results, based on an approximated average annual runoff coefficient of 10%, indicate that runoff water amounts during an average and wet rainfall year appear sufficient to grow agricultural crops in these ancient fields. However, drought years are of course more problematic. The modelling results are supported by the successful growth of trees in similar terraced wadi fields next to Horvat Haluqim, established by the Jewish National Fund. Given the inherent uncertainties involved in modelling, it is encouraging to note that the trees did survive also drought years. Our model may be applied to evaluate the effect of climatic changes on runoff water harvesting systems, looking back into the past and also to assess possible impact of future climate change scenarios in modern water harvesting projects.

Investigation of runoff response to land use/land cover change on the case of Aynalem catchment, North of Ethiopia

The impact of land use/land cover and climate change on the hydrology are global issues affecting the whole catchment of the river basin. The main objective of this study was to investigate runoff response to land use/land cover change in Aynalem catchment, located in Tigray regional state, northern Ethiopia. The study analyzed the historical land cover changes from 1995 to 2015 that have taken place in the catchment and its effect on the runoff of the catchment. The land cover changes within the catchment were examined through classification of satellite images with integrated use of ERDAS Imagine (Version 9.2) and ArcGIS software. Land cover change analysis between the periods of 1995 and 2015 has shown that the urban area has increased from 1.39% to 7.50%, Cropland from 54.03% to 65.69% and Water bodies from 0.14% to 0.42%, while Planted Forest area has decreased from 3.61% to 2.92%, Grassland 2.22%–1.90% and Open Shrub lands from 38.61% to 21.53%. Further, Water and Energy Transfer between Soil, Plants, and Atmosphere (WetSpa) model was used to investigate the runoff response to a land cover change on the study area. The model was calibrated (1994–1998) and validated (1999–2001) against the observed daily stream flow data. WetSpa model parameters sensitivity analysis result shown that the groundwater recession coefficient (Kg), Initial active groundwater storage (Go) and Surface runoff exponent (K_run) are the most sensitive parameters affecting the hydrology of the catchment. The WetSpa model application in Aynalem catchment performances very good in reproducing the hydrological process of the catchment with coefficient of determination (R2), Nash and Sutcliff efficiency (NSE) values of 0.82 and 0.90 for calibration, 0.78 and 0.88 for validation, respectively. The WetSpa model application with land useland cover maps of 1995, 2003 and 2015 shows annual runoff increased by 21.1% from the year of 1995–2003 and 23.5% from 2003 to 2015 and also, 44.6% from 1995 to 2015. The increment in runoff is likely to have been caused by the change of the land use/land cover from shrubs and grass lands to urban and cultivated lands.

An Integrated Approach for Identifying and Prioritizing Potential Areas as Conservation Reserves in the Western Ghats, India

We studied the Agasthyamalai region of the Western Ghats to identify and prioritize potential areas to declare as Conservation Reserves using biological and social values in the southern Western Ghats. In this two phase study, throughthe desktop analysis (ERDAS Imagine, IRS-LISS4 data) identified four major forest patches viz., Kallar (24.05 km2), Ponmudi (57.17 km2), Chankili (119.64 km2) and Achancovil (7.55 km2) under the Palode and Kulathupuzha Forest Ranges of Thiruvananthapuram Forest Division (FD) and Achancovil Range of Achancovil FD. Second phase aggregated data pertaining to above four patches on presence of climax type of forests, biological wealth indicated by species richness, presence of endemic and critical species of plants and animals (vertebrate species excluding mammals) and indigenous peoples’ reliance on natural resources like water and NTFP. An overlay analysis using Arc GIS 9.1, the thematic layers have been created and subsequently integrated to infer the hierarchy within the four patches. The highest weighted average conservation value (=117.5) was scored by Ponmudi, followed by (=100) Chankili and (=90) Achancovil, where as lowest score of 67.5 attributed to Kallar patch. Highest dependency value of 40 was attributed to Achancovil, followed by Ponmudi and Chankili equally scored (=35), while the Kallar scored only 25. Based on sum of conservation and dependency values, Ponmudi patch stands out with highest priority (=152.5) in Agasthyamalai Biosphere Reserve, and others trail behind respectively.

