Daerah Bahaya Banjir Di Sub Daerah Aliran Sungai Sepauk Dan Tempunak, Kabupaten Sintang, Provinsi Kalimantan Barat (Flood Hazard in Sepauk and Tempunak Sub Watersheds, Sintang Regency, West Kalimantan Province)

Flood-prone areas mapping is often constrained by limited data availability at the site level. A quick assessment of sub watershed degradation method can be used to identify the degradation level of a sub watershed includes the flood hazard areas. This method is very easy to be applied at a site level using Geographic Information System (GIS), although it has minimum data. The aim of this study was to analyze the level of flood hazard in Sepauk and Tempunak Sub Watersheds, Sintang Regency, West Kalimantan Province. The required data were DEM/ SRTM (Digital Elevation Model/ Shuttle Radar Topography Mission), daily rainfall, and land cover. Quick assessment of sub watershed degradation method was applied to classify the flood-prone level of the study areas. The results showed that most of the study areas were categorized as high level of flood hazard (78% for Sepauk and 56% for Tempunak). The land covers of those areas were dominated by mixed dryland agriculture, bare land, and settlements. In addition, high level of flood hazard areas in Sepauk Sub Watershed was also affected by the existence of mining and dryland agriculture areas. Since the land cover change is a dynamic process, the flood hazard areas mapping should also be adjusted continuously to minimize the flood impact

Land Suitability Evaluation of Abandoned Tin-mining Areas for Agricultural Development in Bangka Island, Indonesia

Kepulauan Bangka Belitung, Indonesia is one of the tin mineral-producer in the world. Agricultural crops could be a wise option for the reclamation since abandoned tin-mining lands have a high potency to be used as agricultural lands. This study was aimed to evaluate of the land/soil characteristics of abandoned tin-mining areas and to establish land suitability of the land area for agriculture used to formulate appropriate land development measures and amelioration strategies for utilization of mined areas for crop production. The land evaluation was conducted by comparing the land characteristics in every type of abandoned tin-mining areas with its crop requirements. The current suitability showed that in general food crops, vegetable crops, fruit crops, and industrial crops were consider as not suitable (N). Spice and medicinal crops [pepper (Piper nigrum L.) and citronella (Andropogoh nardus L. Rendle)] were consider as not suitable (N), while the Jatropha (Jatropha curcas L.) and Kemiri Sunan (Aleurites moluccana L. Willd) crops were considered as marginally suitable (S3) in abandoned tin-mining areas. The forest crops and forage crops were considered as marginally suitable (S3). The water availability, soil texture, and low soil fertility were considered as the limiting factors of all crops to get optimum production. For agricultural development, the soil physical and chemical properties of abandoned tin-mining land must be improved through integrated farming

Land Cover Change Detection in the Urban Catchments of Dar es Salaam, Tanzania using Remote Sensing and GIS Techniques

In this study, the Maximum Likelihood (ML) classification, Normalized Difference Vegetation Index (NDVI) and Artificial Neural Network (ANN) methods were applied to three (3) Landsat images collected over time (1979, 1998 and 2014), that contained historical land cover features for the urban catchments of Dar es Salaam. Five major land cover classes were identified, mapped, and the land cover changes investigated. The major land cover changes observed from post-classification comparisons of the classified images are: the forest land losing 17.09% of its area in the period 1979-1998 to other land covers, mainly turning to grassland, and from 1998 to 2014, 17.55% of the total study area turned to high and medium/low-density built-up areas. Growth in urban settlement and infrastructure was observed to be continuously increasing and the high and medium/low-density built-up areas are projected to cover 66.09% of the total area by 2030; this is an increment of 29.01% from 37.08% coverage in 2014. This shift in land cover was further validated by the results of the Normalized Difference Vegetation Index (NDVI) analysis which showed a similar trend (shift from thick vegetation towards barren land) from 1998 to 2014, with median NDVI values changing from 0.52 to 0.36 respectively. These land cover changes are most likely the results of activities related to the increase in total population, the influx of urban population and the growth of the economy.Keywords: Maximum Likelihood, NDVI, Artificial Neural Network, Landsat, QGIS

