Spatial distribution of Echinolitorina peruviana (Lamarck, 1882) for intertidal rocky shore in Antofagasta (23° S, Chile).

The intertidal rocky shores in continental Chile have high species diversity mainly in northern Chile (18-27° S), and one of the most widespread species is the gastropod Echinolittorina peruviana (Lamarck, 1822). The aim of the present study is do a first characterization of spatial distribution of E. peruviana in along rocky shore in Antofagasta town in northern Chile. Individuals were counted in nine different sites that also were determined their spectral properties using remote sensing techniques (LANDSAT ETM+). The results revealed that sites without marked human intervention have more abundant in comparison to sites located in the town, also in all studied sites was found an aggregated pattern, and in six of these sites were found a negative binomial distribution. The low density related to sites with human intervention is supported when spectral properties for sites were included. These results would agree with other similar results for rocky shore in northern and southern Chile.

Mapping Bauxite Mining Residues Using Remote Sensing Techniques

Bauxite residuals from abandoned mining sites are both an environmental challenge and a possible source of secondary raw materials. Processing of multispectral and hyperspectral images with the best available techniques can help to produce multiscale spatial maps of elements inside and around the mining sites. The authors propose a procedure for mapping elements concentration using multiple data sets at different scales and resolutions. A comparison between multispectral Sentinel-2 images and hyperspectral PRISMA processing is performed over some case studies of bauxite residues in the Mediterranean area. Specifically, a case study from Italy is composed regarding artificial canyons created by past artisanal mining activities and by stockpiles of extracted bauxite. Hyperspectral punctual measurements (spectroradiometer surveys) were taken in various zones of the bauxite site, where infield topsoil samples were also taken for X-ray fluorescence chemical analysis. Final concentration maps were estimated by performing geostatistical techniques.

EMPREGO DO SENSORIAMENTO REMOTO PARA ANÁLISE DO USO E OCUPAÇÃO DO SOLO NO PERÍMETRO IRRIGADO VÁRZEAS DE SOUSA-PB

EMPREGO DO SENSORIAMENTO REMOTO PARA ANÁLISE DO USO E OCUPAÇÃO DO SOLO NO PERÍMETRO IRRIGADO VÁRZEAS DE SOUSA-PB LEONCIO GONÇALVES RODRIGUES1; ANA CÉLIA MAIA MEIRELES2 E CARLOS WAGNER OLIVEIRA3 1Mestrando em Desenvolvimento Regional Sustentável, Universidade Federal do Cariri-UFCA, Rua Ícaro Moreira de Sousa, nº 126, Muriti, 63130-025, Crato, Ceará, Brasil, [email protected]. 2 Professora titular do Programa de pós graduação em Desenvolvimento Regional Sustentável, Universidade Federal do Cariri-UFCA, Rua Ícaro Moreira de Sousa, nº 126, Muriti, 63130-025, Crato, Ceará, Brasil, [email protected] 3 Professor titular do Programa de pós graduação em Desenvolvimento Regional Sustentável, Universidade Federal do Cariri-UFCA, Rua Ícaro Moreira de Sousa, nº 126, Muriti, 63130-025, Crato, Ceará, Brasil, [email protected] 1 RESUMO O perímetro irrigado várzeas de Sousa (PIVAS) é um grande produtor de culturas como coco, banana, sorgo, algodão dentre outras. Tem grande importância para o desenvolvimento econômico da região do alto sertão da Paraíba. Possui características impares como a distribuição de água para todos os lotes por potencial gravitacional. Para a sustentabilidade do perímetro é necessário o monitoramento constante de suas áreas, para se poder desenvolver estratégias que auxiliam no desenvolvimento sustentável. Nesse sentido, o sensoriamento remoto é uma ferramenta ideal por permitir a obtenção rápida e precisa de informações sobre uma área, o que pode auxiliar na tomada de decisão. Partindo desse pressuposto, o objetivo deste trabalho é apresentar um conjunto de técnicas de sensoriamento que possibilitem o monitoramento de áreas irrigadas ou ambientais. Para tanto foi determinado do uso e ocupação do solo, o índice de vegetação por diferença normalizada (NDVI) e o índice de vegetação ajustado ao solo (SAVI) para o PIVAS. Onde se observou que as técnicas de sensoriamento remoto auxiliam na compreensão de áreas no espaço e tempo. Palavras-chave: monitoramento, manejo, satélite. RODRIGUES, L. G.; MEIRELES, A. C. M.; OLIVEIRA, C, W. USE OF REMOTE SENSING TO ANALYZE THE USE AND OCCUPANCY OF THE SOIL IN THE PERIMETER IRRIGATED VÁRZEAS DE SOUSA-PB. 2 ABSTRACT The floodplain-irrigated perimeter of Sousa (PIVAS) is a major producer of crops such as coconut, banana, sorghum, cotton, among others. It is of great importance for the economic development of the upper wilderness region of Paraiba. It has unique characteristics such as water distribution to all lots by gravitational potential. For the sustainability of the perimeter, constant monitoring of its areas is necessary, to be able to develop strategies that help in sustainable development. In this sense, remote sensing is an ideal tool as it allows for quick and accurate obtaining information about an area, which can help in decision making. Based on this assumption, this work aims to present a set of sensing techniques that enable monitoring of irrigated or environmental areas. For this purpose, the normalized difference vegetation index (NDVI) and the soil-adjusted vegetation index (SAVI) were determined for the PIVAS. Where it was observed that remote sensing techniques help understand areas in space and time. Keywords: monitoring, management, satellite.