Determination of Opium Poppy (Papaver Somniferum) Parcels Using High-Resolution Satellite Imagery

Narcotic plants contain substances that cause unusual excitation and subsequent depression of the central nervous system. Many narcotic plants contain substances that have medicinal properties and are used primarily as pain relievers. Opium poppy (Papaver somniferum) is one of the most cultivated narcotic plants. The planning of Opium poppy growing is controlled by United Nations and Drugs and Medicines Control Program. This study was conducted to establish a basis for determining the traceability of poppy cultivating areas using remote sensing in the large plain. A very high-resolution QuickBird-2 satellite image was used in the study. The software of ERDAS Imagine and eCognition Developer was performed for image processing and classification. A variety of classification methods were performed on the satellite image. ArcGIS software was used for accuracy assessment, ground control, and map production of the poppy cultivating area. The accuracy of classification methods was compared. The producer–user accuracy was estimated as 97.99% using spectral difference sub-segmentation process of multiresolution segmentation algorithm in object-based classifications method. This algorithm can be a practical approach for determining of opium poppy parcels in the large plain.

Monitoring LULC changes and its impact on the LST and NDVI in District 1 of Shiraz City

Today, immediate and long-term change detection and monitoring using remote sensing (RS) data and geographical information system (GIS) is of paramount importance in generating information about the latest land use/land cover (LULC), land surface temperature (LST), and normalized difference vegetation index (NDVI) in accordance with spatial and temporal changes. Therefore, to obtain these components, a multi-temporal dataset was used consisting of two sets of Landsat Thematic Mapper (TM) images from 1986 to 2011 period across District 1 of Shiraz. Additionally, to investigate the relationship between LST and NDVI over seasons, four Landsat images were used. LULC, LST, and NDVI components were retrieved using Landsat image in ERDAS IMAGINE 9.2 image processing software. Results showed that during the study period, the city had experienced a massive urban (residential) growth. Moreover, change detection suggested that residential areas had increased by 13.17 km2 and vegetation zones (garden) and barren lands had decreased by 4.6 and 8.63 km2, respectively, during 1985–2011 period. The study of the relationship between vegetation index (land cover) and vegetation (land use) in District 1 showed that with reduced vegetation zone (land use), the quality of vegetation (land cover) had deteriorated. These findings indicate that reduced quality of vegetation cover and consequently its Reduction can have a positive effect on the temperature patterns. In general, the negative correlation between vegetation and LST caused by lower vegetation quality was less significant in 2011 compared to 1986, while there the correlation between vegetation and LST in summer was higher than other seasons.

Impacts of land use/land cover change on stream flow and sediment yield of Gojeb watershed, Omo-Gibe basin, Ethiopia

Land use/land cover (LULC) change is an important landscape process capable of altering the fluxes of water, sediment, contaminants and energy. In this study, Soil and Water Assessment Tool (SWAT) model was used to examine the effects of LULC on the hydrological process of Gojeb Watershed in the Omo-Gibe basin. The performance of the model was evaluated through sensitivity, uncertainty analysis, calibration and validation. The LULC change analyses for three periods (1989, 2000 and 2013) were performed using ERDAS Imagine 2014 with a maximum likelihood classifier. The time series LULC changes results were used for estimation of stream flow and sediment yield. The result has shown that during the study period most parts of the forest land were converted into cultivated land with an increase of cultivated land by 14.97% over the study periods which resulted in an increase of stream flow and sediment yield by 8.6 m3/s and 41.07ton/km2 respectively. The Nash sutcliff efficiency (NSE), coefficient of determination (R2) and percent of bias (PBIAS) were used for evaluating the model performance. The model results have shown a good agreement with the observed values with NSE > 0.75, R2 > 0.78, and PBIAS < 0.5 values. Based on the validated sediment yield results of 2013 land use, high potential source of spatial variability of sediment was found at middle and downstream of the watershed. Hence, for the critical sub-watersheds, the design and development of three best management practices (BMPs) were performed. These best management scenarios include: S1 (filter strip), S2 (terrace/ bund) and S3 (reforestation). Based on these scenarios, the findings have shown a sediment yield reductions by 22.9%, 29.4% and 32.3% with the implementation of S1, S2 and S3 respectively. Therefore, based on the findings, implementing S3 is the best management strategy as compared to other options and hence, such intervention should be encouraged at a wider scale for efficient sediment reductions of Gojeb watershed.

