Wildan Syakhreza Adwin P.

Key Skills

Software

No software listed

Top Subject Matter

REDD+ forest monitoring

LULC mapping

deforestation verification

Top Data Types

Image

Text

Document

Top Task Types

Land Cover Classification

Data Collection

Classification

Freelancer Overview

Remote Sensing Individual Consultant — Indonesian Environment Fund (Green Climate Fund REDD+ Result Based Payment). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include ArcGIS Pro (ArcPy), InVEST, and Random Forest. Education includes Bachelor of Science, Universitas Gadjah Mada (2023). AI-training focus includes data types such as Geospatial, Tiled Imagery, and Image and labeling workflows including Land Cover Classification, Data Collection, and Classification.

Labeling Experience

Remote Sensing Consultant - Indonesian Environment Fund

ImageClassification

As a Remote Sensing Individual Consultant, you monitor and analyze forest and land cover change to support REDD+ compliance under international reporting requirements. You lead large-scale satellite imagery processing, LULC classification, and spatial validation to ensure results are consistent and reliable. You apply QA/QC practices and compare satellite-derived deforestation with field observations while coordinating technical outputs for GCF results-based payment documentation. • Monitored 2.5M-hectare forest landscapes across South Sumatra, Bengkulu, and Lampung for REDD+ compliance. • Quantified 11,000+ hectares of forest loss through quarterly LULC classifications for SIMONTANA. • Processed 400+ Landsat 8/9 OLI scenes using pansharpening and multi-temporal compilation. • Automated data cleaning with ArcPy and performed QA/QC and ground-truth validation for reporting.

2025 - Present

Remote Sensing Individual Consultant — Indonesian Environment Fund (Green Climate Fund REDD+ Result Based Payment)

Land Cover Classification

Performed quarterly LULC classifications to quantify forest loss for REDD+ compliance and reporting. Conducted satellite-derived deforestation QA/QC to ensure reliability of results-based payment datasets. Validated deforestation findings against ground-truth field observations to meet GCF international verification standards. • Processed 400+ Landsat 8/9 OLI scenes with pansharpening and multi-temporal compilation • Maintained spatial consistency across 40,000+ polygon datasets via geoprocessing and attribute validation • Automated polygon data cleaning using ArcPy in ArcGIS Pro • Performed QA/QC on deforestation datasets for GCF results-based payment reporting

2025 - Present

GIS & Administrative Officer — Bamboo Village Trust (Climate Breakthrough Awards – Bamboo Village Initiatives)

Data Collection

Collected and assembled spatial baseline data for landscape assessment to support grant selection and field validation. Led field surveys to validate land suitability and compiled cross-sector geospatial inputs from open and satellite sources. Delivered spatial dashboards and standardized GIS processing workflows across multiple international partners. • Conducted landscape assessment across 11 bamboo agroforestry areas (~22,000 ha) • Compiled ecological, economic, and socio-cultural geospatial data using Sentinel/Planet and OpenStreetMap • Trained communities in participatory mapping and FGD-based landscape data collection • Led field surveys in multiple provinces/countries to validate land suitability for restoration grants

2023 - 2024

GIS Expert Assistant — WWF-Indonesia (GEF RIMBA Ecosystem Corridor)

Land Cover Classification

Produced LULC maps at multiple resolutions and gathered reference data for ground-truth validation across study regions. Automated satellite imagery processing workflows to improve temporal consistency of regional datasets. Supported technical reporting by translating spatial findings into outputs for policy decisions related to wildlife corridors and road impacts. • Produced 1:25,000 and 1:250,000 LULC maps across four Sumatran regions • Collected 100+ LULC reference points and 20+ soil/landform samples for validation • Automated Landsat & Sentinel-2 processing workflow using repeatable steps • Modeled land cover scenarios and validated model accuracy (>75%)

2022 - 2023

Education

Work History