Evaluación del nivel de degradación de suelo y pastura en tres geoformas de Florencia-Caquetá

La principal actividad económica del departamento del Caquetá es la ganadería, la baja estabilidad por prácticas de manejo inadecuada y disminución en la fertilidad, promueven la degradación de suelo y pastura en el departamento. Se evaluó el nivel de degradación del suelo y de pastura en tres geoformas (vega, lomerío y montaña) del municipio de Florencia-Caquetá. Para la degradación de suelo se evaluaron las características físicas, químicas y biológicas, para la degradación de la pastura se estableció color de pastura, materia muerta, suelo desnudo, malezas y edad. Referente a los suelos de las tres geoformas estudiadas presentaron nivel de degradación física moderada a partir de la densidad aparente, degradación química de ligera a ninguna con respecto a contenido de nitrógeno total, fosforo disponible, PSI y sales disueltas y degradación biológica de ninguna a ligera con relación a materia orgánica. De acuerdo a la degradación de la pastura, vega y montaña presentaron nivel de degradación leve y lomerío presento nivel de degradación severa

Procjena korištenja zemljišta i preobrazbe zemljišnog pokrova i urbane dinamike koristeći viševremenske satelitske podatke

Assessment of Land use and land cover (LULC) transformations at different spatial levels is crucial in several areas, including protection of the environment, resource utilization, planning and sustainability. The present work is an attempt to carry out a detailed study of LULC transformations and to analyze urban areas in Srinagar city (India) using multi-temporal Landsat satellite data for the year 1995 to 2019. Seven different LULC classes were delineated for the selected periods by a supervised method using maximum likelihood classifier algorithm in ERDAS Imagine 14. The findings indicate that over the specified periods substantial changes have occurred in terms of LULC. Overall seven categories were identified and, throughout studies, three trends of LULC change were observed (1) continuous expansion of the area under the class of built-up, barren, horticulture (2) agriculture, water and marshy class are continuously decreasing (3) increase (1995–2010) and decrease (2010–2019) in forest classes between two periods. During the study period, in built-up (+), horticulture (+), agriculture (–) water (–) and marshes (–) most significant changes have been observed, referencing to change in percentage within each class, the maximum variability was observed in built-up (148.07%), horticulture (40.87%), marshes (–58.37%), water (–22%) and agriculture (–35.38%). For quantitative assessment changes Land Consumption Rate (LCR) and Land Absorption Coefficient (LAC) were introduced. The overall research scenario shows that the LULC transition in the city is very evident. The rapid change of LULC in the ecologically sensitive Srinagar city is driven mainly by anthropogenic sources and has a negative environmental influence.Procjena korištenja zemljišta i preobrazbe zemljišnog pokrova (LULC) na različitim prostornim razinama važna je u nekoliko područja uključujući zaštitu okoliša, iskorištavanje prirodnih izvora, planiranje i održivost. U ovom radu pokušava se provesti detaljna studija LULC preobrazbi i analizirati urbana područja u gradu Srinagar (Indija) koristeći viševremenske satelitske podatke Landsat za razdoblje od 1995. do 2019. godine. Iscrtano je sedam različitih LULC klasa za odabrano razdoblje uz pomoć nadzirane metode koristeći algoritam klasifikatora najveće vjerojatnosti u ERDAS Imagine 14. Rezultati ukazuju na to da su se u određenim razdobljima dogodile znatne promjene u smislu LULC-a. Svih sedam kategorija je identificirano te su kroz studije promatrana tri trenda izmjene LULC-a (1) stalno širenje područja u klasi izgrađenosti, neplodnosti, hortikulture (2) poljoprivreda, vode i močvarno tlo se stalno smanjuju (3) porast (1995–2010) i smanjenje (2010–2019) u klasi šuma između dva razdoblja. Tijekom razdoblja provođenja studije, u klasi izgrađenosti (+), hortikulture (+), poljoprivrede (–) voda (–) i močvarnog tla (–) opažene su najznačajnije promjene izražene u postocima unutar svake klase, najveća varijabilnost je uočena u klasi izgrađenosti (148,07%), hortikulture (40,87%), močvarnog tla (–58,37%), vode (–22%) i poljoprivrede (–35,38%). U svrhu kvantitativne procjene promjena uvedene su stopa korištenja zemljišta (LCR) i koeficijent apsorpcije zemljišta (LAC). Sveukupan istraživački scenarij pokazuje da je LULC tranzicija u gradu vrlo očita. Brze izmjene LULC-a u ekološki osjetljivom gradu Srinagaru vođene su uglavnom antropogenim izvorima te imaju negativan utjecaj na okoliš

