ANALISIS SPASIAL POLA PERUBAHAN PENGGUNAAN LAHAN PERTANIAN (STUDI KASUS NAGARI CUBADAK)

2019 ◽  
Vol 4 (2) ◽  
pp. 62-68
Author(s):  
Afrital Rezki, S.Pd., M.Si ◽  
Erna Juita ◽  
Dasrizal Dasrizal ◽  
Arie Zella Putra Ulni
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Survey Methods ◽  
Descriptive Analysis ◽  
Remote Sensing Data ◽  
Physical Factors ◽  
Sports Facilities ◽  
Remote Sensing Images ◽  
Sensing Data ◽  
Type Of Land Use

Perkembangan penggunaan tanah secara spasial di Nagari Cubadak dibatasi oleh faktor fisik yang didominasi oleh kemiringan landai dan agak sedikit curam. Penelitian ini dilakukan dengan tujuan untuk  mengetahui dan menganalisis Penggunaan tanah dan Pola perubahan penggunaan tanah untuk pertanian secara spasial di Nagari Cubadak. Penelitian ini menggunakan metode yang dilakukan adalah metode interpretasi citra penginderaan jauh, metode survey, dan analisis deskriptif berbasis keruangan. Interpretasi citra penginderaan jauh dilakukan untuk mengetahui informasi jenis penggunaan lahan khususnya pertanian aktual dan tahun-tahun terdahulu berdasarkan nilai digital yang terekam pada data penginderaan jauh. Dari penelitian ini dapat disimpulkan bahwa, Penggunaan tanah di Nagari Cubadak bisa diklasifikasikan delapan (8) jenis penggunaan lahan yakni; Bangunan Umum, Fasilitas Olahraga, Kolam, Makam, Perumahan, Sawah, Tanah Kosong, Tegalan dan Tempat Ibadah. Kemudian, pengurangan penggunaan tanah 1990–2000 yang paling banyak terdiri dari penggunaan tanah tegalan dengan 91 kavling, paling banyak berubah menjadi perumahan sebanyak 75 kavling, kemudian pengurangan sawah dengan 25 kavling, paling banyak berubah menjadi tegalan dengan 35 kavling dan kolam 20 kavling dengan pengurangan 52 kavling.The development of spatial land use in Nagari Cubadak limited by physical factors which are dominated by sloping slopes and slightly steep. This research was conducted with the aim to find out and analyze land use and the pattern of changes in land use for agriculture spatially in Nagari Cubadak. This study uses the method used is the method of interpretation of remote sensing images, survey methods, and spatial-based descriptive analysis. Interpretation of remote sensing imagery is done to find out information on the type of land use, especially actual and previous years based on digital values recorded on remote sensing data. From this study it can be concluded that, Land use in Nagari Cubadak can be classified as eight (8) types of land use namely; Public Buildings, Sports Facilities, Swimming, Graves, Housing, Paddy Fields, Empty Land, fields and places of worship. Then, the reduction in land use from 1990 to 2000 which mostly consisted of the use of upland land with 91 plots, at most turned into housing lots of 75 plots, then reduced fields with 25 plots, most changed to moor with 35 plots and pools of 20 plots with subtraction 52 lots.

scholarly journals An Efficient Decision Support System for Flood Inundation Management Using Intermittent Remote-Sensing Data

2021 ◽  
Vol 13 (14) ◽  
pp. 2818
Author(s):  
Hai Sun ◽  
Xiaoyi Dai ◽  
Wenchi Shou ◽  
Jun Wang ◽  
Xuejing Ruan
Keyword(s):  
Remote Sensing ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Water Body ◽  
Remote Sensing Data ◽  
Flood Inundation ◽  
Remote Sensing Images ◽  
Sensing Data ◽  
Tracking Model

Timely acquisition of spatial flood distribution is an essential basis for flood-disaster monitoring and management. Remote-sensing data have been widely used in water-body surveys. However, due to the cloudy weather and complex geomorphic environment, the inability to receive remote-sensing images throughout the day has resulted in some data being missing and unable to provide dynamic and continuous flood inundation process data. To fully and effectively use remote-sensing data, we developed a new decision support system for integrated flood inundation management based on limited and intermittent remote-sensing data. Firstly, we established a new multi-scale water-extraction convolutional neural network named DEU-Net to extract water from remote-sensing images automatically. A specific datasets training method was created for typical region types to separate the water body from the confusing surface features more accurately. Secondly, we built a waterfront contour active tracking model to implicitly describe the flood movement interface. In this way, the flooding process was converted into the numerical solution of the partial differential equation of the boundary function. Space upwind difference format and the time Euler difference format were used to perform the numerical solution. Finally, we established seven indicators that considered regional characteristics and flood-inundation attributes to evaluate flood-disaster losses. The cloud model using the entropy weight method was introduced to account for uncertainties in various parameters. In the end, a decision support system realizing the flood losses risk visualization was developed by using the ArcGIS application programming interface (API). To verify the effectiveness of the model constructed in this paper, we conducted numerical experiments on the model's performance through comparative experiments based on a laboratory scale and actual scale, respectively. The results were as follows: (1) The DEU-Net method had a better capability to accurately extract various water bodies, such as urban water bodies, open-air ponds, plateau lakes etc., than the other comparison methods. (2) The simulation results of the active tracking model had good temporal and spatial consistency with the image extraction results and actual statistical data compared with the synthetic observation data. (3) The application results showed that the system has high computational efficiency and noticeable visualization effects. The research results may provide a scientific basis for the emergency-response decision-making of flood disasters, especially in data-sparse regions.

