scholarly journals Analysis of land development potential using remote sensing for Kangra District, Himachal Pradesh, India.

2022 ◽  
Author(s):  
Sidhu Shruti
Keyword(s):  
Remote Sensing ◽  
Land Development ◽  
Himachal Pradesh ◽  
Development Potential

Research on Evaluation and Development Potential Analysis of Low-Slope Hilly Land Resources

2013 ◽  
Vol 444-445 ◽  
pp. 1260-1264
Author(s):  
Jie Lv ◽  
Xi Ping Yuan ◽  
Shu Gan ◽  
Ming Long Yang ◽  
Qiong He ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Clustering ◽  
Land Development ◽  
Fuzzy Comprehensive Evaluation ◽  
Land Resources ◽  
Local Conditions ◽  
Development Potential ◽  
Potential Analysis ◽  
Ecological Benefit ◽  
Development And Utilization

Investigation and potential analysis of low-slope hilly land resources is a foundational work for carrying out land development and utilization scenically. In this paper, based on status of land use change survey data in 2011 and satellite remote sensing data of study area, at the same time,we combined with the practical situation of study area, by using superposition analysis, spatial clustering and fuzzy comprehensive evaluation, did an investigation to low-slope hilly land resources which slopes between 8 degree and 25 degree, analyzed theoretical potential and actual potential of low-slope hilly development and utilization, in order to provide the basis and reference for land use work. The results of the project show: (1) development potential of low-slope hilly land resources is large; (2) the discrepancy beteen theoretical potential and actual potential is obvious; (3) the strategic of development and utilization must be adjust measures to local conditions, pay equal attention to ecological benefit, social benefit and economic benefit and considerate landscape and ecological balance comprehensively.

scholarly journals Combining Remote-Sensing-Derived Data and Historical Maps for Long-Term Back-Casting of Urban Extents

2021 ◽  
Vol 13 (18) ◽  
pp. 3672
Author(s):  
Johannes H. Uhl ◽  
Stefan Leyk ◽  
Zekun Li ◽  
Weiwei Duan ◽  
Basel Shbita ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Color Space ◽  
Area Under The Curve ◽  
Land Development ◽  
Historical Maps ◽  
Human Settlement ◽  
Historical Building ◽  
Seamless Integration

Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature–human systems (e.g., the dynamics of the wildland–urban interface). Herein, we propose a framework that jointly uses remote-sensing-derived human settlement data (i.e., the Global Human Settlement Layer, GHSL) and scanned, georeferenced historical maps to automatically generate historical urban extents for the early 20th century. By applying unsupervised color space segmentation to the historical maps, spatially constrained to the urban extents derived from the GHSL, our approach generates historical settlement extents for seamless integration with the multi-temporal GHSL. We apply our method to study areas in countries across four continents, and evaluate our approach against historical building density estimates from the Historical Settlement Data Compilation for the US (HISDAC-US), and against urban area estimates from the History Database of the Global Environment (HYDE). Our results achieve Area-under-the-Curve values >0.9 when comparing to HISDAC-US and are largely in agreement with model-based urban areas from the HYDE database, demonstrating that the integration of remote-sensing-derived observations and historical cartographic data sources opens up new, promising avenues for assessing urbanization and long-term land cover change in countries where historical maps are available.

Remote Sensing Monitoring and Analysis on Land Utilization Status on Aksu River Basin of Xinjiang Uygur Autonomous Region

2011 ◽  
Vol 282-283 ◽  
pp. 177-180
Author(s):  
Bai Lian Lai
Keyword(s):  
Remote Sensing ◽  
River Basin ◽  
Great Influence ◽  
Land Development ◽  
Tarim River ◽  
Tarim River Basin ◽  
Land Utilization ◽  
Factors Affecting ◽  
Remote Sensing Monitoring ◽  
The Tarim River Basin

Aksu river is one of the biggest branches in the Tarim river basin, where the land utilization and its changes have great influence on the water supply in the lower reaches, and they are also the main factors affecting its ecological restoration. This paper, with the help of three-level intermediate resolution and remote sensor, carries out the remote sensing monitoring and analysis on its land utilization, analyses the changes of farmland and construction land, and provides basis for the planning of land development and the comprehensive assessment for the ecological environment.

