Building footprint extraction and counting on very high-resolution satellite imagery using object detection deep learning framework

W Nurkarim, AW Wijayanto - Earth Science Informatics, 2023 - Springer
Building footprints are the most visible features in urban areas. Detecting building footprint
has a substantial position in decision-making problems such as city planning and …

Mono-temporal and multi-temporal approaches for burnt area detection using Sentinel-2 satellite imagery (a case study of Rokan Hilir Regency, Indonesia)

N Afira, AW Wijayanto - Ecological Informatics, 2022 - Elsevier
Accurate and up-to-date information about the burnt area is important in estimating
environmental losses, prioritizing rehabilitation areas, and determining future planning …

Develo** relative spatial poverty index using integrated remote sensing and geospatial big data approach: A case study of east java, Indonesia

SR Putri, AW Wijayanto, AD Sakti - ISPRS International Journal of Geo …, 2022 - mdpi.com
Poverty data are usually collected through on-the-ground household-based socioeconomic
surveys. Unfortunately, data collection with such conventional methods is expensive …

[PDF][PDF] Machine learning applied to sentinel-2 and landsat-8 multispectral and medium-resolution satellite imagery for the detection of rice production areas in Nganjuk …

TDT Saadi, AW Wijayanto - … Journal of Remote Sensing and Earth …, 2021 - researchgate.net
Statistics Indonesia (BPS) has been introducing the use of Area Sampling Frame (ASF)
surveys from 2018 to estimate rice production areas, although the process continues to …

Multi-source satellite imagery and point of interest data for poverty map** in East Java, Indonesia: Machine learning and deep learning approaches

SR Putri, AW Wijayanto, S Pramana - Remote Sensing Applications …, 2023 - Elsevier
This study proposes a novel approach to provide a more granular poverty map in terms of
coverage (up to a grid level with the spatial resolution of 1.5 km) with less cost and time to …

Machine Learning-Based Rice Field Map** in Kulon Progo using a Fusion of Multispectral and SAR Imageries

Y Khoirurrizqi, R Sasongko, NLE Utami, A Irbah… - Forum …, 2023 - journals.ums.ac.id
The land-conversion of rice fields can reduce rice production and negatively impact food
security. Consequently, monitoring is essential to prevent the loss of productive agricultural …

Oil palm trees detection and counting on Microsoft Bing Maps Very High Resolution (VHR) satellite imagery and Unmanned Aerial Vehicles (UAV) data using image …

YC Putra, AW Wijayanto, GA Chulafak - Ecological Informatics, 2022 - Elsevier
Palm oil is one of the highest producing vegetable oil crops globally, with production
increasing rapidly over the last 40 years from 5 million tonnes in 1980 to 74.5 million tonnes …

Maize field area detection in East Java, Indonesia: An integrated multispectral remote sensing and machine learning approach

AW Wijayanto, DW Triscowati… - 2020 12th …, 2020 - ieeexplore.ieee.org
An accurate and high quality of agricultural monitoring and statistics commonly requires a
huge amount of resources in terms of human, cost, and time. In this paper, we introduce a …

Spatially granular poverty index (SGPI) for urban poverty map** in Jakarta metropolitan area (JMA): a remote sensing satellite imageries and geospatial big data …

NA Utami, AW Wijayanto, S Pramana… - Earth Science Informatics, 2023 - Springer
Accurate and comprehensive urban poverty monitoring is undoubtedly essential to support
the urban poverty alleviation targets in many develo** countries. The currently available …

Using Remote Sensing and Climate Data to Map the Extent and Severity of Balsam Woolly Adelgid Infestation in Northern Utah, USA

MJ Campbell, JP Williams, EM Berryman - Forests, 2023 - mdpi.com
Balsam woolly adelgid (Hemiptera: Adelges picea Ratzeburg; BWA) is a nonnative, invasive
insect that has infested fir trees in the US for over a century, yet robust methods for map** …