scholarly journals Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data

2015 ◽  
Vol 19 (1) ◽  
pp. 507-532 ◽  
Author(s):  
P. Karimi ◽  
W. G. M. Bastiaanssen
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Water Resource Management ◽  
Hydrological Modeling ◽  
Remote Sensing Data ◽  
Actual Evapotranspiration ◽  
Primary Concern ◽  
Suitable Alternative ◽  
Sensing Data ◽  
Water Accounting

Abstract. The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and not generally accessible. Remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the reliability of remote sensing algorithms to accurately determine the spatial distribution of actual evapotranspiration, rainfall and land use. For our validation we used only those papers that covered study periods of seasonal to annual cycles because the accumulated water balance is the primary concern. Review papers covering shorter periods only (days, weeks) were not included in our review. Our review shows that by using remote sensing, the absolute values of evapotranspiration can be estimated with an overall accuracy of 95% (SD 5%) and rainfall with an overall absolute accuracy of 82% (SD 15%). Land use can be identified with an overall accuracy of 85% (SD 7%). Hence, more scientific work is needed to improve the spatial mapping of rainfall and land use using multiple space-borne sensors. While not always perfect at all spatial and temporal scales, seasonally accumulated actual evapotranspiration maps can be used with confidence in water accounting and hydrological modeling.

scholarly journals Research on Land Use Changes in Panjin City Basing on Remote Sensing Data

2018 ◽  
Vol 153 ◽  
pp. 062050
Author(s):  
Hua Ding ◽  
Ru Ren Li ◽  
Li Shuang Sun ◽  
Xin Wang ◽  
Yu Mei Liu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
Sensing Data

scholarly journals Efficient land use based on remote sensing data

2021 ◽  
Vol 3 ◽  
pp. 180-185
Author(s):  
Y. M. Kenzhegaliyev ◽  
◽  
◽  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Remote Sensing Data ◽  
Crop Productivity ◽  
The State ◽  
Agricultural Crops ◽  
Earth Remote Sensing ◽  
Spectral Reflectivity ◽  
Sensing Data ◽  
Current Location

The goal -is to explore ways of using Earth remote sensing data for efficient land use. Methods - detailed information on current location of certain types of agricultural crops in the study areas has been summarized, which opens up opportunities for the effective use of cultivated areas. It was revealed that the basis of the principle of the method under consideration is the relationship between the state and structure of vegetation types with its reflective ability. It has been determined that information on the spectral reflective property of the vegetation cover in the future can help replace more laborious methods of laboratory analysis. For classification of farmland, satellite images of medium spatial resolution with a combination of channels in natural colors were selected. Results - a method for identifying agricultural plants by classification according to the maximum likelihood algorithm was considered. The commonly used complexes of geoinformation software products with modules for special image processing allow displaying indicators in the form of raster images. It is shown that the use of Earth remote sensing data is the most relevant solution in the field of crop recognition and makes it possible to simplify the implementation of such types of work as the analysis of the intensity of land use, the assessment of the degree of pollution with weeds and determination of crop productivity. Conclusions - the research results given in the article indicate that timely information on the current location of certain types of agricultural crops in the studied territories significantly simplifies the implementation of the tasks and increases the resource potential of agricultural lands. In turn, the timing of the survey and the state of environment affect the spectral reflectivity of vegetation.

scholarly journals Groundwater Potential Zones in Relation to Catchment Condition in Orenburg, Russia

2019 ◽  
pp. 60-65
Author(s):  
K Choudhary ◽  
M S Boori ◽  
A Kupriyanov
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Remote Sensing Data ◽  
Ground Truth ◽  
Groundwater Potential ◽  
Groundwater Potential Zone ◽  
Potential Zone ◽  
Ground Truth Data ◽  
Groundwater Availability ◽  
Sensing Data

The main objective of this study was to detect groundwater availability for agriculture in the Orenburg, Russia. Remote sensing data (RS) and geographic information system (GIS) were used to locate potential zones for groundwater in Orenburg. Diverse maps such as a base map, geomorphological, geological structural, lithology, drainage, slope, land use/cover and groundwater potential zone were prepared using the satellite remote sensing data, ground truth data, and secondary data. ArcGIS software was utilized to manipulate these data sets. The groundwater availability of the study was classified into different classes such as very high, high, moderate, low and very low based on its hydro-geomorphological conditions. The land use/cover map was prepared using a digital classification technique with the limited ground truth for mapping irrigated areas in the Orenburg, Russia.

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