scholarly journals Integrating Satellite-Derived Data as Spatial Predictors in Multiple Regression Models to Enhance the Knowledge of Air Temperature Patterns

Urban Science ◽  
2019 ◽  
Vol 3 (4) ◽  
pp. 101 ◽  
Author(s):  
Lucille Alonso ◽  
Florent Renard
Keyword(s):  
Remote Sensing ◽  
Air Temperature ◽  
Urban Areas ◽  
Land Development ◽  
Explanatory Variables ◽  
Dense Networks ◽  
Urban Heat ◽  
Derived Data ◽  
Computer Resources

With the phenomenon of urban heat island and thermal discomfort felt in urban areas, exacerbated by climate change, it is necessary to best estimate the air temperature in every part of an area, especially in the context of the on-going rationalization weather stations network. In addition, the comprehension of air temperature patterns is essential for multiple applications in the fields of agriculture, hydrology, land development or public health. Thus, this study proposes to estimate the air temperature from 28 explanatory variables, using multiple linear regressions. The innovation of this study is to integrate variables from remote sensing into the model in addition to the variables traditionally used like the ones from the Land Use Land Cover. The contribution of spectral indices is significant and makes it possible to improve the quality of the prediction model. However, modeling errors are still present. Their locations and magnitudes are analyzed. However, although the results provided by modelling are of good quality in most cases, particularly thanks to the introduction of explanatory variables from remote sensing, this can never replace dense networks of ground-based measurements. Nevertheless, the methodology presented, applicable to any territory and not requiring specific computer resources, can be highly useful in many fields, particularly for urban planners.

scholarly journals Geomorphological Analysis and Hydrological Potential Zone of Baira River Watershed, Churah in Chamba District of Himachal Pradesh, India

2017 ◽  
Vol 2 (1) ◽  
pp. 26 ◽  
Author(s):  
Kuldeep Pareta ◽  
Upasana Pareta
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Himachal Pradesh ◽  
Morphometric Parameters ◽  
Landsat 8 ◽  
Potential Zone ◽  
Gis Technology ◽  
River Watershed ◽  
Geomorphological Analysis

In the present study, an attempt has been made to study the quantitative geomorphological analysis and hydrological characterization of 95 micro-watersheds (MWS) of Baira river watershed in Himachal Pradesh, India with an area of 425.25 Km2. First time in the world, total 173 morphometric parameters have been generated in a single watershed using satellite remote sensing data (i.e. IRS-P6 ResourceSAT-1 LISS-III, LandSAT-7 ETM+, and LandSAT-8 PAN & OLI merge data), digital elevation models (i.e. IRS-P5 CartoSAT-1 DEM, ASTER DEM data), and soI topographical maps of 1: 50,000 scale. The ninety-five micro-watersheds (MWS) of Baira river watershed have been prioritized through the morphometric analysis of different morphometric parameters (i.e. drainage network, basin geometry, drainage texture analysis, and relief characterizes ). The study has concurrently established the importance of geomorphometry as well as the utility of remote sensing and GIS technology for hydrological characterization of the watershed and there for better resource and environmental managements.

scholarly journals Land Use/Land Cover Change Detection and Urban Sprawl Analysis in the Mount Makiling Forest Reserve Watersheds and Buffer Zone, Philippines

Environments ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 9
Author(s):  
Merlyn Soriano ◽  
Noba Hilvano ◽  
Ronald Garcia ◽  
Aldrin Hao ◽  
Aldin Alegre ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Sprawl ◽  
Human Activities ◽  
Land Development ◽  
Buffer Zone ◽  
Land Conversion ◽  
Land Use Land Cover ◽  
Forest Reserve

