Multi-criteria Land Suitability Analysis for Agriculture in Semi-Arid Region of Kadapa District, Southern India: Geospatial Approaches

This research proposes an integrated methodology for incorporating RS, GIS and AHP techniques for the assessment of agricultural land suitability. In Kadapa district, Andhra Pradesh, India, study is being done on how to best promote agriculture as a source of income to boost the economy of the region. A combined RS, GIS and AHP techniques has been utilized that incorporates organizing AHP hierarchy, criteria specification, pairwise comparison, and criterion map preparation. Land suitability comparison showed that an area of 4.42 km2 (2.62%) is appropriate for irrigation, while an area of 54.39 km2 (32.33%) is appropriate moderately suitable for rainfed agriculture and 95.76 km2 (56.93%) is marginally suitable for agricultural productions. About 13.64 km2 (8.11%) land is currently not suitable for agricultural production. Additionally, the analysis clearly shows the necessity of a decrease in irrigated agricultural land and an increase in dry farm agricultural land. This application of RS, GIS and AHP based agricultural land suitability analysis is helpful in referring agricultural activities to the areas with good physical and environmental conditions, allowing maximum agricultural efficiency in the countryside, increasing non-agricultural uses in areas with low efficiency, and avoiding the construction and environmental pressures on suitable farmland.

Use of ASTER DEM data for Morphometric Analysis of Megech Dirma-Watersheds, Blue Nile Basin, Ethiopia: Implications for Soil and Water Conservation

Quantitative morphometric analysis was carried out for Megech-Dirma, sub-basin of the Blue Nile, by estimating (1) linear, (2) aerial, and (3) relief aspects. An endeavor has been made to measure the Megech-Dirma watershed’s morphometric characteristics to implement conservation methods for soil and water properly. ASTER DEM has been used as input data for extracting morphometric parameters. Strahler’s classification scheme was used to classify the extracted drainage network in ArcGIS extension ArcMap 10.4. The watershed covers a total surface area of 1309.56 km2. The shape of the watersheds as calculated from elongation, circularity, and form factors reveals the elongated shape and the watersheds parade dendritic pattern. The sub-watersheds include third-order for Megech and sixth-order streams. Lower stream orders, in particular first-order streams, dominate the sub-watersheds. The length of overland flow has a higher value (1.06) for Megech indicates low relief, whereas the values of length of overland flow, which are relatively low (0.20) for Dirma, indicate high relief. The drainage density of the study watershed was morphometrically analyzed and obtained 0.47 km/km2 for the Megech sub-basin, which indicates the basin is highly permeable and result in better underground water storage capacity and 2.46 for the Dirma sub-basin indicating very coarse and coarse channel, respectively. The ruggedness number for Megech and Dirma sub-basins was 0.56 and 0.07, respectively, indicating moderate and long, rugged topography, which could be susceptible to flash flood and soil erosion. The dissection index values for Megech 0.40 and 0.36 for Dirma show river sub-basins are moderately dissected. The ruggedness number is 0.56 for Megech implies moderate soil erosion probability, whereas the high infiltration number (14.29) for Dirma river shows the high runoff potential in the sub-basin. The findings of this study include drainage morphometry data that can be used to better understand watershed characteristics and serve as a framework for better planning, management, and decision-making to ensure the long-term use of watershed resources of water and soil.

Coastal Stability using Remote Sensing and Radioactive Materials in the Northwest Nile Delta Coast, Egypt

This paper points to changes of the coastline using two ways, calculating the annual rate of erosion using 1) radioactive materials and 2) GIS and DSAS extension. Finally, both results were verified. Radioactivity results indicate both erosion and accretion zones, the annual scavenging rate in Promontory area shows that it is presented main accretion area, unlike the results of the DSAS extension, which showed that the Promontory is erosion area. The Burullus area annual scavenging rate results showing erosion, despite results of DSAS, it shows that it is an accretion area, but this was clarified by calculating the average distance between the shoreline of 2017 and 2018, and the 2018 shoreline retreat with an average distance 41.4 cm, which makes the Burullus region suffer from erosion. Two methods showed similarity in results in the Edco area, which shows that the Edco area suffers from erosion.