English

Land use land cover (LULC) dynamics are a widespread, accelerating, and significant process driven by human actions. LULC changes analysis is one of the most precise techniques to understand how land was used in the past, what types of changes are to be expected in the future, as well as the forces and processes behind the changes. This study was carried out to evaluate the historical and future trends as well as driving forces of LULC changes in Somodo watershed South Western, Ethiopia. It was accompanied using satellite image of Landsat5 TM 1985 and 1995, Landsat7 ETM+ 1999, 2005 and Landsat8 OLI/TIROS 2017. In addition, field observations, Key informant interview (KII) and Focus Group Discussion (FGD) were also conducted. ERDAS Imagine 9.1, QGIS 2.18 and IDRSI Selva 17.00, software were used for satellite image processing, map preparation, and LULC change prediction respectively. During the 32 year period between 1985 and 2017, the proportion of area covered by forest and agriculture was decreased by 60.57 ha (12.7%) and 5.22 ha (1.1%) respectively. In contrast, home garden Agroforestry/settlement and grassland were increased by 49.77 ha (7.5%) and 16.02 ha (6.7%) respectively. If the existing rate of LULC change lasts, in 2029 agriculture and forestland are predicted to increase by 91.24 ha and 20.52 ha respectively, while grassland and home garden Agroforestry/settlement are predicted to decrease by 99.97 ha and 11.79 ha respectively. LULC change in the study area is an outcome of several proximate and underlying drivers. The major proximate driving forces of LULC change in the watershed are illegal logging and fuel wood extraction, Expansion of plantation, expansion of settlement, agricultural expansion, and construction of infrastructures. Demographic, Economic, Technological, Institution and policy, and Biophysical factors constitute the major underlying drivers of LULC change in the study area. Population growth is the major underlying cause for LULC change in the study area. Then, Participatory Forest Management through plantation and community nursery expansion is required for forest cover improvement in the watershed. This study also suggests further study on the impact of LULC change in the area. Key words: Drivers, geographic information system (GIS), Land use/Land cover Change prediction, Somodo Watershed.

Appraisal of Urban Heat Island Detection of Peshawar Using Land Surface Temperature and Its Impacts on Environment

Last couple of decades witnessed a rapid escalation in urban temperature of Peshawar city and its neighboring localities. This alarming condition gave birth to climatic term urban heat island-created drastic alteration in surface temperatures. In this study, thermal infrared remote sensing data have been employed to map out and monitor such micro-climatic variation in temperatures in land use/land cover exposed surface to the environment. To assess these outcomes resulting from human activities, Landsat TM data band 6 was subjected through ERDAS Imagine 2013. For further processing, ARC GIS helped a lot in making maps to pinpoint the heat island in and around the city. Moreover, a relationship of land surface temperature with urban sprawl, environmental and industrialization was established. This study has shown a substantial upsurge in temperature about to 1°–3°. Urban sprawl and industrialization at the edges are accounting for these conditions. Urban and industrial data have also reinforced the fact being drawn from remotely sensed data. Hence, evaluation of land surface temperature data captured through remote satellite has proven to be effective tool not only for monitoring and analyzing temperature but also for assessing its adverse impacts on the environment and climate.

Analyzing site suitability for solid waste disposal through GIS multi-criteria decision making hierarchy process

Currently the human beings are encircled by multiple types of problems, out of those the environmental degradation issue is one of the major problem which is caused by over population, rapid increase of urbanization and industrialization which result in production of huge quantity of solid wastes. Thus the effectual solid waste management and its disposal arrangements are required. Another major problem being faced globally is to locate an appropriate area for the disposal of hazardous wastes by overcoming main constraints including environmental, economic and political for spotting of a suitable site. In this study our focus is to spot a proper landfill site for the disposal of hazardous wastes for which we have selected industrial (radioactive) wastes of the district of Karachi East as a area for research. This district has wide range of Korangi Industrial Area and small portion of Landhi Industrial Area. In this research we have used methods of Decision Support System (DSS) based on Geographical Information System (GIS) and Remote Sensing (RS) concerning all supportable measures. With the assist of Analytic Hierarchy Process (AHP) and Multi-Criteria Decision Making (MCDM), suitable alternative site for dumping solid waste has been selected on the basis of different factors performed on Arc Map 10.3, Erdas Imagine, e-Cognition developer by considering the decision maker’s expectations. The results show that after performing different investigations on the suitability indexes, the analyzed area which is most suitable for solid waste dumping is 200m away from Malir River.

Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Onitsha, South East Nigeria

The increasing urbanization generally is brought about by many eco-environmental problems, such as the drastic change of land use and development of urban heat island. This study identified the pattern of land cover changes in Onitsha, South East Nigeria, and assessed the trend in temperature over the area from 1986 to 2016, simulated the land cover changes for 2030 and 2044, and estimated their impacts on land surface temperature (LST). These were with the view to determining the effects of changes in land use/cover on the LST in the area. Primary and secondary data were used for the study. The primary data were coordinates of geographic features within the study area, collected through the use of global positioning system. The secondary data were minimum and maximum temperature data from the Nigerian Meteorological Agency (NIMET), high-resolution Quick-bird imagery, Landsat TM/ETM imageries for four epochs (1986, 2002, and 2016) with path and row of 189 and 56. Individual components (bare surface, built-up, vegetation and surface water bodies) in the study area were extracted from the images. Radiometric correction was first performed (for 2016 landsat imagery) to fill the line scan corrector (LSC) gaps using Focal Analysis tool in ERDAS Imagine 14.0. This was followed with clipping of the satellite imagery to extract only those portions that are within the boundary of the study area. Supervised image classification was done for the three series of remotely sensed imageries to extract the spatial pattern of land cover change. The results revealed that the study area has been growing to a relatively compact urban agglomeration. The concentration of built-up area at the western and the central part of the study area has been getting larger and more aggregated. Built-up area increased by 11.49% from 1986 to 2002 and 5.68% from 2002 to 2016 while vegetation decreased by 6.03% from 50.26% in 1986 to 44.23% in 2002. The decrease further continued from 44.23% in 2002 to 29.79% in 2016 (change of 14.44%). Expansion to spread into the sub-urban and rural communities bounding the metropolis, converting agricultural and green area to built-up areas. The land cover trend of the study area from the period of 1986-2016 shows dramatic changes for the dominant land cover types. The analyzed trend in temperature change shows that the central parts of the city have a temperature higher than the outlying parts. The results indicated that the average temperature of the study area increased from 24&#176C in 1986 to 28&#176C in 2016. The simulated land cover also showed a decreasing trend in vegetal cover. The study concluded that the increase in built-up area caused an annual increase in land surface temperature (0.31&#176C) over the study period.

Evaluating Land Use/Land Cover Change and Its Socioeconomic Implications in Agarfa District of Bale Zone, Southeastern Ethiopia

A systematic analysis of land use/cover change is so decisive to exactly understand the extent of change and take essential measures to curb down the rate of changes and protect the land cover resources sustainably. This land use/land cover change study was conducted in Agarfa district of Bale zone, Oromia Regional State, Southeastern Ethiopia. The objectives of this study were to evaluate the trends, drivers and its socio-economic and environmental implication in study area. A descriptive research method was employed to achieve the intended objectives of the study. In the three years (1976, 1995, and 2014) Landsat Satellite images and socio-economic survey were the main data sources for this study. ERDAS Imagine and Arch-GIS tools were used to classify and generate land use/land cover maps of the study area. Survey questionnaires, key informant interviews, and field observation were employed to obtain information on drivers and its socio-economic and environmental implication in the district. The results show that the land use/land cover of the study area had changed dramatically during the period of 38 years. A rapid loss of forest land and shrub land cover in the landscape took place between 1976 and 2014. Conversely, agriculture and grazing lands were increased by 30% and 42% respectively at the expense of the lost land use/land cover types. Forest land is the most converted cover type during the entire study period. In the 38 years, forest lands diminished by over 65% of the original forest cover that was existed at the base year (1976). Local climate change, declining agricultural productivity and livestock quantity and quality and scarcity of fuel wood and constructional materials were some of the socio-economic and livelihood impacts of land use and land cover change of the study area. Thus, this finding affords information to land users and policy makers on extent of the change and social forces leading to this changes and its subsequent implication on local socio-economic and environmental conditions of the study area.