Assessing and Delineation of Groundwater Recharge Areas in Coastal Arid Area in Tunisia Using GIS, Remote Sensing Techniques and Self-organizing Map

In Gabès region (southeastern Tunisia), given the semi-arid to arid climate conditions, groundwater is an essential resource to supply the growth needs of the socio-economic development. To ensure sustainable development and preserve water resources, a careful estimation of the present day recharge amount and the delineation of the potential zones of rainfall precipitation are of required for an accurate evaluation of regional water balance. In this context, this study aims to a preliminary assessment of groundwater recharge in Gabes basin in regard to the delineation of the potential recharge areas of phreatic aquifers. Thus, a geological and hydrogeological collected database coupled with remote sensing techniques (RST) were used for the determination of the lateral variation of recharging zone ,Treatment by ArcGIS and Matlab softwares and Kohonen self-organizing maps (K-SOM) approaches.The obtained results indicate that five recharge potential areas have been identified and classified as 27% very low, 23% low, 40% moderate recharge, 7% good and 3 % very good potential recharge located principally on southern part of the study region .This distribution is controlled principally by the geomorphological, geologic, and hydrogeologic features of the region . Reasonable management strategies based on a perennial exploitation of these low renewable resources are required to optimize the water dependent socio-economic development. The estimated groundwater potential recharge of Gabès aquifer system using K-SOM and RST is of 11.4 Mm3.y-1. This recharging rate is very low it present 7% of the total rain, thus it must be ameliorated. K-SOM and RST approach is a useful method for groundwater potential recharge mapping and is a helpful of wells establishment and groundwater sustainable management.an isotopic analyses is recommended to ameliorate the decision maker to establish the adequate strategy.

Quantifying Nutrient Content in the Leaves of Cowpea Using Remote Sensing

Although hyperspectral remote sensing techniques have increasingly been used in the nutritional quantification of plants, it is important to understand whether the method shows a satisfactory response during the various phenological stages of the crop. The aim of this study was to quantify the levels of phosphorus (P), potassium (K), calcium (Ca) and zinc (Zn) in the leaves of Vigna Unguiculata (L.) Walp using spectral data obtained by a spectroradiometer. A randomised block design was used, with three treatments and twenty-five replications. The crop was evaluated at three growth stages: V4, R6 and R9. Single-band models were fitted using simple correlations. For the band ratio models, the wavelengths were selected by 2D correlation. For the models using partial least squares regression (PLSR), the stepwise method was used. The model showing the best fit was used to estimate the phosphorus content in the single-band (R² = 0.62; RMSE = 0.54 and RPD = 1.61), band ratio (R² = 0.66; RMSE = 0.65 and RPD = 1.52) and PLSR models, using data from each of the phenological stages (R² = 0.80; RMSE = 0.47 and RPD = 1.66). Accuracy in modelling leaf nutrients depends on the phenological stage, as well as the amount of data used, and is more accurate with a larger number of samples.

Effect of Locust Invasion and Mitigation Using Remote Sensing Techniques: A Case Study of North Sindh Pakistan

This study comprises the identification of the locust outbreak that happened in February 2020. It is not possible to conduct ground-based surveys to monitor such huge disasters in a timely and adequate manner. Therefore, we used a combination of automatic and manual remote sensing data processing techniques to find out the aftereffects of locust attack effectively. We processed MODIS -normalized difference vegetation index (NDVI ) manually on ENVI and Landsat 8 NDVI using the Google Earth Engine (GEE ) cloud computing platform. We found from the results that, (a) NDVI computation on GEE is more effective, prompt, and reliable compared with the results of manual NDVI computations; (b) there is a high effect of locust disasters in the northern part of Sindh, Thul, Ghari Khairo, Garhi Yaseen, Jacobabad, and Ubauro, which are more vulnerable; and (c) NDVI value suddenly decreased to 0.68 from 0.92 in 2020 using Landsat NDVI and from 0.81 to 0.65 using MODIS satellite imagery. Results clearly indicate an abrupt decrease in vegetation in 2020 due to a locust disaster. That is a big threat to crop yield and food production because it provides a major portion of food chain and gross domestic product for Sindh, Pakistan.