Procjena korištenja zemljišta i preobrazbe zemljišnog pokrova i urbane dinamike koristeći viševremenske satelitske podatke

Assessment of Land use and land cover (LULC) transformations at different spatial levels is crucial in several areas, including protection of the environment, resource utilization, planning and sustainability. The present work is an attempt to carry out a detailed study of LULC transformations and to analyze urban areas in Srinagar city (India) using multi-temporal Landsat satellite data for the year 1995 to 2019. Seven different LULC classes were delineated for the selected periods by a supervised method using maximum likelihood classifier algorithm in ERDAS Imagine 14. The findings indicate that over the specified periods substantial changes have occurred in terms of LULC. Overall seven categories were identified and, throughout studies, three trends of LULC change were observed (1) continuous expansion of the area under the class of built-up, barren, horticulture (2) agriculture, water and marshy class are continuously decreasing (3) increase (1995–2010) and decrease (2010–2019) in forest classes between two periods. During the study period, in built-up (+), horticulture (+), agriculture (–) water (–) and marshes (–) most significant changes have been observed, referencing to change in percentage within each class, the maximum variability was observed in built-up (148.07%), horticulture (40.87%), marshes (–58.37%), water (–22%) and agriculture (–35.38%). For quantitative assessment changes Land Consumption Rate (LCR) and Land Absorption Coefficient (LAC) were introduced. The overall research scenario shows that the LULC transition in the city is very evident. The rapid change of LULC in the ecologically sensitive Srinagar city is driven mainly by anthropogenic sources and has a negative environmental influence.Procjena korištenja zemljišta i preobrazbe zemljišnog pokrova (LULC) na različitim prostornim razinama važna je u nekoliko područja uključujući zaštitu okoliša, iskorištavanje prirodnih izvora, planiranje i održivost. U ovom radu pokušava se provesti detaljna studija LULC preobrazbi i analizirati urbana područja u gradu Srinagar (Indija) koristeći viševremenske satelitske podatke Landsat za razdoblje od 1995. do 2019. godine. Iscrtano je sedam različitih LULC klasa za odabrano razdoblje uz pomoć nadzirane metode koristeći algoritam klasifikatora najveće vjerojatnosti u ERDAS Imagine 14. Rezultati ukazuju na to da su se u određenim razdobljima dogodile znatne promjene u smislu LULC-a. Svih sedam kategorija je identificirano te su kroz studije promatrana tri trenda izmjene LULC-a (1) stalno širenje područja u klasi izgrađenosti, neplodnosti, hortikulture (2) poljoprivreda, vode i močvarno tlo se stalno smanjuju (3) porast (1995–2010) i smanjenje (2010–2019) u klasi šuma između dva razdoblja. Tijekom razdoblja provođenja studije, u klasi izgrađenosti (+), hortikulture (+), poljoprivrede (–) voda (–) i močvarnog tla (–) opažene su najznačajnije promjene izražene u postocima unutar svake klase, najveća varijabilnost je uočena u klasi izgrađenosti (148,07%), hortikulture (40,87%), močvarnog tla (–58,37%), vode (–22%) i poljoprivrede (–35,38%). U svrhu kvantitativne procjene promjena uvedene su stopa korištenja zemljišta (LCR) i koeficijent apsorpcije zemljišta (LAC). Sveukupan istraživački scenarij pokazuje da je LULC tranzicija u gradu vrlo očita. Brze izmjene LULC-a u ekološki osjetljivom gradu Srinagaru vođene su uglavnom antropogenim izvorima te imaju negativan utjecaj na okoliš