Analysis of Urban Expansion and Modeling of LULC Changes Using Geospatial Techniques: The Case of Adama City

In the last decades, Adama city has experienced drastic changes in its shape, not just in its vast geographical expansion, but also by internal transformations. Subsequently, understanding and evaluating the spatiotemporal variability of urban land use and land cover (LULC) shifts, and it is important to bring forth the right strategies and processes to track population development in decision-making. The goal of this analysis was therefore to examine LULC changes that have taken place over 37 years, forecast the long-term urban development in Adama City using geospatial techniques. To attain this, satellite data of Landsat 1973, 2000 and 2010 was downloaded from USGS Earth Explorer and processed using Arc GIS 10.5, Erdas 9.2, and Idrisi 32. A supervised classification technique has been used to prepare the base maps with six land cover classes that are accustomed to generate LULC maps. The maps are cross-tabulated to measure LULC changes, to look at land-use transfers between the land cover classes, to spot increases and declines in built-up areas in comparison to other land cover classes, and to determine the spatial changes in built-up areas. Finally, Markov Chain and CA-Markov techniques were used to model the LULC changes in the Adama district and to forecast possible changes in urban land use. The model was verified by the Kappa statistics and also by the application of other validation techniques. The growth of built-up areas in the last 37 years has risen from 2% in 1973, 10% in 2000 and 23% in 2010 and estimated about 60% over the next 30 years (2040).

Monitoring and Measuring the Urban Forms Using Spatial Metrics of Howrah City, India

Monitoring and measurement of urban growth pattern with the help of urban-rural gradient and spatial metrics are gaining significant importance in recent times. Rapid and unplanned urban growth has a great impact on natural resources, local ecology, forestry and infrastructure. Temporal satellite data, gradient analysis and landscape metrics of urban landscapes will help to evolve appropriate strategies for integrated planning and sustainable management of natural resources. This communication focuses on spatiotemporal patterns of land use dynamics of Howrah Municipal Corporation (HMC), India and its surroundings with six buffer zones of 2kms. Analysis has been carried out on HMC using temporal remote sensing data. HMC has been used to identify the changes in the gradient of urban to peri-urban and rural regions. Further, the entire study area has been divided into eight zones radiated from city center based on directions. Different landscape metrics have been computed for each zone which helps to understand the spatiotemporal patterns and associated dynamics of the landscape at local levels.

Satellite Data Based Soil Water Index as a Tool to Monitor Droughts and Agricultural Crisis -An Example of Yavatmal District, Maharashtra, India

Yavatmal is one of the drought prone districts in Maharashtra state of India and has witnessed an agricultural crisis to the extent that hundreds of its farmers have committed suicides in recent years. Satellite data based products have previously been used globally for monitoring and predicting of drought, but not for monitoring their extreme impacts that may include farmer-suicides. In this study, the performance of the Soil Water Index (SWI) derived from the surface soil moisture estimated by the European Space Agency’s Advanced Scatterometer (ASCAT) is assessed. Using the 2007-2015 data, it was found that the relationship of the SWI anomaly was bit stronger (coefficient. of correlation = 0.59) with the meteorological drought or precipitation than with the agricultural drought or crop yields of major crops (coefficient. of correlation = 0.50). The farmer-suicide rate was better correlated with the SWI anomaly averaged annually than with the SWI anomaly averaged only for the monsoon months (June, July, August, and September). The correlation between the SWI averaged annually increased to 0.89 when the averages were taken for three years, with the highest correlation occurring between the suicide rate and the SWI anomaly averaged for three years. However, a positive relationship between SWI and the suicide rate indicated that drought was not a major factor responsible for suicide occurrence and other possible factors responsible for suicide occurrence need to examine in detail.