Land-use and Land-cover Analysis of Kaduna South Local Government Area, Kaduna State, Nigeria

This study assessed the land-use and land-cover changes of Kaduna South LGA, Kaduna State within the period of 30 years (1987 to 2016). Remote Sensing and Geographic Information System approach was employed in the study, where Landsat 5, 7, and 8 series images of 1987, 2001, and 2016 were classified into four categories; built-up, agricultural, vegetation, and water-body. The classification results, after accuracy assessment, provided the LULC makeup statistics at each epoch. The image classification results were crossed to ascertain the transitions between the study epochs. ERDAS Imagine 14.0 was used for the image bands combination, subset, classification and accuracy assessment while the analysis, manipulation and presentation were executed in ArcMap 10.3. The study revealed that the built-up land increased from 26.71% in 1987 to 59.41% in 2016, while agricultural land decreased from 44.14% to 11.56% in 2016. Water-body increased from 0.77% to 0.78% over the period. Also observed that vegetation increased from 28.38% to 31.36%, and then decreased to 28.25% in 2016. Therefore, the study recommends that land use/land cover change studies should be carried out and updated annually as it forms a basis for planning and decision making towards environmental sustainability.

Altitudinal Zone Land Use Changes in I?dir Plain Using Overlay Analysis Combined with Remote Sensing Methods

Increments in populations, variations in irrigation systems coupled with drainage conditions caused significant changes in land use. In order to examine the changes in land uses between 1987 and 2017, IAŸdA±r plain and its surrounding area were investigated using ArcGIS and Erdas Imagine. During these periods, urban area has increased by 142%. In IAŸdA±r province, urban areas expanded towards agricultural areas. Depending upon drainage-amendment, irrigation opportunities and ever-mounting mechanized agriculture, dry agriculture areas have transformed into irrigated agriculture areas. Moreover, available urban areas expanded in favor farming and pasture areas. Herein, urban area increased from 7 to 13% by raising the area 27.000 hectares for the last 30 years. With the overlay analysis, up to recent years, the urban areas which are in the 800-1000 meters altitude zone have increased from 2 to 6%. In addition, the agricultural areas which were of 121.500 hectares in 1987 decreased 9000 hectares to 112.500 hectares in 2017. In the same years, irrigated agricultural areas that were of 27.000 hectares increased up to 72.000 hectares in 2017. However, dryland agricultural areas that were of 94.500 hectares in the same year decreased as 40,500 hectares. Thereby while the irrigated agricultural areas which occupied the 6% of total use increased up to 16%, the dryland agriculture areas which was 21% decreased to 9% in 2017. While 84% of the lands of 800-1000 altitude zone were dryland agricultural areas and 6% of the land was irrigated agriculture areas in 1987, the dryland agricultural areas decreased to 19% and the irrigated agricultural areas increased up to 68% in 2017.

Multicriteria Evaluation of Transport Plan for High‐Speed Rail: An Application to Beijing‐Xiongan

Beijing has an enormous transportation challenge: to relieve the extreme congestion that has arisen, largely due to overpopulation. To meet this challenge, the city administration has decided to extend its territory; a new city will be planned and built. This new city, Xiongan, will reduce the burden on the capital. A new high‐speed railway (HSR) line is designed to transport millions of people every day within less than an hour. This study applies the potential of Geographical Information Systems (GIS) and multicriteria methods, Analytic Hierarchy Process (AHP) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE II), to determine the best alternative of transportation for the new high‐speed railway line between Beijing and Xiongan, comparing different ones. The methodology consists of two stages. In the first stage remote sensing datasets such as ASTER DEM and LANDSAT images and GIS software such as ERDAS IMAGINE and ArcGIS have been used to determine settlement distribution, station location, elevation model, slope percentage, vegetation percentage, and route alignment for a new high‐speed railway line for better understanding of its spatial distribution pattern over the study area. The second phase of the study focusing on assessing the various alternatives of transportation has been determined, and three approaches to choosing the best alternative have been introduced. In the paper we examine criteria associated with travel and economic criteria: travel time, the number of train stops, public satisfaction with transport, the number of seats per day, connectivity, operating costs, profit, and the payback period. Six alternatives of transportation have been studied. The stops in Guan and stations in the metro’s rings have been investigated. In the second stage, the Analytic Hierarchy Process (AHP) and PROMETHEE II methods have been used to select the best alternative. The first approach uses only criteria related to the trip, as the criterion to choose the best alternative is the maximum of the net outranking flows by PROMETHEE II method; the second approach applies two independent criteria: the ratio of normalized operating costs and the normalized net outranking flows, and the ratio of the normalized payback period and the normalized net outranking flows; the third approach includes all defined criteria, and the criterion of choosing the best alternative is the maximum of net outranking flows as calculated by the PROMETHEE II method. The approaches have been analyzed with the purpose of comparing the results. The result indicates that it is expedient to have a station in Guan, which will increase the connection and connectivity among the cities while providing fast mobility options for a large number of inhabitants of Guan city. Furthermore, the result from Remote Sensing and GIS analysis demonstrates that the proposed high‐speed railway line will be environmentally sustainable and is economically/socially feasible and that it will certainly attract current and future passengers because of their needs.