Change detection and GIS-based fuzzy AHP to evaluate the degradation and reclamation land of Tikrit City, Iraq

LULC factors in Tikrit city (Iraq) and the neighboring municipalities are studied among 1989, 2002 and 2015 using various techniques of remote sensing, geographical information system (GIS), and fuzzy analytical hierarchy process (FAHP). Satellite imagery with GIS helped to assess the standard LULC changes in the long term period. FAHP permitted estimating the importance of various LULC by determination of the suitable weight for used factors and then producing the evaluating models. Using different techniques, two models were created (1) to estimate the degradation of the land (2) is generated to determine the reclamation of the area. The finding reveals that the a overall accuracy of 97.0939%, 98.9199% and 99.5817% or 1989, 2002 and 2015 respectively. The outcomes also revealed that urban, vegetation, and water features area are developed in the long term (1989–2015) about 4.35%, 4.28%, and 1.49%, respectively, while barren area is reduced about 5.57%.The degradation map index showed that the lands strongly debased are these converted from vegetation to barren, followed by moderate to high these changed from water areas to urban, while moderate degradation is noticed of urban transformed to barren soil. Contrary, the reclamation map index illustrated that the lands are powerfully transformed from barren to the vegetation and followed by those converted from barren to the water, while barren transformed to the urban is marked as moderate reclamation. The transformation from urban to vegetation or water was classified as the low and deficient class to evaluate the area. The study is also revealed that the integration of remote sensing and GIS produces a successful method for LULC monitoring and managing the environment

SCDNET: A novel convolutional network for semantic change detection in high resolution optical remote sensing imagery

Abstract With the continuing improvement of remote-sensing (RS) sensors, it is crucial to monitor Earth surface changes at fine scale and in great detail. Thus, semantic change detection (SCD), which is capable of locating and identifying "from-to" change information simultaneously, is gaining growing attention in RS community. However, due to the limitation of large-scale SCD datasets, most existing SCD methods are focused on scene-level changes, where semantic change maps are generated with only coarse boundary or scarce category information. To address this issue, we propose a novel convolutional network for large-scale SCD (SCDNet). It is based on a Siamese UNet architecture, which consists of two encoders and two decoders with shared weights. First, multi-temporal images are given as input to the encoders to extract multi-scale deep representations. A multi-scale atrous convolution (MAC) unit is inserted at the end of the encoders to enlarge the receptive field as well as capturing multi-scale information. Then, difference feature maps are generated for each scale, which are combined with feature maps from the encoders to serve as inputs for the decoders. Attention mechanism and deep supervision strategy are further introduced to improve network performance. Finally, we utilize softmax layer to produce a semantic change map for each time image. Extensive experiments are carried out on two large-scale high-resolution SCD datasets, which demonstrates the effectiveness and superiority of the proposed method

Rapid Urban Growth in the Kathmandu Valley, Nepal: Monitoring Land Use Land Cover Dynamics of a Himalayan City with Landsat Imageries

abstract: The Kathmandu Valley of Nepal epitomizes the growing urbanization trend spreading across the Himalayan foothills. This metropolitan valley has experienced a significant transformation of its landscapes in the last four decades resulting in substantial land use and land cover (LULC) change; however, no major systematic analysis of the urbanization trend and LULC has been conducted on this valley since 2000. When considering the importance of using LULC change as a window to study the broader changes in socio-ecological systems of this valley, our study first detected LULC change trajectories of this valley using four Landsat images of the year 1989, 1999, 2009, and 2016, and then analyzed the detected change in the light of a set of proximate causes and factors driving those changes. A pixel-based hybrid classification (unsupervised followed by supervised) approach was employed to classify these images into five LULC categories and analyze the LULC trajectories detected from them. Our results show that urban area expanded up to 412% in last three decades and the most of this expansion occurred with the conversions of 31% agricultural land. The majority of the urban expansion happened during 1989–2009, and it is still growing along the major roads in a concentric pattern, significantly altering the cityscape of the valley. The centrality feature of Kathmandu valley and the massive surge in rural-to-urban migration are identified as the primary proximate causes of the fast expansion of built-up areas and rapid conversions of agricultural areas