African Civet Habitat Mapping in Illu-Abbabora Zone, Southwest Ethiopia: Geospatial Approach

The African Civet (Civettictis Civetta Shreber, 1778) is one of the important natural animal resources of Ethiopia. Ethiopia is the major producer of the Civet perineal gland secretion (known as “civet”) used extensively as a base in perfume industry. However, there is no improvement in civet farming processes in rural Ethiopia, and the farmers still live in a poor state. Majority of rural population in Ethiopia is depending on agriculture, and hence land-use changes during the past couple of decades are mostly linked to agricultural development. Present study was undertaken to predict the spatial distribution of land-use and land-cover and habitats of the African Civet here in after referred as civet(s) in Illu-Abbabora Zone, Southwest Ethiopia. Landsat images of three years: 1985, 2000 and 2018 were classified to generate land-use/land-cover maps, locate forests and other land classes. Results of the study revealed that forest and wetland habitats decreased by an estimated 11.12 km2/yr-1 and 2.39 km2/yr-1, respectively during the period of 1985-2018. In contrast, the extent of agricultural land, urban area and Gumro tea plantation increased by an estimated 13.36 km2/yr-1, 0.59 km2/yr-1 and 0.43 km2/yr-1, respectively. Habitat suitability approach was found to have great potential in predicting potential habitats of the civets through complex non-linear models.

Modeling Soil Erosion Vulnerability Using RUSLE: A Case Study Upstream of Nangal Reservoir, India

Simulation of soil erosion is an important phenomenon in watershed management studies because of the dynamic nature of soil. The present study demonstrates the capabilities of remote sensing coupled with GIS to extract soil erosion vulnerabilities using RUSLE model. Therefore this study understands spatial distribution of soil erosion at a macro-watershed scale. The input parameters for RUSLE model include the rainfall and erosivity (R) derived using the TRMM satellite precipitation product for a long term implementing regression model. The soil erodibility (K) factor is estimated using available soil map, and the topographic factor (LS) from 12m ALOS PALSAR DEM. The management practice information was extracted from the land use / cover map based on 30m multi spectral LANDSAT-8 of three season datasets. The RUSLE model predicted very low, low, moderate, high and very high erosion in 84.8%, 7.9%, 4.4%, 2.3% and 0.7% of reviewed area, respectively. The results were validated with ground infromation and NDVI, being the main identifiers of soil erosion. As presence of high vegetation indicates higher strength to hold the soil particles together and prevent soil erosion, correlation coefficient was generated to find accuracy of the results with NDVI of the area. The strong positive correlation (0.5) provided scientific support that prediction of soil erosion by RUSLE can be effectively used for watershed management and combating action plan for soil erosion.

Analysis of Remote Sensing based Vegetation Indices (VIs) for Unmanned Aerial System (UAS): A Review

Unmanned Aerial System (UAS) is an efficient tool to bridge the gap between high expensive satellite remote sensing, manned aerial surveys, and labors time consuming conventional fieldwork techniques of data collection. UAS can provide spatial data at very fine (up to a few mm) and desirable temporal resolution. Several studies have used vegetation indices (VIs) calculated from UAS based on optical- and MSS-datasets to model the parameters of biophysical units of the Earth surface. They have used different techniques of estimations, predictions and classifications. However, these results vary according to used datasets and techniques and appear very site-specific. These existing approaches aren’t optimal and applicable for all cases and need to be tested according to sensor category and different geophysical environmental conditions for global applications. UAS remote sensing is a challenging and interesting area of research for sustainable land management.

Site Suitability Analysis for Solid Waste Disposal of Bolpur Municipality, Birbhum District of West Bengal (India): Remote Sensing and AHP Approach

The aim of present study is to find out suitable sites for solid waste disposal (SWD) in the tropical moist sub-humid region of Bolpur municipality, Birbhum district, West Bengal, India using Remote Sensing (RS), Geographic Information System (GIS) and Analytical Hierarchy Process (AHP) techniques. Saaty’s AHP technique was used to delineate the suitable sites for SWD using thematic layers such as land use/land cover, geology, slopes and soils. The ranks were assigned for each individual sub-criterion of thematic layers and weights assigned to each thematic layer for selection of suitable sites for SWD using Arc-GIS environment. Possible landfill sites were categorized into five classes as highly suitable, suitable, moderately suitable and unsuitable. About 16.43% (1.97 km2) and 28 % (3.42 km2) area in the region show as highly suitable and suitable sites for SWD, respectively. On the other hand, 39.13 % (4.69 km2), 9.49 % (1.14 km2) and 6.38% (0.77km2) area show moderately suitable, less suitable and unsuitable for solid waste dumping.