Transition from Land Use/Cover into Urban Expansion in Dutse Metropolis, Jigawa State, Nigeria

The purpose of this research is to analyse the effect of Urban Expansion on Land Use/Cover Change in Dutse, Jigawa State, Nigeria. Landsat TM and ETM+ satellite imageries of 1986, 2000 and 2014 respectively, were used. The imageries were processed using ERDAS IMAGINE 9.2 software. A supervised classification approach using maximum likelihood classifier and Transition Change Analysis were carried out using IDRISSI 17.0 Selva Edition version. Results from the analysis revealed that increase in built-up area resulted to changes in other land use/cover categories between 1986 and 2014. Built up area was 20.4% in 1986 and increased to 28.4% in 2000. Further increase was witnessed in built up area to about 38.2% in 2014. The results further revealed that about 7.2% bare surfaces changed into built-up from 1986-2014. About 14.8% of cultivated land changed into built-up from 1986-2014. Vegetation witnessed a remarkable changes into built-up of about 4.5% from 1986-2014. There is need for Jigawa State Government to equip the planning authorities and other ministries involved in decision making with adequate spatial data to ensure broad based decisions. Land use suitability analysis of the study area is also recommended.

Una herramienta para el análisis de índices espectrales para la detección remota de vegetación y cultivos utilizando imágenes hiperespectrales

Los requerimientos alimentarios en el mundo han aumentado, evidenciando la necesidad de mejorar las técnicas estándar de producción agrícola. Para abordar este problema, una alternativa de solución es la inclusión de elementos tecnológicos como el sensado remoto de vegetación y los cultivos a partir de imágenes hiperespectrales. El sensado remoto y las imágenes hiperespectrales son métodos no invasivos, que permiten monitorear grandes espacios de terreno en cantidades de tiempo reducidas. Estas características han hecho que el sensado remoto a partir de imágenes hiperespectrales sea una herramienta poderosa para desarrollo de procesos de agricultura de precisión. En este artículo se presenta una aplicación de software que permite generar y procesar índices espectrales de vegetación y sus respectivas imágenes de pseudo color, utilizando imágenes hiperespectrales. Las imágenes hiperespectrales utilizadas fueron tomadas de la base de datos del sensor Airborne Visible-Infrared Imaging Spectrometer (AVIRIS), diseñado por la NASA. El objetivo de la aplicación de software es mostrar diferentes elementos asociados con el monitoreo remoto de vegetación y cultivos a partir de imágenes hiperespectrales. Finalmente, se presentan pruebas funcionales para verificar el cumplimiento de los requisitos del software.

МОНИТОРИНГ НАРУШЕНИЙ ПРИРОДНОЙ СРЕДЫ ТЕХНОГЕННЫМИ ПРОЦЕССАМИ ПРИ ДЕШИФРИРОВАНИИ КОСМОСНИМКОВ

The tasks are given for the interpretation of environmental disturbances by technogenic processes: the selection on a satellite image of areas of natural complexes transformed by various types of economic activity; identification and characterization of sources of anthropogenic environmental impact; construction of the on-board version of the map illustrating the conclusions obtained during the interpretation of the satellite image. To perform the interpretation, images of Landsat 8 satellite images were used in two versions: in natural and false colors. Using the processes of automated decoding, in the ERDAS IMAGINE software package, images with different colors were obtained, allowing to divide objects into classes. The method "Spectral analysis" divided objects into 5 classes. According to the results of the interpretive work in MapInfo Professional, two raster images were superimposed on each other, one of which is a picture in natural colors, the other is an image obtained by the Spectral Analysis method. The imposition of raster images as a substrate allowed us to determine the boundaries of the areas that were subjected to industrial and man-made processes. As a result, a scheme was created illustrating the positions of sites subjected to industrial and man-made processes. Created in the MapInfo Professional software package, the scheme contains mining sites for coal and limestone, as well as industrial enterprises, indicated by numbers in the scheme. As a result, a scheme of environmental disturbances by industrial and man-made processes was obtained.