Ecologically Valuable Areas play an important role in providing ecosystem services, however, human activities such as land conversion and urban sprawl pose pressures and threats to these areas. The study assessed the land use/land cover and urban sprawl in the Mount Makiling Forest Reserve (MMFR) Watersheds and Buffer Zone from 1992 to 2015 using remote sensing and Geographic Information System (GIS). Results showed that the land use/cover within the MMFR buffer zone has changed from 1992 to 2015 with built-up areas increasing by 117% despite Proclamation 1257, s. 1998 which regulates human activities in the zone. Based on the Shannon entropy analysis the land development in the MMFR buffer zone tends to be dispersed and sprawling. However, when the magnitude of change of urban sprawl in the buffer zone from 2002 to 2015 was calculated, a decrease in the entropy value was observed which implies a compacting pattern as the human settlement in the buffer zone increases over time. Proclamation 1257, s. 1998 needs to be strengthened to protect MMFR and its buffer zone from further encroachment and pressure. Moreover, remote sensing and GIS proved to be useful tools for assessing urban sprawl in ecologically valuable areas such as MMFR.

scholarly journals Land development pressure on peri-urban forests: A case study in the Regional Municipality of York

2000 ◽  
Vol 76 (2) ◽  
pp. 247-250 ◽  
Author(s):  
D. Puric-Mladenovic ◽  
W. A. Kenney ◽  
F. Csillag
Keyword(s):  
Remote Sensing ◽  
Key Words ◽  
Forest Fragmentation ◽  
Patch Size ◽  
Forest Cover ◽  
Land Development ◽  
High Rate ◽  
Forest Patches ◽  
Key Words Development

Forests patches and forest fragmentation were quantified for seven area municipalities within the Regional Municipality of York for the period from 1975 to 1988. This quantification made it possible to determine the extent of forest changes in space and time. In 1988, forest cover shrank to 30%–50% of its 1975 extent. At the same time, the number of forest patches doubled or tripled and mean patch size and the area of interior (based on a 100 m wide edge) declined indicating a high rate of forest fragmentation. Key words: development, fragmentation, remote sensing, forest

scholarly journals Climate change and its impact on Forest Fire in the state of Himachal Pradesh and Uttarakhand states of India: Remote Sensing and GIS Analysis

2018 ◽  
Vol 7 (2) ◽  
pp. 229-246 ◽  
Author(s):  
Firoz Ahmad ◽  
Laxmi Goparaju
Keyword(s):  
Remote Sensing ◽  
Forest Fire ◽  
Pearson Correlation ◽  
Fire Frequency ◽  
Remote Sensing And Gis ◽  
Himachal Pradesh ◽  
Significant Rise ◽  
The State ◽  
Annual Precipitation ◽  
Maximum Temperature

Abstract We have examined the climate and forest fire data using Remote Sensing and GIS in the state of Himachal Pradesh and Uttarakhand states of India. The significant high forest fire events were observed in district of Pauri Garhwal (22.4%) followed by Naini Tal (16.4%), Tehri Garhwal (8.5%), Almora (7.7%), Chamoli (5.8%), Dehra Dun (4.6%), Uttarkashi (4.3%), Champawat (4.2%), Haridwar (3.6%), Una (3.4%), Bageshwar (3.1%), Udham Singh Nagar (2.9%), Sirmaur (2.7%), Solan (2.3%), Kangra (2.1%), Pithoragarh (1.7%) and Shimla (1.2%). The LULC forest category “Deciduous Broadleaf Forest” occupied 17.2% of total forest area and retain significantly high forest fire percent equivalent to 44.7% of total forest fire events. The study revealed that 79% of forest fire incidence was found in the month of April and May. The fire frequency was found highest in the month of April (among all months) whereas it was spread over the five grids (in the count) where the fire frequencies were greater than 100. The average monthly analysis (from January to June) for maximum temperature (°C), precipitation (mm), solar radiation (MJ/m^2), wind velocity (meter/sec.), wet-days frequency (number of days) and evapotranspiration (mm/day) were found to be in the range of (9.90 to 26.44), (26.06 to 134.71), (11738 to 24119), (1.397 to 2.237), (1.46 to 5.12) and (3.96 to 8.46) respectively. Rapid climate/weather severities which significantly enhance the forest fire events were observed in the month of April and May. The analysis of the Pearson Correlation Coefficient (PCC) values of climate parameters showed a significant correlation with forest fire events. The analysis of predicted (2050) climate anomalies data (RCP-6) for the month of April and annual precipitation manifest the significant rise in April temperature and reduction in annual precipitation observed over large part of high forest fire grids will certainly impact adversely to the future forest fire scenario.

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