Spatiotemporal Change Detection of the Linden Forests in Bursa, Turkey

Nonwood forest products potentially provide many economic, social and environmental benefits in Turkey. Increasing public demand for nonwood forest products has led to the development of spatial planning and updating of existing plans. In order to ensure the sustainable management of nonwood forest products, their trends and spatial distributions by time can be estimated by using land use/land cover change detection approach. The Linden is one of the most important nonwood forest products in Turkey and the most widespread distribution of linden is located in the province of Bursa. In this study, it was aimed to determine the spatiotemporal changes of one of the world's largest linden forests in Yeniköy Forestry Enterprise Chief within the border of Bursa Forestry Regional Directorate. Change detection analysis was applied to Landsat 5 TM image and Landsat 8 OLI/TIRS image captured in August 2008 and in July 2017, respectively. The spatiotemporal change detection was implemented on these two images by using various digital image processing techniques (pre-processing, classification, post-processing, and change detection) through ERDAS Imagine 2015, ArcGIS 10.5, and ENVI 5.3 program. The supervised classification, applied on both images using ERDAS Imagine 2015 program, revealed that there were six significant land use/land cover types in the study area; linden, other deciduous trees, wetlands, swamp, sand, and other lands (settlements, agriculture, open areas). The results indicated that there was increase in the areas of wetlands, sand, and other lands, while the area of linden forest, other deciduous trees, and swamp decreased from 2008 to 2017. According to the accuracy assessment results, the classification processes applied on 2008 and 2017 images provided overall accuracy of 84.38% and 82.81%, respectively. It is determined that some of the linden forests have been converted into residential areas and farmlands to grow crops.

Impact of Human Settlement on Land Use/Land Cover Changes in the Middle River Njoro Sub Watershed in Kenya

This study investigated the use of remote sensing and GIS in evaluating the impacts of human settlement on land use /Land cover changes. The study also investigated the drivers behind the change in the middle of River Njoro sub watershed for a period of 27 years. Drivers of land use change were captured by the use of DPSIR model where Drivers (D) represented human needs, Pressures (P), human activities, State (S), the ecosystem, Impact (I) services from the ecosystem and Response (R), the decisions taken by land users. Land sat MSS and Land sat ETM+ (path 185, row 31) were used in this study. The Land sat ETM+ image (June 1987, May, 2000 and July, 2014) was downloaded from USGS Earth Resources Observation Systems data website. Remote sensing image processing was performed by using ERDAS Imagine 9.1. Three land use/land cover (LULC) classes were established as Human settlement, forest and shrub land. Severe land cover changes was found to have occurred from 1987-2000, where human settlement increased by 52%, shrub land reduced by 19%, and forestry reduced by 72%. In the year 2000 – 2014, human settlement increased by 121%, shrub land reduced by 45%, and forestry reduced by 64%. Forestry and shrub land were found to be consistently reducing while human settlement was increasing. It was evident from the images that the LULC changes with corresponding soil quality deterioration mostly occurred in the upper and middle parts of the Middle river Njoro sub watershed which were initially under forest. To minimize the risk of vegetation destruction and soil degradation, it will be necessary to identify socioeconomic safety nets and initiate restoration of the environment to original pre- catastrophe status.

MODELING OF PARAMETERS FOR FOREST FIRE RISK ZONE MAPPING

Abstract. Forest fire has been regarded as one of the major reasons for the loss of biodiversity and dreadful conditions of environment. Global warming is also increasing the incidence of forest fire at an alarming rate. That’s why, one need to understand the complex biophysical parameters, which are responsible for this disaster. As it is difficult to predict forest fire, fire risk zone map can be useful for combating the forest fire. So the main aim of this study is to generate a Fire risk model to map fire risk zone using Remote Sensing &amp;amp; GIS technique. Pauri Garhwal District, located in Uttarakhand, India, has been selected for this study as it continually faces the problem of forest fire. Landsat-8 data of 18th April, 2016 have been used for land use land cover mapping. Slope and other information have been derived from topographic maps and field information. For thematic and topographic information analysis ArcGIS and ERDAS Imagine software have been used. Forest fire risk model was generated by using AHP method, where each category was assigned subjective weight according to their sensitivity to fire. Three categories of forest fire risk ranging from very high to low were derived. The generated forest fire risk model was found to be in strong agreement with actual fire-affected sites.